4.5 Article

Genome-wide association and regional heritability mapping to identify loci underlying variation in nematode resistance and body weight in Scottish Blackface lambs

Journal

HEREDITY
Volume 110, Issue 5, Pages 420-429

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/hdy.2012.90

Keywords

body weight; GWA analysis; nematode resistance; RHM; sheep; SNP

Funding

  1. 3SR project (Sustainable Solutions for Small Ruminants) - 7th Framework Programme
  2. [245140]
  3. BBSRC [BBS/E/D/20211553] Funding Source: UKRI
  4. Biotechnology and Biological Sciences Research Council [BBS/E/D/20211553] Funding Source: researchfish

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The genetic architecture underlying nematode resistance and body weight in Blackface lambs was evaluated comparing genome-wide association (GWA) and regional heritability mapping (RHM) approaches. The traits analysed were faecal egg count (FEC) and immunoglobulin A activity against third-stage larvae from Teladorsagia circumcincta, as indicators of nematode resistance, and body weight in a population of 752 Scottish Blackface lambs, genotyped with the 50k single-nucleotide polymorphism (SNP) chip. FEC for both Nematodirus and Strongyles nematodes (excluding Nematodirus), as well as body weight were collected at approximately 16, 20 and 24 weeks of age. In addition, a weighted average animal effect was estimated for both FEC and body weight traits. After quality control, 44 388 SNPs were available for the GWA analysis and 42 841 for the RHM, which utilises only mapped SNPs. The same fixed effects were used in both analyses: sex, year, management group, litter size and age of dam, with day of birth as covariate. Some genomic regions of interest for both nematode resistance and body weight traits were identified, using both GWA and RHM approaches. For both methods, strong evidence for association was found on chromosome 14 for Nematodirus average animal effect, chromosome 6 for Strongyles FEC at 16 weeks and chromosome 6 for body weight at 16 weeks. Across the entire data set, RHM identified more regions reaching the suggestive level than GWA, suggesting that RHM is capable of capturing some of the variation not detected by GWA analyses. Heredity (2013) 110, 420-429; doi:10.1038/hdy.2012.90; published online 20 March 2013

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