...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Current opinion in lipidology >Cross-species data integration to prioritize causal genes in lipid metabolism
【24h】

Cross-species data integration to prioritize causal genes in lipid metabolism

机译：跨物种数据整合到脂质代谢中的原因优先考虑

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Purpose of review More than one hundred loci have been identified from human genome-wide association studies (GWAS) for blood lipids. Despite the success of GWAS in identifying loci, subsequent prioritization of causal genes related to these loci remains a challenge. To address this challenge, recent work suggests that candidate causal genes within loci can be prioritized through cross-species integration using genome-wide data from the mouse. Recent findings Mouse model systems provide unparalleled access to primary tissues, like the liver, that are not readily available for human studies. Given the key role the liver plays in controlling blood lipid levels and the wealth of liver genome-wide transcript and protein data available in the mouse, these data can be leveraged. Using coexpression network analysis approaches with mouse genome-wide data, coupled with cross-species analysis of human lipid GWAS, causal genes within lipid loci can be prioritized. Prioritization through both mouse and human along with biochemical validation provide a systematic and valuable method to discover lipid metabolism genes. Summary The prioritization of causal lipid genes within GWAS loci is a challenging process requiring a multidisciplinary approach. Integration of data types across species, such as the mouse, can aid in causal gene prioritization.
机译：None

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号