Abstract
BackgroundIdentifying the location of transcription factor bindings is crucial to understand transcriptional regulation. Currently, Chromatin Immunoprecipitation followed with high-throughput Sequencing (ChIP-seq) is able to locate the transcription factor binding sites (TFBSs) accurately in high throughput and it has become the gold-standard method for TFBS finding experimentally. However, due to its high cost, it is impractical to apply the method in a very large scale. Considering the large number of transcription factors, numerous cell types and various conditions, computational methods are still very valuable to accurate TFBS identification.ResultsIn this paper, we proposed a novel integrated TFBS prediction system, CTF, based on Conditional Random Fields (CRFs). Integrating information from different sources, CTF was able to capture patterns of TFBSs contained in different features (sequence, chromatin and etc) and predicted the TFBS locations with a high accuracy. We compared CTF with several existing tools as well as the PWM baseline method on a dataset generated by ChIP-seq experiments (TFBSs of 13 transcription factors in mouse genome). Results showed that CTF performed significantly better than existing methods tested.ConclusionsCTF is a powerful tool to predict TFBSs by integrating high throughput data and different features. It can be a useful complement to ChIP-seq and other experimental methods for TFBS identification and thus improve our ability to investigate functional elements in post-genomic era.Availability: CTF is freely available to academic users at: http://cbb.sjtu.edu.cn/~ccwei/pub/software/CTF/CTF.php
Highlights
Functional elements in genomes play important roles in many biology processes
Predicting transcription factor binding sites (TFBSs) by integrating Position weight matrix (PWM), transcription start site (TSS) proximity and chromatin signature CTF was evaluated on 13 TFBS datasets
Those with TFBSs were with higher PWM scores, especially for the binding sites of CTCF, Klf4 and Zfx
Summary
Functional elements in genomes play important roles in many biology processes. Enhancers, silencers, and transcriptional factor binding sites (TFBSs) are required in transcription. Identifying functional elements in genomes is one of most important problems in post-genomic era [1,2,3], which is essential to elucidate gene regulation comprehensively. TFBS is one important type of functional elements. Identifying the location of transcription factor bindings is crucial to understand transcriptional regulation. Chromatin Immunoprecipitation followed with high-throughput Sequencing (ChIP-seq) is able to locate the transcription factor binding sites (TFBSs) accurately in high throughput and it has become the goldstandard method for TFBS finding experimentally. Considering the large number of transcription factors, numerous cell types and various conditions, computational methods are still very valuable to accurate TFBS identification
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