生物
拷贝数变化
遗传学
全基因组关联研究
基因组
牛基因组
基因
表型
性状
繁殖
SNP公司
候选基因
计算生物学
进化生物学
基因型
单核苷酸多态性
作者
Sheikh Firdous Ahmad,Akansha Singh,Snehasmita Panda,Waseem Akram Malla,Amit Kumar,Triveni Dutt
出处
期刊:Gene
[Elsevier]
日期:2022-07-01
卷期号:830: 146510-146510
被引量:3
标识
DOI:10.1016/j.gene.2022.146510
摘要
The present study was aimed to analyze the genome-wide copy number variations (CNVs) in Vrindavani composite cattle and concatenate them into CNV regions (CNVRs), and finally test the association of CNVRs with different production and reproduction traits. Genotypic data, generated on BovineSNP50 Beadchip (v3) array for 96 Vrindavani animals, was used to elucidate the CNVs at the genome level. Intensity data covering over 53,218 SNP genotypes on bovine genome was used. Algorithm based on Hidden Markov Model was employed in PennCNV program to detect, normalize and filter CNVs across the genome. 252 putative CNVs, detected via PennCNV program, in different individuals were concatenated into 71 CNV regions (CNVRs) using CNVRuler program. Association of CNVRs with important (re)production traits in Vrindavani animals was assessed using linear regression. Five CNVRs were found to be significantly associated with ten important (re)production traits. The genes harbored in these regions provided useful insights into the association of CNVRs with genes and ultimately the variation at phenotype level. Important genes that overlapped with CNVRs included WASHC4, HS6ST3, MBNL2, TOLLIP, PIDD1 and TSPAN4. Furthermore, the CNVRs were found to overlap with important QTLs available in AnimalQTL database which affect milk yield and composition along with reproduction and immune function traits. The copy number states of three enes were validated using digital droplet PCR technique. The results from the present study significantly enhance the understanding about CNVs in Vrindavani cattle and should help establish its CNV map. The study will also enable further investigation on association of these variants with important traits of economic interest including disease incidence.
科研通智能强力驱动
Strongly Powered by AbleSci AI