Systematic identification of pleiotropic genes from genetic interactions

Author:

Koch Elizabeth N.,Costanzo Michael,Deshpande Raamesh,Andrews Brenda,Boone Charles,Myers Chad L.

Abstract

SummaryModular structures in biological networks are ubiquitous and well-described, yet this organization does not capture the complexity of genes individually influencing many modules. Pleiotropy, the phenomenon of a single genetic locus with multiple phenotypic effects, has previously been measured according to many definitions, which typically count phenotypes associated with genes. We take the perspective that, because genes work in complex and interconnected modules, pleiotropy can be treated as a network-derived characteristic. Here, we use the complete network of yeast genetic interactions (GI) to measure pleiotropy of nearly 2700 essential and nonessential genes. Our method uses frequent item set mining to discover GI modules, annotates them with high-level processes, and uses entropy to measure the functional spread of each gene’s set of containing modules. We classify genes whose modules indicate broad functional influence as having high pleiotropy, while genes with focused functional influence have low pleiotropy. These pleiotropy classes differed in a number of ways: high-pleiotropy genes have comparatively higher expression variance, higher protein abundance, more domains, and higher copy number, while low pleiotropy genes are more likely to be in protein complexes and have many curated phenotypes. We discuss the implications of these results regarding the nature and evolution of pleiotropy.

Publisher

Cold Spring Harbor Laboratory

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3