Detecting and Comparing Non-Coding RNAs in the High-Throughput Era

Abstract

In recent years there has been a growing interest in the field of non-coding RNA. This surge is a direct consequence of the discovery of a huge number of new non-coding genes and of the finding that many of these transcripts are involved in key cellular functions. In this context, accurately detecting and comparing RNA sequences has become important. Aligning nucleotide sequences is a key requisite when searching for homologous genes. Accurate alignments reveal evolutionary relationships, conserved regions and more generally any biologically relevant pattern. Comparing RNA molecules is, however, a challenging task. The nucleotide alphabet is simpler and therefore less informative than that of amino-acids. Moreover for many non-coding RNAs, evolution is likely to be mostly constrained at the structural level and not at the sequence level. This results in very poor sequence conservation impeding comparison of these molecules. These difficulties define a context where new methods are urgently needed in order to exploit experimental results to their full potential. This review focuses on the comparative genomics of non-coding RNAs in the context of new sequencing technologies and especially dealing with two extremely important and timely research aspects: the development of new methods to align RNAs and the analysis of high-throughput data.

Chromosomal polymorphism in mammals: an evolutionary perspective

“…New and rapidly improving computer technologies provide access to genome‐wide resources within a reasonable amount of time, and at a reasonable expense [e.g. 3D DNA FISH (Bolland et al ., ); full, high‐quality genome sequence assemblages (Burton et al ., ); detection and comparison of non‐coding RNA (Bussotti, Notredame & Enright, ); 3D organization of the nucleus (Dekker, Marti‐Renom & Mirny, ); nucleus spatial organization and interacting genes (Merelli, Lio & Milanesi, )]. Importantly, the recent emergence of new generation sequencing (NGS; Bild et al ., ; Sims et al ., ) approaches open genomic investigations to a range of non‐model organisms, specifically those in which CRs exist in different states but on the same genomic background.…”

Improved definition of the mouse transcriptome via targeted RNA sequencing

“…This has also fostered the rapid accumulation of annotated long noncoding RNAs (lncRNAs) (Bussotti et al 2013) and further recognition that the vast majority of genes express alternative isoforms (Katz et al 2015). Current estimates of human lncRNA loci range from 58,648 from a large compendium of RNA-seq data sets (Iyer et al 2015) to 15,900 lncRNA loci (27,670 transcripts) in the more conservative GENCODE catalog (Harrow et al 2012).…”

Rapid evolutionary turnover underlies conserved lncRNA–genome interactions

“…Examples of such evolutionary analyses are scarce yet valuable, such as evidence for the independent evolutionary origins of the mammalian dosage compensation lncRNAs Xist and Rsx, with Xist having arisen from a pseudogenized protein-coding gene (Duret et al 2006;Grant et al 2012). Besides their primary sequence, other lncRNA features are often conserved, including syntenic relationships to other genes (i.e., neighboring genes), short sequence homology (referred to here as "microhomology"), and secondary structure (Chodroff et al 2010;Ulitsky et al 2011;Bussotti et al 2013;Hezroni et al 2015). Despite many predictions from RNA sequencing (RNA-seq) data (Necsulea et al 2014;Hezroni et al 2015), few lncRNA orthologs that function across species have been experimentally verified.…”