Finding RNA-Protein Interaction Sites Using HMMs

Methods Mol Biol. 2017;1552:177-184. doi: 10.1007/978-1-4939-6753-7_13.

Abstract

RNA-binding proteins play important roles in the various stages of RNA maturation through binding to its target RNAs. Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Several Hidden Markov model-based (HMM) approaches have been suggested to identify protein-RNA binding sites from CLIP-Seq datasets. In this chapter, we describe how HMM can be applied to analyze CLIP-Seq datasets, including the bioinformatics preprocessing steps to extract count information from the sequencing data before HMM and the downstream analysis steps following peak-calling.

Keywords: Hidden Markov models; Interaction sites; RNA-binding proteins.

MeSH terms

  • Algorithms*
  • Binding Sites
  • Computational Biology / methods*
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Immunoprecipitation
  • Markov Chains*
  • RNA / metabolism*
  • RNA-Binding Proteins / metabolism*
  • Sequence Analysis, RNA / methods*

Substances

  • RNA-Binding Proteins
  • RNA