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  • 1. Antolín, Roberto
    et al.
    Nettelblad, Carl
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för beräkningsvetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Gorjanc, Gregor
    Money, Daniel
    Hickey, John M.
    A hybrid method for the imputation of genomic data in livestock populations2017Ingår i: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 49, artikel-id 30Artikel i tidskrift (Refereegranskat)
  • 2.
    Besnier, Francois
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Centrum för bioinformatik.
    Wahlberg, Per
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi.
    Rönnegård, Lars
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Centrum för bioinformatik.
    Ek, Weronica
    Swedish University of Agricultural Sciences .
    Andersson, Leif
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Siegel, Paul
    virginia polytechnic institute and state university.
    Carlborg, Örjan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Centrum för bioinformatik.
    Fine mapping and replication of QTL in outbred chicken advanced intercross lines2011Ingår i: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 43, s. 3-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    BACKGROUND: Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F2 populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F2 animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.

    METHODS: We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F2 population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.

    RESULTS: Five of the nine QTL detected with the original F2 population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.

    CONCLUSIONS: Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.

     

  • 3.
    Zan, Yanjun
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Payen, Thibaut
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Lillie, Mette
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Honaker, Christa F.
    Virginia Polytech Inst & State Univ, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA.
    Siegel, Paul B.
    Virginia Polytech Inst & State Univ, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA.
    Carlborg, Örjan
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Genotyping by low-coverage whole-genome sequencing in intercross pedigrees from outbred founders: a cost-efficient approach2019Ingår i: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 51, nr 1, artikel-id 44Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background Experimental intercrosses between outbred founder populations are powerful resources for mapping loci that contribute to complex traits i.e. quantitative trait loci (QTL). Here, we present an approach and its accompanying software for high-resolution reconstruction of founder mosaic genotypes in the intercross offspring from such populations using whole-genome high-coverage sequence data on founder individuals (similar to 30x) and very low-coverage sequence data on intercross individuals (< 0.5x). Sets of founder-line informative markers were selected for each full-sib family and used to infer the founder mosaic genotypes of the intercross individuals. The application of this approach and the quality of the estimated genome-wide genotypes are illustrated in a large F-2 pedigree between two divergently selected lines of chickens. Results We describe how we obtained whole-genome genotype data for hundreds of individuals in a cost- and time-efficient manner by using a Tn5-based library preparation protocol and an imputation algorithm that was optimized for this application. In total, 7.6 million markers segregated in this pedigree and, within each full-sib family, between 10.0 and 13.7% of these were fully informative, i.e. fixed for alternative alleles in the founders from the divergent lines, and were used for reconstruction of the offspring mosaic genotypes. The genotypes that were estimated based on the low-coverage sequence data were highly consistent (> 95% agreement) with those obtained using individual single nucleotide polymorphism (SNP) genotyping. The estimated resolution of the inferred recombination breakpoints was relatively high, with 50% of them being defined on regions shorter than 10 kb. Conclusions A method and software for inferring founder mosaic genotypes in intercross offspring from low-coverage whole-genome sequencing in pedigrees from heterozygous founders are described. They provide high-quality, high-resolution genotypes in a time- and cost-efficient manner. The software is freely available at https://github.com/CarlborgGenomics/Stripes..

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