Systematic approaches to identify functional lncRNAs

Alcid, Eric A; Tsukiyama, Toshio

doi:10.1016/j.gde.2015.12.005

Cited by 10 publications

(4 citation statements)

References 32 publications

(40 reference statements)

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“…We show here that systematic analysis of pairwise GIs can provide insights about the function of individual lncRNAs. The functional maps obtained by GIs could complement the information derived by other high-throughput approaches [76, 77] to help unravel the biological significance of lncRNAs. Although the present study focuses on stable lincRNAs, future work could also analyse GIs for yeast antisense lncRNAs since methodologies are being developed that abrogate the transcription of a specific non-coding RNA without disrupting the expression of its associated sense mRNA [78].…”

Section: Discussionmentioning

confidence: 99%

Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae

et al. 2016

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BackgroundTranscriptome studies have revealed that many eukaryotic genomes are pervasively transcribed producing numerous long non-coding RNAs (lncRNAs). However, only a few lncRNAs have been ascribed a cellular role thus far, with most regulating the expression of adjacent genes. Even less lncRNAs have been annotated as essential hence implying that the majority may be functionally redundant. Therefore, the function of lncRNAs could be illuminated through systematic analysis of their synthetic genetic interactions (GIs).ResultsHere, we employ synthetic genetic array (SGA) in Saccharomyces cerevisiae to identify GIs between long intergenic non-coding RNAs (lincRNAs) and protein-coding genes. We first validate this approach by demonstrating that the telomerase RNA TLC1 displays a GI network that corresponds to its well-described function in telomere length maintenance. We subsequently performed SGA screens on a set of uncharacterised lincRNAs and uncover their connection to diverse cellular processes. One of these lincRNAs, SUT457, exhibits a GI profile associating it to telomere organisation and we consistently demonstrate that SUT457 is required for telomeric overhang homeostasis through an Exo1-dependent pathway. Furthermore, the GI profile of SUT457 is distinct from that of its neighbouring genes suggesting a function independent to its genomic location. Accordingly, we show that ectopic expression of this lincRNA suppresses telomeric overhang accumulation in sut457Δ cells assigning a trans-acting role for SUT457 in telomere biology.ConclusionsOverall, our work proposes that systematic application of this genetic approach could determine the functional significance of individual lncRNAs in yeast and other complex organisms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-016-0325-7) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae

et al. 2016

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“…Among these noncoding RNAs, the long noncoding RNAs (lncRNAs) had more than 200 nt length and could not code proteins, and exerted diverse functions such as cell proliferation, cell apoptosis, angiogenesis, and tumor metastasis. 6 Growing evidence has shown the importance of lncRNA in human diseases, particularly in cancers. Recently, lncRNAs were identified to be associated with the pathogenesis of PE.…”

Section: Introductionmentioning

confidence: 99%

“…The genome‐sequencing projects showed that more than 90% of the genome is transcribed into noncoding RNAs. Among these noncoding RNAs, the long noncoding RNAs (lncRNAs) had more than 200 nt length and could not code proteins, and exerted diverse functions such as cell proliferation, cell apoptosis, angiogenesis, and tumor metastasis . Growing evidence has shown the importance of lncRNA in human diseases, particularly in cancers.…”

Section: Introductionmentioning

confidence: 99%

The lncRNA small nucleolar RNA host gene 5 regulates trophoblast cell proliferation, invasion, and migration via modulating miR‐26a‐5p/N‐cadherin axis

