Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle

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Abstract

Background

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. 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.

Results

Bull 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.

Conclusions

Using 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.

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A new approach for efficient genotype imputation using information from relatives

Mehdi Sargolzaei, Jacques P Chesnais, Flavio S. Schenkel (2014)

Background Genotype imputation can help reduce genotyping costs particularly for implementation of genomic selection. In applications entailing large populations, recovering the genotypes of untyped loci using information from reference individuals that were genotyped with a higher density panel is computationally challenging. Popular imputation methods are based upon the Hidden Markov model and have computational constraints due to an intensive sampling process. A fast, deterministic approach, which makes use of both family and population information, is presented here. All individuals are related and, therefore, share haplotypes which may differ in length and frequency based on their relationships. The method starts with family imputation if pedigree information is available, and then exploits close relationships by searching for long haplotype matches in the reference group using overlapping sliding windows. The search continues as the window size is shrunk in each chromosome sweep in order to capture more distant relationships. Results The proposed method gave higher or similar imputation accuracy than Beagle and Impute2 in cattle data sets when all available information was used. When close relatives of target individuals were present in the reference group, the method resulted in higher accuracy compared to the other two methods even when the pedigree was not used. Rare variants were also imputed with higher accuracy. Finally, computing requirements were considerably lower than those of Beagle and Impute2. The presented method took 28 minutes to impute from 6 k to 50 k genotypes for 2,000 individuals with a reference size of 64,429 individuals. Conclusions The proposed method efficiently makes use of information from close and distant relatives for accurate genotype imputation. In addition to its high imputation accuracy, the method is fast, owing to its deterministic nature and, therefore, it can easily be used in large data sets where the use of other methods is impractical.

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Positional candidate cloning of a QTL in dairy cattle: identification of a missense mutation in the bovine DGAT1 gene with major effect on milk yield and composition.

Bernard Grisart, Wouter Coppieters, Frédéric Farnir … (2002)

We recently mapped a quantitative trait locus (QTL) with a major effect on milk composition--particularly fat content--to the centromeric end of bovine chromosome 14. We subsequently exploited linkage disequilibrium to refine the map position of this QTL to a 3-cM chromosome interval bounded by microsatellite markers BULGE13 and BULGE09. We herein report the positional candidate cloning of this QTL, involving (1) the construction of a BAC contig spanning the corresponding marker interval, (2) the demonstration that a very strong candidate gene, acylCoA:diacylglycerol acyltransferase (DGAT1), maps to that contig, and (3) the identification of a nonconservative K232A substitution in the DGAT1 gene with a major effect on milk fat content and other milk characteristics.

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1000 Bull Genomes Project to Map Simple and Complex Genetic Traits in Cattle: Applications and Outcomes

Ben J. Hayes, Hans D Daetwyler (2019)

The 1000 Bull Genomes Project is a collection of whole-genome sequences from 2,703 individuals capturing a significant proportion of the world's cattle diversity. So far, 84 million single-nucleotide polymorphisms (SNPs) and 2.5 million small insertion deletions have been identified in the collection, a very high level of genetic diversity. The project has greatly accelerated the identification of deleterious mutations for a range of genetic diseases, as well as for embryonic lethals. The rate of identification of causal mutations for complex traits has been slower, reflecting the typically small effect size of these mutations and the fact that many are likely in as-yet-unannotated regulatory regions. Both the deleterious mutations that have been identified and the mutations associated with complex trait variation have been included in low-cost SNP array designs, and these arrays are being genotyped in tens of thousands of dairy and beef cattle, enabling management of deleterious mutations in these populations as well as genomic selection.

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Author and article information

Contributors

Thierry Tribout: thierry.tribout@inrae.fr

Pascal Croiseau: pascal.croiseau@inrae.fr

Rachel Lefebvre: rachel.lefebvre@inrae.fr

Anne Barbat: anne.barbat@inrae.fr

Mekki Boussaha: mekki.boussaha@inrae.fr

Sébastien Fritz: sebastien.fritz@allice.fr

Didier Boichard: didier.boichard@inrae.fr

Chris Hoze: chris.hoze@allice.fr

Marie-Pierre Sanchez:

ORCID: http://orcid.org/0000-0002-1371-5342

marie-pierre.sanchez@inrae.fr

Journal

Journal ID (nlm-ta): Genet Sel Evol

Title: Genetics, Selection, Evolution : GSE

Publisher: BioMed Central (London )

ISSN (Print): 0999-193X

ISSN (Electronic): 1297-9686

Publication date (Electronic): 1 October 2020

Publication date PMC-release: 1 October 2020

Publication date Collection: 2020

Volume: 52

Electronic Location Identifier: 55

Affiliations

[1 ]GRID grid.420312.6, ISNI 0000 0004 0452 7969, Université Paris-Saclay, INRAE, AgroParisTech, GABI, ; 78350 Jouy-en-Josas, France

[2 ]Allice, 75012 Paris, France

Author information

Marie-Pierre Sanchez http://orcid.org/0000-0002-1371-5342

Article

Publisher ID: 575

DOI: 10.1186/s12711-020-00575-1

PMC ID: 7529513

PubMed ID: 32998688

SO-VID: 28d5b663-40f5-43e6-9db2-5d9fdae9f09d

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 10 June 2020

Date accepted : 18 September 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;

Award ID: ANR-05-GENANIMAL-007 (CartoFine)

Award ID: ANR-08-GANI-034 (LactoScan)

Award ID: ANR-08-GENM-030-01 (Amasgen)

Award Recipient : Didier Boichard

Funded by: APIS-GENE

Award ID: CartoFine & Amasgen

Award Recipient : Didier Boichard

Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle

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Most cited references 45

A new approach for efficient genotype imputation using information from relatives

Positional candidate cloning of a QTL in dairy cattle: identification of a missense mutation in the bovine DGAT1 gene with major effect on milk yield and composition.

1000 Bull Genomes Project to Map Simple and Complex Genetic Traits in Cattle: Applications and Outcomes

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