Evolutionary Conservation of RNA Secondary Structure

Overview

Journal Methods Mol Biol

Specialty Molecular Biology

Date 2023 Jan 27

PMID 36705902

Authors

Maria Beatriz Walter Costa

Affiliations

Soon will be listed here.

Abstract

Noncoding RNAs, ncRNAs, naturally fold into structures, which allow them to perform their functions in the cell. Evolutionarily close species share structures and functions. This occurs because of shared selective pressures, resulting in conserved groups. Previous efforts in finding functional RNAs have been made in detecting conserved structures in genomes or alignments. It may occur that, within a conserved group, species-specific structures arise after species split due to positive selection. Detecting positive selection in ncRNAs is a hard problem in biology as well as bioinformatics. To detect positive selection, one should find species-specific structures within a conserved set. This chapter provides protocols to detect and analyze positive selection in ncRNA structures with the SSS-test and other free software.

References

Smith M, Gesell T, Stadler P, Mattick J . Widespread purifying selection on RNA structure in mammals. Nucleic Acids Res. 2013; 41(17):8220-36. PMC: 3783177. DOI: 10.1093/nar/gkt596. View

Pedersen J, Bejerano G, Siepel A, Rosenbloom K, Lindblad-Toh K, Lander E . Identification and classification of conserved RNA secondary structures in the human genome. PLoS Comput Biol. 2006; 2(4):e33. PMC: 1440920. DOI: 10.1371/journal.pcbi.0020033. View

Yao Z, Weinberg Z, Ruzzo W . CMfinder--a covariance model based RNA motif finding algorithm. Bioinformatics. 2005; 22(4):445-52. DOI: 10.1093/bioinformatics/btk008. View

Washietl S, Hofacker I, Lukasser M, Huttenhofer A, Stadler P . Mapping of conserved RNA secondary structures predicts thousands of functional noncoding RNAs in the human genome. Nat Biotechnol. 2005; 23(11):1383-90. DOI: 10.1038/nbt1144. View

Walter Costa M, Honer Zu Siederdissen C, Dunjic M, Stadler P, Nowick K . SSS-test: a novel test for detecting positive selection on RNA secondary structure. BMC Bioinformatics. 2019; 20(1):151. PMC: 6429701. DOI: 10.1186/s12859-019-2711-y. View

Lorenz R, Bernhart S, Honer Zu Siederdissen C, Tafer H, Flamm C, Stadler P . ViennaRNA Package 2.0. Algorithms Mol Biol. 2011; 6:26. PMC: 3319429. DOI: 10.1186/1748-7188-6-26. View

Mathews D, Turner D . Prediction of RNA secondary structure by free energy minimization. Curr Opin Struct Biol. 2006; 16(3):270-8. DOI: 10.1016/j.sbi.2006.05.010. View

Rivas E, Lang R, Eddy S . A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more. RNA. 2011; 18(2):193-212. PMC: 3264907. DOI: 10.1261/rna.030049.111. View

McCaskill J . The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers. 1990; 29(6-7):1105-19. DOI: 10.1002/bip.360290621. View

10.

Tinoco Jr I, Borer P, Dengler B, Levin M, Uhlenbeck O, Crothers D . Improved estimation of secondary structure in ribonucleic acids. Nat New Biol. 1973; 246(150):40-1. DOI: 10.1038/newbio246040a0. View

11.

Mathews D, Disney M, Childs J, Schroeder S, Zuker M, Turner D . Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure. Proc Natl Acad Sci U S A. 2004; 101(19):7287-92. PMC: 409911. DOI: 10.1073/pnas.0401799101. View

12.

Turner D, Mathews D . NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure. Nucleic Acids Res. 2009; 38(Database issue):D280-2. PMC: 2808915. DOI: 10.1093/nar/gkp892. View

13.

Lange S, Maticzka D, Mohl M, Gagnon J, Brown C, Backofen R . Global or local? Predicting secondary structure and accessibility in mRNAs. Nucleic Acids Res. 2012; 40(12):5215-26. PMC: 3384308. DOI: 10.1093/nar/gks181. View

14.

Perdomo-Sabogal A, Kanton S, Walter M, Nowick K . The role of gene regulatory factors in the evolutionary history of humans. Curr Opin Genet Dev. 2014; 29:60-7. DOI: 10.1016/j.gde.2014.08.007. View

15.

Bernhart S, Hofacker I, Will S, Gruber A, Stadler P . RNAalifold: improved consensus structure prediction for RNA alignments. BMC Bioinformatics. 2008; 9:474. PMC: 2621365. DOI: 10.1186/1471-2105-9-474. View

16.

Sabarinathan R, Tafer H, Seemann S, Hofacker I, Stadler P, Gorodkin J . RNAsnp: efficient detection of local RNA secondary structure changes induced by SNPs. Hum Mutat. 2013; 34(4):546-56. PMC: 3708107. DOI: 10.1002/humu.22273. View

17.

Edgar R . MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004; 5:113. PMC: 517706. DOI: 10.1186/1471-2105-5-113. View

18.

Gesell T, Washietl S . Dinucleotide controlled null models for comparative RNA gene prediction. BMC Bioinformatics. 2008; 9:248. PMC: 2453142. DOI: 10.1186/1471-2105-9-248. View

19.

Washietl S, Hofacker I . Consensus folding of aligned sequences as a new measure for the detection of functional RNAs by comparative genomics. J Mol Biol. 2004; 342(1):19-30. DOI: 10.1016/j.jmb.2004.07.018. View

20.

Rivas E, Eddy S . Noncoding RNA gene detection using comparative sequence analysis. BMC Bioinformatics. 2002; 2:8. PMC: 64605. DOI: 10.1186/1471-2105-2-8. View