Imputation-Based Fine-Mapping Suggests That Most QTL in an Outbred Chicken Advanced Intercross Body Weight Line Are Due to Multiple, Linked Loci.

Brandt M, Ahsan M, Honaker CF, Siegel PB, Carlborg Ö

G3 (Bethesda) 7 (1) 119-128 [2017-01-05; online 2017-01-05]

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.

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PubMed 27799342

DOI 10.1534/g3.116.036012

Crossref 10.1534/g3.116.036012

pii: g3.116.036012
pmc: PMC5217102