Genome-wide association study on growth traits in Colombian creole breeds and crossbreeds with Zebu cattle

Abstract

ABSTRACT. Whole genome selection represents an important tool for improving parameters related to the production of livestock. In order to build genomic selection indexes within a particular breed, it is important to identify polymorphisms that have the most significant association with a desired trait. A genome-wide marker association approach based on the Illumina BovineSNP50 BeadChip TM was used to identify genomic regions affecting birth weight (BW), weaning weight (WW), and daily weight gain (DWG) in purebred and crossbred creole cattle populations. We genotyped 654 individuals of Blanco Orejinegro (BON), Romosinuano (ROMO) and Cebú breeds and the crossbreeds BON x Cebú and ROMO x Cebú, and tested 5 genetic control models. In total, 85 single nucleotide polymorphisms (SNPs) were related (P < 0.05) to the 3 evaluated traits; BW was associated with the highest number of SNPs. For statistical falsepositive correction, Bonferroni correction was used. From the results, we identified 7, 6, and 4 SNPs with strong associations with BW, WW, and DWG, respectively. Many of these SNPs were located Genome-wide association studies in Colombian creole cattle on important coding regions of the bovine genome; their ontology and interactions are discussed herein. The results could contribute to the identification of genes involved in the physiology of beef cattle growth and the development of new strategies for breeding management via genomic selection to improve the productivity of creole cattle herds.

Genome‐wide scan for signatures of selection in the Brangus cattle genome

“…In BTA19, UBE2G1 gene was reported as involved in muscle development in Nellore (dos Santos Silva et al, 2020), while in BTA4, QTLs for carcass weight harbouring TFPI2 , GNGT1 and CALCR genes, among others, were reported by Srikanth et al (2020). When the pairwise Brangus–Brahman was analysed, several genes in BTA6 associated with growth and skeletal type traits in cattle breeds were found, including ABCG2 , ADGRA3 , DCAF16 , SLIT2 , NCAPG , LCORL , DCAF16 , FAM184B , PPARGC1A , GRID2 , PI4K2B , SOD3 , CCDC149 , GBA3 , DHX15 and ZCCHC4 (Doyle et al, 2020a, 2020b; Kowalewska‐Łuczak et al, 2010; Li et al, 2014; Lindholm‐Perry et al, 2011; Maiorano et al, 2018; Martínez et al, 2014; Paim et al, 2020a; Sorbolini et al, 2015; Takasuga, 2016; Xia et al, 2017; Zanella et al, 2018). Genes XKR4 , LYPLA1 and TMEM68 located within the candidate region detected on BTA14 were recently reported to play a role in growth phenotypes in Brangus (Paim et al, 2020a), as well as feed intake and average daily gain phenotypes in cross‐bred steers (Lindholm‐Perry et al, 2012).…”

Efecto de marcadores genéticos moleculares en genes inducibles por hipoxia de bovinos criollos y Brown Swiss criados en los Andes de Perú

“…Con base a estos resultados, sería conveniente desarrollar un estudio de GWAS con mayor número de muestras, como los realizados por Wei et al (2016) en ovinos o Liu et al (2019) en equinos, e incluir información fenotípica referida a características fisiológicas que se presentan en el síndrome de mal de altura o que sean propias de animales adaptados a entornos de altitud, tal como se hacen en estudios para características de interés productivo o de adaptación ambiental (Martinez et al, 2014;De Leon et al, 2019), a fin de identificar PNSs de efecto mayor o que puedan estar implicados en los procesos metabólicos intermedios del síndrome de mal de altura y en la adaptación de poblaciones bovinas locales a la altura.…”

Identifying Loci Under Positive Selection in Yellow Korean Cattle (Hanwoo)

“…11,20 To further identify signals displaying strong footprints of selection, scan statistics were used to identify chromosomal selective regions harboring a greater than expected number of signals. 24 A total of nine statistically significant selective regions were 34 Cole et al, 35 Hawken et al, 36 Tenghe et al, 37 Duran Aguilar et al, 38 41 Fortes et al, 42 Buzanskas et al 43 de Oliveira Silva et al, 46 Magalhaes et al, 47 Rempel et al, 48 Ali et al, 49 Saatchi et al, 50 Nayeri et al, 51 Snelling et al, 52 Richardson et al, 53 Sorbolini et al, 54 Mota et al, 55 Mapholi et al, 56 Hawken et al, 36 Fortes et al, 57 Cole et al, 35 Martinez et al, 58 Yurchenko et al, 59 and Michenet et al 40 61 Sorbolini et al, 54 Seabury et al, 45 63 Buzanskas et al, 43 and Pryce et al 64 65 Nalaila et al, 66 Aguilar et al, 38 wang et al, 67 detected ( Table 1 and Table S2), which led to a list of 138 candidate genes. These genes may be an outcome of selection that is closely related to traits of interest, presenting availability of genomic information to be applied on examination of the phenotypic differences between Yellow Hanwoo and Jeju Black.…”