SSS-test: a novel test for detecting positive selection on RNA secondary structure

Abstract

BackgroundLong non-coding RNAs (lncRNAs) play an important role in regulating gene expression and are thus important for determining phenotypes. Most attempts to measure selection in lncRNAs have focused on the primary sequence. The majority of small RNAs and at least some parts of lncRNAs must fold into specific structures to perform their biological function. Comprehensive assessments of selection acting on RNAs therefore must also encompass structure. Selection pressures acting on the structure of non-coding genes can be detected within multiple sequence alignments. Approaches of this type, however, have so far focused on negative selection. Thus, a computational method for identifying ncRNAs under positive selection is needed.ResultsWe introduce the SSS-test (test for Selection on Secondary Structure) to identify positive selection and thus adaptive evolution. Benchmarks with biological as well as synthetic controls yield coherent signals for both negative and positive selection, demonstrating the functionality of the test. A survey of a lncRNA collection comprising 15,443 families resulted in 110 candidates that appear to be under positive selection in human. In 26 lncRNAs that have been associated with psychiatric disorders we identified local structures that have signs of positive selection in the human lineage.ConclusionsIt is feasible to assay positive selection acting on RNA secondary structures on a genome-wide scale. The detection of human-specific positive selection in lncRNAs associated with cognitive disorder provides a set of candidate genes for further experimental testing and may provide insights into the evolution of cognitive abilities in humans.AvailabilityThe SSS-test and related software is available at: https://github.com/waltercostamb/SSS-test. The databases used in this work are available at: http://www.bioinf.uni-leipzig.de/Software/SSS-test/.Electronic supplementary materialThe online version of this article (10.1186/s12859-019-2711-y) contains supplementary material, which is available to authorized users.

Divergent evolution in the genomes of closely related lacertids,Lacerta viridisandL. bilineata, and implications for speciation

“…The predicted ncRNAs (miRNA, snoRNA, tRNA, and lincRNA) in lacertids were tested for structural selection (selection of sites acting on secondary structure in either of the lacertids) with Gekko japonicus as outgroup. We used the Selection on the Secondary Structure (SSS) test [124], a statistical test that assigns selection scores for each given sequence based on the comparison between the structure of the given sequence and the structure of group consensus. It also provides a diversity value for the family that indicates its structural conservation.…”

“…Local conserved structure blocks were predicted for the orthologous lincRNA families, and these blocks were subjected to an adaptation of SSS test based on local structures. The structural selection for lincRNAs was assessed locally, since most base-pairings occur between nucleotides within a short distance [124, 126]. Local blocks of high structural diversity were excluded from further analysis.…”

Selection Pressures on RNA Sequences and Structures

“…We applied the to more than 15 000 human lncRNAs with orthologs in various primates and identified 110 lncRNAs that are candidates for being under positive selection in humans. 3 We observed two types of patterns among these candidates: Some candidates, such as LINC02217, contain local structures with completely different shapes, whereas other candidates, such as SIX3-AS1, maintain their structure but with a clearly increased stability in human compared with their orthologs. We further performed the to investigate which lncRNAs that have been associated with psychiatric disorders might evolve under positive selection.…”

“…Despite the increasing acknowledgment that ncRNAs are functional, a comparable test for noncoding RNA (ncRNA) genes did not exist until recently. 3…”

“…An excess of structural change indicates positive selection, whereas an excess of changes that are structure-conserving supports negative selection. 3 The combines scoring models for structural change for both substitutions and indels. In this model, scores close to zero indicate negative selection and higher scores are indicative of positive selection.…”