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Imputation-Based Fine-Mapping Suggests That Most QTL in an Outbred Chicken Advanced Intercross Body Weight Line Are Due to Multiple, Linked Loci
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. (Carlborg)
Swedish Univ Agr Sci, Div Computat Genet, Dept Clin Sci, S-75007 Uppsala, Sweden.
Virginia Polytech Inst & State Univ, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA.
Virginia Polytech Inst & State Univ, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA.
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2017 (English)In: G3: Genes, Genomes, Genetics, ISSN 2160-1836, E-ISSN 2160-1836, Vol. 7, no 1, p. 119-128Article in journal (Refereed) Published
Abstract [en]

The Virginia chicken lines have been divergently selected for juvenile body weight for more than 50 generations. Today, the high- and low-weight lines show a >12-fold difference for the selected trait, 56-d body weight. These lines provide unique opportunities to study the genetic architecture of long-term, single-trait selection. Previously, several quantitative trait loci (QTL) contributing to weight differences between the lines were mapped in an F2-cross between them, and these were later replicated and fine-mapped in a nine-generation advanced intercross of them. Here, we explore the possibility to further increase the fine-mapping resolution of these QTL via a pedigree-based imputation strategy that aims to better capture the genetic diversity in the divergently selected, but outbred, founder lines. The founders of the intercross were high-density genotyped, and then pedigree-based imputation was used to assign genotypes throughout the pedigree. Imputation increased the marker density 20-fold in the selected QTL, providing 6911 markers for the subsequent analysis. Both single-marker association and multi-marker backward-elimination analyses were used to explore regions associated with 56-d body weight. The approach revealed several statistically and population structure independent associations and increased the mapping resolution. Further, most QTL were also found to contain multiple independent associations to markers that were not fixed in the founder populations, implying a complex underlying architecture due to the combined effects of multiple, linked loci perhaps located on independent haplotypes that still segregate in the selected lines.

Place, publisher, year, edition, pages
2017. Vol. 7, no 1, p. 119-128
National Category
Medical Genetics
Research subject
Bioinformatics; Genetics
Identifiers
URN: urn:nbn:se:uu:diva-313199DOI: 10.1534/g3.116.036012ISI: 000392200800011PubMedID: 27799342OAI: oai:DiVA.org:uu-313199DiVA, id: diva2:1066159
Funder
Swedish Research Council Formas, 221-2013-450Swedish Research Council, 621-2012-4634Available from: 2017-01-17 Created: 2017-01-17 Last updated: 2018-01-18Bibliographically approved

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