Ultra-fast and accurate motif finding in large ChIP-seq datasets reveals transcription factor binding patterns

Author:

Li Yang,Ni Pengyu,Zhang Shaoqiang,Li Guojun,Su Zhengchang

Abstract

ABSTRACTThe availability of a large volume of chromatin immunoprecipitation followed by sequencing (ChIP-seq) datasets for various transcription factors (TF) has provided an unprecedented opportunity to identify all functional TF binding motifs clustered in the enhancers in genomes. However, the progress has been largely hindered by the lack of a highly efficient and accurate tool that is fast enough to find not only the target motifs, but also cooperative motifs contained in very large ChIP-seq datasets with a binding peak length of typical enhancers (∼ 1,000 bp). To circumvent this hurdle, we herein present an ultra-fast and highly accurate motif-finding algorithm, ProSampler, with automatic motif length detection. ProSampler first identifies significant k-mers in the dataset and combines highly similar significant k-mers to form preliminary motifs. ProSampler then merges preliminary motifs with subtle similarity using a novel graph-based Gibbs sampler to find core motifs. Finally, ProSampler extends the core motifs by applying a two-proportion z-test to the flanking positions to identify motifs longer than k. As the number of preliminary motifs is much smaller than that of k-mers in a dataset, we greatly reduce the search space of the Gibbs sampler compared with conventional ones. By storing flanking sequences in a hash table, we avoid extensive IO and the necessity of examining all lengths of motifs in an interval. When evaluated on both synthetic and real ChIP-seq datasets, ProSampler runs orders of magnitude faster than the fastest existing tools while more accurately discovering primary motifs as well as cooperative motifs than do the best existing tools. Using ProSampler, we revealed previously unknown complex motif occurrence patterns in large ChIP-seq datasets, thereby providing insights into the mechanisms of cooperative TF binding for gene transcriptional regulation. Therefore, by allowing fast and accurate mining of the entire ChIP-seq datasets, ProSampler can greatly facilitate the efforts to identify the entire cis-regulatory code in genomes.

Publisher

Cold Spring Harbor Laboratory

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