Faculty Opinions recommendation of Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families.

2018 ◽  
Author(s):  
Janusz Bujnicki ◽  
Pritha Ghosh
Keyword(s):  
Non Coding Rna ◽  
A Genome

scholarly journals Deep learning predicts short non-coding RNA functions from only raw sequence data

2020 ◽  
Vol 16 (11) ◽  
pp. e1008415
Author(s):  
Teresa Maria Rosaria Noviello ◽  
Francesco Ceccarelli ◽  
Michele Ceccarelli ◽  
Luigi Cerulo
Keyword(s):  
Secondary Structure ◽  
Sequence Data ◽  
Computational Cost ◽  
Large Data ◽  
Sequence Information ◽  
Structure Information ◽  
Non Coding Rna ◽  
A Genome ◽  
Data Volume ◽  
Biological Functionality

Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has demanded new computational approaches to annotate their roles. It is widely known that secondary structure is determinant to know RNA function and machine learning based approaches have been successfully proven to predict RNA function from secondary structure information. Here we show that RNA function can be predicted with good accuracy from a lightweight representation of sequence information without the necessity of computing secondary structure features which is computationally expensive. This finding appears to go against the dogma of secondary structure being a key determinant of function in RNA. Compared to recent secondary structure based methods, the proposed solution is more robust to sequence boundary noise and reduces drastically the computational cost allowing for large data volume annotations. Scripts and datasets to reproduce the results of experiments proposed in this study are available at: https://github.com/bioinformatics-sannio/ncrna-deep.

scholarly journals Hda1C restricts the transcription initiation frequency to limit divergent non-coding RNA transcription

2021 ◽  
Author(s):  
Uthra Gowthaman ◽  
Maxim Ivanov ◽  
Isabel Schwarz ◽  
Heta P. Patel ◽  
Niels A. Müller ◽  
...  
Keyword(s):  
Rna Polymerase Ii ◽  
Transcription Initiation ◽  
Histone Deacetylation ◽  
Gene Promoters ◽  
Genetic Screens ◽  
Fluorescence Measurements ◽  
Non Coding Rna ◽  
Genome Wide ◽  
A Genome ◽  
Initiation Frequency

ABSTRACTNucleosome-depleted regions (NDRs) at gene promoters support initiation of RNA Polymerase II transcription. Interestingly, transcription often initiates in both directions, resulting in an mRNA, and a divergent non-coding (DNC) transcript with an unclear purpose. Here, we characterized the genetic architecture and molecular mechanism of DNC transcription in budding yeast. We identified the Hda1 histone deacetylase complex (Hda1C) as a repressor of DNC in high-throughput reverse genetic screens based on quantitative single-cell fluorescence measurements. Nascent transcription profiling showed a genome-wide role of Hda1C in DNC repression. Live-cell imaging of transcription revealed that Hda1C reduced the frequency of DNC transcription. Hda1C contributed to decreased acetylation of histone H3 in DNC regions, supporting DNC repression by histone deacetylation. Our data support the interpretation that DNC results as a consequence of the NDR-based architecture of eukaryotic promoters, but that it is governed by locus-specific repression to maintain genome fidelity.

scholarly journals Deep learning predicts non-coding RNA functions from only raw sequence data

2020 ◽  
Author(s):  
Teresa M.R. Noviello ◽  
Michele Ceccarelli ◽  
Luigi Cerulo
Keyword(s):  
Secondary Structure ◽  
Sequence Data ◽  
Computational Cost ◽  
Large Data ◽  
Sequence Information ◽  
Structure Information ◽  
Non Coding Rna ◽  
A Genome ◽  
Data Volume ◽  
Biological Functionality

