Abstract

BackgroundOver the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows.ResultsBull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits.ConclusionsUsing this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

Highlights

  • Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits

  • At least one QTL was identified for all traits in the HOL dataset with the exception of clinical mastitis score (CM), but no QTL was found for five traits in MON (PY, CM, teat length (TL), fore teat distance (FTD), and teat orientation (TO)) and nine traits in NOR (PY, CM, somatic cell score (SCS), udder depth (UD), fore udder attachment (FUA), FTD, udder balance (UB), TO, and milking speed score (MSS))

  • We identified 15 QTL ID, all linked with production traits, that were shared among the three breeds; they were located in five genomic regions and affected protein content (PC) on BTA3 and BTA6 and fat content (FC) on BTA5, BTA14, and BTA27

Read more

Summary

Introduction

Genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits In general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. The Eurogenomics custom single nucleotide polymorphism (SNP) chip, which has been developed for bovine genomic selection, appears to be an ideal tool for this purpose It contains an add-on feature that can be updated once or twice a year, and it is widely used in multiple breeds [6], which makes it possible to validate the effects of candidate variants detected by GWAS in different large populations

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call