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  • 1.
    Alsmark, Cecilia
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Division of Pharmacognosy.
    Foster, Peter G.
    Sicheritz-Ponten, Thomas
    Nakjang, Sirintra
    Embley, T. Martin
    Hirt, Robert P.
    Patterns of prokaryotic lateral gene transfers affecting parasitic microbial eukaryotes2013In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 14, no 2, p. R19-Article in journal (Refereed)
    Abstract [en]

    Background: The influence of lateral gene transfer on gene origins and biology in eukaryotes is poorly understood compared with those of prokaryotes. A number of independent investigations focusing on specific genes, individual genomes, or specific functional categories from various eukaryotes have indicated that lateral gene transfer does indeed affect eukaryotic genomes. However, the lack of common methodology and criteria in these studies makes it difficult to assess the general importance and influence of lateral gene transfer on eukaryotic genome evolution. Results: We used a phylogenomic approach to systematically investigate lateral gene transfer affecting the proteomes of thirteen, mainly parasitic, microbial eukaryotes, representing four of the six eukaryotic super-groups. All of the genomes investigated have been significantly affected by prokaryote-to-eukaryote lateral gene transfers, dramatically affecting the enzymes of core pathways, particularly amino acid and sugar metabolism, but also providing new genes of potential adaptive significance in the life of parasites. A broad range of prokaryotic donors is involved in such transfers, but there is clear and significant enrichment for bacterial groups that share the same habitats, including the human microbiota, as the parasites investigated. Conclusions: Our data show that ecology and lifestyle strongly influence gene origins and opportunities for gene transfer and reveal that, although the outlines of the core eukaryotic metabolism are conserved among lineages, the genes making up those pathways can have very different origins in different eukaryotes. Thus, from the perspective of the effects of lateral gene transfer on individual gene ancestries in different lineages, eukaryotic metabolism appears to be chimeric.

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  • 2. Andersson, Anders F.
    et al.
    Lundgren, Magnus
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Eriksson, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Rosenlund, Magnus
    Bernander, Rolf
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Nilsson, Peter
    Global analysis of mRNA stability in the archaeon Sulfolobus2006In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 7, no 10, p. R99-Article in journal (Refereed)
    Abstract [en]

    Background: Transcript half-lives differ between organisms, and between groups of genes within the same organism. The mechanisms underlying these differences are not clear, nor are the biochemical properties that determine the stability of a transcript. To address these issues, genome-wide mRNA decay studies have been conducted in eukaryotes and bacteria. In contrast, relatively little is known about RNA stability in the third domain of life, Archaea. Here, we present a microarray-based analysis of mRNA half-lives in the hyperthermophilic crenarchaea Sulfolobus solfatoricus and Sulfolobus acidocaldarius, constituting the first genome-wide study of RNA decay in archaea. Results: The two transcriptomes displayed similar half-life distributions, with medians of about five minutes. Growth-related genes, such as those involved in transcription, translation and energy production, were over-represented among unstable transcripts, whereas uncharacterized genes were over-represented among the most stable. Half-life was negatively correlated with transcript abundance and, unlike the situation in other organisms, also negatively correlated with transcript length. Conclusion: The mRNA half-life distribution of Sulfolobus species is similar to those of much faster growing bacteria, contrasting with the earlier observation that median mRNA half-life is proportional to the minimal length of the cell cycle. Instead, short half-lives may be a general feature of prokaryotic transcriptomes, possibly related to the absence of a nucleus and/or more limited post-transcriptional regulatory mechanisms. The pattern of growth-related transcripts being among the least stable in Sulfolobus may also indicate that the short half-lives reflect a necessity to rapidly reprogram gene expression upon sudden changes in environmental conditions.

  • 3.
    Andersson, Leif
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Swedish University of Agricultural Sciences.
    Archibald, Alan L.
    Bottema, Cynthia D.
    Brauning, Rudiger
    Burgess, Shane C.
    Burt, Dave W.
    Casas, Eduardo
    Cheng, Hans H.
    Clarke, Laura
    Couldrey, Christine
    Dalrymple, Brian P.
    Elsik, Christine G.
    Foissac, Sylvain
    Giuffra, Elisabetta
    Groenen, Martien A.
    Hayes, Ben J.
    Huang, LuSheng S.
    Khatib, Hassan
    Kijas, James W.
    Kim, Heebal
    Lunney, Joan K.
    McCarthy, Fiona M.
    McEwan, John C.
    Moore, Stephen
    Nanduri, Bindu
    Notredame, Cedric
    Palti, Yniv
    Plastow, Graham S.
    Reecy, James M.
    Rohrer, Gary A.
    Sarropoulou, Elena
    Schmidt, Carl J.
    Silverstein, Jeffrey
    Tellam, Ross L.
    Tixier-Boichard, Michele
    Tosser-Klopp, Gwenola
    Tuggle, Christopher K.
    Vilkki, Johanna
    White, Stephen N.
    Zhao, Shuhong
    Zhou, Huaijun
    Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project2015In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16Article in journal (Refereed)
    Abstract [en]

    We describe the organization of a nascent international effort, the Functional Annotation of Animal Genomes (FAANG) project, whose aim is to produce comprehensive maps of functional elements in the genomes of domesticated animal species.

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  • 4.
    Balliu, Brunilda
    et al.
    Stanford Univ, Dept Pathol, Sch Med, Stanford, CA USA.
    Durrant, Matthew
    Stanford Univ, Dept Genet, Sch Med, Stanford, CA USA.
    de Goede, Olivia
    Stanford Univ, Dept Genet, Sch Med, Stanford, CA USA.
    Abell, Nathan
    Stanford Univ, Dept Genet, Sch Med, Stanford, CA USA.
    Li, Xin
    Stanford Univ, Dept Pathol, Sch Med, Stanford, CA USA.
    Liu, Boxiang
    Stanford Univ, Dept Biol, Sch Med, Stanford, CA USA.
    Gloudemans, Michael J.
    Stanford Univ, Dept Genet, Sch Med, Stanford, CA USA.
    Cook, Naomi L.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala Univ, Dept Med Sci, Uppsala, Sweden.
    Smith, Kevin S.
    Stanford Univ, Dept Pathol, Sch Med, Stanford, CA USA.
    Knowles, David A.
    New York Genome Ctr, New York, NY USA.
    Pala, Mauro
    Univ Sassari, Dipartimento Sci Biomed, Sassari, Italy.
    Cucca, Francesco
    Univ Sassari, Dipartimento Sci Biomed, Sassari, Italy.
    Schlessinger, David
    NIA, Lab Genet, Bethesda, MD USA.
    Jaiswal, Siddhartha
    Stanford Univ, Dept Pathol, Sch Med, Stanford, CA USA.
    Sabatti, Chiara
    Stanford Univ, Dept Biomed Data Sci, Sch Med, Stanford, CA USA.
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Ingelsson, Erik
    Stanford Univ, Sch Med, Div Cardiovasc Med, Dep Med, Stanford, CA USA; Stanford Univ, Stanford Cardiovasc Inst, Stanford, CA USA; Stanford Univ, Stanford Diabet Res Ctr, Stanford, CA USA.
    Montgomery, Stephen B.
    Stanford Univ, Dept Pathol, Sch Med, Stanford, CA USA; Stanford Univ, Dept Genet, Sch Med, Stanford, CA USA.
    Genetic regulation of gene expression and splicing during a 10-year period of human aging2019In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 20, no 1, article id 230Article in journal (Refereed)
    Abstract [en]

    Background: Molecular and cellular changes are intrinsic to aging and age-related diseases. Prior cross-sectional studies have investigated the combined effects of age and genetics on gene expression and alternative splicing; however, there has been no long-term, longitudinal characterization of these molecular changes, especially in older age.

    Results: We perform RNA sequencing in whole blood from the same individuals at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging at a population and individual level. We observe that individuals are more similar to their own expression profiles later in life than profiles of other individuals their own age. We identify 1291 and 294 genes differentially expressed and alternatively spliced with age, as well as 529 genes with outlying individual trajectories. Further, we observe a strong correlation of genetic effects on expression and splicing between the two ages, with a small subset of tested genes showing a reduction in genetic associations with expression and splicing in older age.

    Conclusions: These findings demonstrate that, although the transcriptome and its genetic regulation is mostly stable late in life, a small subset of genes is dynamic and is characterized by a reduction in genetic regulation, most likely due to increasing environmental variance with age.

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  • 5.
    Berglund, Jonas
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nevalainen, Elisa M
    Molin, Anna-Maja
    Perloski, Michele
    André, Catherine
    Zody, Michael C
    Sharpe, Ted
    Hitte, Christophe
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lohi, Hannes
    Webster, Matthew T
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Novel origins of copy number variation in the dog genome2012In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 13, no 8, p. R73-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Copy number variants (CNVs) account for substantial variation between genomes and are a major source of normal and pathogenic phenotypic differences. The dog is an ideal model to investigate mutational mechanisms that generate CNVs as its genome lacks a functional ortholog of the PRDM9 gene implicated in recombination and CNV formation in humans. Here we comprehensively assay CNVs using high-density array comparative genomic hybridization in 50 dogs from 17 dog breeds and 3 gray wolves. RESULTS: We use a stringent new method to identify a total of 430 high-confidence CNV loci, which range in size from 9 kb to 1.6 Mb and span 26.4 Mb, or 1.08%, of the assayed dog genome, overlapping 413 annotated genes. Of CNVs observed in each breed, 98% are also observed in multiple breeds. CNVs predicted to disrupt gene function are significantly less common than expected by chance. We identify a significant overrepresentation of peaks of GC content, previously shown to be enriched in dog recombination hotspots, in the vicinity of CNV breakpoints. CONCLUSIONS: A number of the CNVs identified by this study are candidates for generating breed-specific phenotypes. Purifying selection seems to be a major factor shaping structural variation in the dog genome, suggesting that many CNVs are deleterious. Localized peaks of GC content appear to be novel sites of CNV formation in the dog genome by non-allelic homologous recombination, potentially activated by the loss of PRDM9. These sequence features may have driven genome instability and chromosomal rearrangements throughout canid evolution.

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  • 6.
    Bolivar, Paulina
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
    Gueguen, Laurent
    Univ Claude Bernard Lyon 1, CNRS, UMR 5558, Lab Biol & Biometrie Evolut, Lyon, France.
    Duret, Laurent
    Univ Claude Bernard Lyon 1, CNRS, UMR 5558, Lab Biol & Biometrie Evolut, Lyon, France.
    Ellegren, Hans
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
    Mugal, Carina
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
    GC-biased gene conversion conceals the prediction of the nearly neutral theory in avian genomes2019In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 20, article id 5Article in journal (Refereed)
    Abstract [en]

    Background: The nearly neutral theory of molecular evolution predicts that the efficacy of natural selection increases with the effective population size. This prediction has been verified by independent observations in diverse taxa, which show that life-history traits are strongly correlated with measures of the efficacy of selection, such as the d(N)/d(S) ratio. Surprisingly, avian taxa are an exception to this theory because correlations between life-history traits and d(N)/d(S) are apparently absent. Here we explore the role of GC-biased gene conversion on estimates of substitution rates as a potential driver of these unexpected observations.

    Results: We analyze the relationship between d(N)/d(S) estimated from alignments of 47 avian genomes and several proxies for effective population size. To distinguish the impact of GC-biased gene conversion from selection, we use an approach that accounts for non-stationary base composition and estimate d(N)/d(S) separately for changes affected or unaffected by GC-biased gene conversion. This analysis shows that the impact of GC-biased gene conversion on substitution rates can explain the lack of correlations between life-history traits and d(N)/d(S). Strong correlations between life-history traits and d(N)/d(S) are recovered after accounting for GC-biased gene conversion. The correlations are robust to variation in base composition and genomic location.

    Conclusions: Our study shows that gene sequence evolution across a wide range of avian lineages meets the prediction of the nearly neutral theory,the efficacy of selection increases with effective population size. Moreover, our study illustrates that accounting for GC-biased gene conversion is important to correctly estimate the strength of selection.

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  • 7.
    Bornelöv, Susanne
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Univ Cambridge, Wellcome Trust Med Res Council Stem Cell Inst, Cambridge CB2 1QR, England..
    Seroussi, Eyal
    Agr Res Org, Volcani Ctr, Rishon Leziyyon, Israel..
    Yosefi, Sara
    Agr Res Org, Volcani Ctr, Rishon Leziyyon, Israel..
    Pendavis, Ken
    Univ Arizona, Coll Agr & Life Sci, Tucson, AZ 85721 USA..
    Burgess, Shane C.
    Univ Arizona, Coll Agr & Life Sci, Tucson, AZ 85721 USA..
    Grabherr, Manfred
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Friedman-Einat, Miriam
    Agr Res Org, Volcani Ctr, Rishon Leziyyon, Israel..
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Texas A&M Univ, Coll Vet Med & Biomed Sci, Dept Vet Integrat Biosci, College Stn, TX 77843 USA..
    Correspondence on Lovell et al.: identification of chicken genes previously assumed to be evolutionarily lost2017In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 18, article id 112Article in journal (Refereed)
    Abstract [en]

    Through RNA-Seq analyses, we identified 137 genes that are missing in chicken, including the long-sought-after nephrin and tumor necrosis factor genes. These genes tended to cluster in GC-rich regions that have poor coverage in genome sequence databases. Hence, the occurrence of syntenic groups of vertebrate genes that have not been observed in Aves does not prove the evolutionary loss of such genes.

