Functional classification of long non-coding RNAs by k-mer content.
Identifieur interne : 001F66 ( Ncbi/Merge ); précédent : 001F65; suivant : 001F67Functional classification of long non-coding RNAs by k-mer content.
Auteurs : Jessime M. Kirk [États-Unis] ; Susan O. Kim [États-Unis] ; Kaoru Inoue [États-Unis] ; Matthew J. Smola [États-Unis] ; David M. Lee [États-Unis] ; Megan D. Schertzer [États-Unis] ; Joshua S. Wooten [États-Unis] ; Allison R. Baker [États-Unis] ; Daniel Sprague [États-Unis] ; David W. Collins [États-Unis] ; Christopher R. Horning [États-Unis] ; Shuo Wang [États-Unis] ; Qidi Chen [États-Unis] ; Kevin M. Weeks [États-Unis] ; Peter J. Mucha [États-Unis] ; J Mauro Calabrese [États-Unis]Source :
- Nature genetics [ 1546-1718 ] ; 2018.
Descripteurs français
- KwdFr :
- ARN long non codant (), ARN long non codant (génétique), Algorithmes, Alignement de séquences, Analyse de regroupements, Analyse de séquence d'ARN (), Animaux, Annotation de séquence moléculaire, Bases de données génétiques, Canaux potassiques voltage-dépendants (génétique), Cellules HepG2, Cellules K562, Conformation d'acide nucléique, Humains, Motifs nucléotidiques (génétique), Souris, Séquence conservée, Séquence nucléotidique.
- MESH :
- génétique : ARN long non codant, Canaux potassiques voltage-dépendants, Motifs nucléotidiques.
- ARN long non codant, Algorithmes, Alignement de séquences, Analyse de regroupements, Analyse de séquence d'ARN, Animaux, Annotation de séquence moléculaire, Bases de données génétiques, Cellules HepG2, Cellules K562, Conformation d'acide nucléique, Humains, Souris, Séquence conservée, Séquence nucléotidique.
English descriptors
- KwdEn :
- Algorithms, Animals, Base Sequence, Cluster Analysis, Conserved Sequence, Databases, Genetic, Hep G2 Cells, Humans, K562 Cells, Mice, Molecular Sequence Annotation, Nucleic Acid Conformation, Nucleotide Motifs (genetics), Potassium Channels, Voltage-Gated (genetics), RNA, Long Noncoding (chemistry), RNA, Long Noncoding (classification), RNA, Long Noncoding (genetics), Sequence Alignment, Sequence Analysis, RNA (methods).
- MESH :
- chemical , chemistry : RNA, Long Noncoding.
- chemical , classification : RNA, Long Noncoding.
- chemical , genetics : Potassium Channels, Voltage-Gated, RNA, Long Noncoding.
- genetics : Nucleotide Motifs.
- methods : Sequence Analysis, RNA.
- Algorithms, Animals, Base Sequence, Cluster Analysis, Conserved Sequence, Databases, Genetic, Hep G2 Cells, Humans, K562 Cells, Mice, Molecular Sequence Annotation, Nucleic Acid Conformation, Sequence Alignment.
Abstract
The functions of most long non-coding RNAs (lncRNAs) are unknown. In contrast to proteins, lncRNAs with similar functions often lack linear sequence homology; thus, the identification of function in one lncRNA rarely informs the identification of function in others. We developed a sequence comparison method to deconstruct linear sequence relationships in lncRNAs and evaluate similarity based on the abundance of short motifs called k-mers. We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their subcellular localization. Using a novel assay to quantify Xist-like regulatory potential, we directly demonstrated that evolutionarily unrelated lncRNAs can encode similar function through different spatial arrangements of related sequence motifs. K-mer-based classification is a powerful approach to detect recurrent relationships between sequence and function in lncRNAs.
