uu.seUppsala University Publications
Change search
Refine search result
1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the 'Create feeds' function.
  • 1.
    Bornelöv, Susanne
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Rule-based Models of Transcriptional Regulation and Complex Diseases: Applications and Development2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    As we gain increased understanding of genetic disorders and gene regulation more focus has turned towards complex interactions. Combinations of genes or gene and environmental factors have been suggested to explain the missing heritability behind complex diseases. Furthermore, gene activation and splicing seem to be governed by a complex machinery of histone modification (HM), transcription factor (TF), and DNA sequence signals. This thesis aimed to apply and develop multivariate machine learning methods for use on such biological problems. Monte Carlo feature selection was combined with rule-based classification to identify interactions between HMs and to study the interplay of factors with importance for asthma and allergy.

    Firstly, publicly available ChIP-seq data (Paper I) for 38 HMs was studied. We trained a classifier for predicting exon inclusion levels based on the HMs signals. We identified HMs important for splicing and illustrated that splicing could be predicted from the HM patterns. Next, we applied a similar methodology on data from two large birth cohorts describing asthma and allergy in children (Paper II). We identified genetic and environmental factors with importance for allergic diseases which confirmed earlier results and found candidate gene-gene and gene-environment interactions.

    In order to interpret and present the classifiers we developed Ciruvis, a web-based tool for network visualization of classification rules (Paper III). We applied Ciruvis on classifiers trained on both simulated and real data and compared our tool to another methodology for interaction detection using classification. Finally, we continued the earlier study on epigenetics by analyzing HM and TF signals in genes with or without evidence of bidirectional transcription (Paper IV). We identified several HMs and TFs with different signals between unidirectional and bidirectional genes. Among these, the CTCF TF was shown to have a well-positioned peak 60-80 bp upstream of the transcription start site in unidirectional genes.

    List of papers
    1. Combinations of histone modifications mark exon inclusion levels
    Open this publication in new window or tab >>Combinations of histone modifications mark exon inclusion levels
    2012 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, no 1, article id e29911Article in journal (Refereed) Published
    Abstract [en]

    Splicing is a complex process regulated by sequence at the classical splice sites and other motifs in exons and introns with an enhancing or silencing effect. In addition, specific histone modifications on nucleosomes positioned over the exons have been shown to correlate both positively and negatively with exon expression. Here, we trained a model of "IF … THEN …" rules to predict exon inclusion levels in a transcript from histone modification patterns. Furthermore, we showed that combinations of histone modifications, in particular those residing on nucleosomes preceding or succeeding the exon, are better predictors of exon inclusion levels than single modifications. The resulting model was evaluated with cross validation and had an average accuracy of 72% for 27% of the exons, which demonstrates that epigenetic signals substantially mark alternative splicing.

    National Category
    Cell and Molecular Biology
    Identifiers
    urn:nbn:se:uu:diva-175875 (URN)10.1371/journal.pone.0029911 (DOI)000312662100045 ()22242188 (PubMedID)
    Funder
    Knut and Alice Wallenberg FoundationSwedish Foundation for Strategic Research Swedish Research CouncilSwedish Cancer Society
    Available from: 2012-06-13 Created: 2012-06-13 Last updated: 2018-01-12Bibliographically approved
    2. Rule-Based Models of the Interplay between Genetic and Environmental Factors in Childhood Allergy
    Open this publication in new window or tab >>Rule-Based Models of the Interplay between Genetic and Environmental Factors in Childhood Allergy
    Show others...
    2013 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 11, p. e80080-Article in journal (Refereed) Published
    Abstract [en]