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  • 8. Brolin, M
    et al.
    Ribacke, Ulf
    Nilsson, Sandra
    Ankarklev, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Moll, Kirsten
    Wahlgren, Mats
    Chen, Qijun
    Simultaneous transcription of duplicated var2csa gene copies in individual Plasmodium falciparum parasites2009In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 10, no 10, p. R117-Article in journal (Refereed)
    Abstract [en]

    Background: Single nucleotide polymorphisms are common in duplicated genes, causing functional preservation, alteration or silencing. The Plasmodium falciparum genes var2csa and Pf332 are duplicated in the haploid genome of the HB3 parasite line. Whereas the molecular function of Pf332 remains to be elucidated, VAR2CSA is known to be the main adhesin in placental parasite sequestration. Sequence variations introduced upon duplication of these genes provide discriminative possibilities to analyze allele-specific transcription with a bearing towards understanding gene dosage impact on parasite biology. Results: We demonstrate an approach combining real-time PCR allelic discrimination and discriminative RNA-FISH to distinguish between highly similar gene copies in P. falciparum parasites. The duplicated var2csa variants are simultaneously transcribed, both on a population level and intriguingly also in individual cells, with nuclear co-localization of the active genes and corresponding transcripts. This indicates transcriptional functionality of duplicated genes, challenges the dogma of mutually exclusive var gene transcription and suggests mechanisms behind antigenic variation, at least in respect to the duplicated and highly similar var2csa genes. Conclusions: Allelic discrimination assays have traditionally been applied to study zygosity in diploid genomes. The assays presented here are instead successfully applied to the identification and evaluation of transcriptional activity of duplicated genes in the haploid genome of the P. falciparum parasite. Allelic discrimination and gene or transcript localization by FISH not only provide insights into transcriptional regulation of genes such as the virulence associated var genes, but also suggest that this sensitive and precise approach could be used for further investigation of genome dynamics and gene regulation.

  • 9.
    Chen, Zhi-Qiang
    et al.
    Swedish Univ Agr Sci, Umeå Plant Sci Ctr, Dept Forest Genet & Plant Physiol, SE-90183 Umeå, Sweden..
    Zan, Yanjun
    Swedish Univ Agr Sci, Umeå Plant Sci Ctr, Dept Forest Genet & Plant Physiol, SE-90183 Umeå, Sweden..
    Milesi, Pascal
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Zhou, Linghua
    Swedish Univ Agr Sci, Umeå Plant Sci Ctr, Dept Forest Genet & Plant Physiol, SE-90183 Umeå, Sweden..
    Chen, Jun
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab. Zhejiang Univ, Coll Life Sci, Hangzhou 310058, Zhejiang, Peoples R China..
    Li, Lili
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Cui, BinBin
    Baoding Univ, Coll Biochem & Environm Engn, Baoding 071000, Hebei, Peoples R China..
    Niu, Shihui
    Beijing Forestry Univ, Beijing Adv Innovat Ctr Tree Breeding Mol Design, Beijing, Peoples R China..
    Westin, Johan
    Skogforsk, Box 3, SE-91821 Savar, Sweden.;Swedish Univ Agr Sci, Unit Field Based Forest Res, SE-90183 Umeå, Sweden..
    Karlsson, Bo
    Skogforsk, Ekebo 2250, SE-26890 Svalov, Sweden..
    Garcia-Gil, Maria Rosario
    Swedish Univ Agr Sci, Umeå Plant Sci Ctr, Dept Forest Genet & Plant Physiol, SE-90183 Umeå, Sweden..
    Lascoux, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wu, Harry X.
    Swedish Univ Agr Sci, Umeå Plant Sci Ctr, Dept Forest Genet & Plant Physiol, SE-90183 Umeå, Sweden.;Beijing Forestry Univ, Beijing Adv Innovat Ctr Tree Breeding Mol Design, Beijing, Peoples R China.;CSIRO Natl Collect Res Australia, Black Mt Lab, Canberra, ACT 2601, Australia..
    Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis2021In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 22, no 1, article id 179Article in journal (Refereed)
    Abstract [en]

    Background: Genome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees.

    Results: We identify 55 novel quantitative trait loci (QTLs) that are associated with phenotypic variation. The largest number of QTLs is associated with the budburst stage, followed by diameter at breast height, wood quality, and frost damage. Two QTLs with the largest effect have a pleiotropic effect for budburst stage, frost damage, and diameter and are associated with MAP3K genes. Genotype data called from exome capture, recently developed SNP array and gene expression data indirectly support this discovery.

    Conclusion: Several important QTLs associated with growth and frost damage have been verified in several southern and northern progeny plantations, indicating that these loci can be used in QTL-assisted genomic selection. Our study also demonstrates that existing heterogeneous phenotypic data from breeding programs, collected over several decades, is an important source for GWAS and that such integration into GWAS should be a major area of inquiry in the future.

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  • 10. Dyke, Stephanie O M
    et al.
    Cheung, Warren A
    Joly, Yann
    Ammerpohl, Ole
    Lutsik, Pavlo
    Rothstein, Mark A
    Caron, Maxime
    Busche, Stephan
    Bourque, Guillaume
    Rönnblom, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Rheumatology.
    Flicek, Paul
    Beck, Stephan
    Hirst, Martin
    Stunnenberg, Henk
    Siebert, Reiner
    Walter, Jörn
    Pastinen, Tomi
    Epigenome data release: a participant-centered approach to privacy protection2015In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16, article id 142Article in journal (Refereed)
    Abstract [en]

    Large-scale epigenome mapping by the NIH Roadmap Epigenomics Project, the ENCODE Consortium and the International Human Epigenome Consortium (IHEC) produces genome-wide DNA methylation data at one base-pair resolution. We examine how such data can be made open-access while balancing appropriate interpretation and genomic privacy. We propose guidelines for data release that both reduce ambiguity in the interpretation of open-access data and limit immediate access to genetic variation data that are made available through controlled access.

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  • 11. Fairfield, Heather
    et al.
    Gilbert, Griffith J
    Barter, Mary
    Corrigan, Rebecca R
    Curtain, Michelle
    Ding, Yueming
    D'Ascenzo, Mark
    Gerhardt, Daniel J
    He, Chao
    Huang, Wenhui
    Richmond, Todd
    Rowe, Lucy
    Probst, Frank J
    Bergström, David E
    Murray, Stephen A
    Bult, Carol
    Richardson, Joel
    Kile, Benjamin T
    Gut, Ivo
    Hager, Jorg
    Sigurdsson, Snaevar
    Mauceli, Evan
    Di Palma, Federica
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Cunningham, Michael L
    Cox, Timothy C
    Justice, Monica J
    Spector, Mona S
    Lowe, Scott W
    Albert, Thomas
    Donahue, Leah Rae
    Jeddeloh, Jeffrey
    Shendure, Jay
    Reinholdt, Laura G
    Mutation discovery in mice by whole exome sequencing2011In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 12, no 9, p. R86-Article in journal (Refereed)
    Abstract [en]

    We report the development and optimization of reagents for in-solution, hybridization-based capture of the mouse exome. By validating this approach in a multiple inbred strains and in novel mutant strains, we show that whole exome sequencing is a robust approach for discovery of putative mutations, irrespective of strain background. We found strong candidate mutations for the majority of mutant exomes sequenced, including new models of orofacial clefting, urogenital dysmorphology, kyphosis and autoimmune hepatitis.

  • 12. Fleischer, Thomas
    et al.
    Frigessi, Arnoldo
    Johnson, Kevin C.
    Edvardsen, Hege
    Touleimat, Nizar
    Klajic, Jovana
    Riis, Margit L. H.
    Haakensen, Vilde D.
    Wärnberg, Fredrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Endocrine Surgery.
    Naume, Bjorn
    Helland, Aslaug
    Borresen-Dale, Anne-Lise
    Tost, Jorg
    Christensen, Brock C.
    Kristensen, Vessela N.
    Genome-wide DNA methylation profiles in progression to in situ and invasive carcinoma of the breast with impact on gene transcription and prognosis2014In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 15, no 8, p. 435-Article in journal (Refereed)
    Abstract [en]

    Background: Ductal carcinoma in situ (DCIS) of the breast is a precursor of invasive breast carcinoma. DNA methylation alterations are thought to be an early event in progression of cancer, and may prove valuable as a tool in clinical decision making and for understanding neoplastic development. Results: We generate genome-wide DNA methylation profiles of 285 breast tissue samples representing progression of cancer, and validate methylation changes between normal and DCIS in an independent dataset of 15 normal and 40 DCIS samples. We also validate a prognostic signature on 583 breast cancer samples from The Cancer Genome Atlas. Our analysis reveals that DNA methylation profiles of DCIS are radically altered compared to normal breast tissue, involving more than 5,000 genes. Changes between DCIS and invasive breast carcinoma involve around 1,000 genes. In tumors, DNA methylation is associated with gene expression of almost 3,000 genes, including both negative and positive correlations. A prognostic signature based on methylation level of 18 CpGs is associated with survival of breast cancer patients with invasive tumors, as well as with survival of patients with DCIS and mixed lesions of DCIS and invasive breast carcinoma. Conclusions: This work demonstrates that changes in the epigenome occur early in the neoplastic progression, provides evidence for the possible utilization of DNA methylation-based markers of progression in the clinic, and highlights the importance of epigenetic changes in carcinogenesis.

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  • 13.
    Foox, Jonathan
    et al.
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA.;Weill Cornell Med, HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsau, New York, NY 10021 USA..
    Nordlund, Jessica
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab. EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.
    Lalancette, Claudia
    Univ Michigan Med, BRCF Epigen Core, Ann Arbor, MI 48109 USA..
    Gong, Ting
    Univ Hawaii, Dept Quantitat Hlth Sci, John A Burns Sch Med, Honolulu, HI 96813 USA..
    Lacey, Michelle
    Tulane Univ, New Orleans, LA 70118 USA..
    Lent, Samantha
    AbbVie Genom Res Ctr, 1 N Waukegan Rd, N Chicago, IL 60036 USA..
    Langhorst, Bradley W.
    New England Biolabs Inc, Ipswich, MA 01938 USA..
    Ponnaluri, V. K. Chaithanya
    New England Biolabs Inc, Ipswich, MA 01938 USA..
    Williams, Louise
    New England Biolabs Inc, Ipswich, MA 01938 USA..
    Padmanabhan, Karthik Ramaswamy
    Univ Michigan Med, BRCF Epigen Core, Ann Arbor, MI 48109 USA..
    Cavalcante, Raymond
    Univ Michigan Med, BRCF Epigen Core, Ann Arbor, MI 48109 USA..
    Lundmark, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab. EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.
    Butler, Daniel
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA..
    Mozsary, Christopher
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA..
    Gurvitch, Justin
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA..
    Greally, John M.
    Albert Einstein Coll Med, Bronx, NY 10461 USA..
    Suzuki, Masako
    Albert Einstein Coll Med, Bronx, NY 10461 USA..
    Menor, Mark
    Univ Hawaii, Dept Quantitat Hlth Sci, John A Burns Sch Med, Honolulu, HI 96813 USA..
    Nasu, Masaki
    Univ Hawaii, Dept Quantitat Hlth Sci, John A Burns Sch Med, Honolulu, HI 96813 USA..
    Alonso, Alicia
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA..
    Sheridan, Caroline
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA.;Weill Cornell Med, Div Hematol Oncol, Dept Med, Epigen Core Facil, New York, NY USA..
    Scherer, Andreas
    EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.;Univ Helsinki, Inst Mol Med Finland FIMM, Helsinki, Finland..
    Bruinsma, Stephen
    Illumina Inc, Madison, WI 53705 USA..
    Golda, Gosia
    Jagiellonian Univ, Fac Biochem Biophys & Biotechnol, Krakow, Poland..
    Muszynska, Agata
    Jagiellonian Univ, Malopolska Ctr Biotechnol, Krakow, Poland..
    Labaj, Pawel P.
    Jagiellonian Univ, Malopolska Ctr Biotechnol, Krakow, Poland..
    Campbell, Matthew A.
    New England Biolabs Inc, Ipswich, MA 01938 USA..
    Wos, Frank
    New York Genome Ctr, New York, NY 10013 USA..
    Raine, Amanda
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.
    Liljedahl, Ulrika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab. EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.
    Axelsson, Tomas
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab. EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.
    Wang, Charles
    Loma Linda Univ, Ctr Genom, Sch Med, Loma Linda, CA 92350 USA..
    Chen, Zhong
    Loma Linda Univ, Ctr Genom, Sch Med, Loma Linda, CA 92350 USA..
    Yang, Zhaowei
    Loma Linda Univ, Ctr Genom, Sch Med, Loma Linda, CA 92350 USA.;Guangzhou Med Univ, Guangzhou Inst Resp Hlth, Dept Allergy & Clin Immunol, State Key Lab Resp Dis,Affiliated Hosp 1, Guangzhou, Peoples R China..
    Li, Jing
    Loma Linda Univ, Ctr Genom, Sch Med, Loma Linda, CA 92350 USA.;Guangzhou Med Univ, Guangzhou Inst Resp Hlth, Dept Allergy & Clin Immunol, State Key Lab Resp Dis,Affiliated Hosp 1, Guangzhou, Peoples R China..
    Yang, Xiaopeng
    Zhengzhou Univ, Dept Neurol, Affiliated Hosp 2, Zhengzhou 450014, Peoples R China..
    Wang, Hongwei
    Univ Chicago, Dev Med, Chicago, IL 60637 USA..
    Melnick, Ari
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA..
    Guo, Shang
    Zhengzhou Univ, Affiliated Hosp 2, Shanghai 200233, Peoples R China..
    Blume, Alexander
    Max Delbrueck Ctr Mol Med, Berlin Inst Med Syst Biol, Bioinformat & Omics Data Sci Platform, Berlin, Germany..
    Franke, Vedran
    Max Delbrueck Ctr Mol Med, Berlin Inst Med Syst Biol, Bioinformat & Omics Data Sci Platform, Berlin, Germany..
    Ibanez de Caceres, Inmaculada
    EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.;IdiPAZ, Canc Epigenet Lab, INGEMM, Madrid, Spain..
    Rodriguez-Antolin, Carlos
    EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.;IdiPAZ, Canc Epigenet Lab, INGEMM, Madrid, Spain..
    Rosas, Rocio
    EATRIS ERIC European Infrastruct Translat Med, De Boelelaan 1118, NL-1081 HZ Amsterdam, Netherlands.;IdiPAZ, Canc Epigenet Lab, INGEMM, Madrid, Spain..
    Davis, Justin Wade
    AbbVie Genom Res Ctr, 1 N Waukegan Rd, N Chicago, IL 60036 USA..
    Ishii, Jennifer
    New York Genome Ctr, New York, NY 10013 USA..
    Megherbi, Dalila B.
    Univ Massachusetts Lowell, Francis Coll Engn, CMINDS Res Ctr, Lowell, MA 01854 USA..
    Xiao, Wenming
    US FDA, Ctr Devices & Radiol Hlth, 10903 New Hampshire Ave, Silver Spring, MD 20993 USA..
    Liao, Will
    New York Genome Ctr, New York, NY 10013 USA..
    Xu, Joshua
    US FDA, Div Bioinformat & Biostat, Natl Ctr Toxicol Res, 3900 NCTR Rd, Jefferson, AR 72079 USA..
    Hong, Huixiao
    US FDA, Div Bioinformat & Biostat, Natl Ctr Toxicol Res, 3900 NCTR Rd, Jefferson, AR 72079 USA..
    Ning, Baitang
    US FDA, Div Bioinformat & Biostat, Natl Ctr Toxicol Res, 3900 NCTR Rd, Jefferson, AR 72079 USA..
    Tong, Weida
    US FDA, Div Bioinformat & Biostat, Natl Ctr Toxicol Res, 3900 NCTR Rd, Jefferson, AR 72079 USA..
    Akalin, Altuna
    Max Delbrueck Ctr Mol Med, Berlin Inst Med Syst Biol, Bioinformat & Omics Data Sci Platform, Berlin, Germany..
    Wang, Yunliang
    Zhengzhou Univ, Affiliated Hosp 2, Shanghai 200233, Peoples R China..
    Deng, Youping
    Univ Hawaii, Dept Quantitat Hlth Sci, John A Burns Sch Med, Honolulu, HI 96813 USA..
    Mason, Christopher E.
    Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10021 USA.;Weill Cornell Med, HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsau, New York, NY 10021 USA.;Feil Family Brain & Mind Res Inst, New York, NY 10065 USA.;Weill Cornell Med, WorldQuant Initiat Quantitat Predict, New York, NY 10021 USA..
    The SEQC2 epigenomics quality control (EpiQC) study2021In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 22, no 1, article id 332Article in journal (Refereed)
    Abstract [en]

    Background

    Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA’s Epigenomics Quality Control Group.

