Evidence map›Paper›PMID 41131485›Full record

ArticleGenetics, selection, evolution : GSE2025

Application of a French cattle pangenome, from structural variant discovery to association studies on key phenotypes.

Valentin Sorin, Maulana Mughitz Naji, Clément Birbes, Cécile Grohs, Clémentine Escouflaire, Sébastien Fritz, Camille Eché, Camille Marcuzzo, Amandine Suin, Cécile Donnadieu and 9 more

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
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

19 authors.

Valentin SorinINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France. valentin.sorin@inrae.fr.ORCID http://orcid.org/0009-0001-1533-6637
Maulana Mughitz NajiINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France.
Clément BirbesBioInfoMics, MIAT UR875, Sigenae, INRAE, Genotoul Bioinfo, 31326, Castanet-Tolosan, France.
Cécile GrohsINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France.
Clémentine EscouflaireINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France.
Sébastien FritzINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France.
Camille EchéINRAE, US 1426, GeT-PlaGe, Genotoul, France Génomique, Université de Toulouse, 31326, Castanet-Tolosan, France.
Camille MarcuzzoINRAE, US 1426, GeT-PlaGe, Genotoul, France Génomique, Université de Toulouse, 31326, Castanet-Tolosan, France.
Amandine SuinINRAE, US 1426, GeT-PlaGe, Genotoul, France Génomique, Université de Toulouse, 31326, Castanet-Tolosan, France.
Cécile DonnadieuINRAE, US 1426, GeT-PlaGe, Genotoul, France Génomique, Université de Toulouse, 31326, Castanet-Tolosan, France.
Christine GaspinBioInfoMics, MIAT UR875, Sigenae, INRAE, Genotoul Bioinfo, 31326, Castanet-Tolosan, France.
Carole IampietroINRAE, US 1426, GeT-PlaGe, Genotoul, France Génomique, Université de Toulouse, 31326, Castanet-Tolosan, France.
Denis MilanINRAE, US 1426, GeT-PlaGe, Genotoul, France Génomique, Université de Toulouse, 31326, Castanet-Tolosan, France.
Laurence DrouilhetGenPhySE, INRAE, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France.
Gwenola Tosser-KloppGenPhySE, INRAE, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France.
Didier BoichardINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France.
Christophe KloppBioInfoMics, MIAT UR875, Sigenae, INRAE, Genotoul Bioinfo, 31326, Castanet-Tolosan, France.
Marie-Pierre SanchezINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France.
Mekki BoussahaINRAE, AgroParisTech, GABI, Université Paris Saclay, 78350, Jouy en Josas, France. mekki.boussaha@inrae.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe current cattle reference genome assembly, a pseudo-linear sequence produced using sequences from a single Hereford cow, represents a limitation when performing genetic studies, especially when investigating the whole spectrum of genetic variations within the species. Detecting structural variations (SVs) poses significant challenges when relying solely on conventional methods of sequencing read mapping to the current bovine genome assembly.

resultsIn this study, we used long-reads (LR) and bioinformatic tools to construct a comprehensive bovine pangenome, using as a backbone the Hereford ARS-UCD1.2 reference genome assembly, and incorporating genetic diversity of 64 good quality de novo genome assemblies representing 14 French dairy and beef cattle breeds. Using a combination of complementary approaches, we explored the pangenome graph and identified 2.563 Gb of sequences common to all samples, and cumulated 0.295 Gb of variable sequences. Notably, we discovered 0.159 Gb of novel sequences not present in the current reference genome assembly. Our analysis also revealed 109,275 SVs, of which 84,612 were bi-allelic. These included 27,171 insertions and 24,592 deletions, while the remaining 32,849 SVs corresponded to alternate allele sequences defined as sequence substitutions between the reference genome and the sample sequence. Genome-wide association studies using SNPs and a panel of 221 SVs, shared between the pangenome and the EuroGMD chip, revealed well-known QTLs across the genome for the Holstein, Montbéliarde and Normande breeds. Among those, a QTL on chromosome 11 presents an SV with a highly significant effect on stature in the Holstein breed. This SV is a 6.2 kb deletion affecting the 5'UTR, first exon and part of the first intron of the MATN3 gene, suggesting a potential regulatory and coding effect.

conclusionsOur study provides new insights into the genetic diversity of 14 French dairy and beef breeds and highlights the utility of pangenome graphs in capturing structural variation. The identified SV associated with stature highlights the importance of integrating SVs into GWAS for a more comprehensive understanding of complex traits.

Indexed as

GenomeGenomic Structural VariationAnimalsCattleFranceGenetic VariationGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID41131485
PMCPMC12551211

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.