    Both genetic and environmental factors are important for the development of allergic diseases. However, a detailed understanding of how such factors act together is lacking. To elucidate the interplay between genetic and environmental factors in allergic diseases, we used a novel bioinformatics approach that combines feature selection and machine learning. In two materials, PARSIFAL (a European cross-sectional study of 3113 children) and BAMSE (a Swedish birth-cohort including 2033 children), genetic variants as well as environmental and lifestyle factors were evaluated for their contribution to allergic phenotypes. Monte Carlo feature selection and rule based models were used to identify and rank rules describing how combinations of genetic and environmental factors affect the risk of allergic diseases. Novel interactions between genes were suggested and replicated, such as between ORMDL3 and RORA, where certain genotype combinations gave odds ratios for current asthma of 2.1 (95% CI 1.2-3.6) and 3.2 (95% CI 2.0-5.0) in the BAMSE and PARSIFAL children, respectively. Several combinations of environmental factors appeared to be important for the development of allergic disease in children. For example, use of baby formula and antibiotics early in life was associated with an odds ratio of 7.4 (95% CI 4.5-12.0) of developing asthma. Furthermore, genetic variants together with environmental factors seemed to play a role for allergic diseases, such as the use of antibiotics early in life and COL29A1 variants for asthma, and farm living and NPSR1 variants for allergic eczema. Overall, combinations of environmental and life style factors appeared more frequently in the models than combinations solely involving genes. In conclusion, a new bioinformatics approach is described for analyzing complex data, including extensive genetic and environmental information. Interactions identified with this approach could provide useful hints for further in-depth studies of etiological mechanisms and may also strengthen the basis for risk assessment and prevention.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-213817 (URN)10.1371/journal.pone.0080080 (DOI)000327311900057 ()
    Available from: 2014-01-05 Created: 2014-01-04 Last updated: 2017-12-06Bibliographically approved
    3. Ciruvis: a web-based tool for rule networks and interaction detection using rule-based classifiers
    Open this publication in new window or tab >>Ciruvis: a web-based tool for rule networks and interaction detection using rule-based classifiers
    2014 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 15, p. 139-Article in journal (Refereed) Published
    Abstract [en]

    Background: The use of classification algorithms is becoming increasingly important for the field of computational biology. However, not only the quality of the classification, but also its biological interpretation is important. This interpretation may be eased if interacting elements can be identified and visualized, something that requires appropriate tools and methods. Results: We developed a new approach to detecting interactions in complex systems based on classification. Using rule-based classifiers, we previously proposed a rule network visualization strategy that may be applied as a heuristic for finding interactions. We now complement this work with Ciruvis, a web-based tool for the construction of rule networks from classifiers made of IF-THEN rules. Simulated and biological data served as an illustration of how the tool may be used to visualize and interpret classifiers. Furthermore, we used the rule networks to identify feature interactions, compared them to alternative methods, and computationally validated the findings. Conclusions: Rule networks enable a fast method for model visualization and provide an exploratory heuristic to interaction detection. The tool is made freely available on the web and may thus be used to aid and improve rule-based classification.

    Keyword
    Visualization, Rules, Interactions, Interaction detection, Classification, Rule-based classification
    National Category
    Biochemistry and Molecular Biology
    Identifiers
    urn:nbn:se:uu:diva-228027 (URN)10.1186/1471-2105-15-139 (DOI)000336679600001 ()
    Available from: 2014-07-02 Created: 2014-07-02 Last updated: 2017-12-05Bibliographically approved
    4. Different distribution of histone modifications in genes with unidirectional and bidirectional transcription and a role of CTCF and cohesin in directing transcription
    Open this publication in new window or tab >>Different distribution of histone modifications in genes with unidirectional and bidirectional transcription and a role of CTCF and cohesin in directing transcription
    2015 (English)In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 16, article id 300Article in journal (Refereed) Published
    Abstract [en]

    Background: Several post-translational histone modifications are mainly found in gene promoters and are associated with the promoter activity. It has been hypothesized that histone modifications regulate the transcription, as opposed to the traditional view with transcription factors as the key regulators. Promoters of most active genes do not only initiate transcription of the coding sequence, but also a substantial amount of transcription of the antisense strand upstream of the transcription start site (TSS). This promoter feature has generally not been considered in previous studies of histone modifications and transcription factor binding.