    Results

    Each sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms.

    Conclusions

    The data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.

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  • 14.
    Franco, Irene
    et al.
    Karolinska Inst, Ctr Innovat Med, Dept Biosci & Nutr, Huddinge, Sweden.
    Helgadottir, Hafdis T.
    Karolinska Inst, Ctr Innovat Med, Dept Biosci & Nutr, Huddinge, Sweden.
    Moggio, Aldo
    Karolinska Inst, Integrated Cardio Metab Ctr, Dept Med Huddinge, Huddinge, Sweden.
    Larsson, Malin
    Linkoping Univ, Dept Phys Chem & Biol, Sci Life Lab, Linkoping, Sweden.
    Vrtacnik, Peter
    Karolinska Inst, Ctr Innovat Med, Dept Biosci & Nutr, Huddinge, Sweden.
    Johansson, Anna C. V.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Norgren, Nina
    Umea Univ, Dept Mol Biol, Sci Life Lab, Umea, Sweden.
    Lundin, Par
    Karolinska Inst, Ctr Innovat Med, Dept Biosci & Nutr, Huddinge, Sweden;Stockholm Univ, DBB, Sci Life Lab, Stockholm, Sweden.
    Mas-Ponte, David
    Barcelona Inst Sci & Technol, Genome Data Sci, Inst Res Biomed IRB Barcelona, Barcelona 08028, Spain.
    Nordstrom, Johan
    Karolinska Univ Hosp, Karolinska Inst, Dept Clin Sci Intervent & Technol, Div Transplantat Surg, Huddinge, Sweden.
    Lundgren, Torbjorn
    Karolinska Univ Hosp, Karolinska Inst, Dept Clin Sci Intervent & Technol, Div Transplantat Surg, Huddinge, Sweden.
    Stenvinkel, Peter
    Karolinska Univ Hosp, Karolinska Inst, Div Renal Med, Dept Clin Sci Intervent & Technol, Huddinge, Sweden.
    Wennberg, Lars
    Karolinska Univ Hosp, Karolinska Inst, Dept Clin Sci Intervent & Technol, Div Transplantat Surg, Huddinge, Sweden.
    Supek, Fran
    Barcelona Inst Sci & Technol, Genome Data Sci, Inst Res Biomed IRB Barcelona, Barcelona 08028, Spain;ICREA, Barcelona, Spain.
    Eriksson, Maria
    Karolinska Inst, Ctr Innovat Med, Dept Biosci & Nutr, Huddinge, Sweden.
    Whole genome DNA sequencing provides an atlas of somatic mutagenesis in healthy human cells and identifies a tumor-prone cell type2019In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 20, no 1, article id 285Article in journal (Refereed)
    Abstract [en]

    Background: The lifelong accumulation of somatic mutations underlies age-related phenotypes and cancer. Mutagenic forces are thought to shape the genome of aging cells in a tissue-specific way. Whole genome analyses of somatic mutation patterns, based on both types and genomic distribution of variants, can shed light on specific processes active in different human tissues and their effect on the transition to cancer. Results: To analyze somatic mutation patterns, we compile a comprehensive genetic atlas of somatic mutations in healthy human cells. High-confidence variants are obtained from newly generated and publicly available whole genome DNA sequencing data from single non-cancer cells, clonally expanded in vitro. To enable a well-controlled comparison of different cell types, we obtain single genome data (92% mean coverage) from multi-organ biopsies from the same donors. These data show multiple cell types that are protected from mutagens and display a stereotyped mutation profile, despite their origin from different tissues. Conversely, the same tissue harbors cells with distinct mutation profiles associated to different differentiation states. Analyses of mutation rate in the coding and non-coding portions of the genome identify a cell type bearing a unique mutation pattern characterized by mutation enrichment in active chromatin, regulatory, and transcribed regions. Conclusions: Our analysis of normal cells from healthy donors identifies a somatic mutation landscape that enhances the risk of tumor transformation in a specific cell population from the kidney proximal tubule. This unique pattern is characterized by high rate of mutation accumulation during adult life and specific targeting of expressed genes and regulatory regions.

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  • 15.
    Fuxelius, Hans-Henrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Darby, Alistair C.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Cho, N. H.
    Andersson, Siv G. E.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Visualization of pseudogenes in intracellular bacteria reveals the different tracks to gene destruction2008In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 9, no 2, p. R42-Article in journal (Refereed)
    Abstract [en]

    Background: Pseudogenes reveal ancestral gene functions. Some obligate intracellular bacteria, such as Mycobacterium leprae and Rickettsia spp., carry substantial fractions of pseudogenes. Until recently, horizontal gene transfers were considered to be rare events in obligate host-associated bacteria. Results: We present a visualization tool that displays the relationships and positions of degraded and partially overlapping gene sequences in multiple genomes. With this tool we explore the origin and deterioration patterns of the Rickettsia pseudogenes and find that variably present genes and pseudogenes tend to have been acquired more recently, are more divergent in sequence, and exhibit a different functional profile compared with genes conserved across all species. Overall, the origin of only one-quarter of the variable genes and pseudogenes can be traced back to the common ancestor of Rickettsia and the outgroup genera Orientia and Wolbachia. These sequences contain only a few disruptive mutations and show a broad functional distribution profile, much like the core genes. The remaining genes and pseudogenes are extensively degraded or solely present in a single species. Their functional profile was heavily biased toward the mobile gene pool and genes for components of the cell wall and the lipopolysaccharide. Conclusion: Reductive evolution of the vertically inherited genomic core accounts for 25% of the predicted genes in the variable segments of the Rickettsia genomes, whereas 75% stems from the flux of the mobile gene pool along with genes for cell surface structures. Thus, most of the variably present genes and pseudogenes in Rickettsia have arisen from recent acquisitions.

  • 16.
    Genshaft, Alex S.
    et al.
    MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;MIT, Dept Chem, Cambridge, MA 02139 USA.;Broad Inst MIT & Harvard, Cambridge, MA USA.;MIT, Ragon Inst Massachusetts Gen Hosp, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;Harvard Univ, Cambridge, MA 02138 USA..
    Li, Shuqiang
    Broad Inst MIT & Harvard, Cambridge, MA USA..
    Gallant, Caroline J.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Darmanis, Spyros
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Sci Life Lab, Uppsala, Sweden.;Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA.;Stanford Univ, Dept Appl Phys, Stanford, CA 94305 USA.;Howard Hughes Med Inst, Stanford, CA USA..
    Prakadan, Sanjay M.
    MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;MIT, Dept Chem, Cambridge, MA 02139 USA.;Broad Inst MIT & Harvard, Cambridge, MA USA.;MIT, Ragon Inst Massachusetts Gen Hosp, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;Harvard Univ, Cambridge, MA 02138 USA..
    Ziegler, Carly G. K.
    MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;Broad Inst MIT & Harvard, Cambridge, MA USA.;MIT, Ragon Inst Massachusetts Gen Hosp, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;Harvard Univ, Cambridge, MA 02138 USA.;Harvard Univ, Div Hlth Sci & Technol, Cambridge, MA 02138 USA.;MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA..
    Lundberg, Martin
    Olink Prote, Uppsala, Sweden..
    Fredriksson, Simon
    Olink Prote, Uppsala, Sweden..
    Hong, Joyce
    MIT, Dept Elect Engn & Comp Sci, Cambridge, MA 02139 USA..
    Regev, Aviv
    Broad Inst MIT & Harvard, Cambridge, MA USA.;MIT, Dept Biol, Boston, MA 02142 USA.;MIT, Koch Inst, Boston, MA 02142 USA.;Howard Hughes Med Inst, Chevy Chase, MD 20815 USA..
    Livak, Kenneth J.
    Fluidigm Corp, San Francisco, CA 94080 USA..
    Landegren, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Shalek, Alex K.
    MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;MIT, Dept Chem, Cambridge, MA 02139 USA.;Broad Inst MIT & Harvard, Cambridge, MA USA.;MIT, Ragon Inst Massachusetts Gen Hosp, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;Harvard Univ, Cambridge, MA 02138 USA.;Harvard Univ, Div Hlth Sci & Technol, Cambridge, MA 02138 USA.;MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA..
    Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction2016In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 17, article id 188Article in journal (Refereed)
    Abstract [en]

    We present a scalable, integrated strategy for coupled protein and RNA detection from single cells. Our approach leverages the DNA polymerase activity of reverse transcriptase to simultaneously perform proximity extension assays and complementary DNA synthesis in the same reaction. Using the Fluidigm C1 (TM) system, we profile the transcriptomic and proteomic response of a human breast adenocarcinoma cell line to a chemical perturbation, benchmarking against in situ hybridizations and immunofluorescence staining, as well as recombinant proteins, ERCC Spike-Ins, and population lysate dilutions. Through supervised and unsupervised analyses, we demonstrate synergies enabled by simultaneous measurement of single-cell protein and RNA abundances. Collectively, our generalizable approach highlights the potential for molecular metadata to inform highly-multiplexed single-cell analyses.

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  • 17. Gerardo, Nicole M
    et al.
    Altincicek, Boran
    Anselme, Caroline
    Atamian, Hagop
    Barribeau, Seth M
    de Vos, Martin
    Duncan, Elizabeth J
    Evans, Jay D
    Gabaldón, Toni
    Ghanim, Murad
    Heddi, Adelaziz
    Kaloshian, Isgouhi
    Latorre, Amparo
    Moya, Andres
    Nakabachi, Atsushi
    Parker, Benjamin J
    Pérez-Brocal, Vincente
    Pignatelli, Miguel
    Rahbé, Yvan
    Ramsey, John S
    Spragg, Chelsea J
    Tamames, Javier
    Tamarit, Daniel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Evolution.
    Tamborindeguy, Cecilia
    Vincent-Monegat, Caroline
    Vilcinskas, Andreas
    Immunity and other defenses in pea aphids, Acyrthosiphon pisum.2010In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 11, no 2Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Recent genomic analyses of arthropod defense mechanisms suggest conservation of key elements underlying responses to pathogens, parasites and stresses. At the center of pathogen-induced immune responses are signaling pathways triggered by the recognition of fungal, bacterial and viral signatures. These pathways result in the production of response molecules, such as antimicrobial peptides and lysozymes, which degrade or destroy invaders. Using the recently sequenced genome of the pea aphid (Acyrthosiphon pisum), we conducted the first extensive annotation of the immune and stress gene repertoire of a hemipterous insect, which is phylogenetically distantly related to previously characterized insects models.

    RESULTS: Strikingly, pea aphids appear to be missing genes present in insect genomes characterized to date and thought critical for recognition, signaling and killing of microbes. In line with results of gene annotation, experimental analyses designed to characterize immune response through the isolation of RNA transcripts and proteins from immune-challenged pea aphids uncovered few immune-related products. Gene expression studies, however, indicated some expression of immune and stress-related genes.

    CONCLUSIONS: The absence of genes suspected to be essential for the insect immune response suggests that the traditional view of insect immunity may not be as broadly applicable as once thought. The limitations of the aphid immune system may be representative of a broad range of insects, or may be aphid specific. We suggest that several aspects of the aphid life style, such as their association with microbial symbionts, could facilitate survival without strong immune protection.

  • 18. Glass, Daniel
    et al.
    Viñuela, Ana
    Davies, Matthew N
    Ramasamy, Adaikalavan
    Parts, Leopold
    Knowles, David
    Brown, Andrew A
    Hedman, Åsa K
    Small, Kerrin S
    Buil, Alfonso
    Grundberg, Elin
    Nica, Alexandra C
    Di Meglio, Paola
    Nestle, Frank O
    Ryten, Mina
    Durbin, Richard
    McCarthy, Mark I
    Deloukas, Panagiotis
    Dermitzakis, Emmanouil T
    Weale, Michael E
    Bataille, Veronique
    Spector, Tim D
    Gene expression changes with age in skin, adipose tissue, blood and brain.2013In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 14, no 7Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Previous studies have demonstrated that gene expression levels change with age. These changes are hypothesized to influence the aging rate of an individual. We analyzed gene expression changes with age in abdominal skin, subcutaneous adipose tissue and lymphoblastoid cell lines in 856 female twins in the age range of 39-85 years. Additionally, we investigated genotypic variants involved in genotype-by-age interactions to understand how the genomic regulation of gene expression alters with age.

