Abstract

Gastrointestinal nematode infections are one of the main health/economic issues in sheep industries, worldwide. Indicator traits for resistance such as faecal egg count (FEC) are commonly used in genomic studies; however, published results are inconsistent among breeds. Meta (or joint)-analysis is a tool for aggregating information from multiple independent studies. The aim of this study was to identify loci underlying variation in FEC, as an indicator of nematode resistance, in a joint analysis using data from three populations (Scottish Blackface, Sarda × Lacaune and Martinik Black-Belly × Romane), genotyped with the ovine 50k SNP chip. The trait analysed was the average animal effect for Strongyles and Nematodirus FEC data. Analyses were performed with regional heritability mapping (RHM), fitting polygenic effects with either the whole genomic relationship matrix or matrices excluding the chromosome being interrogated. Across-population genomic covariances were set to zero. After quality control, 4123 animals and 38 991 SNPs were available for the analysis. RHM identified genome-wide significant regions on OAR4, 12, 14, 19 and 20, with the latter being the most significant. The OAR20 region is close to the major histocompatibility complex, which has often been proposed as a functional candidate for nematode resistance. This region was significant only in the Sarda × Lacaune population. Several other regions, on OAR1, 3, 4, 5, 7, 12, 19, 20 and 24, were significant at the suggestive level.

Highlights

  • Gastrointestinal nematode infections are one of the main health issues in grazing ruminants and have a great impact on sheep industries, worldwide

  • Indicator traits for resistance such as faecal egg count (FEC) are commonly used in genomic studies; published results are inconsistent among breeds

  • Analyses were performed with regional heritability mapping (RHM), fitting polygenic effects with either the whole genomic relationship matrix or matrices excluding the chromosome being interrogated

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Summary

Introduction

Gastrointestinal nematode infections are one of the main health issues in grazing ruminants and have a great impact on sheep industries, worldwide. (e.g. Crawford et al 2006; Davies et al 2006) or genome-wide association (GWA) analyses (e.g. Kemper et al 2011; Salle et al 2012; Riggio et al 2013). This may be due to both the apparent genetic complexity of the trait and the fact that these studies are very diverse, involving a variety of sheep breeds, nematode species and experimental approaches. We propose that there are statistical techniques which can be used to jointly analyse these diverse datasets and gain greater power These are based on the concept of meta-analysis, a tool for aggregating information from multiple independent studies (Cochran 1954; Fleiss 1993).

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