Association analysis and functional annotation of imputed sequence data within genomic regions influencing resistance to gastro-intestinal parasites detected by an LDLA approach in a nucleus flock of Sarda dairy sheep.


Journal

Genetics, selection, evolution : GSE
ISSN: 1297-9686
Titre abrégé: Genet Sel Evol
Pays: France
ID NLM: 9114088

Informations de publication

Date de publication:
03 Jan 2022
Historique:
received: 08 04 2021
accepted: 03 12 2021
entrez: 4 1 2022
pubmed: 5 1 2022
medline: 6 1 2022
Statut: epublish

Résumé

Gastroinestinal nematodes (GIN) are one of the major health problem in grazing sheep. Although genetic variability of the resistance to GIN has been documented, traditional selection is hampered by the difficulty of recording phenotypes, usually fecal egg count (FEC). To identify causative mutations or markers in linkage disequilibrium (LD) to be used for selection, the detection of quantitative trait loci (QTL) for FEC based on linkage disequilibrium-linkage analysis (LDLA) was performed on 4097 ewes (from 181 sires) all genotyped with the OvineSNP50 Beadchip. Identified QTL regions (QTLR) were imputed from whole-genome sequences of 56 target animals of the population. An association analysis and a functional annotation of imputed polymorphisms in the identified QTLR were performed to pinpoint functional variants with potential impact on candidate genes identified from ontological classification or differentially expressed in previous studies. After clustering close significant locations, ten QTLR were defined on nine Ovis aries chromosomes (OAR) by LDLA. The ratio between the ANOVA estimators of the QTL variance and the total phenotypic variance ranged from 0.0087 to 0.0176. QTL on OAR4, 12, 19, and 20 were the most significant. The combination of association analysis and functional annotation of sequence data did not highlight any putative causative mutations. None of the most significant SNPs showed a functional effect on genes' transcript. However, in the most significant QTLR, we identified genes that contained polymorphisms with a high or moderate impact, were differentially expressed in previous studies, contributed to enrich the most represented GO process (regulation of immune system process, defense response). Among these, the most likely candidate genes were: TNFRSF1B and SELE on OAR12, IL5RA on OAR19, IL17A, IL17F, TRIM26, TRIM38, TNFRSF21, LOC101118999, VEGFA, and TNF on OAR20. This study performed on a large experimental population provides a list of candidate genes and polymorphisms which could be used in further validation studies. The expected advancements in the quality of the annotation of the ovine genome and the use of experimental designs based on sequence data and phenotypes from multiple breeds that show different LD extents and gametic phases may help to identify causative mutations.

Sections du résumé

BACKGROUND BACKGROUND
Gastroinestinal nematodes (GIN) are one of the major health problem in grazing sheep. Although genetic variability of the resistance to GIN has been documented, traditional selection is hampered by the difficulty of recording phenotypes, usually fecal egg count (FEC). To identify causative mutations or markers in linkage disequilibrium (LD) to be used for selection, the detection of quantitative trait loci (QTL) for FEC based on linkage disequilibrium-linkage analysis (LDLA) was performed on 4097 ewes (from 181 sires) all genotyped with the OvineSNP50 Beadchip. Identified QTL regions (QTLR) were imputed from whole-genome sequences of 56 target animals of the population. An association analysis and a functional annotation of imputed polymorphisms in the identified QTLR were performed to pinpoint functional variants with potential impact on candidate genes identified from ontological classification or differentially expressed in previous studies.
RESULTS RESULTS
After clustering close significant locations, ten QTLR were defined on nine Ovis aries chromosomes (OAR) by LDLA. The ratio between the ANOVA estimators of the QTL variance and the total phenotypic variance ranged from 0.0087 to 0.0176. QTL on OAR4, 12, 19, and 20 were the most significant. The combination of association analysis and functional annotation of sequence data did not highlight any putative causative mutations. None of the most significant SNPs showed a functional effect on genes' transcript. However, in the most significant QTLR, we identified genes that contained polymorphisms with a high or moderate impact, were differentially expressed in previous studies, contributed to enrich the most represented GO process (regulation of immune system process, defense response). Among these, the most likely candidate genes were: TNFRSF1B and SELE on OAR12, IL5RA on OAR19, IL17A, IL17F, TRIM26, TRIM38, TNFRSF21, LOC101118999, VEGFA, and TNF on OAR20.
CONCLUSIONS CONCLUSIONS
This study performed on a large experimental population provides a list of candidate genes and polymorphisms which could be used in further validation studies. The expected advancements in the quality of the annotation of the ovine genome and the use of experimental designs based on sequence data and phenotypes from multiple breeds that show different LD extents and gametic phases may help to identify causative mutations.

Identifiants

pubmed: 34979909
doi: 10.1186/s12711-021-00690-7
pii: 10.1186/s12711-021-00690-7
pmc: PMC8722200
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2

Informations de copyright

© 2021. The Author(s).

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Auteurs

Sara Casu (S)

Genetics and Biotechnology - Agris Sardegna, Olmedo, Italy.

Mario Graziano Usai (MG)

Genetics and Biotechnology - Agris Sardegna, Olmedo, Italy. gmusai@agrisricerca.it.

Tiziana Sechi (T)

Genetics and Biotechnology - Agris Sardegna, Olmedo, Italy.

Sotero L Salaris (SL)

Genetics and Biotechnology - Agris Sardegna, Olmedo, Italy.

Sabrina Miari (S)

Genetics and Biotechnology - Agris Sardegna, Olmedo, Italy.

Giuliana Mulas (G)

Genetics and Biotechnology - Agris Sardegna, Olmedo, Italy.

Claudia Tamponi (C)

Department of Veterinary Medicine, University of Sassari, Sassari, Italy.

Antonio Varcasia (A)

Department of Veterinary Medicine, University of Sassari, Sassari, Italy.

Antonio Scala (A)

Department of Veterinary Medicine, University of Sassari, Sassari, Italy.

Antonello Carta (A)

Genetics and Biotechnology - Agris Sardegna, Olmedo, Italy.

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