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South African Journal of Animal Science

versão On-line ISSN 2221-4062
versão impressa ISSN 0375-1589

Resumo

ZWANE, A.A. et al. Gene-set enrichment analysis of selective sweeps reveals phenotypic traits in Nguni cattle. S. Afr. j. anim. sci. [online]. 2021, vol.51, n.6, pp.761-777. ISSN 2221-4062.  http://dx.doi.org/10.4314/sajas.v51i6.9.

Adaptation of animals to different environments is typically associated with structural and functional genomic variations. High throughput SNP genotyping and next-generation sequencing (NGS) have made it possible to study positive selection footprints and adaptation traits. Nguni is a small frame-size breed, mostly horned, and well known for being adapted to diverse South African environmental conditions. This study used previously identified selective sweeps to perform functional analysis of genes related to phenotypic characteristics in Nguni. Two hundred and sixty-four candidate selective sweeps were used for gene-set enrichment analysis in molecular functional categories (KEGG pathways) using the database for annotation, visualization, and integrated discovery (DAVID). In total, 107 genes were identified across all the chromosomes with 74 genes associated with eight phenotype queries, including fat content, milk production, walking ability, heat tolerance, meat production, reproduction, and bone and muscle development. Gene CRHR2was associated with meat quality (juiciness and flavour). The IRAK3 gene was associated with decreased body size, feed intake and fatness in cattle, and CARD15 with disease resistance. Gene annotation using phenotype queries identified four genes (SPI, YWHAZ, RGS4, and RGS5) that were associated with myometrial relaxation in cattle. Genes such as NOD2 and IL21R were associated with inflammatory bowel diseases in cattle, whereas CPLS gene was associated with fat content. These genes are important to the phenotypic and adaptive characteristics present in South African Nguni cattle and hold potential for selection for traits of economic importance.

Palavras-chave : annotation; genes; phenotypes; selective sweeps.

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