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Analysis of variation at transcription factor binding sites in Drosophila and humans

BACKGROUND: Advances in sequencing technology have boosted population genomics and made it possible to map the positions of transcription factor binding sites (TFBSs) with high precision. Here we investigate TFBS variability by combining transcription factor binding maps generated by ENCODE, modENCO...

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Detalles Bibliográficos
Autores principales: Spivakov, Mikhail, Akhtar, Junaid, Kheradpour, Pouya, Beal, Kathryn, Girardot, Charles, Koscielny, Gautier, Herrero, Javier, Kellis, Manolis, Furlong, Eileen EM, Birney, Ewan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3491393/
https://www.ncbi.nlm.nih.gov/pubmed/22950968
http://dx.doi.org/10.1186/gb-2012-13-9-r49
Descripción
Sumario:BACKGROUND: Advances in sequencing technology have boosted population genomics and made it possible to map the positions of transcription factor binding sites (TFBSs) with high precision. Here we investigate TFBS variability by combining transcription factor binding maps generated by ENCODE, modENCODE, our previously published data and other sources with genomic variation data for human individuals and Drosophila isogenic lines. RESULTS: We introduce a metric of TFBS variability that takes into account changes in motif match associated with mutation and makes it possible to investigate TFBS functional constraints instance-by-instance as well as in sets that share common biological properties. We also take advantage of the emerging per-individual transcription factor binding data to show evidence that TFBS mutations, particularly at evolutionarily conserved sites, can be efficiently buffered to ensure coherent levels of transcription factor binding. CONCLUSIONS: Our analyses provide insights into the relationship between individual and interspecies variation and show evidence for the functional buffering of TFBS mutations in both humans and flies. In a broad perspective, these results demonstrate the potential of combining functional genomics and population genetics approaches for understanding gene regulation.