Genome-wide detection of CNVs and their association with performance traits in broilers.
Abstract Background: Copy number variations (CNVs) are a major type of structural genomic variants that underlie genetic architecture and phenotypic variation of complex traits, not only in humans, but also in livestock animals. We identified CNVs along the chicken genome and analyzed their associat...
| Autores: | , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Brasil |
| Institución: | Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
| Repositorio: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
| Idioma: | inglés |
| OAI Identifier: | oai:www.alice.cnptia.embrapa.br:doc/1133197 |
| Acceso en línea: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1133197 https://doi.org/10.1186/s12864-021-07676-1 |
| Access Level: | acceso abierto |
| Palabra clave: | GWAS CNVs Copy number variations QTLs QPCR Desempenho zootécnico Genética Animal Gallus Domesticus Performance Animal genetics Genome-wide association study Animal performance Quantitative trait loci Quantitative polymerase chain reaction Gallus gallus |
| Sumario: | Abstract Background: Copy number variations (CNVs) are a major type of structural genomic variants that underlie genetic architecture and phenotypic variation of complex traits, not only in humans, but also in livestock animals. We identified CNVs along the chicken genome and analyzed their association with performance traits. Genome-wide CNVs were inferred from Affymetrix® high density SNP-chip data for a broiler population. CNVs were concatenated into segments and association analyses were performed with linear mixed models considering a genomic relationship matrix, for birth weight, body weight at 21, 35, 41 and 42 days, feed intake from 35 to 41 days, feed conversion ratio from 35 to 41 days and, body weight gain from 35 to 41 days of age. Results: We identified 23,214 autosomal CNVs, merged into 5042 distinct CNV regions (CNVRs), covering 12.84% of the chicken autosomal genome. One significant CNV segment was associated with BWG on GGA3 (q-value = 0.00443); one significant CNV segment was associated with BW35 (q-value = 0.00571), BW41 (q-value = 0.00180) and BW42 (q-value = 0.00130) on GGA3, and one significant CNV segment was associated with BW on GGA5 (q-value = 0.00432). All significant CNV segments were verified by qPCR, and a validation rate of 92.59% was observed. These CNV segments are located nearby genes, such as KCNJ11, MyoD1 and SOX6, known to underlie growth and development. Moreover, gene-set analyses revealed terms linked with muscle physiology, cellular processes regulation and potassium channels. Conclusions: Overall, this CNV-based GWAS study unravels potential candidate genes that may regulate performance traits in chickens. Our findings provide a foundation for future functional studies on the role of specific genes in regulating performance in chickens. Keywords: GWAS, Performance, CNVs, QTLs, qPCR |
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