Single‐step genome‐wide association study reveals candidate genes for body mass index trait in Yunong‐black pigs

生物 候选基因 全基因组关联研究 特质 遗传学 数量性状位点 基因 遗传关联 基因组 体质指数 计算生物学 单核苷酸多态性 基因型 内分泌学 计算机科学 程序设计语言
作者
Ziyi Wu,Tengfei Dou,Jiahao Wu,Liyao Bai,Zhang Yong-qian,Shengyuan Zan,Songbai Yang,Hao Zhou,Jinyi Han,Xuelei Han,Ruimin Qiao,Kejun Wang,Feng Yang,Xinjian Li,Xiuling Li
出处
期刊:Animal Genetics [Wiley]
卷期号:56 (1)
标识
DOI:10.1111/age.13501
摘要

Body mass index (BMI) can serve as a reasonable indicator of overall body fat content in pigs. This study aimed to identify underlying variants and candidate genes associated with BMI in Yunong-black pigs. A single-step genome-wide association analysis (GWAS) was performed on 1405 BMI records and 924 Yunong-black pigs genotyped using a 50 K SNP Chip. De-regressed estimated breeding values were taken as the response variable in the GWAS. The estimated heritability for BMI was 0.157. Nine significant regions were associated with BMI, accounting for 12.828% of genetic variance, with the highest region explaining 1.969% of the genetic variance. Linkage disequilibrium analysis of the nine significant regions revealed that SNPs in six single-step GWAS-identified genomic regions were all located in the linkage disequilibrium blocks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of the 29 protein-coding genes annotated to these regions revealed that FABP2, a key gene associated with BMI in human, was enriched in the fatty acid binding term and the fat digestion and absorption pathway. This study provides a better insight into the genetic architecture of the BMI trait, and offers potential molecular markers for the breeding of Yunong-black pigs.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Lucas应助ww采纳,获得10
刚刚
1秒前
ttttttuu完成签到,获得积分10
1秒前
2秒前
刘涵完成签到 ,获得积分10
2秒前
小马甲应助zhui采纳,获得10
2秒前
10完成签到,获得积分10
2秒前
2秒前
2秒前
Rainielove0215完成签到,获得积分0
3秒前
zz完成签到,获得积分10
4秒前
4秒前
kyle完成签到,获得积分10
6秒前
感性的凉面完成签到,获得积分20
6秒前
6秒前
请叫我风吹麦浪应助末岛采纳,获得10
7秒前
Aprial发布了新的文献求助30
7秒前
dd发布了新的文献求助10
7秒前
传奇3应助科研小菜鸟采纳,获得10
7秒前
在水一方应助惠惠采纳,获得10
8秒前
9秒前
冷艳贵公子王少完成签到 ,获得积分10
9秒前
KatzeBaliey完成签到,获得积分10
9秒前
9秒前
9秒前
10秒前
zz发布了新的文献求助10
10秒前
10秒前
Twikky发布了新的文献求助10
11秒前
11秒前
小马甲应助芒果采纳,获得10
12秒前
12秒前
心想事成完成签到,获得积分10
14秒前
隐形曼青应助噔噔噔噔采纳,获得10
14秒前
wei发布了新的文献求助10
14秒前
Nature完成签到,获得积分10
14秒前
樱桃苏打水完成签到,获得积分10
15秒前
zhui发布了新的文献求助10
15秒前
金色热浪发布了新的文献求助10
15秒前
pinging应助讲你ing采纳,获得10
17秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527884
求助须知:如何正确求助?哪些是违规求助? 3108006
关于积分的说明 9287444
捐赠科研通 2805757
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716904
科研通“疑难数据库(出版商)”最低求助积分说明 709794