    Results: We annotated protein-coding genes as bi- or unidirectional depending on their mode of transcription and compared histone modifications and transcription factor occurrences between them. We found that H3K4me3, H3K9ac, and H3K27ac were significantly more enriched upstream of the TSS in bidirectional genes compared with the unidirectional ones. In contrast, the downstream histone modification signals were similar, suggesting that the upstream histone modifications might be a consequence of transcription rather than a cause. Notably, we found well-positioned CTCF and RAD21 peaks approximately 60-80 bp upstream of the TSS in the unidirectional genes. The peak heights were related to the amount of antisense transcription and we hypothesized that CTCF and cohesin act as a barrier against antisense transcription.

    Conclusions: Our results provide insights into the distribution of histone modifications at promoters and suggest a novel role of CTCF and cohesin as regulators of transcriptional direction.

    Keyword
    Antisense transcription, CTCF, RAD21, Cohesin, CAGE, Epigenetics, Transcription factor, Histone modification
    National Category
    Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:uu:diva-230158 (URN)10.1186/s12864-015-1485-5 (DOI)000355166000001 ()25881024 (PubMedID)
    Available from: 2014-08-19 Created: 2014-08-19 Last updated: 2017-12-05Bibliographically approved
  • 2.
    Bornelöv, Susanne
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Enroth, Stefan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Visualization of Rules in Rule-Based Classifiers2012In: INTELLIGENT DECISION TECHNOLOGIES (IDT'2012), VOL 1, 2012, Vol. 15, p. 329-338Conference paper (Refereed)
    Abstract [en]

    Interpretation and visualization of the classification models are important parts of machine learning. Rule-based classifiers often contain too many rules to be easily interpreted by humans, and methods for post-classification analysis of the rules are needed. Here we present a strategy for circular visualization of sets of classification rules. The Circos software was used to generate graphs showing all pairs of conditions that were present in the rules as edges inside a circle. We showed using simulated data that all two-way interactions in the data were found by the classifier and displayed in the graph, although the single attributes were constructed to have no correlation to the decision class. For all examples we used rules trained using the rough set theory, but the visualization would by applicable to any sort of classification rules. This method for rule visualization may be useful for applications where interaction terms are expected, and the size of the model limits the interpretability.

  • 3.
    Bornelöv, Susanne
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Wadelius, Claes
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Different distribution of histone modifications in genes with unidirectional and bidirectional transcription and a role of CTCF and cohesin in directing transcription2015In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 16, article id 300Article in journal (Refereed)
    Abstract [en]

    Background: Several post-translational histone modifications are mainly found in gene promoters and are associated with the promoter activity. It has been hypothesized that histone modifications regulate the transcription, as opposed to the traditional view with transcription factors as the key regulators. Promoters of most active genes do not only initiate transcription of the coding sequence, but also a substantial amount of transcription of the antisense strand upstream of the transcription start site (TSS). This promoter feature has generally not been considered in previous studies of histone modifications and transcription factor binding.

    Results: We annotated protein-coding genes as bi- or unidirectional depending on their mode of transcription and compared histone modifications and transcription factor occurrences between them. We found that H3K4me3, H3K9ac, and H3K27ac were significantly more enriched upstream of the TSS in bidirectional genes compared with the unidirectional ones. In contrast, the downstream histone modification signals were similar, suggesting that the upstream histone modifications might be a consequence of transcription rather than a cause. Notably, we found well-positioned CTCF and RAD21 peaks approximately 60-80 bp upstream of the TSS in the unidirectional genes. The peak heights were related to the amount of antisense transcription and we hypothesized that CTCF and cohesin act as a barrier against antisense transcription.

    Conclusions: Our results provide insights into the distribution of histone modifications at promoters and suggest a novel role of CTCF and cohesin as regulators of transcriptional direction.