    RESULTS: Using a linear mixed model, differential expression with age was identified in 1,672 genes in skin and 188 genes in adipose tissue. Only two genes expressed in lymphoblastoid cell lines showed significant changes with age. Genes significantly regulated by age were compared with expression profiles in 10 brain regions from 100 postmortem brains aged 16 to 83 years. We identified only one age-related gene common to the three tissues. There were 12 genes that showed differential expression with age in both skin and brain tissue and three common to adipose and brain tissues.

    CONCLUSIONS: Skin showed the most age-related gene expression changes of all the tissues investigated, with many of the genes being previously implicated in fatty acid metabolism, mitochondrial activity, cancer and splicing. A significant proportion of age-related changes in gene expression appear to be tissue-specific with only a few genes sharing an age effect in expression across tissues. More research is needed to improve our understanding of the genetic influences on aging and the relationship with age-related diseases.

  • 19. Gnerre, Sante
    et al.
    Lander, Eric S
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Jaffe, David B
    Assisted assembly: how to improve a de novo genome assembly by using related species2009In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 10, no 8, p. R88-Article in journal (Refereed)
    Abstract [en]

    We describe a new assembly algorithm, where a genome assembly with low sequence coverage, either throughout the genome or locally, due to cloning bias, is considerably improved through an assisting process via a related genome. We show that the information provided by aligning the whole-genome shotgun reads of the target against a reference genome can be used to substantially improve the quality of the resulting assembly.

  • 20. Götz, Dorothee
    et al.
    Paytubi, Sonia
    Munro, Stacey
    Lundgren, Magnus
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Bernander, Rolf
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    White, Malcolm F.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Molecular Evolution.
    Responses of hyperthermophilic crenarchaea to UV irradiation2007In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 8, no 10, p. R220-Article in journal (Refereed)
    Abstract [en]

    Background:

    DNA damage leads to cellular responses that include the increased expression of DNA repair genes, repression of DNA replication and alterations in cellular metabolism. Archaeal information processing pathways resemble those in eukaryotes, but archaeal damage response pathways remain poorly understood.

    Results:

    We analyzed the transcriptional response to UV irradiation in two related crenarchaea, Sulfolobus solfataricus and Sulfolobus acidocaldarius. Sulfolobus species encounter high levels of DNA damage in nature, as they inhabit high temperature, aerobic environments and are exposed to sunlight. No increase in expression of DNA repair genes following UV irradiation was observed. There was, however, a clear transcriptional response, including repression of DNA replication and chromatin proteins. Differential effects on the expression of the three transcription factor B ( tfb) genes hint at a mechanism for the modulation of transcriptional patterns in response to DNA damage. TFB3, which is strongly induced following UV irradiation, competes with TFB1 for binding to RNA polymerase in vitro, and may act as a repressor of transcription or an alternative transcription factor for certain promoters.

    Conclusion:

    A clear response to DNA damage was observed, with down-regulation of the DNA replication machinery, changes in transcriptional regulatory proteins, and up-regulation of the biosynthetic enzymes for beta-carotene, which has UV protective properties, and proteins that detoxify reactive oxygen species. However, unlike eukaryotes and bacteria, there was no induction of DNA repair proteins in response to DNA damage, probably because these are expressed constitutively to deal with increased damage arising due to high growth temperatures.

  • 21. Herman, Jonathan D.
    et al.
    Rice, Daniel P.
    Ribacke, Ulf
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Microbiology.
    Silterra, Jacob
    Deik, Amy A.
    Moss, Eli L.
    Broadbent, Kate M.
    Neafsey, Daniel E.
    Desai, Michael M.
    Clish, Clary B.
    Mazitschek, Ralph
    Wirth, Dyann F.
    A genomic and evolutionary approach reveals non-genetic drug resistance in malaria2014In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 15, no 11, p. 511-Article in journal (Refereed)
    Abstract [en]

    Background: Drug resistance remains a major public health challenge for malaria treatment and eradication. Individual loci associated with drug resistance to many antimalarials have been identified, but their epistasis with other resistance mechanisms has not yet been elucidated. Results: We previously described two mutations in the cytoplasmic prolyl-tRNA synthetase (cPRS) gene that confer resistance to halofuginone. We describe here the evolutionary trajectory of halofuginone resistance of two independent drug resistance selections in Plasmodium falciparum. Using this novel methodology, we discover an unexpected non-genetic drug resistance mechanism that P. falciparum utilizes before genetic modification of the cPRS. P. falciparum first upregulates its proline amino acid homeostasis in response to halofuginone pressure. We show that this non-genetic adaptation to halofuginone is not likely mediated by differential RNA expression and precedes mutation or amplification of the cPRS gene. By tracking the evolution of the two drug resistance selections with whole genome sequencing, we further demonstrate that the cPRS locus accounts for the majority of genetic adaptation to halofuginone in P. falciparum. We further validate that copy-number variations at the cPRS locus also contribute to halofuginone resistance. Conclusions: We provide a three-step model for multi-locus evolution of halofuginone drug resistance in P. falciparum. Informed by genomic approaches, our results provide the first comprehensive view of the evolutionary trajectory malaria parasites take to achieve drug resistance. Our understanding of the multiple genetic and non-genetic mechanisms of drug resistance informs how we will design and pair future anti-malarials for clinical use.

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  • 22.
    Holland, Linda Z.
    et al.
    Univ Calif San Diego, Scripps Inst Oceanog, Marine Biol Res Div, La Jolla, CA 92093 USA.
    Ocampo Daza, Daniel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology. Univ Calif Merced, Sch Nat Sci, Merced, CA 95343 USA.
    A new look at an old question: when did the second whole genome duplication occur in vertebrate evolution?2018In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 19, article id 209Article in journal (Refereed)
    Abstract [en]

    A recent study used 61 extant animal genomes to reconstruct the chromosomes of the hypothetical amniote ancestor. Comparison of this karyotype to the 17 chordate linkage groups previously inferred in the ancestral chordate indicated that two whole genome duplications probably occurred in the lineage preceding the ancestral vertebrate.

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  • 23.
    Hughes, Diarmaid
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Evaluating genome dynamics: the constraints on rearrangements within bacterial genomes2000In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 1, no 6, p. 0006.1-0006.8Article, review/survey (Other academic)
    Abstract [en]

    Inversions and translocations distinguish the genomes of closely related bacterial species, but most of these rearrangements preserve the relationship between the rearranged fragments and the axis of chromosome replication. Within species, such rearrangements are found less frequently, except in the case of clinical isolates of human pathogens, where rearrangements are very frequent.

  • 24.
    Hunt, George
    et al.
    Stockholm Univ, Wenner Gren Inst, Dept Mol Biosci, Stockholm, Sweden..
    Vaid, Roshan
    Stockholm Univ, Wenner Gren Inst, Dept Mol Biosci, Stockholm, Sweden..
    Pirogov, Sergei
    Stockholm Univ, Wenner Gren Inst, Dept Mol Biosci, Stockholm, Sweden..
    Pfab, Alexander
    Stockholm Univ, Wenner Gren Inst, Dept Mol Biosci, Stockholm, Sweden..
    Ziegenhain, Christoph
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Sandberg, Rickard
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Reimegård, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Mannervik, Mattias
    Stockholm Univ, Wenner Gren Inst, Dept Mol Biosci, Stockholm, Sweden..
    Tissue-specific RNA Polymerase II promoter-proximal pause release and burst kinetics in a Drosophila embryonic patterning network2024In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 25, no 1, article id 2Article in journal (Refereed)
    Abstract [en]

    Background

    Formation of tissue-specific transcriptional programs underlies multicellular development, including dorsoventral (DV) patterning of the Drosophila embryo. This involves interactions between transcriptional enhancers and promoters in a chromatin context, but how the chromatin landscape influences transcription is not fully understood.

    Results

    Here we comprehensively resolve differential transcriptional and chromatin states during Drosophila DV patterning. We find that RNA Polymerase II pausing is established at DV promoters prior to zygotic genome activation (ZGA), that pausing persists irrespective of cell fate, but that release into productive elongation is tightly regulated and accompanied by tissue-specific P-TEFb recruitment. DV enhancers acquire distinct tissue-specific chromatin states through CBP-mediated histone acetylation that predict the transcriptional output of target genes, whereas promoter states are more tissue-invariant. Transcriptome-wide inference of burst kinetics in different cell types revealed that while DV genes are generally characterized by a high burst size, either burst size or frequency can differ between tissues.

    Conclusions

    The data suggest that pausing is established by pioneer transcription factors prior to ZGA and that release from pausing is imparted by enhancer chromatin state to regulate bursting in a tissue-specific manner in the early embryo. Our results uncover how developmental patterning is orchestrated by tissue-specific bursts of transcription from Pol II primed promoters in response to enhancer regulatory cues.

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  • 25. Hurst, Laurence D.
    et al.
    Sachenkova, Oxana
    Daub, Carsten
    Forrest, Alistair R. R.
    Huminiecki, Lukasz
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    A simple metric of promoter architecture robustly predicts expression breadth of human genes suggesting that most transcription factors are positive regulators2014In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 15, no 7, p. 413-Article in journal (Refereed)
    Abstract [en]

    Background: Conventional wisdom holds that, owing to the dominance of features such as chromatin level control, the expression of a gene cannot be readily predicted from knowledge of promoter architecture. This is reflected, for example, in a weak or absent correlation between promoter divergence and expression divergence between paralogs. However, an inability to predict may reflect an inability to accurately measure or employment of the wrong parameters. Here we address this issue through integration of two exceptional resources: ENCODE data on transcription factor binding and the FANTOM5 high-resolution expression atlas. Results: Consistent with the notion that in eukaryotes most transcription factors are activating, the number of transcription factors binding a promoter is a strong predictor of expression breadth. In addition, evolutionarily young duplicates have fewer transcription factor binders and narrower expression. Nonetheless, we find several binders and cooperative sets that are disproportionately associated with broad expression, indicating that models more complex than simple correlations should hold more predictive power. Indeed, a machine learning approach improves fit to the data compared with a simple correlation. Machine learning could at best moderately predict tissue of expression of tissue specific genes. Conclusions: We find robust evidence that some expression parameters and paralog expression divergence are strongly predictable with knowledge of transcription factor binding repertoire. While some cooperative complexes can be identified, consistent with the notion that most eukaryotic transcription factors are activating, a simple predictor, the number of binding transcription factors found on a promoter, is a robust predictor of expression breadth.

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    fulltext
  • 26.
    Hård, Joanna
    et al.
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Al Hakim, Ezeddin
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Kindblom, Marie
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Björklund, Åsa K.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Sennblad, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Demirci, Ilke
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Paterlini, Marta
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Reu, Pedro
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Borgström, Erik
    KTH Royal Inst Technol, Div Gene Technol, Scilifelab, Solna, Sweden.
    Ståhl, Patrik L.
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Michaelsson, Jakob
    Karolinska Inst, Dept Med, Ctr Infect Med, Huddinge, Sweden.
    Mold, Jeff E.
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Frisen, Jonas
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden.
    Conbase: a software for unsupervised discovery of clonal somatic mutations in single cells through read phasing2019In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 20, article id 68Article in journal (Refereed)
    Abstract [en]

    Accurate variant calling and genotyping represent major limiting factors for downstream applications of single-cell genomics. Here, we report Conbase for the identification of somatic mutations in single-cell DNA sequencing data. Conbase leverages phased read data from multiple samples in a dataset to achieve increased confidence in somatic variant calls and genotype predictions. Comparing the performance of Conbase to three other methods, we find that Conbase performs best in terms of false discovery rate and specificity and provides superior robustness on simulated data, in vitro expanded fibroblasts and clonal lymphocyte populations isolated directly from a healthy human donor.

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  • 27.
    Höijer, Ida
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Johansson, Josefin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Gudmundsson, Sanna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab. Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA.
    Chin, Chen-Shan
    Bunikis, Ignas
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Häggqvist, Susana
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Emmanouilidou, Anastasia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wilbe, Maria
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    den Hoed, Marcel
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Bondeson, Marie-Louise
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Feuk, Lars
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Gyllensten, Ulf
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Ameur, Adam
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia.
    Amplification-free long-read sequencing reveals unforeseen CRISPR-Cas9 off-target activity2020In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 21, no 1, article id 290Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: One ongoing concern about CRISPR-Cas9 genome editing is that unspecific guide RNA (gRNA) binding may induce off-target mutations. However, accurate prediction of CRISPR-Cas9 off-target activity is challenging. Here, we present SMRT-OTS and Nano-OTS, two novel, amplification-free, long-read sequencing protocols for detection of gRNA-driven digestion of genomic DNA by Cas9 in vitro.

    RESULTS: The methods are assessed using the human cell line HEK293, re-sequenced at 18x coverage using highly accurate HiFi SMRT reads. SMRT-OTS and Nano-OTS are first applied to three different gRNAs targeting HEK293 genomic DNA, resulting in a set of 55 high-confidence gRNA cleavage sites identified by both methods. Twenty-five of these sites are not reported by off-target prediction software, either because they contain four or more single nucleotide mismatches or insertion/deletion mismatches, as compared with the human reference. Additional experiments reveal that 85% of Cas9 cleavage sites are also found by other in vitro-based methods and that on- and off-target sites are detectable in gene bodies where short-reads fail to uniquely align. Even though SMRT-OTS and Nano-OTS identify several sites with previously validated off-target editing activity in cells, our own CRISPR-Cas9 editing experiments in human fibroblasts do not give rise to detectable off-target mutations at the in vitro-predicted sites. However, indel and structural variation events are enriched at the on-target sites.

    CONCLUSIONS: Amplification-free long-read sequencing reveals Cas9 cleavage sites in vitro that would have been difficult to predict using computational tools, including in dark genomic regions inaccessible by short-read sequencing.

