Dataset Information

Genome-Wide Computational Identification of Biologically Significant Cis-Regulatory Elements and Associated Transcription Factors from Rice.

ABSTRACT: The interactions between transcription factors (TFs) and cis-acting regulatory elements (CREs) provide crucial information on the regulation of gene expression. The determination of TF-binding sites and CREs experimentally is costly and time intensive. An in silico identification and annotation of TFs, and the prediction of CREs from rice are made possible by the availability of whole genome sequence and transcriptome data. In this study, we tested the applicability of two algorithms developed for other model systems for the identification of biologically significant CREs of co-expressed genes from rice. CREs were identified from the DNA sequences located upstream from the transcription start sites, untranslated regions (UTRs), and introns, and downstream from the translational stop codons of co-expressed genes. The biologically significance of each CRE was determined by correlating their absence and presence in each gene with that gene's expression profile using a meta-database constructed from 50 rice microarray data sets. The reliability of these methods in the predictions of CREs and their corresponding TFs was supported by previous wet lab experimental data and a literature review. New CREs corresponding to abiotic stresses, biotic stresses, specific tissues, and developmental stages were identified from rice, revealing new pieces of information for future experimental testing. The effectiveness of some-but not all-CREs was found to be affected by copy number, position, and orientation. The corresponding TFs that were most likely correlated with each CRE were also identified. These findings not only contribute to the prioritization of candidates for further analysis, the information also contributes to the understanding of the gene regulatory network.

SUBMITTER: Ho CL

PROVIDER: S-EPMC6918188 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Genome-Wide Computational Identification of Biologically Significant Cis-Regulatory Elements and Associated Transcription Factors from Rice.

Ho Chai-Ling CL Geisler Matt M

Plants (Basel, Switzerland) 20191023 11

The interactions between transcription factors (TFs) and cis-acting regulatory elements (CREs) provide crucial information on the regulation of gene expression. The determination of TF-binding sites and CREs experimentally is costly and time intensive. An in silico identification and annotation of TFs, and the prediction of CREs from rice are made possible by the availability of whole genome sequence and transcriptome data. In this study, we tested the applicability of two algorithms developed f ...[more]

PMID: 31652796

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Project description:BackgroundThe male germ line in flowering plants is initiated within developing pollen grains via asymmetric division. The smaller cell then becomes totally encased within a much larger vegetative cell, forming a unique "cell within a cell structure". The generative cell subsequently divides to give rise to two non-motile diminutive sperm cells, which take part in double fertilization and lead to the seed set. Sperm cells are difficult to investigate because of their presence within the confines of the larger vegetative cell. However, recently developed techniques for the isolation of rice sperm cells and the fully annotated rice genome sequence have allowed for the characterization of the transcriptional repertoire of sperm cells. Microarray gene expression data has identified a subset of rice genes that show unique or highly preferential expression in sperm cells. This information has led to the identification of cis-regulatory elements (CREs), which are conserved in sperm-expressed genes and are putatively associated with the control of cell-specific expression.FindingsWe aimed to identify the CREs associated with rice sperm cell-specific gene expression data using in silico prediction tools. We analyzed 1-kb upstream regions of the top 40 sperm cell co-expressed genes for over-represented conserved and novel motifs. Analysis of upstream regions with the SIGNALSCAN program with the PLACE database, MEME and the Mclip tool helped to find combinatorial sets of known transcriptional factor-binding sites along with two novel motifs putatively associated with the co-expression of sperm cell-specific genes.ConclusionsOur data shows the occurrence of novel motifs, which are putative CREs and are likely targets of transcriptional factors regulating sperm cell gene expression. These motifs can be used to design the experimental verification of regulatory elements and the identification of transcriptional factors that regulate sperm cell-specific gene expression.

Dataset Information

Genome-Wide Computational Identification of Biologically Significant Cis-Regulatory Elements and Associated Transcription Factors from Rice.

Publications

Genome-Wide Computational Identification of Biologically Significant Cis-Regulatory Elements and Associated Transcription Factors from Rice.

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