  • 4.
    Bornelöv, Susanne
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Marillet, Simon
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Ciruvis: a web-based tool for rule networks and interaction detection using rule-based classifiers2014In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 15, p. 139-Article in journal (Refereed)
    Abstract [en]

    Background: The use of classification algorithms is becoming increasingly important for the field of computational biology. However, not only the quality of the classification, but also its biological interpretation is important. This interpretation may be eased if interacting elements can be identified and visualized, something that requires appropriate tools and methods. Results: We developed a new approach to detecting interactions in complex systems based on classification. Using rule-based classifiers, we previously proposed a rule network visualization strategy that may be applied as a heuristic for finding interactions. We now complement this work with Ciruvis, a web-based tool for the construction of rule networks from classifiers made of IF-THEN rules. Simulated and biological data served as an illustration of how the tool may be used to visualize and interpret classifiers. Furthermore, we used the rule networks to identify feature interactions, compared them to alternative methods, and computationally validated the findings. Conclusions: Rule networks enable a fast method for model visualization and provide an exploratory heuristic to interaction detection. The tool is made freely available on the web and may thus be used to aid and improve rule-based classification.

  • 5.
    Bornelöv, Susanne
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Saaf, Annika
    Melen, Erik
    Bergstrom, Anna
    Moghadam, Behrooz Torabi
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Pulkkinen, Ville
    Acevedo, Nathalie
    Pietras, Christina Orsmark
    Ege, Markus
    Braun-Fahrlaender, Charlotte
    Riedler, Josef
    Doekes, Gert
    Kabesch, Michael
    van Hage, Marianne
    Kere, Juha
    Scheynius, Annika
    Soderhall, Cilla
    Pershagen, Goran
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Rule-Based Models of the Interplay between Genetic and Environmental Factors in Childhood Allergy2013In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 11, p. e80080-Article in journal (Refereed)
    Abstract [en]

    Both genetic and environmental factors are important for the development of allergic diseases. However, a detailed understanding of how such factors act together is lacking. To elucidate the interplay between genetic and environmental factors in allergic diseases, we used a novel bioinformatics approach that combines feature selection and machine learning. In two materials, PARSIFAL (a European cross-sectional study of 3113 children) and BAMSE (a Swedish birth-cohort including 2033 children), genetic variants as well as environmental and lifestyle factors were evaluated for their contribution to allergic phenotypes. Monte Carlo feature selection and rule based models were used to identify and rank rules describing how combinations of genetic and environmental factors affect the risk of allergic diseases. Novel interactions between genes were suggested and replicated, such as between ORMDL3 and RORA, where certain genotype combinations gave odds ratios for current asthma of 2.1 (95% CI 1.2-3.6) and 3.2 (95% CI 2.0-5.0) in the BAMSE and PARSIFAL children, respectively. Several combinations of environmental factors appeared to be important for the development of allergic disease in children. For example, use of baby formula and antibiotics early in life was associated with an odds ratio of 7.4 (95% CI 4.5-12.0) of developing asthma. Furthermore, genetic variants together with environmental factors seemed to play a role for allergic diseases, such as the use of antibiotics early in life and COL29A1 variants for asthma, and farm living and NPSR1 variants for allergic eczema. Overall, combinations of environmental and life style factors appeared more frequently in the models than combinations solely involving genes. In conclusion, a new bioinformatics approach is described for analyzing complex data, including extensive genetic and environmental information. Interactions identified with this approach could provide useful hints for further in-depth studies of etiological mechanisms and may also strengthen the basis for risk assessment and prevention.

  • 6.
    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.

  • 7.
    Bysani, Madhu Sudhan Reddy
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wallerman, Ola
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bornelöv, Susanne
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Zatloukal, Kurt
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wadelius, Claes
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    ChIP-seq in steatohepatitis and normal liver tissue identifies candidate disease mechanisms related to progression to cancer2013In: BMC Medical Genomics, ISSN 1755-8794, E-ISSN 1755-8794, Vol. 6, p. 50-Article in journal (Refereed)
    Abstract [en]

