Cargando…

Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs

BACKGROUND: Transcription factors (TFs) have long been known to be principally activators of transcription in eukaryotes and prokaryotes. The growing awareness of the ubiquity of microRNAs (miRNAs) as suppressive regulators in eukaryotes, suggests the possibility of a mutual, preferential, self-regu...

Descripción completa

Detalles Bibliográficos
Autores principales: Croft, Larry, Szklarczyk, Damian, Jensen, Lars Juhl, Gorodkin, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3430561/
https://www.ncbi.nlm.nih.gov/pubmed/22824421
http://dx.doi.org/10.1186/1752-0509-6-90
_version_ 1782241950967005184
author Croft, Larry
Szklarczyk, Damian
Jensen, Lars Juhl
Gorodkin, Jan
author_facet Croft, Larry
Szklarczyk, Damian
Jensen, Lars Juhl
Gorodkin, Jan
author_sort Croft, Larry
collection PubMed
description BACKGROUND: Transcription factors (TFs) have long been known to be principally activators of transcription in eukaryotes and prokaryotes. The growing awareness of the ubiquity of microRNAs (miRNAs) as suppressive regulators in eukaryotes, suggests the possibility of a mutual, preferential, self-regulatory connectivity between miRNAs and TFs. Here we investigate the connectivity from TFs and miRNAs to other genes and each other using text mining, TF promoter binding site and 6 different miRNA binding site prediction methods. RESULTS: In the first approach text mining of PubMed abstracts reveal statistically significant associations between miRNAs and both TFs and signal transduction gene classes. Secondly, prediction of miRNA targets in human and mouse 3’UTRs show enrichment only for TFs but not consistently across prediction methods for signal transduction or other gene classes. Furthermore, a random sample of 986 TarBase entries was scored for experimental evidence by manual inspection of the original papers, and enrichment for TFs was observed to increase with score. Low-scoring TarBase entries, where experimental evidence is anticorrelated miRNA:mRNA expression with predicted miRNA targets, appear not to select for real miRNA targets to any degree. Our manually validated text-mining results also suggests that miRNAs may be activated by more TFs than other classes of genes, as 7% of miRNA:TF co-occurrences in the literature were TFs activating miRNAs. This was confirmed when thirdly, we found enrichment for predicted, conserved TF binding sites in miRNA and TF genes compared to other gene classes. CONCLUSIONS: We see enrichment of connections between miRNAs and TFs using several independent methods, suggestive of a network of mutual activating and suppressive regulation. We have also built regulatory networks (containing 2- and 3-loop motifs) for mouse and human using predicted miRNA and TF binding sites and we have developed a web server to search and display these loops, available for the community at http://rth.dk/resources/tfmirloop.
format Online
Article
Text
id pubmed-3430561
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-34305612012-08-30 Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs Croft, Larry Szklarczyk, Damian Jensen, Lars Juhl Gorodkin, Jan BMC Syst Biol Research Article BACKGROUND: Transcription factors (TFs) have long been known to be principally activators of transcription in eukaryotes and prokaryotes. The growing awareness of the ubiquity of microRNAs (miRNAs) as suppressive regulators in eukaryotes, suggests the possibility of a mutual, preferential, self-regulatory connectivity between miRNAs and TFs. Here we investigate the connectivity from TFs and miRNAs to other genes and each other using text mining, TF promoter binding site and 6 different miRNA binding site prediction methods. RESULTS: In the first approach text mining of PubMed abstracts reveal statistically significant associations between miRNAs and both TFs and signal transduction gene classes. Secondly, prediction of miRNA targets in human and mouse 3’UTRs show enrichment only for TFs but not consistently across prediction methods for signal transduction or other gene classes. Furthermore, a random sample of 986 TarBase entries was scored for experimental evidence by manual inspection of the original papers, and enrichment for TFs was observed to increase with score. Low-scoring TarBase entries, where experimental evidence is anticorrelated miRNA:mRNA expression with predicted miRNA targets, appear not to select for real miRNA targets to any degree. Our manually validated text-mining results also suggests that miRNAs may be activated by more TFs than other classes of genes, as 7% of miRNA:TF co-occurrences in the literature were TFs activating miRNAs. This was confirmed when thirdly, we found enrichment for predicted, conserved TF binding sites in miRNA and TF genes compared to other gene classes. CONCLUSIONS: We see enrichment of connections between miRNAs and TFs using several independent methods, suggestive of a network of mutual activating and suppressive regulation. We have also built regulatory networks (containing 2- and 3-loop motifs) for mouse and human using predicted miRNA and TF binding sites and we have developed a web server to search and display these loops, available for the community at http://rth.dk/resources/tfmirloop. BioMed Central 2012-07-23 /pmc/articles/PMC3430561/ /pubmed/22824421 http://dx.doi.org/10.1186/1752-0509-6-90 Text en Copyright ©2012 Croft et al.; http://creativecommons.org/licenses/by/2.0 licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Croft, Larry
Szklarczyk, Damian
Jensen, Lars Juhl
Gorodkin, Jan
Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs
title Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs
title_full Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs
title_fullStr Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs
title_full_unstemmed Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs
title_short Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs
title_sort multiple independent analyses reveal only transcription factors as an enriched functional class associated with micrornas
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3430561/
https://www.ncbi.nlm.nih.gov/pubmed/22824421
http://dx.doi.org/10.1186/1752-0509-6-90
work_keys_str_mv AT croftlarry multipleindependentanalysesrevealonlytranscriptionfactorsasanenrichedfunctionalclassassociatedwithmicrornas
AT szklarczykdamian multipleindependentanalysesrevealonlytranscriptionfactorsasanenrichedfunctionalclassassociatedwithmicrornas
AT jensenlarsjuhl multipleindependentanalysesrevealonlytranscriptionfactorsasanenrichedfunctionalclassassociatedwithmicrornas
AT gorodkinjan multipleindependentanalysesrevealonlytranscriptionfactorsasanenrichedfunctionalclassassociatedwithmicrornas