Yang

Lan

et al. 2018

J of Cellular Biochemistry

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Pre-eclampsia (PE) is a pregnancy-specific disease characterized by the occurrence of hypertension and proteinuria after two weeks of gestation. Long noncoding RNAs (lncRNAs) are emerging as key regulators in PE development.This study aims to investigate the role of lncRNA, small nucleolar RNA host gene 5 (SNHG5), in the pathogenesis of PE. The expression of SNHG5 was significantly downregulated in placental tissues from patients with severe PE compared normal controls. Overexpression of SNHG5 promoted trophoblast (HTR-8/SVneo) cell proliferation, invasion, and migration, and flow cytometry results showed that SNHG5 overexpression inhibited apoptosis and caused a decrease of cell population at the G 0 /G 1 phase and an increase of cell population at the S phase, while knockdown of SNHG5 had the opposite effects. The interaction between SNHG5 and miR-26a-5p was predicted by bioinformatics analysis and confirmed by luciferase reporter assay and RNA immunoprecipitation, and miR-26a-5p was negatively regulated by SNHG5; miR-26a-5p expression was upregulated in PE placental tissues and was inversely correlated with SNHG5 expression. Furthermore, miR-26a-5p was predicted to target the 3′ untranslated region of N-cadherin, which was confirmed by luciferase reporter assay, and miR-26a-5p overexpression suppressed N-cadherin expression in HTR-8/SVneo cells. N-cadherin mRNA expression was downregulated in PE placental tissues and was positively correlated with SNHG5 expression.Both overexpression of miR-26a-5p and knockdown of N-cadherin suppressed HTR-8/SVneo cell invasion and migration, and also attenuated the effects of SNHG5 on the cellular functions of HTR-8/SVneo cells. In conclusion, our study suggested that SNHG5 promotes trophoblast cell proliferation, invasion, and migration at least partly via regulating the miR-26a-5p/N-cadherin axis. K E Y W O R D Sinvasion and migration, miR-26a-5p, N-cadherin, pre-eclampsia (PE), small nucleolar RNA host gene 5 (SNHG5), trophoblast J Cell Biochem. 2019;120:3173-3184.wileyonlinelibrary.com/journal/jcb

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“…Similar to the structure of mRNAs, lncRNAs have a poly tail and promoter structure after splicing [ 10 ]. Since lncRNAs and mRNAs have certain similarities and both have biological functions [ 11 ], the identification and differentiation of lncRNAs and mRNAs deserve further study. Moreover, previous studies have shown that some lncRNAs expressed with high abundance are poorly conserved, while some low-expressed lncRNAs have important functions [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

PreLnc: An Accurate Tool for Predicting lncRNAs Based on Multiple Features

Cao

Wang

et al. 2020

Genes

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Accumulating evidence indicates that long non-coding RNAs (lncRNAs) have certain similarities with messenger RNAs (mRNAs) and are associated with numerous important biological processes, thereby demanding methods to distinguish them. Based on machine learning algorithms, a variety of methods are developed to identify lncRNAs, providing significant basic data support for subsequent studies. However, many tools lack certain scalability, versatility and balance, and some tools rely on genome sequence and annotation. In this paper, we propose a convenient and accurate tool “PreLnc”, which uses high-confidence lncRNA and mRNA transcripts to build prediction models through feature selection and classifiers. The false discovery rate (FDR) adjusted P-value and Z-value were used for analyzing the tri-nucleotide composition of transcripts of different species. Conclusions can be drawn from the experiment that there were significant differences in RNA transcripts among plants, which may be related to evolutionary conservation and the fact that plants are under evolutionary pressure for a longer time than animals. Combining with the Pearson correlation coefficient, we use the incremental feature selection (IFS) method and the comparison of multiple classifiers to build the model. Finally, the balanced random forest was used to construct the classifier, and PreLnc obtained 91.09% accuracy for 349,186 transcripts of animals and plants. In addition, by comparing standard performance measurements, PreLnc performed better than other prediction tools.

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Systematic approaches to identify functional lncRNAs

Cited by 10 publications

References 32 publications

Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae

Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae

The lncRNA small nucleolar RNA host gene 5 regulates trophoblast cell proliferation, invasion, and migration via modulating miR‐26a‐5p/N‐cadherin axis

PreLnc: An Accurate Tool for Predicting lncRNAs Based on Multiple Features

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