Binding Sites Analyser (BiSA): Software for Genomic Binding Sites Archiving and Overlap Analysis

Abstract

Genome-wide mapping of transcription factor binding and histone modification reveals complex patterns of interactions. Identifying overlaps in binding patterns by different factors is a major objective of genomic studies, but existing methods to archive large numbers of datasets in a personalised database lack sophistication and utility. Therefore we have developed transcription factor DNA binding site analyser software (BiSA), for archiving of binding regions and easy identification of overlap with or proximity to other regions of interest. Analysis results can be restricted by chromosome or base pair overlap between regions or maximum distance between binding peaks. BiSA is capable of reporting overlapping regions that share common base pairs; regions that are nearby; regions that are not overlapping; and average region sizes. BiSA can identify genes located near binding regions of interest, genomic features near a gene or locus of interest and statistical significance of overlapping regions can also be reported. Overlapping results can be visualized as Venn diagrams. A major strength of BiSA is that it is supported by a comprehensive database of publicly available transcription factor binding sites and histone modifications, which can be directly compared to user data. The documentation and source code are available on http://bisa.sourceforge.net

Bioinformatic analysis of cis-regulatory interactions between progesterone and estrogen receptors in breast cancer

“…It is designed to identify factors that target the same genomic locations. As described in examples in our previous study ( Khushi et al, 2014 ) the OCV should be greater than 0.5 for partner factors, reflecting a statistically significant correlation between two binding patterns. For example the OCV for known partners, FOXA3 (query) to FOXA1 (reference) was 0.72 ( Motallebipour et al, 2009 ).…”

“…In summary, we have evidence for a biologically relevant interplay between PR and ER α in a subset of binding sites in breast cancer cells. Our analysis demonstrated the utility of our previously published software BiSA ( Khushi et al, 2014 ), which has a comprehensive knowledge base, consisting of transcription factor binding sites and histone modifications collected from previously published studies. Using BiSA we identified that ER α and PR co-locate on a subset of binding sites.…”

“…The BiSA database provides a good starting point for studying overlapping binding by a range of transcription factors from a comprehensive collection of published studies ( Khushi et al, 2014 ). The datasets available in BiSA represent the original genomic locations identified in the published studies from which they are sourced.…”

“…Overlapping features were studied in BiSA ( Khushi et al, 2014 ). BiSA is a bioinformatics database resource that can be run on Windows as a personal resource or web-based under Galaxy ( Goecks et al, 2010 ) as a collaborative tool.…”

“…Therefore in this report we investigated the interaction of these nuclear receptors on DNA. Our previously published BiSA database ( Khushi et al, 2014 ) contains a number of datasets describing ER α and PR binding sites for various cell lines, therefore, we investigated the binding pattern of these factors in the T-47D breast cancer cell line. T-47D cells are derived from metastatic female human breast cancer and are known to be ER α and PR positive and their growth is simulated by the treatment of estrogen ( Chalbos et al, 1982 ; Ström et al, 2004 ).…”