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  • 28.
    Ison, Jon
    et al.
    Tech Univ Denmark, Natl Life Sci Supercomp Ctr, Bldg 208, DK-2800 Lyngby, Denmark.
    Ienasescu, Hans
    Tech Univ Denmark, Natl Life Sci Supercomp Ctr, Bldg 208, DK-2800 Lyngby, Denmark.
    Chmura, Piotr
    Univ Copenhagen, Novo Nordisk Fdn Ctr Prot Res, Fac Hlth & Med Sci, DK-2200 Copenhagen, Denmark.
    Rydza, Emil
    Univ Copenhagen, Novo Nordisk Fdn Ctr Prot Res, Fac Hlth & Med Sci, DK-2200 Copenhagen, Denmark.
    Menager, Herve
    Inst Pasteur, Hub Bioinformat & Biostat, C3BI USR, 3756 IP CNRS, Paris, France.
    Kalas, Matus
    Univ Bergen, Computat Biol Unit, Dept Informat, N-5020 Bergen, Norway.
    Schwammle, Veit
    Univ Southern Denmark, Dept Biochem & Mol Biol, Campusvej 55, DK-5230 Odense, Denmark;Univ Southern Denmark, VILLUM Ctr Bioanalyt Sci, Campusvej 55, DK-5230 Odense, Denmark.
    Gruening, Bjoern
    Albert Ludwigs Univ Freiburg, Dept Comp Sci, Georges Kohler Allee 106, D-79110 Freiburg, Germany.
    Beard, Niall
    Univ Manchester, Sch Comp Sci, Oxford Rd, Manchester M13 9PL, Lancs, England.
    Lopez, Rodrigo
    EMBL European Bioinformat Inst, Wellcome Trust Genome Campus, Cambridge CB10 1SD, England.
    Duvaud, Severine
    SIB Swiss Inst Bioinformat, Quartier Sorge Batiment Amphipole, CH-1015 Lausanne, Switzerland.
    Stockinger, Heinz
    SIB Swiss Inst Bioinformat, Quartier Sorge Batiment Amphipole, CH-1015 Lausanne, Switzerland.
    Persson, Bengt
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Varekova, Radka Svobodova
    Masaryk Univ Brno, CEITEC Cent European Inst Technol, Kamenice 5, Brno 62500, Czech Republic.
    Racek, Tomas
    Masaryk Univ Brno, CEITEC Cent European Inst Technol, Kamenice 5, Brno 62500, Czech Republic.
    Vondrasek, Jiri
    Czech Acad Sci, Inst Organ Chem & Biochem, Flemingovo Namesti 2, Prague 16000, Czech Republic.
    Peterson, Hedi
    Univ Tartu, Inst Comp Sci, ELIXIR EE, J Liivi 2, Tartu, Estonia.
    Salumets, Ahto
    Univ Tartu, Inst Comp Sci, ELIXIR EE, J Liivi 2, Tartu, Estonia.
    Jonassen, Inge
    Hooft, Rob
    Dutch Techcentre Life Sci, Jaarbeurspl 6, NL-3521 AL Utrecht, Netherlands.
    Nyronen, Tommi
    CSC IT Ctr Sci, POB 405, FI-02101 Espoo, Finland.
    Valencia, Alfonso
    BSC, Barcelona 08034, Spain;ICREA, Pg Lluis Co 23, Barcelona 08010, Spain.
    Capella, Salvador
    BSC, Barcelona 08034, Spain.
    Gelpi, Josep
    BSC, Barcelona 08034, Spain;Univ Barcelona, INB BSC CNS, Dept Biochem & Mol Biomed, Barcelona, Spain.
    Zambelli, Federico
    Natl Res Council CNR, Inst Biomembranes Bioenerget & Mol Biotechnol, Via Amendola 165-A, Bari, Italy;Univ Milan, Dept Biosci, Via Celoria 26, Milan, Italy.
    Savakis, Babis
    Biomed Sci Res Ctr, Alexander Fleming 34 Al Fleming Str, Vari 16672, Greece.
    Leskosek, Brane
    Univ Ljubljana, Fac Med, ELIXIR SI, Vrazov Trg 2, SI-1000 Ljubljana, Slovenia.
    Rapacki, Kristoffer
    Blanchet, Christophe
    CNRS, UMS 3601, Inst Francais Bioinformat, IFB Core, 2 Rue Gaston Cremieux, F-91000 Evry, France.
    Jimenez, Rafael
    ELIXIR Hub, Wellcome Trust Genome Campus, Cambridge CB10 1SD, England.
    Oliveira, Arlindo
    Inst Super Tecn, INESC ID, R Alves Redol 9, Lisbon, Portugal.
    Vriend, Gert
    Radboud Univ Nijmegen, Med Ctr, Postbus 9101, NL-6500 HB Nijmegen, Netherlands.
    Collin, Olivier
    Plateforme GenOuest Univ Rennes, INRIA, CNRS, IRISA, F-35000 Rennes, France.
    van Helden, Jacques
    Aix Marseille Univ, INSERM, Lab Theory & Approaches Genome Complex TAGC, Marseille, France.
    Longreen, Peter
    Tech Univ Denmark, Natl Life Sci Supercomp Ctr, Bldg 208, DK-2800 Lyngby, Denmark.
    Brunak, Soren
    Univ Copenhagen, Novo Nordisk Fdn Ctr Prot Res, Fac Hlth & Med Sci, DK-2200 Copenhagen, Denmark;Tech Univ Denmark, Dept Bio & Hlth Informat, Bldg 208, DK-2800 Lyngby, Denmark.
    The bio.tools registry of software tools and data resources for the life sciences2019In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 20, no 1, article id 164Article in journal (Refereed)
    Abstract [en]

    Bioinformaticians and biologists rely increasingly upon workflows for the flexible utilization of the many life science tools that are needed to optimally convert data into knowledge. We outline a pan-European enterprise to provide a catalogue () of tools and databases that can be used in these workflows. bio.tools not only lists where to find resources, but also provides a wide variety of practical information.

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  • 29.
    Kanoni, Stavroula
    et al.
    Queen Mary Univ London, Barts & London Sch Med & Dent, William Harvey Res Inst, Charterhouse Sq, London EC1M 6BQ, England.
    Gustafsson, Stefan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Ingelsson, Erik
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Stanford Univ, Sch Med, Dept Med, Div Cardiovasc Med, Stanford, CA 94305 USA;Stanford Univ, Stanford Cardiovasc Inst, Stanford, CA 94305 USA;Stanford Univ, Stanford Diabet Res Ctr, Stanford, CA 94305 USA.
    Demirkan, Ayse
    Univ Med Ctr Rotterdam, Dept Epidemiol, Erasmus MC, Rotterdam, Netherlands;Univ Surrey, Dept Clin & Expt Res, Sect Stat Multiom, Guildford, Surrey, England.
    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis2022In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 23, article id 268Article in journal (Refereed)
    Abstract [en]

    Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

    Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N=1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

    Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

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  • 30.
    Karawita, Anjana C.
    et al.
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.;Commonwealth Sci & Ind Res Org, Australian Ctr Dis Preparedness, 5 Portarlington Rd, Geelong 3220, Vic, Australia.
    Cheng, Yuanyuan
    Univ Sydney, Sch Life & Environm Sci, Sydney 2006, NSW, Australia.
    Chew, Keng Yih
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Challagulla, Arjun
    Commonwealth Sci & Ind Res Org, Australian Ctr Dis Preparedness, 5 Portarlington Rd, Geelong 3220, Vic, Australia.
    Kraus, Robert
    Max Planck Inst Anim Behav, Dept Migrat, ,, D-78315 Radolfzell am Bodensee, Germany.;Univ Konstanz, Dept Biol, D-78457 Constance, Germany.
    Mueller, Ralf C.
    Max Planck Inst Anim Behav, Dept Migrat, ,, D-78315 Radolfzell am Bodensee, Germany.;Univ Konstanz, Dept Biol, D-78457 Constance, Germany.
    Tong, Marcus Z. W.
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Hulme, Katina D.
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Bielefeldt-Ohmann, Helle
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Steele, Lauren E.
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Wu, Melanie
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Sng, Julian
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Noye, Ellesandra
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Bruxner, Timothy J.
    Univ Queensland, Inst Mol Biosci, St Lucia 4072, Qld, Australia.
    Au, Gough G.
    Commonwealth Sci & Ind Res Org, Australian Ctr Dis Preparedness, 5 Portarlington Rd, Geelong 3220, Vic, Australia.
    Lowther, Suzanne
    Commonwealth Sci & Ind Res Org, Australian Ctr Dis Preparedness, 5 Portarlington Rd, Geelong 3220, Vic, Australia.
    Blommaert, Julie
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Systematic Biology. New Zealand Inst Plant & Food Res Ltd, Nelson 7010, New Zealand.
    Suh, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Systematic Biology. Univ East Anglia, Sch Biol Sci, Norwich Res Pk, Norwich NR4 7TU, Norfolk, England.
    McCauley, Alexander J.
    Commonwealth Sci & Ind Res Org, Australian Ctr Dis Preparedness, 5 Portarlington Rd, Geelong 3220, Vic, Australia.
    Kaur, Parwinder
    Univ Western Australia, Sch Agr & Environm, Perth, WA 6009, Australia.
    Dudchenko, Olga
    Baylor Coll Med, Ctr Genome Architecture, Dept Mol & Human Genet, Houston, TX 77030 USA.;Rice Univ, Ctr Theoret Biol Phys, Dept Comp Sci, Houston, TX 77030 USA.
    Aiden, Erez
    Univ Western Australia, Sch Agr & Environm, Perth, WA 6009, Australia.;Baylor Coll Med, Ctr Genome Architecture, Dept Mol & Human Genet, Houston, TX 77030 USA.;Rice Univ, Ctr Theoret Biol Phys, Dept Comp Sci, Houston, TX 77030 USA.;Broad Inst & Harvard, Cambridge, MA 02139 USA.;ShanghaiTech, Shanghai Inst Adv Immunochem Studies, ,, Pudong 201210, Peoples R China.
    Fedrigo, Olivier
    Rockefeller Univ, Vertebrate Genome Lab, New York, NY 10065 USA.
    Formenti, Giulio
    Rockefeller Univ, Vertebrate Genome Lab, New York, NY 10065 USA.
    Mountcastle, Jacquelyn
    Rockefeller Univ, Vertebrate Genome Lab, New York, NY 10065 USA.
    Chow, William
    Welcome Sanger Inst, Tree Life, Cambridge CB10 1SA, England.
    Martin, Fergal J.
    European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England.
    Ogeh, Denye N.
    European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England.
    Thiaud-Nissen, Francoise
    NIH, Natl Ctr Biotechnol Informat, Natl Lib Med, Bethesda, MD USA.
    Howe, Kerstin
    Welcome Sanger Inst, Tree Life, Cambridge CB10 1SA, England.
    Tracey, Alan
    Welcome Sanger Inst, Tree Life, Cambridge CB10 1SA, England.
    Smith, Jacqueline
    Univ Edinburgh, Roslin Inst, Royal Dick Sch Vet Studies, Easter Bush Campus, Roslin EH25 9RG, Midlothian, Scotland.
    Kuo, Richard I.
    Univ Edinburgh, Roslin Inst, Royal Dick Sch Vet Studies, Easter Bush Campus, Roslin EH25 9RG, Midlothian, Scotland.
    Renfree, Marilyn B.
    Univ Melbourne, Sch Biosci, Melbourne, Vic 3052, Australia.
    Kimura, Takashi
    Hokkaido Univ, Fac Vet Med, Sapporo, Hokkaido 0600818, Japan.
    Sakoda, Yoshihiro
    Hokkaido Univ, Fac Vet Med, Sapporo, Hokkaido 0600818, Japan.
    McDougall, Mathew
    New Zealand Fish & Game Eastern Reg, Rotorua 3046, New Zealand.
    Spencer, Hamish G.
    Univ Otago, Dept Zool, Dunedin 9054, New Zealand.
    Pyne, Michael
    Currumbin Wildlife Sanctuary, Currumbin, Qld 4223, Australia.
    Tolf, Conny
    Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst EEMiS, SE-39182 Kalmar, Sweden.
    Waldenstroem, Jonas
    Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst EEMiS, SE-39182 Kalmar, Sweden.
    Jarvis, Erich D.
    Rockefeller Univ, Vertebrate Genome Lab, New York, NY 10065 USA.
    Baker, Michelle L.
    Commonwealth Sci & Ind Res Org, Australian Ctr Dis Preparedness, 5 Portarlington Rd, Geelong 3220, Vic, Australia.
    Burt, David W.
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    Short, Kirsty R.
    Univ Queensland, Sch Chem & Mol Biosci, St Lucia 4072, Qld, Australia.
    The swan genome and transcriptome, it is not all black and white2023In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 24, no 1, article id 13Article in journal (Refereed)
    Abstract [en]

    Background The Australian black swan (Cygnus atratus) is an iconic species with contrasting plumage to that of the closely related northern hemisphere white swans. The relative geographic isolation of the black swan may have resulted in a limited immune repertoire and increased susceptibility to infectious diseases, notably infectious diseases from which Australia has been largely shielded. Unlike mallard ducks and the mute swan (Cygnus olor), the black swan is extremely sensitive to highly pathogenic avian influenza. Understanding this susceptibility has been impaired by the absence of any available swan genome and transcriptome information.

    Results Here, we generate the first chromosome-length black and mute swan genomes annotated with transcriptome data, all using long-read based pipelines generated for vertebrate species. We use these genomes and transcriptomes to show that unlike other wild waterfowl, black swans lack an expanded immune gene repertoire, lack a key viral pattern-recognition receptor in endothelial cells and mount a poorly controlled inflammatory response to highly pathogenic avian influenza. We also implicate genetic differences in SLC45A2 gene in the iconic plumage of the black swan.

    Conclusion Together, these data suggest that the immune system of the black swan is such that should any avian viral infection become established in its native habitat, the black swan would be in a significant peril.

