Evidence map›Paper›PMID 32998688›Full record

ArticleGenetics, selection, evolution : GSE2020

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

Thierry Tribout, Pascal Croiseau, Rachel Lefebvre, Anne Barbat, Mekki Boussaha, Sébastien Fritz, Didier Boichard, Chris Hoze, Marie-Pierre Sanchez

Open access · goldAbstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
6.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 76 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 2 countries.

Thierry TriboutUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Pascal CroiseauUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Rachel LefebvreUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Anne BarbatUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Mekki BoussahaUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Sébastien FritzUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Didier BoichardUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Chris HozeUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Marie-Pierre SanchezUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France. marie-pierre.sanchez@inrae.fr.ORCID http://orcid.org/0000-0002-1371-5342
AgroParisTech · FR

Funding

Agence Nationale de la Recherche ANR-05-GENANIMAL-007 (CartoFine)Agence Nationale de la Recherche ANR-08-GANI-034 (LactoScan)Agence Nationale de la Recherche ANR-08-GENM-030-01 (Amasgen)APIS-GENE CartoFine & Amasgen
6 · The paper itself

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.

Indexed as

Quantitative Trait LociAnimalsCattleFemaleLactationMammary Glands, AnimalMilkPolymorphism, GeneticQuantitative Trait, Heritable

Identifiers

PMID32998688
PMCPMC7529513
OpenAlexW3091504354

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.