DOI: 10.1038/s41588-018-0207-8
PubMed: 30224646
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pubmed:30224646Le document en format XML
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<series><title level="j">Nature genetics</title>
<idno type="eISSN">1546-1718</idno>
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<term>Animals</term>
<term>Base Sequence</term>
<term>Cluster Analysis</term>
<term>Conserved Sequence</term>
<term>Databases, Genetic</term>
<term>Hep G2 Cells</term>
<term>Humans</term>
<term>K562 Cells</term>
<term>Mice</term>
<term>Molecular Sequence Annotation</term>
<term>Nucleic Acid Conformation</term>
<term>Nucleotide Motifs (genetics)</term>
<term>Potassium Channels, Voltage-Gated (genetics)</term>
<term>RNA, Long Noncoding (chemistry)</term>
<term>RNA, Long Noncoding (classification)</term>
<term>RNA, Long Noncoding (genetics)</term>
<term>Sequence Alignment</term>
<term>Sequence Analysis, RNA (methods)</term>
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<term>ARN long non codant (génétique)</term>
<term>Algorithmes</term>
<term>Alignement de séquences</term>
<term>Analyse de regroupements</term>
<term>Analyse de séquence d'ARN ()</term>
<term>Animaux</term>
<term>Annotation de séquence moléculaire</term>
<term>Bases de données génétiques</term>
<term>Canaux potassiques voltage-dépendants (génétique)</term>
<term>Cellules HepG2</term>
<term>Cellules K562</term>
<term>Conformation d'acide nucléique</term>
<term>Humains</term>
<term>Motifs nucléotidiques (génétique)</term>
<term>Souris</term>
<term>Séquence conservée</term>
<term>Séquence nucléotidique</term>
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<term>RNA, Long Noncoding</term>
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<term>Base Sequence</term>
<term>Cluster Analysis</term>
<term>Conserved Sequence</term>
<term>Databases, Genetic</term>
<term>Hep G2 Cells</term>
<term>Humans</term>
<term>K562 Cells</term>
<term>Mice</term>
<term>Molecular Sequence Annotation</term>
<term>Nucleic Acid Conformation</term>
<term>Sequence Alignment</term>
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<term>Analyse de regroupements</term>
<term>Analyse de séquence d'ARN</term>
<term>Animaux</term>
<term>Annotation de séquence moléculaire</term>
<term>Bases de données génétiques</term>
<term>Cellules HepG2</term>
<term>Cellules K562</term>
<term>Conformation d'acide nucléique</term>
<term>Humains</term>
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<front><div type="abstract" xml:lang="en">The functions of most long non-coding RNAs (lncRNAs) are unknown. In contrast to proteins, lncRNAs with similar functions often lack linear sequence homology; thus, the identification of function in one lncRNA rarely informs the identification of function in others. We developed a sequence comparison method to deconstruct linear sequence relationships in lncRNAs and evaluate similarity based on the abundance of short motifs called k-mers. We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their subcellular localization. Using a novel assay to quantify Xist-like regulatory potential, we directly demonstrated that evolutionarily unrelated lncRNAs can encode similar function through different spatial arrangements of related sequence motifs. K-mer-based classification is a powerful approach to detect recurrent relationships between sequence and function in lncRNAs.</div>
</front>
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<DateCompleted><Year>2019</Year>
<Month>04</Month>
<Day>26</Day>
</DateCompleted>
<DateRevised><Year>2019</Year>
<Month>09</Month>
<Day>03</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1546-1718</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>50</Volume>
<Issue>10</Issue>
<PubDate><Year>2018</Year>
<Month>10</Month>
</PubDate>
</JournalIssue>
<Title>Nature genetics</Title>
<ISOAbbreviation>Nat. Genet.</ISOAbbreviation>
</Journal>
<ArticleTitle>Functional classification of long non-coding RNAs by k-mer content.</ArticleTitle>
<Pagination><MedlinePgn>1474-1482</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1038/s41588-018-0207-8</ELocationID>
<Abstract><AbstractText>The functions of most long non-coding RNAs (lncRNAs) are unknown. In contrast to proteins, lncRNAs with similar functions often lack linear sequence homology; thus, the identification of function in one lncRNA rarely informs the identification of function in others. We developed a sequence comparison method to deconstruct linear sequence relationships in lncRNAs and evaluate similarity based on the abundance of short motifs called k-mers. We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their subcellular localization. Using a novel assay to quantify Xist-like regulatory potential, we directly demonstrated that evolutionarily unrelated lncRNAs can encode similar function through different spatial arrangements of related sequence motifs. K-mer-based classification is a powerful approach to detect recurrent relationships between sequence and function in lncRNAs.</AbstractText>
