针对东黑猪生长特征的单个和多个位点模型全基因组关联研究
Kailing Sun1, Yuan Hong2, Wenyu Zhang1
1Zhejiang A&F University, Hangzhou, China.
Animal bioscience
|July 16, 2025
概括
这项研究确定了39个重要的定量特征位点 (QTLs),用于猪生长特征,包括体重和平均每日增长. 这些发现为改善养猪计划提供了有价值的遗传标记.
科学领域:
- 动物遗传学动物遗传学
- 量化遗传学 量化遗传学
- 基因组选择 基因组选择
背景情况:
- 体重和平均每日增长等生长特征是生猪生产中的关键经济指标.
- 对于这些特征,只有有限的遗传标记可用,特别是在中国本土猪品种中.
研究的目的:
- 发现单核酸多态性 (SNP) 标记物和候选基因与东黑猪的体重和平均每日增加相关.
- 为了确定提高猪生长性能的新型遗传基因位置.
主要方法:
- 基因组广泛关联研究 (GWAS) 在358只东黑猪身上进行.
- 用中国Chip-1猪SNP50K珠芯片进行基因型鉴定.
- 分析使用了三个单位 (GLM) 和三个多位 (MLMM,FarmCPU,BLINK) 模型.
主要成果:
- 对于生长特征,确定了39个重要的定量特征位点 (QTL).
- 26个QTL与体重相关,13个QTL与平均每日增长相关.
- 确定了包括MACROD2,ASB13和ATP12A在内的候选基因. GLM模型确定了最重要的SNP (27),而FarmCPU和BLINK分别确定了12个和13个QTL.
结论:
- 18个新的QTL被确定为体重和平均每日增长.
- 已识别的遗传标记物和候选基因可以作为猪养殖中标记物辅助选择的基础.
- 这项研究有助于提高猪的体重和平均每日增益特征.
关键词:
平均每天的增益.身体重量 体重 体重在GWAS中,GWAS就是GWAS.多个位置的模型模型.猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪猪定量特征的位置 (locus) 是一个定量特征的位置.更多相关视频
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