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  • 31. Karlsson, Elinor K
    et al.
    Sigurdsson, Snaevar
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Ivansson, Emma
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Thomas, Rachael
    Elvers, Ingegerd
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wright, Jason
    Howald, Cedric
    Tonomura, Noriko
    Perloski, Michele
    Swofford, Ross
    Biagi, Tara
    Fryc, Sarah
    Anderson, Nathan
    Courtay-Cahen, Celine
    Youell, Lisa
    Ricketts, Sally L
    Mandlebaum, Sarah
    Rivera, Patricio
    von Euler, Henrik
    Kisseberth, William C
    London, Cheryl A
    Lander, Eric S
    Couto, Guillermo
    Comstock, Kenine
    Starkey, Mike P
    Modiano, Jaime F
    Breen, Matthew
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Genome-wide analyses implicate 33 loci in heritable dog osteosarcoma, including regulatory variants near CDKN2A/B2013In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 14, no 12, article id R132Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Canine osteosarcoma is clinically nearly identical to the human disease, but is common and highly heritable, making genetic dissection feasible.

    RESULTS: Through genome-wide association analyses in three breeds (greyhounds, Rottweilers, and Irish wolfhounds), we identify 33 inherited risk loci explaining 55% to 85% of phenotype variance in each breed. The greyhound locus exhibiting the strongest association, located 150 kilobases upstream of the genes CDKN2A/B, is also the most rearranged locus in canine osteosarcoma tumors. The top germline candidate variant is found at a >90% frequency in Rottweilers and Irish wolfhounds, and alters an evolutionarily constrained element that we show has strong enhancer activity in human osteosarcoma cells. In all three breeds, osteosarcoma-associated loci and regions of reduced heterozygosity are enriched for genes in pathways connected to bone differentiation and growth. Several pathways, including one of genes regulated by miR124, are also enriched for somatic copy-number changes in tumors.

    CONCLUSIONS: Mapping a complex cancer in multiple dog breeds reveals a polygenic spectrum of germline risk factors pointing to specific pathways as drivers of disease.

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  • 32.
    Le Duc, Diana
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Functional Pharmacology.
    Renaud, Gabriel
    Krishnan, Arunkumar
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Functional Pharmacology.
    Almén, Markus Sällman
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Functional Pharmacology.
    Huynen, Leon
    Prohaska, Sonja J.
    Ongyerth, Matthias
    Bitarello, Barbara D.
    Schiöth, Helgi B.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Functional Pharmacology.
    Hofreiter, Michael
    Stadler, Peter F.
    Pruefer, Kay
    Lambert, David
    Kelso, Janet
    Schoeneberg, Torsten
    Kiwi genome provides insights into evolution of a nocturnal lifestyle2015In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16, article id 147Article in journal (Refereed)
    Abstract [en]

    Background: Kiwi, comprising five species from the genus Apteryx, are endangered, ground-dwelling bird species endemic to New Zealand. They are the smallest and only nocturnal representatives of the ratites. The timing of kiwi adaptation to a nocturnal niche and the genomic innovations, which shaped sensory systems and morphology to allow this adaptation, are not yet fully understood. Results: We sequenced and assembled the brown kiwi genome to 150-fold coverage and annotated the genome using kiwi transcript data and non-redundant protein information from multiple bird species. We identified evolutionary sequence changes that underlie adaptation to nocturnality and estimated the onset time of these adaptations. Several opsin genes involved in color vision are inactivated in the kiwi. We date this inactivation to the Oligocene epoch, likely after the arrival of the ancestor of modern kiwi in New Zealand. Genome comparisons between kiwi and representatives of ratites, Galloanserae, and Neoaves, including nocturnal and song birds, show diversification of kiwi's odorant receptors repertoire, which may reflect an increased reliance on olfaction rather than sight during foraging. Further, there is an enrichment of genes influencing mitochondrial function and energy expenditure among genes that are rapidly evolving specifically on the kiwi branch, which may also be linked to its nocturnal lifestyle. Conclusions: The genomic changes in kiwi vision and olfaction are consistent with changes that are hypothesized to occur during adaptation to nocturnal lifestyle in mammals. The kiwi genome provides a valuable genomic resource for future genome-wide comparative analyses to other extinct and extant diurnal ratites.

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  • 33.
    Liu, Shujing
    et al.
    Swedish Univ Agr Sci, Dept Plant Biol, S-75007 Uppsala, Sweden.;Linnean Ctr Plant Biol, S-75007 Uppsala, Sweden..
    Trejo-Arellano, Minerva S.
    Swedish Univ Agr Sci, Dept Plant Biol, S-75007 Uppsala, Sweden.;Linnean Ctr Plant Biol, S-75007 Uppsala, Sweden.;John Innes Ctr, Dept Cell & Dev Biol, Norwich NR4 7UH, Norfolk, England..
    Qiu, Yichun
    Swedish Univ Agr Sci, Dept Plant Biol, S-75007 Uppsala, Sweden.;Linnean Ctr Plant Biol, S-75007 Uppsala, Sweden.;Max Planck Inst Mol Plant Physiol, D-14476 Potsdam, Germany..
    Eklund, D. Magnus
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution.
    Koehler, Claudia
    Swedish Univ Agr Sci, Dept Plant Biol, S-75007 Uppsala, Sweden.;Linnean Ctr Plant Biol, S-75007 Uppsala, Sweden.;Max Planck Inst Mol Plant Physiol, D-14476 Potsdam, Germany..
    Hennig, Lars
    Swedish Univ Agr Sci, Dept Plant Biol, S-75007 Uppsala, Sweden.;Linnean Ctr Plant Biol, S-75007 Uppsala, Sweden..
    H2A ubiquitination is essential for Polycomb Repressive Complex 1-mediated gene regulation in Marchantia polymorpha2021In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 22, no 1, article id 253Article in journal (Refereed)
    Abstract [en]

    Background Polycomb repressive complex 1 (PRC1) and PRC2 are chromatin regulators maintaining transcriptional repression. The deposition of H3 lysine 27 tri-methylation (H3K27me3) by PRC2 is known to be required for transcriptional repression, whereas the contribution of H2A ubiquitination (H2Aub) in the Polycomb repressive system remains unclear in plants. Results We directly test the requirement of H2Aub for gene regulation in Marchantia polymorpha by generating point mutations in H2A that prevent ubiquitination by PRC1. These mutants show reduced H3K27me3 levels on the same target sites as mutants defective in PRC1 subunits MpBMI1 and the homolog MpBMI1L, revealing that PRC1-catalyzed H2Aub is essential for Polycomb system function. Furthermore, by comparing transcriptome data between mutants in MpH2A and MpBMI1/1L, we demonstrate that H2Aub contributes to the PRC1-mediated transcriptional level of genes and transposable elements. Conclusion Together, our data demonstrates that H2Aub plays a direct role in H3K27me3 deposition and is required for PRC1-mediated transcriptional changes in both genes and transposable elements in Marchantia.

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  • 34. Magee, Anthony I
    et al.
    Parmryd, Ingela
    Detergent-resistant membranes and the protein composition of lipid rafts2003In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 4, no 11, p. 234-Article, review/survey (Refereed)
    Abstract [en]

    The plasma membrane of eukaryotic cells contains lipid rafts with protein and lipid compositions differing from the bulk plasma membrane. Several recent proteomic studies have addressed the composition of lipid rafts, but the different definitions used for lipid rafts need scrutinizing before results can be evaluated.

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  • 35. Manning, Gerard
    et al.
    Reiner, David S.
    Lauwaet, Tineke
    Dacre, Michael
    Smith, Alias
    Zhai, Yufeng
    Svärd, Staffan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Microbiology.
    Gillin, Frances D.
    The minimal kinome of Giardia lamblia illuminates early kinase evolution and unique parasite biology2011In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 12, no 7, p. R66-Article in journal (Refereed)
    Abstract [en]

    Background: The major human intestinal pathogen Giardia lamblia is a very early branching eukaryote with a minimal genome of broad evolutionary and biological interest.

    Results: To explore early kinase evolution and regulation of Giardia biology, we cataloged the kinomes of three sequenced strains. Comparison with published kinomes and those of the excavates Trichomonas vaginalis and Leishmania major shows that Giardia's 80 core kinases constitute the smallest known core kinome of any eukaryote that can be grown in pure culture, reflecting both its early origin and secondary gene loss. Kinase losses in DNA repair, mitochondrial function, transcription, splicing, and stress response reflect this reduced genome, while the presence of other kinases helps define the kinome of the last common eukaryotic ancestor. Immunofluorescence analysis shows abundant phospho-staining in trophozoites, with phosphotyrosine abundant in the nuclei and phosphothreonine and phosphoserine in distinct cytoskeletal organelles. The Nek kinase family has been massively expanded, accounting for 198 of the 278 protein kinases in Giardia. Most Neks are catalytically inactive, have very divergent sequences and undergo extensive duplication and loss between strains. Many Neks are highly induced during development. We localized four catalytically active Neks to distinct parts of the cytoskeleton and one inactive Nek to the cytoplasm.

    Conclusions: The reduced kinome of Giardia sheds new light on early kinase evolution, and its highly divergent sequences add to the definition of individual kinase families as well as offering specific drug targets. Giardia's massive Nek expansion may reflect its distinctive lifestyle, biphasic life cycle and complex cytoskeleton.

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  • 36.
    Mayrhofer, Markus
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
    DiLorenzo, Sebastian
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Isaksson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue2013In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 14, no 3, p. R24-Article in journal (Refereed)
    Abstract [en]

    Whole-genome sequencing of tumor tissue has the potential to provide comprehensive characterization of genomic alterations in tumor samples. We present Patchwork, a new bioinformatic tool for allele-specific copy number analysis using whole-genome sequencing data. Patchwork can be used to determine the copy number of homologous sequences throughout the genome, even in aneuploid samples with moderate sequence coverage and tumor cell content. No prior knowledge of average ploidy or tumor cell content is required. Patchwork is freely available as an R package, installable via R-Forge (http://patchwork.r-forge.r-project.org/).

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  • 37.
    Meadows, Jennifer
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Kidd, Jeffrey M.
    Univ Michigan, Dept Human Genet, Ann Arbor, MI 48107 USA..
    Wang, Guo-Dong
    Chinese Acad Sci, Kunming Inst Zool, State Key Lab Genet Resources & Evolut, Kunming 650223, Peoples R China..
    Parker, Heidi G.
    NHGRI, NIH, 50 South Dr,Bldg 50 Room 5351, Bethesda, MD 20892 USA..
    Schall, Peter Z.
    Univ Michigan, Dept Human Genet, Ann Arbor, MI 48107 USA..
    Bianchi, Matteo
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Christmas, Matthew
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bougiouri, Katia
    Univ Copenhagen, Globe Inst, Sect Mol Ecol & Evolut, Oster Voldgade 5-7, DK-1350 Copenhagen, Denmark..
    Buckley, Reuben M.
    NHGRI, NIH, 50 South Dr,Bldg 50 Room 5351, Bethesda, MD 20892 USA..
    Hitte, Christophe
    Univ Rennes, Inst Genet & Dev Rennes UMR6290, CNRS, F-35000 Rennes, France..
    Nguyen, Anthony K.
    Univ Michigan, Dept Human Genet, Ann Arbor, MI 48107 USA..
    Wang, Chao
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jagannathan, Vidhya
    Univ Bern, Inst Genet, Vetsuisse Fac, CH-3001 Bern, Switzerland..
    Niskanen, Julia E.
    Univ Helsinki, Dept Med & Clin Genet, Dept Vet Biosci, Helsinki 02900, Finland.;Folkhalsan Res Ctr, Helsinki 02900, Finland..
    Frantz, Laurent A. F.
    Queen Mary Univ London, Sch Biol & Behav Sci, London E1 4NS, England.;Ludwig Maximilians Univ Munchen, Dept Vet Sci, Palaeogen Grp, D-80539 Munich, Germany..
    Arumilli, Meharji
    Univ Helsinki, Dept Med & Clin Genet, Dept Vet Biosci, Helsinki 02900, Finland.;Folkhalsan Res Ctr, Helsinki 02900, Finland..
    Hundi, Sruthi
    Univ Helsinki, Dept Med & Clin Genet, Dept Vet Biosci, Helsinki 02900, Finland.;Folkhalsan Res Ctr, Helsinki 02900, Finland..
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Broad Inst MIT & Harvard, Cambridge, MA 02142 USA..
    Ginja, Catarina
    Univ Porto, BIOPOLIS CIBIO InBIO Ctr Invest Biodiversidade & R, ArchGen Grp, P-4485661 Vairao, Portugal..
    Agustina, Kadek Karang
    Udayana Univ, Dept Publ Hlth, Bali 80361, Indonesia..
    Andre, Catherine
    Univ Rennes, Inst Genet & Dev Rennes UMR6290, CNRS, F-35000 Rennes, France..
    Boyko, Adam R.
    Cornell Univ, Dept Biomed Sci, 930 Campus Rd, Ithaca, NY 14853 USA..
    Davis, Brian W.
    Texas A&M Univ, Sch Vet Med & Biomed Sci, Dept Vet Integrat Biosci, College Stn, TX 77843 USA..
    Drögemüller, Michaela
    Univ Bern, Inst Genet, Vetsuisse Fac, CH-3001 Bern, Switzerland..
    Feng, Xin-Yao
    Chinese Acad Sci, Kunming Inst Zool, State Key Lab Genet Resources & Evolut, Kunming 650223, Peoples R China..
    Gkagkavouzis, Konstantinos
    Aristotle Univ Thessaloniki, Sch Biol, Dept Genet, Thessaloniki 54124, Macedonia, Greece.;Ctr Interdisciplinary Res & Innovat CIRI AUTH, Balkan Ctr, Genom & Epigen Translat Res GENeTres, Thessaloniki, Greece..
    Iliopoulos, Giorgos
    NGO Callisto, Wildlife & Nat Conservat Soc, Thessaloniki 54621, Greece..
    Harris, Alexander C.
    NHGRI, NIH, 50 South Dr,Bldg 50 Room 5351, Bethesda, MD 20892 USA..
    Hytonen, Marjo K.
    Univ Helsinki, Dept Med & Clin Genet, Dept Vet Biosci, Helsinki 02900, Finland.;Folkhalsan Res Ctr, Helsinki 02900, Finland..
    Kalthoff, Daniela C.
    NGO Callisto, Wildlife & Nat Conservat Soc, Thessaloniki 54621, Greece..
    Liu, Yan-Hu
    Chinese Acad Sci, Kunming Inst Zool, State Key Lab Genet Resources & Evolut, Kunming 650223, Peoples R China..
    Lymberakis, Petros
    Univ Crete, Nat Hist Museum Crete, Iraklion 71202, Greece.;Univ Crete, Dept Biol, Iraklion 71202, Greece.;Univ Crete, Sch Sci & Engn, Biol Dept, Iraklion, Greece.;Fdn Res & Technol Hellas FORTH, Inst Mol Biol & Biotechnol IMBB, Palaeogen & Evolutionary Genet Lab, Iraklion, Greece..
    Poulakakis, Nikolaos
    Univ Crete, Nat Hist Museum Crete, Iraklion 71202, Greece.;Univ Crete, Dept Biol, Iraklion 71202, Greece.;Univ Crete, Sch Sci & Engn, Biol Dept, Iraklion, Greece.;Fdn Res & Technol Hellas FORTH, Inst Mol Biol & Biotechnol IMBB, Palaeogen & Evolutionary Genet Lab, Iraklion, Greece..
    Pires, Ana Elisabete
    Univ Porto, BIOPOLIS CIBIO InBIO Ctr Invest Biodiversidade & R, ArchGen Grp, P-4485661 Vairao, Portugal..
    Racimo, Fernando
    Univ Copenhagen, Globe Inst, Sect Mol Ecol & Evolut, Oster Voldgade 5-7, DK-1350 Copenhagen, Denmark..
    Ramos-Almodovar, Fabian
    Univ Michigan, Dept Human Genet, Ann Arbor, MI 48107 USA..
    Savolainen, Peter
    KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, S-17121 Solna, Sweden..
    Venetsani, Semina
    Aristotle Univ Thessaloniki, Sch Biol, Dept Genet, Thessaloniki 54124, Macedonia, Greece..
    Tammen, Imke
    Univ Sydney, Sydney Sch Vet Sci, Sydney, NSW 2570, Australia..
    Triantafyllidis, Alexandros
    Aristotle Univ Thessaloniki, Sch Biol, Dept Genet, Thessaloniki 54124, Macedonia, Greece.;Ctr Interdisciplinary Res & Innovat CIRI AUTH, Balkan Ctr, Genom & Epigen Translat Res GENeTres, Thessaloniki, Greece..
    vonHoldt, Bridgett
    Princeton Univ, Dept Ecol & Evolutionary Biol, Princeton, NJ 08544 USA..
    Wayne, Robert K.
    Univ Calif Los Angeles, Dept Ecol & Evolutionary Biol, Ecol & Evolutionary Biol, Los Angeles, CA 90095 USA..
    Larson, Greger
    Univ Oxford, Sch Archaeol, Palaeogen & Bioarchaeol Res Network, Oxford OX1 3TG, England..
    Nicholas, Frank W.
    Univ Sydney, Sydney Sch Vet Sci, Sydney, NSW 2570, Australia..
    Lohi, Hannes
    Univ Helsinki, Dept Med & Clin Genet, Dept Vet Biosci, Helsinki 02900, Finland..
    Leeb, Tosso
    Univ Bern, Inst Genet, Vetsuisse Fac, CH-3001 Bern, Switzerland..
    Zhang, Ya-Ping
    Chinese Acad Sci, Kunming Inst Zool, State Key Lab Genet Resources & Evolut, Kunming 650223, Peoples R China..
    Ostrander, Elaine A.
    NHGRI, NIH, 50 South Dr,Bldg 50 Room 5351, Bethesda, MD 20892 USA..
    Genome sequencing of 2000 canids by the Dog10K consortium advances the understanding of demography, genome function and architecture2023In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 24, article id 187Article in journal (Refereed)
    Abstract [en]

