CNV-based genome-wide association studies with performance traits in broilers

• Ano de defesa: 2020
• Autor(a) principal: Fernandes, Anna Carolina
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: CNVs; Desempenho; GWAS; Performance; qPCR; QTLs
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/11/11139/tde-11022021-115104/

Chicken (Gallus Gallus) is an important source of animal protein, considered a biological research model in the genetics field and a species of considerable economic relevance worldwide, mainly as a consequence of constant improvement of performance traits. In this sense, selection of animals that present phenotypic traits of interest is fundamental. Therefore, the identification of genetic variations and their association with production traits of economic importance are crucial steps for a better understanding of the biological mechanisms that control these complex characteristics. An important source of known variation in the DNA are copy number variations (CNVs), which can contribute significantly to phenotypic variation in several species. In this context, genotypic data from approximately 1,500 animals from a paternal broiler line (TT), obtained using a high-density SNP array (600k, Affymetrix), were used to identify genomic regions and candidate genes associated with performance traits. We performed a CNV-based genome-wide association study (GWAS) using the CNVRanger software, adjusting a linear mixed model, to identify regions in the genome associated with birth weight, body weight at 21 days, body weight at 35 days, body weight at 41 days, body weight at 42 days, feed intake, feed conversion ratio and body weight gain. CNV segments significantly associated with birth weight, body weight at 35, 41 and 42 days and body weight gain were identified. After the association analyses, validation of these significantly associated CNV segments was performed by qPCR. The search for candidate genes was made within each associated genomic region, considering Gene Ontology (GO) terms and also the literature information. We identified novel genomic regions associated with these traits and important candidate genes for muscle growth and development, such as KCNJ11, MyoD1 and SOX6, with known role on chicken growth and muscle development, providing new information for a better understanding of the regulation of genetic control for performance in broilers.