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dc.contributor.authorChen, Jenny
dc.contributor.authorShishkin, Alexander A.
dc.contributor.authorZhu, Xiaopeng
dc.contributor.authorKadri, Sabah
dc.contributor.authorMaza, Itay
dc.contributor.authorHanna, Jacob H.
dc.contributor.authorRegev, Aviv
dc.contributor.authorGarber, Manuel
dc.date2022-08-11T08:08:23.000
dc.date.accessioned2022-08-23T15:53:23Z
dc.date.available2022-08-23T15:53:23Z
dc.date.issued2015-11-11
dc.date.submitted2018-06-21
dc.identifier.citation<p>bioRxiv 031385; doi: https://doi.org/10.1101/031385. <a href="https://doi.org/10.1101/031385" target="_blank">Link to preprint on bioRxiv service.</a></p>
dc.identifier.doi10.1101/031385
dc.identifier.urihttp://hdl.handle.net/20.500.14038/29342
dc.description<p>This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.</p>
dc.description.abstractBACKGROUND: Recent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across multitudes of species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: 1) identifying truly noncoding genes from de novo reconstructed transcriptomes, and 2) prioritizing hundreds of resulting putative lncRNAs from each sample for downstream experimental interrogation. RESULTS: We present slncky, a computational lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-Sequencing data and further prioritizes lncRNAs by characterizing selective constraint as a proxy for function. Our filtering pipeline is comparable to manual curation efforts and more sensitive than previously published approaches. Further, we develop, for the first time, a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for both sequence and transcript evolution. Our analysis reveals that selection acts in several distinct patterns, and uncovers two notable classes of lncRNAs: one showing strong purifying selection at RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript. CONCLUSION: Our novel comparative methods for lncRNAs reveals 233 constrained lncRNAs out of tens of thousands of currently annotated transcripts, which we believe should be prioritized for further interrogation. To aid in their analysis we provide the slncky Evolution Browser as a resource for experimentalists.
dc.language.isoen_US
dc.relation<p>Now published in <em>Genome Biology</em> doi: <a href="http://dx.doi.org/10.1186/s13059-016-0880-9" target="_blank">10.1186/s13059-016-0880-9</a>.</p>
dc.rightsThe copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC 4.0 International license.
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectevolutionary biology
dc.subjectRNA
dc.subjectlong non-coding RNAs
dc.subjectslncky
dc.subjectlong noncoding RNAs
dc.subjectevolution
dc.subjectcomparative genomics
dc.subjectmolecular evolution
dc.subjectannotation
dc.subjectlincRNA
dc.subjectRNA-Seq
dc.subjecttranscriptome
dc.subjectAmino Acids, Peptides, and Proteins
dc.subjectComputational Biology
dc.subjectEcology and Evolutionary Biology
dc.subjectGenetic Phenomena
dc.subjectNucleic Acids, Nucleotides, and Nucleosides
dc.titleEvolutionary analysis across mammals reveals distinct classes of long noncoding RNAs [preprint]
dc.typePreprint
dc.source.journaltitlebioRxiv
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=2578&amp;context=faculty_pubs&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/1568
dc.identifier.contextkey12352831
refterms.dateFOA2022-08-23T15:53:23Z
html.description.abstract<p>BACKGROUND: Recent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across multitudes of species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: 1) identifying truly noncoding genes from de novo reconstructed transcriptomes, and 2) prioritizing hundreds of resulting putative lncRNAs from each sample for downstream experimental interrogation.</p> <p>RESULTS: We present slncky, a computational lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-Sequencing data and further prioritizes lncRNAs by characterizing selective constraint as a proxy for function. Our filtering pipeline is comparable to manual curation efforts and more sensitive than previously published approaches. Further, we develop, for the first time, a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for both sequence and transcript evolution. Our analysis reveals that selection acts in several distinct patterns, and uncovers two notable classes of lncRNAs: one showing strong purifying selection at RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript.</p> <p>CONCLUSION: Our novel comparative methods for lncRNAs reveals 233 constrained lncRNAs out of tens of thousands of currently annotated transcripts, which we believe should be prioritized for further interrogation. To aid in their analysis we provide the slncky Evolution Browser as a resource for experimentalists.</p>
dc.identifier.submissionpathfaculty_pubs/1568
dc.contributor.departmentProgram in Molecular Medicine
dc.contributor.departmentProgram in Bioinformatics and Integrative Biology


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The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC 4.0 International license.
Except where otherwise noted, this item's license is described as The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC 4.0 International license.