Populational landscape of INDELs affecting transcription factor-binding sites in humans

BMC Genomics

Research Article

Sandro J. de Souza¹  Jorge E.S. de Souza²  André M. Ribeiro-dos-Santos³  Vandeclécio L. da Silva⁴ 

[1] Brain Institute, UFRN, Av. Nascimento de Castro, 2155 - 59056-450, Natal, RN, Brazil;Instituto de Bioinformática e Biotecnologia, Natal, RN, Brazil;Instituto Metrópole Digital, UFRN, Natal, RN, Brazil;PhD Program in Genetics and Molecular Biology, UFPA, Belém, PA, Brazil;PhD Program in Genetics and Molecular Biology, UFPA, Belém, PA, Brazil;Instituto de Bioinformática e Biotecnologia, Natal, RN, Brazil;

关键词: Transcription factor;    Transcription factor-binding site;    INDEL;    Population genetics;   

DOI  :  10.1186/s12864-015-1744-5

 received in 2015-02-21, accepted in 2015-07-02,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundDifferences in gene expression have a significant role in the diversity of phenotypes in humans. Here we integrated human public data from ENCODE, 1000 Genomes and Geuvadis to explore the populational landscape of INDELs affecting transcription factor-binding sites (TFBS). A significant fraction of TFBS close to the transcription start site of known genes is affected by INDELs with a consequent effect at the expression of the associated gene.ResultsHundreds of TFBS-affecting INDELs (TFBS-ID) show a differential frequency between human populations, suggesting a role of natural selection in the spread of such variant INDELs. A comparison with a dataset of known human genomic regions under natural selection allowed us to identify several cases of TFBS-ID likely involved in populational adaptations. Ontology analyses on the differential TFBS-ID further indicated several biological processes under natural selection in different populations.ConclusionTogether, our results strongly suggest that INDELs have an important role in modulating gene expression patterns in humans. The dataset we make available, together with other data reporting variability at both regulatory and coding regions of genes, represent a powerful tool for studies aiming to better understand the evolution of gene regulatory networks in humans.

【 授权许可】

Unknown   
© Ribeiro-dos-Santos et al. 2015. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.