AbstractNon-coding RNAs (ncRNAs) are small non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has demanded new computational approaches to annotate their roles. It is widely known that secondary structure is determinant to know RNA function and machine learning based approaches have been successfully proven to predict RNA function from secondary structure information.Here we show that RNA function can be predicted with good accuracy from raw sequence information without the necessity of computing secondary structure features which is computationally expensive. This finding appears to go against the dogma of secondary structure being a key determinant of function in RNA. Compared to recent secondary structure based methods, the proposed solution is more robust to sequence boundary noise and reduces drastically the computational cost allowing for large data volume annotations.Scripts and datasets to reproduce the results of experiments proposed in this study are available at: https://github.com/bioinformatics-sannio/ncrna-deep

scholarly journals Hairpin: a tool for predicting structural non-coding RNA genes ad initio

2019 ◽  
Author(s):  
Jakob Peder Pettersen
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Secondary Structure ◽  
Dna Sequences ◽  
Secondary Structures ◽  
Biological Signal ◽  
Non Coding Rna ◽  
A Genome ◽  
K 12 ◽  
Rna Genes

AbstractBackgroundStructural RNA genes play important and various roles in gene expression and its regulation. Finding such RNA genes in a genome poses a challenge, which in most cases is solved by homology approaches. Ab intio methods for prediction exist, but are not that much explored.ResultsWe introduce hairpin which identify potential structural RNA genes only based on the sequence. We use the algorithm to predict RNA genes in Escherichia coli K-12. When looking at very short regions of the genome, we do not get results differing very much from a random shuffling of the genome. However, at longer stretches it is a clear biological signal. It turns out that none of the regions predicted to code for RNA genes have such an annotation in literature.ConclusionsArbitrary DNA sequences seem to give rise to transcripts with secondary structures similar to real ncRNA. We therefore conclude that exclusively looking at secondary structure base-parings is in general a futile approach.

scholarly journals Long non-coding RNA MIR4300HG polymorphisms are associated with postoperative nausea and vomiting: a genome-wide association study

2020 ◽  
Author(s):  
Shigekazu Sugino ◽  
Daisuke Konno ◽  
Yosuke Kawai ◽  
Masao Nagasaki ◽  
Yasuhiro Endo ◽  
...  
Keyword(s):  
Postoperative Nausea ◽  
Genome Wide Association Study ◽  
Postoperative Nausea And Vomiting ◽  
Nausea And Vomiting ◽  
Candidate Snps ◽  
Nucleotide Polymorphisms ◽  
Non Coding Rna ◽  
Genome Wide ◽  
A Genome ◽  
Long Non Coding Rna

Abstract Background: Genetic factors such as single nucleotide polymorphisms (SNPs) play a key role in the development of postoperative nausea and vomiting (PONV). However, previous findings are not widely applicable to different populations because of population-specific genetic variation. We developed a Japanese-specific DNA microarray for high-throughput genotyping. The aim of the current study was to identify SNPs associated with PONV on a genome-wide scale using this microarray in a sample of Japanese surgical patients. Methods: Associations between 659,636 SNPs and the incidence of PONV 24 h after surgery in a limited sample of 24 female patients were assessed using the microarray. After imputation of genotypes at 24,330,529 SNPs, 78 SNPs were found to be associated with the incidence of PONV. We chose 4 of the 78 SNPs to focus on by in silico functional annotation. Finally, we genotyped these 4 candidate SNPs in 255 patients using real-time PCR to verify association with the incidence of PONV. Results: The T > C variant of rs11232965 in the long non-coding RNA MIR4300HG was significantly associated with reduced incidence of PONV among genotypes and between alleles (p = 0.01 and 0.007). Conclusions: We identified a novel SNP (rs11232965) in the long non-coding RNA MIR4300HG that is associated with PONV. The rs11232965-SNP variant (T > C) is protective against the incidence of PONV. Trial registration: This study was registered at the UMIN Clinical Trials Registry (Identifier: UMIN000022903, date of registration: June 27th, 2016, retrospectively registered, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000026392).

scholarly journals Long non-coding RNA MIR4300HG polymorphisms are associated with postoperative nausea and vomiting: a genome-wide association study