    Background: Steatohepatitis occurs in alcoholic liver disease and may progress to liver cirrhosis and hepatocellular carcinoma. Its molecular pathogenesis is to a large degree unknown. Histone modifications play a key role in transcriptional regulations as marks for silencing and activation of gene expression and as marks for functional elements. Many transcription factors (TFs) are crucial for the control of the genes involved in metabolism, and abnormality in their function may lead to disease. Methods: We performed ChIP-seq of the histone modifications H3K4me1, H3K4me3 and H3K27ac and a candidate transcription factor (USF1) in liver tissue from patients with steatohepatitis and normal livers and correlated results to mRNA-expression and genotypes. Results: We found several regions that are differentially enriched for histone modifications between disease and normal tissue, and qRT-PCR results indicated that the expression of the tested genes strongly correlated with differential enrichment of histone modifications but is independent of USF1 enrichment. By gene ontology analysis of differentially modified genes we found many disease associated genes, some of which had previously been implicated in the etiology of steatohepatitis. Importantly, the genes associated to the strongest histone peaks in the patient were over-represented in cancer specific pathways suggesting that the tissue was on a path to develop to cancer, a common complication to the disease. We also found several novel SNPs and GWAS catalogue SNPs that are candidates to be functional and therefore needs further study. Conclusion: In summary we find that analysis of chromatin features in tissue samples provides insight into disease mechanisms.

  • 8.
    Bysani, Madhusudhan Reddy
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics.
    Wallerman, Ola
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics.
    Bornelöv, Susanne
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Zatloukal, Kurt
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Wadelius, Claes
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics.
    ChIP-seq in steatohepatitis and normal liver tissue identifies candidate disease mechanisms related to progression to cancerManuscript (preprint) (Other academic)
  • 9.
    Dabrowski, M. J.
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bornelöv, Susanne
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Kruczyk, M.
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Baltzer, N.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    'True' null allele detection in microsatellite loci: a comparison of methods, assessment of difficulties and survey of possible improvements2015In: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998, Vol. 15, no 3, p. 477-488Article in journal (Refereed)
    Abstract [en]

    Null alleles are alleles that for various reasons fail to amplify in a PCR assay. The presence of null alleles in microsatellite data is known to bias the genetic parameter estimates. Thus, efficient detection of null alleles is crucial, but the methods available for indirect null allele detection return inconsistent results. Here, our aim was to compare different methods for null allele detection, to explain their respective performance and to provide improvements. We applied several approaches to identify the true' null alleles based on the predictions made by five different methods, used either individually or in combination. First, we introduced simulated true' null alleles into 240 population data sets and applied the methods to measure their success in detecting the simulated null alleles. The single best-performing method was ML-NullFreq_frequency. Furthermore, we applied different noise reduction approaches to improve the results. For instance, by combining the results of several methods, we obtained more reliable results than using a single one. Rule-based classification was applied to identify population properties linked to the false discovery rate. Rules obtained from the classifier described which population genetic estimates and loci characteristics were linked to the success of each method. We have shown that by simulating true' null alleles into a population data set, we may define a null allele frequency threshold, related to a desired true or false discovery rate. Moreover, using such simulated data sets, the expected null allele homozygote frequency may be estimated independently of the equilibrium state of the population.

  • 10.
    Enroth, Stefan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Bornelöv, Susanne
    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 Genetics and Pathology.
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Combinations of histone modifications control exon expressionArticle in journal (Other academic)
  • 11.
    Enroth, Stefan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bornelöv, Susanne
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Wadelius, Claes
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Genetics.
    Komorowski, Jan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Combinations of histone modifications mark exon inclusion levels2012In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, no 1, article id e29911Article in journal (Refereed)
    Abstract [en]

    Splicing is a complex process regulated by sequence at the classical splice sites and other motifs in exons and introns with an enhancing or silencing effect. In addition, specific histone modifications on nucleosomes positioned over the exons have been shown to correlate both positively and negatively with exon expression. Here, we trained a model of "IF … THEN …" rules to predict exon inclusion levels in a transcript from histone modification patterns. Furthermore, we showed that combinations of histone modifications, in particular those residing on nucleosomes preceding or succeeding the exon, are better predictors of exon inclusion levels than single modifications. The resulting model was evaluated with cross validation and had an average accuracy of 72% for 27% of the exons, which demonstrates that epigenetic signals substantially mark alternative splicing.

