植物转录因子分类、预测和数据库构建

doi:10.13560/j.cnki.biotech.bull.1985.2015.11.004

生物技术通报 ›› 2015, Vol. 31 ›› Issue (11): 68-77.doi: 10.13560/j.cnki.biotech.bull.1985.2015.11.004

植物转录因子分类、预测和数据库构建

靳进朴¹, 郭安源^1,2, 何坤^1,3, 张禾^1,4, 朱其慧^1,5, 陈新¹, 高歌¹, 罗静初¹

1. 北京大学生命科学学院北京大学蛋白质与植物基因研究重点实验室北京大学生物信息中心，北京 100871；
2. 华中科技大学生命科学与技术学院，武汉 430074；
3. 孟山都公司，美国；
4.密歇根大学，美国；
5. 杰克森基因组医学实验室，美国

收稿日期:2015-10-31 出版日期:2015-11-26 发布日期:2015-11-26
作者简介:靳进朴，男，博士后，研究方向: 生物信息学；E-mail: jinjp@mail.cbi.pku.edu.cn
基金资助:
国家自然科学基金项目(31071160，31171242，31470330)，博士后科学基金项目(2014M560017，2015T80015)

Classification, Prediction and Database Construction of Plant Transcription Factors

Jin Jinpu¹, Guo Anyuan^1，2, He Kun^1，3, Zhang He^1，4, Zhu Qihui^1，5, Chen Xin¹, Gao Ge¹, Luo Jingchu¹

1. College of Life Sciences，the State Key Laboratory of Protein and Plant Gene Research，Center for Bioinformatics, Peking University，Beijing 100871；2. College of Life Science and Technology，Huazhong University of Science and Technology，Wuhan 430074；3. Monsanto Company，USA；4. University of Michigan，USA；5. The Jackson Laboratory for Genomic Medicine, USA

Received:2015-10-31 Published:2015-11-26 Online:2015-11-26

摘要/Abstract

摘要： 转录因子在植物生长发育和应对胁迫等过程中具有重要调控作用，基因组水平上系统预测植物转录因子是研究其功能和演化的基础。通过深入全面的文献调研，总结了一套完整的植物转录因子家族分类规则，开发了转录因子预测流程，构建了转录因子预测平台。基于该流程，从83种绿色植物中预测到129 288个转录因子，分属58个家族。对预测到的转录因子，从家族和个体两个层次进行了详尽注释，构建了植物转录因子数据库PlantTFDB(http://planttfdb.cbi.pku.edu.cn)。PlantTFDB提供了覆盖绿色植物主要谱系的转录因子，其中大部分为具有重要经济价值的单子叶和双子叶植物，已成为植物转录因子功能和演化研究的重要信息资源和分析平台。

关键词: 转录因子, 转录因子家族分类, 转录因子预测, 植物转录因子数据库

Abstract: Transcription factors(TFs)play key regulatory roles in both plant development and stress response. Genome-wide prediction of TFs is essential for functional and evolutionary studies of plant TFs. We made extensive literature review with thousands papers related to plant TFs and summarized a set of classification rules for plant TFs and developed a TF prediction pipeline. Using this pipeline, we predicted 129 288 TFs, classified into 58 families, from 83 plant species covering the main lineages of green plants including many economically important monocot and dicot crops. We made high-quality annotations for these TFs and built a plant TF database PlantTFDB(http: //planttfdb.cbi.pku.edu.cn). A TF prediction server was also developed for users to predict TFs from their own sequences. PlantTFDB has been served as an important portal for the functional and evolutionary studies of plant TF research community.

Key words: transcription factor, classification of transcription factor, prediction of transcription factor, plant transcription factor database

靳进朴, 郭安源, 何坤, 张禾, 朱其慧, 陈新, 高歌, 罗静初. 植物转录因子分类、预测和数据库构建[J]. 生物技术通报, 2015, 31(11): 68-77.

Jin Jinpu, Guo Anyuan, He Kun, Zhang He, Zhu Qihui, Chen Xin, Gao Ge, Luo Jingchu. Classification, Prediction and Database Construction of Plant Transcription Factors[J]. Biotechnology Bulletin, 2015, 31(11): 68-77.

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植物转录因子分类、预测和数据库构建

Classification, Prediction and Database Construction of Plant Transcription Factors

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