2020 ◽  
Author(s):  
Shigekazu Sugino ◽  
Daisuke Konno ◽  
Yosuke Kawai ◽  
Masao Nagasaki ◽  
Yasuhiro Endo ◽  
...  
Keyword(s):  
Postoperative Nausea ◽  
Genome Wide Association Study ◽  
Postoperative Nausea And Vomiting ◽  
Nausea And Vomiting ◽  
Surgical Patients ◽  
Candidate Snps ◽  
Non Coding Rna ◽  
Genome Wide ◽  
A Genome ◽  
Long Non Coding Rna

Abstract Background: Genetic factors such as single nucleotide polymorphisms (SNPs) play a key role in the development of postoperative nausea and vomiting (PONV). However, previous findings are not widely applicable to different populations because of population-specific genetic variation. We developed a Japanese-specific DNA microarray for high-throughput genotyping. The aim of the current study is to identify causal SNPs associated with PONV on a genome-wide scale using this microarray in a sample of Japanese surgical patients. Methods: Genomic DNA was obtained from 256 surgical patients. We first determined associations between 659,636 SNPs and the incidence of PONV 24hrs after surgery in a limited sample of 24 female patients using the microarray. After imputation of genotypes at 24,330,529 SNPs, 78 SNPs were found to be associated with the incidence of PONV. We chose 4 of the 78 SNPs to focus on by in silico functional annotation. Finally, we genotyped these 4 candidate SNPs in 255 patients using real-time PCR to verify association with the incidence of PONV. Results: The T > C variant of rs11232965 in the long non-coding RNA MIR4300HG was significantly associated with reduced incidence of PONV among genotypes and between alleles (p = 0.01 and 0.007). Conclusions: We identified a novel causal SNP (rs11232965) in the long non-coding RNA MIR4300HG that is associated with PONV. The rs11232965-SNP variant (T > C) is protective against the incidence of PONV. Trial registration: This study was registered at the UMIN Clinical Trials Registry (Identifier: UMIN000022903, date of registration: June 27th, 2016, retrospectively registered, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000026392).

scholarly journals Long non-coding RNA MIR4300HG polymorphisms are associated with postoperative nausea and vomiting: a genome-wide association study

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Shigekazu Sugino ◽  
Daisuke Konno ◽  
Yosuke Kawai ◽  
Masao Nagasaki ◽  
Yasuhiro Endo ◽  
...  
Keyword(s):  
Postoperative Nausea ◽  
Genome Wide Association Study ◽  
Postoperative Nausea And Vomiting ◽  
Nausea And Vomiting ◽  
Candidate Snps ◽  
Nucleotide Polymorphisms ◽  
Non Coding Rna ◽  
Genome Wide ◽  
A Genome ◽  
Long Non Coding Rna

Abstract Background Genetic factors such as single-nucleotide polymorphisms (SNPs) play a key role in the development of postoperative nausea and vomiting (PONV). However, previous findings are not widely applicable to different populations because of population-specific genetic variation. We developed a Japanese-specific DNA microarray for high-throughput genotyping. The aim of the current study was to identify SNPs associated with PONV on a genome-wide scale using this microarray in a sample of Japanese surgical patients. Methods Associations between 659,636 SNPs and the incidence of PONV 24 h after surgery in a limited sample of 24 female patients were assessed using the microarray. After imputation of genotypes at 24,330,529 SNPs, 78 SNPs were found to be associated with the incidence of PONV. We chose 4 of the 78 SNPs to focus on by in silico functional annotation. Finally, we genotyped these 4 candidate SNPs in 255 patients using real-time PCR to verify association with the incidence of PONV. Results The T > C variant of rs11232965 in the long non-coding RNA MIR4300HG was significantly associated with reduced incidence of PONV among genotypes and between alleles (p = 0.01 and 0.007). Conclusions We identified a novel SNP (rs11232965) in the long non-coding RNA MIR4300HG that is associated with PONV. The rs11232965-SNP variant (T > C) is protective against the incidence of PONV. Trial registration This study was registered at the UMIN Clinical Trials Registry (Identifier: UMIN000022903, date of registration: June 27, 2016, retrospectively registered.

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