  • 12.
    Lee, Mi Ok
    et al.
    Texas A&M Univ, Dept Vet Pathobiol, College Stn, TX 77843 USA..
    Bornelöv, Susanne
    Uppsala University, Science for Life Laboratory, SciLifeLab. Univ Cambridge, Wellcome Trust Med Res Council Stem Cell Inst, Cambridge CB2 1QR, England..
    Andersson, Leif
    Uppsala University, Science for Life Laboratory, SciLifeLab. Texas A&M Univ, Coll Vet Med, Dept Vet Integrat Biosci, College Stn, TX 77843 USA..
    Lamont, Susan J.
    Iowa State Univ, Dept Anim Sci, Ames, IA 50011 USA..
    Chen, Junfeng
    Uppsala University, Science for Life Laboratory, SciLifeLab. Texas A&M Univ, Dept Vet Pathobiol, College Stn, TX 77843 USA.
    Womack, James E.
    Texas A&M Univ, Dept Vet Pathobiol, College Stn, TX 77843 USA..
    Duplication of chicken defensin7 gene generated by gene conversion and homologous recombination2016In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 113, no 48, p. 13815-13820Article in journal (Refereed)
    Abstract [en]

    Defensins constitute an evolutionary conserved family of cationic antimicrobial peptides that play a key role in host innate immune responses to infection. Defensin genes generally reside in complex genomic regions that are prone to structural variation, and defensin genes exhibit extensive copy number variation in humans and in other species. Copy number variation of defensin genes was examined in inbred lines of Leghorn and Fayoumi chickens, and a duplication of defensin7 was discovered in the Fayoumi breed. Analysis of junction sequences confirmed the occurrence of a simple tandem duplication of defensin7 with sequence identity at the junction, suggesting nonallelic homologous recombination between defensin7 and defensin6. The duplication event generated two chimeric promoters that are best explained by gene conversion followed by homologous recombination. Expression of defensin7 was not elevated in animals with two genes despite both genes being transcribed in the tissues examined. Computational prediction of promoter regions revealed the presence of several putative transcription factor binding sites generated by the duplication event. These data provide insight into the evolution and possible function of large gene families and specifically, the defensins.

  • 13.
    Seroussi, Eyal
    et al.
    Volcani Ctr, Agr Res Org, Dept Anim Sci, Rishon Letsiyon.
    Pitel, Frederique
    Univ Toulouse, INRA, GenPhySE, INPT, ENVT, Castanet Tolosan.
    Leroux, Sophie
    Univ Toulouse, INRA, GenPhySE, INPT, ENVT, Castanet Tolosan.
    Morisson, Mireille
    Univ Toulouse, INRA, GenPhySE, INPT, ENVT, Castanet Tolosan.
    Bornelöv, Susanne
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Miyara, Shoval
    Volcani Ctr, Agr Res Org, Dept Anim Sci, Rishon Letsiyon.
    Yosefi, Sara
    Volcani Ctr, Agr Res Org, Dept Anim Sci, Rishon Letsiyon.
    Cogburn, Larry A.
    Univ Delaware, Dept Anim & Food Sci, Newark.
    Burt, David W.
    Univ Edinburgh, Roslin Inst, Midlothian.; Univ Edinburgh, Royal (Dick) Sch Vet Studies, Midlothian.
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Texas A&M Univ, Coll Vet Med & Biomed Sci, Dept Vet Integrat Biosci, College Stn, Texas.; Swedish Univ Agr Sci, Dept Anim Breeding & Genet, Uppsala.
    Friedman-Einat, Miriam
    Volcani Ctr, Agr Res Org, Dept Anim Sci, Rishon Letsiyon.
    Correction to: Mapping of leptin and its syntenic genes to chicken chromosome 1p2017In: BMC Genetics, ISSN 1471-2156, E-ISSN 1471-2156, Vol. 18, no 113Article in journal (Other academic)
1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf