title: Emerging applications of read profiles towards the functional annotation of the genome.
abstract: Functional annotation of the genome is important to understand the phenotypic complexity of various species. The road toward functional annotation involves several challenges ranging from experiments on individual molecules to large-scale analysis of high-throughput sequencing (HTS) data. HTS data is typically a result of the protocol designed to address specific research questions. The sequencing results in reads, which when mapped to a reference genome often leads to the formation of distinct patterns (read profiles). Interpretation of these read profiles is essential for their analysis in relation to the research question addressed. Several strategies have been employed at varying levels of abstraction ranging from a somewhat ad hoc to a more systematic analysis of read profiles. These include methods which can compare read profiles, e.g., from direct (non-sequence based) alignments to classification of patterns into functional groups. In this review, we highlight the emerging applications of read profiles for the annotation of non-coding RNA and cis-regulatory elements (CREs) such as enhancers and promoters. We also discuss the biological rationale behind their formation.
authors.affiliation: Center for non-coding RNA in Technology and Health, Department of Veterinary Clinical and Animal Sciences (IKVH), University of Copenhagen Frederiksberg C, Denmark.
authors.forename: Sachin
authors.initials: S
authors.lastname: Pundhir
authors.affiliation: Computational Biology Lab, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas Heraklion, Greece.
authors.forename: Panayiota
authors.initials: P
authors.lastname: Poirazi
authors.affiliation: Center for non-coding RNA in Technology and Health, Department of Veterinary Clinical and Animal Sciences (IKVH), University of Copenhagen Frederiksberg C, Denmark.
authors.forename: Jan
authors.initials: J
authors.lastname: Gorodkin
keywords: ChIP-seq; RNA-seq; enhancer; non-coding RNA; patterns; read profile