在远处的物种中对转录组进行比较分析
Mark B Gerstein1, Joel Rozowsky2, Koon-Kiu Yan2
11] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [3] Department of Computer Science, Yale University, 51 Prospect Street, New Haven, Connecticut 06511, USA [4] [5].
在不同物种中比较转录组揭示了基本的生物学原理. 这项研究确定了共享的基因表达模式和一种通用模型,用于从人类,虫和的染色质数据中预测基因活性.
科学领域:
- 进行比较的基因组学.
- 文字转录学 (Transcriptomics) 是一个学科.
- 发育生物学是发展生物学.
背景情况:
- 转录组提供了基因组活动的快照.
- 跨物种的转录组比较可以揭示基本的生物学原理.
- 以前的比较仅限于物种或科目内.
研究的目的:
- 通过远距离的动物物种 (人类,虫,) 在转录组中识别保存的特征.
- 开发一种通用模型,从染色体数据中预测基因表达.
- 为了比较跨物种的非编码转录水平.
主要方法:
- 通过ENCODE和modENCODE联盟生成RNA测序数据和统一处理.
- 在人类,虫和中对转录组进行比较分析.
- 使用染色体特征的预测模型的开发和应用.
主要成果:
- 发现共享的共同表达模块,其中许多富含发育基因,跨越metazoan类.
- 识别了虫和胚胎之间的新型发育阶段对齐.
- 量化不同物种中每个基因对的相似非正规转录水平.
- 证明基因表达水平可以从促进性染色体特征预测,使用生物体独立模型.
结论:
- 跨不同物种的转录组比较揭示了古老的,保存的特征.
- 动物的发育过程显示了动物之间保留的调节原则.
- 一个通用模型可以从各种物种的染色质数据中预测基因表达,突出显示保存的调节机制.
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