A new exhaustive method and strategy for finding motifs in ChIP-enriched regions

• Published in: PloS one Vol. 9; no. 1; p. e86044
• Main Authors: Jia, Caiyan, Carson, Matthew B, Wang, Yang, Lin, Youfang, Lu, Hui
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 24.01.2014; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Animals; Binding Sites; Bioengineering; Bioinformatics; Biology; Chromatin; Chromatin Immunoprecipitation; Computational Biology - methods; Computer Science; Data analysis; Data processing; Datasets; Deoxyribonucleic acid; DNA; DNA sequencing; DNA-Binding Proteins - metabolism; Embryonic Stem Cells; Enrichment; Epigenetics; Gene expression; Gene sequencing; Genomes; Genomics; Health care; High-Throughput Nucleotide Sequencing; Immunoprecipitation; Information technology; Mathematics; Medicine; Methods; Mice; Nucleotide Motifs; Nucleotide sequence; Position-Specific Scoring Matrices; Protein binding; Search algorithms; Sensitivity and Specificity; Stem cells; Transcription factors; Transcription Factors - metabolism; Beijing China; Chicago Illinois; United States > US; Illinois; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0086044

ChIP-seq, which combines chromatin immunoprecipitation (ChIP) with next-generation parallel sequencing, allows for the genome-wide identification of protein-DNA interactions. This technology poses new challenges for the development of novel motif-finding algorithms and methods for determining exact protein-DNA binding sites from ChIP-enriched sequencing data. State-of-the-art heuristic, exhaustive search algorithms have limited application for the identification of short (l, d) motifs (l ≤ 10, d ≤ 2) contained in ChIP-enriched regions. In this work we have developed a more powerful exhaustive method (FMotif) for finding long (l, d) motifs in DNA sequences. In conjunction with our method, we have adopted a simple ChIP-enriched sampling strategy for finding these motifs in large-scale ChIP-enriched regions. Empirical studies on synthetic samples and applications using several ChIP data sets including 16 TF (transcription factor) ChIP-seq data sets and five TF ChIP-exo data sets have demonstrated that our proposed method is capable of finding these motifs with high efficiency and accuracy. The source code for FMotif is available at http://211.71.76.45/FMotif/.