Plant Transcription Regulation Analysis And Database Construction Based On Text Mining And High-Throughput Sequencing Technology

As one of the main forms of life,plants have evolved a complex and efficient gene expression regulation mechanism to regulate growth and development and respond to external environmental stimuli.Literatures published in recent years have shown that the signal cascade will converge at the level of gene regulation when responding to developmental programs or external stimuli.Transcription is the initial step of gene expression and also an important part of gene expression,which has always been a research hotspot in biology.Transcription factors are the main regulators at the transcription level.Therefore,clarifying the regulatory relationship between transcription factors and target genes is a key step in understanding the regulatory circuitry underlying complex traits.and clarifying the regulatory relationship between transcription factors and target genes is a key step in understanding the regulatory mechanisms behind complex features.We use biological text mining and high-throughput sequencing analysis technology to obtain all-round data on plant transcription factor regulation relationships,and build a comprehensive plant transcription regulation relationship database Plan TRN as a reference resource for studying transcription regulation mechanisms(http://bis.zju.edu.cn/plantrn).The current database contains 380,526 transcriptional regulatory relationship data of 1222 transcription factors in 81 plant species.Including:(1)Using biological text mining to obtain 4051 transcriptional regulatory relationships in 80 plant species from literature abstracts,including 58 transcription factor-miRNA regulatory relationships from 4 plant species;(2)According to ChIP-seq Annotated 376475 transcriptional regulatory relationships dominated by 102 transcription factors in 7 plant species,including 5732 transcription factor-miRNA regulatory relationships from 4 plant species.PlanTRN provides detailed transcription regulation information,as well as species browsing,network visualization modules and multi-level data retrieval functions,and supports the download of all data.This study provides an integrated platform through the analysis and mining of existing literature and sequencing data resources,provides an effective reference resource for the study of plant transcription regulation mechanisms,and expands the bioinformatics resources for plant gene expression regulation.