    Background: The international Dog10K project aims to sequence and analyze several thousand canine genomes. Incorporating 20 x data from 1987 individuals, including 1611 dogs (321 breeds), 309 village dogs, 63 wolves, and four coyotes, we identify genomic variation across the canid family, setting the stage for detailed studies of domestication, behavior, morphology, disease susceptibility, and genome architecture and function.

    Results: We report the analysis of > 48 M single-nucleotide, indel, and structural variants spanning the autosomes, X chromosome, and mitochondria. We discover more than 75% of variation for 239 sampled breeds. Allele sharing analysis indicates that 94.9% of breeds form monophyletic clusters and 25 major clades. German Shepherd Dogs and related breeds show the highest allele sharing with independent breeds from multiple clades. On average, each breed dog differs from the UU_Cfam_GSD_1.0 reference at 26,960 deletions and 14,034 insertions greater than 50 bp, with wolves having 14% more variants. Discovered variants include retrogene insertions from 926 parent genes. To aid functional prioritization, single-nucleotide variants were annotated with SnpEff and Zoonomia phyloP constraint scores. Constrained positions were negatively correlated with allele frequency. Finally, the utility of the Dog10K data as an imputation reference panel is assessed, generating high-confidence calls across varied genotyping platform densities including for breeds not included in the Dog10K collection.

    Conclusions: We have developed a dense dataset of 1987 sequenced canids that reveals patterns of allele sharing, identifies likely functional variants, informs breed structure, and enables accurate imputation. Dog10K data are publicly available.

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  • 38.
    Motallebipour, Mehdi
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Ameur, Adam
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Bysani, Madhusudhan Reddy
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics.
    Patra, Kalicharan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Physiology and Developmental Biology, Animal Development and Genetics.
    Wallerman, Ola
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics.
    Mangion, Jonathan
    Barker, Melissa
    McKernan, Kevin
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Wadelius, Claes
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics.
    Differential binding and co-binding pattern of FOXA1 and FOXA3 and their relation to H3K4me3 in HepG2 cells revealed by ChIP-seq2009In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 10, no 11, p. R129-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The forkhead box/winged helix family members FOXA1, FOXA2, and FOXA3 are of high importance in development and specification of the hepatic linage and the continued expression of liver-specific genes. RESULTS: Here, we present a genome-wide location analysis of FOXA1 and FOXA3 binding sites in HepG2 cells through chromatin immunoprecipitation with detection by sequencing (ChIP-seq) studies and compare these with our previous results on FOXA2. We found that these factors often bind close to each other in different combinations and consecutive immunoprecipitation of chromatin for one and then a second factor (ChIP-reChIP) shows that this occurs in the same cell and on the same DNA molecule, suggestive of molecular interactions. Using co-immunoprecipitation, we further show that FOXA2 interacts with both FOXA1 and FOXA3 in vivo, while FOXA1 and FOXA3 do not appear to interact. Additionally, we detected diverse patterns of trimethylation of lysine 4 on histone H3 (H3K4me3) at transcriptional start sites and directionality of this modification at FOXA binding sites. Using the sequence reads at polymorphic positions, we were able to predict allele specific binding for FOXA1, FOXA3, and H3K4me3. Finally, several SNPs associated with diseases and quantitative traits were located in the enriched regions. CONCLUSIONS: We find that ChIP-seq can be used not only to create gene regulatory maps but also to predict molecular interactions and to inform on the mechanisms for common quantitative variation.

  • 39.
    Mugal, Carina F.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
    Ellegren, Hans
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
    Substitution rate variation at human CpG sites correlates with non-CpG divergence, methylation level and GC content2011In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 12, no 6, p. R58-Article in journal (Refereed)
    Abstract [en]

    Background: A major goal in the study of molecular evolution is to unravel the mechanisms that induce variation in the germ line mutation rate and in the genome-wide mutation profile. The rate of germ line mutation is considerably higher for cytosines at CpG sites than for any other nucleotide in the human genome, an increase commonly attributed to cytosine methylation at CpG sites. The CpG mutation rate, however, is not uniform across the genome and, as methylation levels have recently been shown to vary throughout the genome, it has been hypothesized that methylation status may govern variation in the rate of CpG mutation.

    Results: Here, we use genome-wide methylation data from human sperm cells to investigate the impact of DNA methylation on the CpG substitution rate in introns of human genes. We find that there is a significant correlation between the extent of methylation and the substitution rate at CpG sites. Further, we show that the CpG substitution rate is positively correlated with non-CpG divergence, suggesting susceptibility to factors responsible for the general mutation rate in the genome, and negatively correlated with GC content. We only observe a minor contribution of gene expression level, while recombination rate appears to have no significant effect.

    Conclusions: Our study provides the first direct empirical support for the hypothesis that variation in the level of germ line methylation contributes to substitution rate variation at CpG sites. Moreover, we show that other genomic features also impact on CpG substitution rate variation.

  • 40.
    Nordlund, Jessica
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bäcklin, Christofer L
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Wahlberg, Per
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Busche, Stephan
    Berglund, Eva C
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Eloranta, Maija-Leena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Rheumatology.
    Flaegstad, Trond
    Forestier, Erik
    Frost, Britt-Marie
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health.
    Harila-Saari, Arja
    Heyman, Mats
    Jónsson, Olafur G
    Larsson, Rolf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Palle, Josefine
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, Pediatrics.
    Rönnblom, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Rheumatology.
    Schmiegelow, Kjeld
    Sinnett, Daniel
    Söderhäll, Stefan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, Pediatrics.
    Pastinen, Tomi
    Gustafsson, Mats G
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Lönnerholm, Gudmar
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health.
    Syvänen, Ann-Christine
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia2013In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 14, no 9, p. r105-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND:

    Although aberrant DNA methylation has been observed previously in acute lymphoblastic leukemia (ALL), the patterns of differential methylation have not been comprehensively determined in all subtypes of ALL on a genome-wide scale. The relationship between DNA methylation, cytogenetic background, drug resistance and relapse in ALL is poorly understood.

    RESULTS:

    We surveyed the DNA methylation levels of 435,941 CpG sites in samples from 764 children at diagnosis of ALL and from 27 children at relapse. This survey uncovered four characteristic methylation signatures. First, compared with control blood cells, the methylomes of ALL cells shared 9,406 predominantly hypermethylated CpG sites, independent of cytogenetic background. Second, each cytogenetic subtype of ALL displayed a unique set of hyper- and hypomethylated CpG sites. The CpG sites that constituted these two signatures differed in their functional genomic enrichment to regions with marks of active or repressed chromatin. Third, we identified subtype-specific differential methylation in promoter and enhancer regions that were strongly correlated with gene expression. Fourth, a set of 6,612 CpG sites was predominantly hypermethylated in ALL cells at relapse, compared with matched samples at diagnosis. Analysis of relapse-free survival identified CpG sites with subtype-specific differential methylation that divided the patients into different risk groups, depending on their methylation status.

    CONCLUSIONS:

    Our results suggest an important biological role for DNA methylation in the differences between ALL subtypes and in their clinical outcome after treatment.

  • 41.
    Pochon, Zoe
    et al.
    Ctr Palaeogenet, Stockholm, Sweden.;Stockholm Univ, Dept Archaeol & Class Studies, Stockholm, Sweden..
    Bergfeldt, Nora
    Ctr Palaeogenet, Stockholm, Sweden.;Stockholm Univ, Dept Zool, Stockholm, Sweden.;Swedish Museum Nat Hist, Dept Bioinformat & Genet, Stockholm, Sweden..
    Kirdok, Emrah
    Mersin Univ, Fac Sci, Dept Biotechnol, Mersin, Turkey..
    Vicente, Mario
    Ctr Palaeogenet, Stockholm, Sweden.;Stockholm Univ, Dept Archaeol & Class Studies, Stockholm, Sweden..
    Naidoo, Thijessen
    Uppsala University, Science for Life Laboratory, SciLifeLab. Ctr Palaeogenet, Stockholm, Sweden.;Stockholm Univ, Dept Archaeol & Class Studies, Stockholm, Sweden.;Sci Life Lab, Ancient DNA Unit, Stockholm, Sweden..
    van der Valk, Tom
    Ctr Palaeogenet, Stockholm, Sweden.;Swedish Museum Nat Hist, Dept Bioinformat & Genet, Stockholm, Sweden..
    Altinisik, N. Ezgi
    Hacettepe Univ, Dept Anthropol, Human G Lab, TR-06800 Beytepe, Ankara, Turkey..
    Krzewinska, Maja
    Ctr Palaeogenet, Stockholm, Sweden.;Stockholm Univ, Dept Archaeol & Class Studies, Stockholm, Sweden..
    Dalen, Love
    Ctr Palaeogenet, Stockholm, Sweden.;Stockholm Univ, Dept Zool, Stockholm, Sweden..
    Gotherstrom, Anders
    Mirabello, Claudio
    Linköping Univ, Dept Phys Chem & Biol, Sci Life Lab, Natl Bioinformat Infrastruct Sweden, Linköping, Sweden..
    Unneberg, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Evolution. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Oskolkov, Nikolay
    Lund Univ, Dept Biol, Sci Life Lab, Natl Bioinformat Infrastruct Sweden, Lund, Sweden..
    aMeta: an accurate and memory-efficient ancient metagenomic profiling workflow2023In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 24, no 1, article id 242Article in journal (Refereed)
    Abstract [en]

    Analysis of microbial data from archaeological samples is a growing field with great potential for understanding ancient environments, lifestyles, and diseases. However, high error rates have been a challenge in ancient metagenomics, and the availability of computational frameworks that meet the demands of the field is limited. Here, we propose aMeta, an accurate metagenomic profiling workflow for ancient DNA designed to minimize the amount of false discoveries and computer memory requirements. Using simulated data, we benchmark aMeta against a current state-of-the-art workflow and demonstrate its superiority in microbial detection and authentication, as well as substantially lower usage of computer memory.

