Abstract
At the molecular level, response to an external factor or an internal condition causes reprogramming of temporal and spatial transcription. When an organism undergoes physiological and/or morphological changes, several signaling pathways are activated simultaneously. Examples of such complex reactions are the response to temperature changes, dehydration, various biologically active substances, and others. A significant part of the regulatory ensemble in such complex reactions remains unidentified. We developed metaRE, an R package for the systematic search for cis-regulatory elements enriched in the promoters of the genes significantly changed their transcription in a complex reaction. metaRE mines multiple expression profiling datasets generated to test the same organism’s response and identifies simple and composite cis-regulatory elements systematically associated with differential expression of genes. Here, we showed metaRE performance for the identification of low-temperature-responsive cis-regulatory code in Arabidopsis thaliana and Danio rerio. MetaRE identified potential binding sites for known as well as unknown cold response regulators. A notable part of cis-elements was found in both searches discovering great conservation in low-temperature responses between plants and animals.
Highlights
More than two decades have passed since the establishment of whole-genome expression profiling methods
Arabidopsis and zebrafish transcriptome datasets on low positive temperature treatment were retrieved from the GEO database. 22 out of 40 datasets for Arabidopsis thaliana and 16 out of 24 datasets for Danio rerio passed the quality control for well-clustered replicas giving a sufficient number of differentially expressed genes (DEGs)
We developed a metaRE R package which identifies the cistrome associated with the case of study via a meta-analysis of multiple transcriptomic experiments
Summary
More than two decades have passed since the establishment of whole-genome expression profiling methods. The way to detect the robust gene sets might be comprehensive He and coauthors (2016) analyzed DEGs in nine transcriptomic datasets on breast cancer: DEGs were identified by Fisher’s method for p-values combination [6]. A better way to identify a full set of cis-elements, or a “cistrome”, associated with a transcriptional response, is a meta-analysis of individual transcriptomes and not the robust DEGs. Authors of the cis-Metalysis program performed a meta-analysis of transcriptomics data on bee [7]. The methods for comprehensive meta-analysis of transcription profiles for cis-elements prediction described above have proven to be powerful in specific studies They were not implemented in a ready-to-use package. We show the performance of metaRE on cold-stress-responsive and hypothermia-responsive transcriptome datasets in Arabidopsis and zebrafish
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