</Abstract>
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<ForeName>Jessime M</ForeName>
<Initials>JM</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
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<ForeName>Susan O</ForeName>
<Initials>SO</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.</Affiliation>
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<ForeName>Kaoru</ForeName>
<Initials>K</Initials>
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</AffiliationInfo>
<AffiliationInfo><Affiliation>National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.</Affiliation>
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<ForeName>Matthew J</ForeName>
<Initials>MJ</Initials>
<AffiliationInfo><Affiliation>Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Ribometrix, Durham, NC, USA.</Affiliation>
</AffiliationInfo>
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<ForeName>David M</ForeName>
<Initials>DM</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
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<ForeName>Megan D</ForeName>
<Initials>MD</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
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<ForeName>Joshua S</ForeName>
<Initials>JS</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
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<ForeName>Allison R</ForeName>
<Initials>AR</Initials>
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<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Harvard Medical School, Ph.D. Program in Biological and Biomedical Sciences, Boston, MA, USA.</Affiliation>
</AffiliationInfo>
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<ForeName>Daniel</ForeName>
<Initials>D</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Curriculum in Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Collins</LastName>
<ForeName>David W</ForeName>
<Initials>DW</Initials>
<AffiliationInfo><Affiliation>Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Horning</LastName>
<ForeName>Christopher R</ForeName>
<Initials>CR</Initials>
<AffiliationInfo><Affiliation>Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Shuo</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Chen</LastName>
<ForeName>Qidi</ForeName>
<Initials>Q</Initials>
<AffiliationInfo><Affiliation>Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Weeks</LastName>
<ForeName>Kevin M</ForeName>
<Initials>KM</Initials>
<Identifier Source="ORCID">http://orcid.org/0000-0002-6748-9985</Identifier>
<AffiliationInfo><Affiliation>Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Mucha</LastName>
<ForeName>Peter J</ForeName>
<Initials>PJ</Initials>
<AffiliationInfo><Affiliation>Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.</Affiliation>
</AffiliationInfo>
</Author>
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<ForeName>J Mauro</ForeName>
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<AffiliationInfo><Affiliation>Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jmcalabr@med.unc.edu.</Affiliation>
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<Agency>NIGMS NIH HHS</Agency>
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<Acronym>GM</Acronym>
<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
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<Country>United States</Country>
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<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
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<Grant><GrantID>R01 GM121806</GrantID>
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<Agency>NIGMS NIH HHS</Agency>
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</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D020014" MajorTopicYN="N">K562 Cells</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D051379" MajorTopicYN="N">Mice</DescriptorName>
</MeshHeading>
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<affiliations><list><country><li>États-Unis</li>
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<region><li>Caroline du Nord</li>
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<settlement><li>Chapel Hill (Caroline du Nord)</li>
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<orgName><li>Université de Caroline du Nord à Chapel Hill</li>
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<name sortKey="Inoue, Kaoru" sort="Inoue, Kaoru" uniqKey="Inoue K" first="Kaoru" last="Inoue">Kaoru Inoue</name>
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<name sortKey="Sprague, Daniel" sort="Sprague, Daniel" uniqKey="Sprague D" first="Daniel" last="Sprague">Daniel Sprague</name>
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<name sortKey="Wooten, Joshua S" sort="Wooten, Joshua S" uniqKey="Wooten J" first="Joshua S" last="Wooten">Joshua S. Wooten</name>
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