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  • 42. Quignon, Pascale
    et al.
    Giraud, Mathieu
    Rimbault, Maud
    Lavigne, Patricia
    Tacher, Sandrine
    Morin, Emmanuelle
    Retout, Elodie
    Valin, Anne-Sophie
    Lindblad-Toh, Kerstin
    Nicolas, Jacques
    Galibert, Francis
    The dog and rat olfactory receptor repertoires2005In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 6, no 10, p. R83-R83Article in journal (Refereed)
  • 43.
    Rasmussen, Markus
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Sundström, Magnus
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular and Morphological Pathology.
    Kultima, Hanna Göransson
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Botling, Johan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular and Morphological Pathology.
    Micke, Patrick
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular and Morphological Pathology.
    Birgisson, Helgi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Colorectal Surgery.
    Glimelius, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Oncology.
    Isaksson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Allele-specific copy number analysis of tumor samples with aneuploidy and tumor heterogeneity2011In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 12, no 10, p. R108-Article in journal (Refereed)
    Abstract [en]

    We describe a bioinformatic tool, Tumor Aberration Prediction Suite (TAPS), for the identification of allele-specific copy numbers in tumor samples using data from Affymetrix SNP arrays. It includes detailed visualization of genomic segment characteristics and iterative pattern recognition for copy number identification, and does not require patient-matched normal samples. TAPS can be used to identify chromosomal aberrations with high sensitivity even when the proportion of tumor cells is as low as 30%. Analysis of cancer samples indicates that TAPS is well suited to investigate samples with aneuploidy and tumor heterogeneity, which is commonly found in many types of solid tumors.

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  • 44. Ren, Luyao
    et al.
    Duan, Xiaoke
    Dong, Lianhua
    Zhang, Rui
    Yang, Jingcheng
    Gao, Yuechen
    Peng, Rongxue
    Hou, Wanwan
    Liu, Yaqing
    Li, Jingjing
    Yu, Ying
    Zhang, Naixin
    Shang, Jun
    Liang, Fan
    Wang, Depeng
    Chen, Hui
    Sun, Lele
    Hao, Lingtong
    Scherer, Andreas
    Nordlund, Jessica
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Precision Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab. EATRIS ERIC-European Infrastructure for Translational Medicine, Amsterdam, the Netherlands.
    Xiao, Wenming
    Xu, Joshua
    Tong, Weida
    Hu, Xin
    Jia, Peng
    Ye, Kai
    Li, Jinming
    Jin, Li
    Hong, Huixiao
    Wang, Jing
    Fan, Shaohua
    Fang, Xiang
    Zheng, Yuanting
    Shi, Leming
    Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance2023In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 24, no 1, article id 270Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results is incomplete, as they are limited to benchmark regions. Therefore, it is important to develop DNA reference materials that enable the assessment of variant detection performance across the entire genome.

    RESULTS: We established a DNA reference material suite from four immortalized cell lines derived from a family of parents and monozygotic twins. Comprehensive reference datasets of 4.2 million small variants and 15,000 structural variants were integrated and certified for evaluating the reliability of germline variant calls inside the benchmark regions. Importantly, the genetic built-in-truth of the Quartet family design enables estimation of the precision of variant calls outside the benchmark regions. Using the Quartet reference materials along with study samples, batch effects are objectively monitored and alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Moreover, the matched RNA and protein reference materials and datasets from the Quartet project enables cross-omics validation of variant calls from multiomics data.

    CONCLUSIONS: The Quartet DNA reference materials and reference datasets provide a unique resource for objectively assessing the quality of germline variant calls throughout the whole-genome regions and improving the reliability of large-scale genomic profiling.

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  • 45.
    Sakthikumar, Sharadha
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Broad Institute, Cambridge, MA, 02142, USA.
    Roy, Ananya
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab. Broad Institute, Cambridge, Massachusetts, USA.
    Haseeb, Lulu
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Pettersson, Mats E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Sundström, Elisabeth
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Marinescu, Voichita D.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Broad Institute, Cambridge, Massachusetts, USA.
    Forsberg Nilsson, Karin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Whole-genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes2020In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 21, no 1, article id 127Article in journal (Refereed)
    Abstract [en]

    Background

    Glioblastoma (GBM) has one of the worst 5-year survival rates of all cancers. While genomic studies of the disease have been performed, alterations in the non-coding regulatory regions of GBM have largely remained unexplored. We apply whole-genome sequencing (WGS) to identify non-coding mutations, with regulatory potential in GBM, under the hypothesis that regions of evolutionary constraint are likely to be functional, and somatic mutations are likely more damaging than in unconstrained regions.

    Results

    We validate our GBM cohort, finding similar copy number aberrations and mutated genes based on coding mutations as previous studies. Performing analysis on non-coding constraint mutations and their position relative to nearby genes, we find a significant enrichment of non-coding constraint mutations in the neighborhood of 78 genes that have previously been implicated in GBM. Among them, SEMA3C and DYNC1I1 show the highest frequencies of alterations, with multiple mutations overlapping transcription factor binding sites. We find that a non-coding constraint mutation in the SEMA3C promoter reduces the DNA binding capacity of the region. We also identify 1776 other genes enriched for non-coding constraint mutations with likely regulatory potential, providing additional candidate GBM genes. The mutations in the top four genes, DLX5, DLX6, FOXA1, and ISL1, are distributed over promoters, UTRs, and multiple transcription factor binding sites.

    Conclusions

    These results suggest that non-coding constraint mutations could play an essential role in GBM, underscoring the need to connect non-coding genomic variation to biological function and disease pathology.

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  • 46. Sheng, Zheya
    et al.
    Pettersson, Mats E
    Honaker, Christa F
    Siegel, Paul B
    Carlborg, Örjan
    SLU.
    Standing genetic variation as a major contributor to adaptation in the Virginia chicken lines selection experiment.2015In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Artificial selection provides a powerful approach to study the genetics of adaptation. Using selective-sweep mapping, it is possible to identify genomic regions where allele-frequencies have diverged during selection. To avoid false positive signatures of selection, it is necessary to show that a sweep affects a selected trait before it can be considered adaptive. Here, we confirm candidate, genome-wide distributed selective sweeps originating from the standing genetic variation in a long-term selection experiment on high and low body weight of chickens.

    RESULTS: Using an intercross between the two divergent chicken lines, 16 adaptive selective sweeps were confirmed based on their association with the body weight at 56 days of age. Although individual additive effects were small, the fixation for alternative alleles across the loci contributed at least 40 % of the phenotypic difference for the selected trait between these lines. The sweeps contributed about half of the additive genetic variance present within and between the lines after 40 generations of selection, corresponding to a considerable portion of the additive genetic variance of the base population.

    CONCLUSIONS: Long-term, single-trait, bi-directional selection in the Virginia chicken lines has resulted in a gradual response to selection for extreme phenotypes without a drastic reduction in the genetic variation. We find that fixation of several standing genetic variants across a highly polygenic genetic architecture made a considerable contribution to long-term selection response. This provides new fundamental insights into the dynamics of standing genetic variation during long-term selection and adaptation.

  • 47. Shu, Huan
    et al.
    Nakamura, Miyuki
    Siretskiy, Alexey
    Borghi, Lorenzo
    Moraes, Izabel
    Wildhaber, Thomas
    Gruissem, Wilhelm
    Hennig, Lars
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Arabidopsis replacement histone variant H3.3 occupies promoters of regulated genes2014In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 15, no 4, p. R62-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Histone variants establish structural and functional diversity of chromatin by affecting nucleosome stability and histone-protein interactions. H3.3 is an H3 histone variant that is incorporated into chromatin outside of S-phase in various eukaryotes. In animals, H3.3 is associated with active transcription and possibly maintenance of transcriptional memory. Plant H3 variants, which evolved independently of their animal counterparts, are much less well understood.

    RESULTS: We profile the H3.3 distribution in Arabidopsis at mono-nucleosomal resolution using native chromatin immunoprecipitation. This results in the precise mapping of H3.3-containing nucleosomes, which are not only enriched in gene bodies as previously reported, but also at a subset of promoter regions and downstream of the 3[prime] ends of active genes. While H3.3 presence within transcribed regions is strongly associated with transcriptional activity, H3.3 at promoters is often independent of transcription. In particular, promoters with GA motifs carry H3.3 regardless of the gene expression levels. H3.3 on promoters of inactive genes is associated with H3K27me3 at gene bodies. In addition, H3.3-enriched plant promoters often contain RNA Pol II considerably upstream of the transcriptional start site. H3.3 and RNA Pol II are found on active as well as on inactive promoters and are enriched at strongly regulated genes.

    CONCLUSIONS: In animals and plants, H3.3 organizes chromatin in transcribed regions and in promoters. The results suggest a function of H3.3 in transcriptional regulation and support a model that a single ancestral H3 evolved into H3 variants with similar sub-functionalization patterns in plants and animals.

  • 48.
    Sood, Sanjana
    et al.
    XRGenomics Ltd, London, England.;Kings Coll London, Div Genet & Mol Med, Guys Hosp, London SE1 9RT, England..
    Gallagher, Iain J.
    XRGenomics Ltd, London, England.;Univ Stirling, Sch Hlth, Stirling FK9 4LA, Scotland..
    Lunnon, Katie
    Kings Coll London, Dept Old Age Psychiat, London SE1 9RT, England..
    Rullman, Eric
    Karolinska Univ Hosp, Div Clin Physiol, Stockholm, Sweden..
    Keohane, Aoife
    Kings Coll London, Dept Old Age Psychiat, London SE1 9RT, England..
    Crossland, Hannah
    Kings Coll London, Div Genet & Mol Med, Guys Hosp, London SE1 9RT, England.;Derby Royal Hosp, Sch Med, Derby, England..
    Phillips, Bethan E.
    Derby Royal Hosp, Sch Med, Derby, England..
    Cederholm, Tommy
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism.
    Jensen, Thomas
    Med Prognosis Inst AS, Horsholm, Denmark..
    van Loon, Luc J. C.
    Maastricht Univ, NUTRIM, Maastricht, Netherlands..
    Lannfelt, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Geriatrics.
    Kraus, William E.
    Duke Univ, Sch Med, Duke Mol Physiol Inst, Durham, NC USA..
    Atherton, Philip J.
    Derby Royal Hosp, Sch Med, Derby, England..
    Howard, Robert
    Kings Coll London, Dept Old Age Psychiat, London SE1 9RT, England..
    Gustafsson, Thomas
    Karolinska Univ Hosp, Div Clin Physiol, Stockholm, Sweden..
    Hodges, Angela
    Kings Coll London, Dept Old Age Psychiat, London SE1 9RT, England..
    Timmons, James A.
    XRGenomics Ltd, London, England.;Kings Coll London, Div Genet & Mol Med, Guys Hosp, London SE1 9RT, England..
    A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status2015In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16, article id 185Article in journal (Refereed)
    Abstract [en]

    Background: Diagnostics of the human ageing process may help predict future healthcare needs or guide preventative measures for tackling diseases of older age. We take a transcriptomics approach to build the first reproducible multi-tissue RNA expression signature by gene-chip profiling tissue from sedentary normal subjects who reached 65 years of age in good health. Results: One hundred and fifty probe-sets form an accurate classifier of young versus older muscle tissue and this healthy ageing RNA classifier performed consistently in independent cohorts of human muscle, skin and brain tissue (n = 594, AUC = 0.83-0.96) and thus represents a biomarker for biological age. Using the Uppsala Longitudinal Study of Adult Men birth-cohort (n = 108) we demonstrate that the RNA classifier is insensitive to confounding lifestyle biomarkers, while greater gene score at age 70 years is independently associated with better renal function at age 82 years and longevity. The gene score is 'up-regulated' in healthy human hippocampus with age, and when applied to blood RNA profiles from two large independent age-matched dementia case-control data sets (n = 717) the healthy controls have significantly greater gene scores than those with cognitive impairment. Alone, or when combined with our previously described prototype Alzheimer disease (AD) RNA 'disease signature', the healthy ageing RNA classifier is diagnostic for AD. Conclusions: We identify a novel and statistically robust multi-tissue RNA signature of human healthy ageing that can act as a diagnostic of future health, using only a peripheral blood sample. This RNA signature has great potential to assist research aimed at finding treatments for and/or management of AD and other ageing-related conditions.

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  • 49. Tang, Ruqi
    et al.
    Noh, Hyun Ji
    Wang, Dongqing
    Sigurdsson, Snaevar
    Swofford, Ross
    Perloski, Michele
    Duxbury, Margaret
    Patterson, Edward E.
    Albright, Julie
    Castelhano, Marta
    Auton, Adam
    Boyko, Adam R.
    Feng, Guoping
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Karlsson, Elinor K.
    Candidate genes and functional noncoding variants identified in a canine model of obsessive-compulsive disorder2014In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 15, no 3, p. R25-Article in journal (Refereed)
    Abstract [en]

    Background: Obsessive-compulsive disorder (OCD), a severe mental disease manifested in time-consuming repetition of behaviors, affects 1 to 3% of the human population. While highly heritable, complex genetics has hampered attempts to elucidate OCD etiology. Dogs suffer from naturally occurring compulsive disorders that closely model human OCD, manifested as an excessive repetition of normal canine behaviors that only partially responds to drug therapy. The limited diversity within dog breeds makes identifying underlying genetic factors easier. Results: We use genome-wide association of 87 Doberman Pinscher cases and 63 controls to identify genomic loci associated with OCD and sequence these regions in 8 affected dogs from high-risk breeds and 8 breed-matched controls. We find 119 variants in evolutionarily conserved sites that are specific to dogs with OCD. These case-only variants are significantly more common in high OCD risk breeds compared to breeds with no known psychiatric problems. Four genes, all with synaptic function, have the most case-only variation: neuronal cadherin (CDH2), catenin alpha2 (CTNNA2), ataxin-1 (ATXN1), and plasma glutamate carboxypeptidase (PGCP). In the 2 Mb gene desert between the cadherin genes CDH2 and DSC3, we find two different variants found only in dogs with OCD that disrupt the same highly conserved regulatory element. These variants cause significant changes in gene expression in a human neuroblastoma cell line, likely due to disrupted transcription factor binding. Conclusions: The limited genetic diversity of dog breeds facilitates identification of genes, functional variants and regulatory pathways underlying complex psychiatric disorders that are mechanistically similar in dogs and humans.

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  • 50. Wang, Jing
    et al.
    Ding, Jihua
    Tan, Biyue
    Robinson, Kathryn M.
    Michelson, Ingrid H.
    Johansson, Anna
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nystedt, Björn
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Scofield, Douglas G.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
    Nilsson, Ove
    Jansson, Stefan
    Street, Nathaniel R.
    Ingvarsson, Pär K.
    A major locus controls local adaptation and adaptive life history variation in a perennial plant2018In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 19, article id 72Article in journal (Refereed)
12 1 - 50 of 53
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