The Landscape of long noncoding RNA classification
•ncRNAs constitute the majority of transcriptional output of the human genome.•Lack of functional knowledge of most of ncRNAs has led to classification with a number of issues.•A new classification is emerging rooted in unbiased whole-genome surveys of RNA.•The new classification should allow for ea...
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| Published in | Trends in genetics Vol. 31; no. 5; pp. 239 - 251 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Elsevier Ltd
01.05.2015
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| Subjects | |
| Online Access | Get full text |
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| Abstract | •ncRNAs constitute the majority of transcriptional output of the human genome.•Lack of functional knowledge of most of ncRNAs has led to classification with a number of issues.•A new classification is emerging rooted in unbiased whole-genome surveys of RNA.•The new classification should allow for easy data integration across multiple experiments.
Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long noncoding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the noncoding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual unambiguous classification framework results in a number of challenges in the annotation and interpretation of noncoding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel the function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then, we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. |
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| AbstractList | Highlights • ncRNAs constitute the majority of transcriptional output of the human genome. • Lack of functional knowledge of most of ncRNAs has led to classification with a number of issues. • A new classification is emerging rooted in unbiased whole-genome surveys of RNA. • The new classification should allow for easy data integration across multiple experiments. Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long noncoding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the noncoding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual unambiguous classification framework results in a number of challenges in the annotation and interpretation of noncoding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel the function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then, we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long noncoding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the noncoding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual unambiguous classification framework results in a number of challenges in the annotation and interpretation of noncoding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel the function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then, we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets.Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long noncoding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the noncoding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual unambiguous classification framework results in a number of challenges in the annotation and interpretation of noncoding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel the function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then, we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. •ncRNAs constitute the majority of transcriptional output of the human genome.•Lack of functional knowledge of most of ncRNAs has led to classification with a number of issues.•A new classification is emerging rooted in unbiased whole-genome surveys of RNA.•The new classification should allow for easy data integration across multiple experiments. Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long noncoding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the noncoding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual unambiguous classification framework results in a number of challenges in the annotation and interpretation of noncoding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel the function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then, we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. |
| Author | St. Laurent, Georges Wahlestedt, Claes Kapranov, Philipp |
| Author_xml | – sequence: 1 givenname: Georges surname: St. Laurent fullname: St. Laurent, Georges organization: St. Laurent Institute, 317 New Boston St., Suite 201, Woburn, MA 01801 USA – sequence: 2 givenname: Claes surname: Wahlestedt fullname: Wahlestedt, Claes email: cwahlestedt@med.miami.edu organization: Center for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136 USA – sequence: 3 givenname: Philipp surname: Kapranov fullname: Kapranov, Philipp email: philippk08@hotmail.com organization: Institute of Genomics, School of Biomedical Sciences, Huaqiao Univerisity, 668 Jimei Road, Xiamen, China 361021 |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25869999$$D View this record in MEDLINE/PubMed |
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| Snippet | •ncRNAs constitute the majority of transcriptional output of the human genome.•Lack of functional knowledge of most of ncRNAs has led to classification with a... Highlights • ncRNAs constitute the majority of transcriptional output of the human genome. • Lack of functional knowledge of most of ncRNAs has led to... Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long noncoding RNAs (lncRNAs). lncRNA classification has... |
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| SubjectTerms | Animals annotation of long non-coding RNAs classification of long non-coding RNAs function of long non-coding RNAs Humans lincRNA lncRNA long non-coding RNA Medical Education RNA, Long Noncoding - chemistry RNA, Long Noncoding - classification RNA, Long Noncoding - genetics systems biology transcriptome vlincRNA |
| Title | The Landscape of long noncoding RNA classification |
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