A joint analysis to identify loci underlying variation in nematode resistance in three European sheep populations

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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.

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Most cited references 26

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Two models for study-to-study variation in a meta-analysis are presented, critiqued and illustrated. One, the fixed effects model, takes the studies being analysed as the universe of interest; the other, the random effects model, takes these studies as representing a sample from a larger population of possible studies. With emphasis on clinical trials, this paper illustrates in some detail the application of both models to three summary measures of the effect of an experimental intervention versus a control: the standardized difference for comparing two means, and the relative risk and odds ratio for comparing two proportions.

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Detecting signatures of selection through haplotype differentiation among hierarchically structured populations.

Maria Ines Fariello, Simon Boitard, Hugo Naya … (2013)

The detection of molecular signatures of selection is one of the major concerns of modern population genetics. A widely used strategy in this context is to compare samples from several populations and to look for genomic regions with outstanding genetic differentiation between these populations. Genetic differentiation is generally based on allele frequency differences between populations, which are measured by FST or related statistics. Here we introduce a new statistic, denoted hapFLK, which focuses instead on the differences of haplotype frequencies between populations. In contrast to most existing statistics, hapFLK accounts for the hierarchical structure of the sampled populations. Using computer simulations, we show that each of these two features-the use of haplotype information and of the hierarchical structure of populations-significantly improves the detection power of selected loci and that combining them in the hapFLK statistic provides even greater power. We also show that hapFLK is robust with respect to bottlenecks and migration and improves over existing approaches in many situations. Finally, we apply hapFLK to a set of six sheep breeds from Northern Europe and identify seven regions under selection, which include already reported regions but also several new ones. We propose a method to help identifying the population(s) under selection in a detected region, which reveals that in many of these regions selection most likely occurred in more than one population. Furthermore, several of the detected regions correspond to incomplete sweeps, where the favorable haplotype is only at intermediate frequency in the population(s) under selection.

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Meta-analysis in genome-wide association studies.

Eleftheria Zeggini, John Ioannidis (2009)

The advent of genome-wide association studies has allowed considerable progress in the identification and robust replication of common gene variants that confer susceptibility to common diseases and other phenotypes of interest. These genetic effect sizes are almost invariably moderate to small in magnitude and single studies, even if large, are underpowered to detect them with confidence. Meta-analysis of many genome-wide association studies improves the power to detect more associations, and to investigate the consistency or heterogeneity of these associations across diverse datasets and study populations. In this review, we discuss the key methodological issues in the set-up, information gathering and processing, and analysis of meta-analyses of genome-wide association datasets. We illustrate, as an example, the application of meta-analysis methods in the elucidation of common genetic variants associated with Type 2 diabetes. Finally, we discuss the prospects and caveats for future application of meta-analysis methods in the genome-wide setting.

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Author and article information

Journal

Journal ID (nlm-ta): J Anim Breed Genet

Journal ID (iso-abbrev): J. Anim. Breed. Genet

Journal ID (publisher-id): jbg

Title: Journal of Animal Breeding and Genetics

Publisher: BlackWell Publishing Ltd (Oxford, UK )

ISSN (Print): 0931-2668

ISSN (Electronic): 1439-0388

Publication date (Print): December 2014

Publication date (Electronic): 08 January 2014

Volume: 131

Issue: 6

Pages: 426-436

Affiliations

[1 ]The Roslin Institute and R(D)SVS, University of Edinburgh Easter Bush, Midlothian, UK

[2 ]Station d'Amélioration Génétique des Animaux, INRA, UR631 Castanet-Tolosan, France

[3 ]Settore Genetica e Biotecnologie, AGRIS Sardegna Olmedo, Sassari, Italy

Author notes

Correspondence Valentina Riggio, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK., Tel: +44 (0) 131 651 9100;, Fax: +44 (0) 131 651 9105;, E-mail: valentina.riggio@ 123456roslin.ed.ac.uk

Article

DOI: 10.1111/jbg.12071

PMC ID: 4258091

PubMed ID: 24397290

SO-VID: 6c9e909b-cc67-4326-b832-900a9939b328

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This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

A joint analysis to identify loci underlying variation in nematode resistance in three European sheep populations

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Core Readings in Statistical Mediation Analysis

Most cited references 26

The statistical basis of meta-analysis.

Detecting signatures of selection through haplotype differentiation among hierarchically structured populations.

Meta-analysis in genome-wide association studies.

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