Genome wide association analysis on semen volume and milk yield using different strategies of imputation to whole genome sequence in French dairy goats
Autor: | Christèle Robert-Granié, Claire Oget, Gwenola Tosser-Klopp, Isabelle Palhiere, Estelle Talouarn, Rachel Rupp, Philippe Bardou, Virginie Clément |
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Přispěvatelé: | Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de l'Elevage (IDELE), Occitanie region Animal Genetics Division of the French National Institute for Agriculture, Food and Environment (INRAE-GA) |
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Male
0301 basic medicine [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT] lcsh:QH426-470 Genotype Genetic Linkage Quantitative Trait Loci Sequence data Genome-wide association study Biology 03 medical and health sciences French Alpine and Saanen Semen Genetics Capra hircus Animals 1000 Genomes Project Genotyping Genetics (clinical) Genetic association Imputation 2. Zero hunger Genome GWAS analysis Milk yield Models Genetic Whole Genome Sequencing Goats 0402 animal and dairy science Genomics 04 agricultural and veterinary sciences biology.organism_classification 040201 dairy & animal science Breed lcsh:Genetics Milk Phenotype 030104 developmental biology Capra Algorithms Imputation (genetics) Genome-Wide Association Study Research Article |
Zdroj: | BMC Genetics BMC Genetics, BioMed Central, 2020, 21 (1), ⟨10.1186/s12863-020-0826-9⟩ BMC Genetics, Vol 21, Iss 1, Pp 1-13 (2020) |
ISSN: | 1471-2156 |
DOI: | 10.1186/s12863-020-0826-9⟩ |
Popis: | Background Goats were domesticated 10,500 years ago to supply humans with useful resources. Since then, specialized breeds that are adapted to their local environment have been developed and display specific genetic profiles. The VarGoats project is a 1000 genomes resequencing program designed to cover the genetic diversity of the Capra genus. In this study, our main objective was to assess the use of sequence data to detect genomic regions associated with traits of interest in French Alpine and Saanen breeds. Results Direct imputation from the GoatSNP50 BeadChip genotypes to sequence level was investigated in these breeds using FImpute and different reference panels: within-breed, all Capra hircus sequenced individuals, European goats and French mainland goats. The best results were obtained with the French goat panel with allele and genotype concordance rates reaching 0.86 and 0.75 in the Alpine and 0.86 and 0.73 in the Saanen breed respectively. Mean correlations tended to be low in both breeds due to the high proportion of variants with low frequencies. For association analysis, imputation was performed using FImpute for 1129 French Alpine and Saanen males using within-breed and French panels on 23,338,436 filtered variants. The association results of both imputation scenarios were then compared. In Saanen goats, a large region on chromosome 19 was significantly linked to semen volume and milk yield in both scenarios. Significant variants for milk yield were annotated for 91 genes on chromosome 19 in Saanen goats. For semen volume, the annotated genes include YBOX2 which is related to azoospermia or oligospermia in other species. New signals for milk yield were detected on chromosome 2 in Alpine goats and on chromosome 5 in Saanen goats when using a multi-breed panel. Conclusion Even with very small reference populations, an acceptable imputation quality can be achieved in French dairy goats. GWAS on imputed sequences confirmed the existence of QTLs and identified new regions of interest in dairy goats. Adding identified candidates to a genotyping array and sequencing more individuals might corroborate the involvement of identified regions while removing potential imputation errors. |
Databáze: | OpenAIRE |
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