在玉米发展图谱中整合欧米网络
Justin W Walley1, Ryan C Sartor2, Zhouxin Shen2
1Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093, USA. Department of Plant Pathology and Microbiology, Iowa State University, Ames, IA 50011, USA.
Science (New York, N.Y.)
|August 20, 2016
概括
由玉米RNA和蛋白质数据构建的基因调控网络 (GRNs) 显示出不同的但互补的见解. 整合多种数据类型显著提高了GRN对基因功能的预测能力.
科学领域:
- 植物分子生物学
- 系统生物学
- 基因组学
背景情况:
- 基因调控网络 (GRNs) 对于理解全系统基因功能至关重要.
- 基于信使RNA (mRNA) 或蛋白质表达的共同表达网络是GRN重建的关键.
研究的目的:
- 使用玉米mRNA,蛋白质和蛋白数据构建和比较GRNs.
- 评估整合不同分子数据类型对GRN预测能力的影响.
主要方法:
- 开发了一个大规模的玉米基因表达图谱 (62,547 mRNA, 17,862 种蛋白, 6,227 种蛋白).
- 根据mRNA和蛋白质数据重建的协同表达网络.
- 综合mRNA,蛋白质和蛋白数据用于增强GRN分析.
主要成果:
- mRNA和蛋白质共同表达网络显示出显著的差异,约85%的高度连接的枢纽没有保存.
- 从mRNA或蛋白质数据获得的网络在类似的功能类别中得到了丰富.
- 网络有效地预测了已知的监管关系.
结论:
- 玉米RNA和蛋白质共同表达网络为GRN构建提供了不同的但相辅相成的信息.
- 整合多组数据 (mRNA,蛋白质,蛋白质) 显著提高了GRN的预测能力和功能洞察力.
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