Predicting long non-coding RNAs using RNA sequencing
The advent of next-generation sequencing, and in particular RNA-sequencing (RNA-seq), technologies has expanded our knowledge of the transcriptional capacity of human and other animal, genomes. In particular, recent RNA-seq studies have revealed that transcription is widespread across the mammalian...
| Հիմնական հեղինակներ: | , |
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| Ձևաչափ: | Journal article |
| Հրապարակվել է: |
2013
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| _version_ | 1826264528544858112 |
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| author | Ilott, N Ponting, C |
| author_facet | Ilott, N Ponting, C |
| author_sort | Ilott, N |
| collection | OXFORD |
| description | The advent of next-generation sequencing, and in particular RNA-sequencing (RNA-seq), technologies has expanded our knowledge of the transcriptional capacity of human and other animal, genomes. In particular, recent RNA-seq studies have revealed that transcription is widespread across the mammalian genome, resulting in a large increase in the number of putative transcripts from both within, and intervening between, known protein-coding genes. Long transcripts that appear to lack protein-coding potential (long non-coding RNAs, lncRNAs) have been the focus of much recent research, in part owing to observations of their cell-type and developmental time-point restricted expression patterns. A variety of sequencing protocols are currently available for identifying lncRNAs including RNA polymerase II occupancy, chromatin state maps and - the focus of this review - deep RNA sequencing. In addition, there are numerous analytical methods available for mapping reads and assembling transcript models that predict the presence and structure of lncRNAs from RNA-seq data. Here we review current methods for identifying lncRNAs using large-scale sequencing data from RNA-seq experiments and highlight analytical considerations that are required when undertaking such projects. © 2013 Elsevier Inc. All rights reserved. |
| first_indexed | 2024-03-06T20:09:17Z |
| format | Journal article |
| id | oxford-uuid:2a02e88d-4d84-491d-ac48-89444819976e |
| institution | University of Oxford |
| last_indexed | 2024-03-06T20:09:17Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:2a02e88d-4d84-491d-ac48-89444819976e2022-03-26T12:22:25ZPredicting long non-coding RNAs using RNA sequencingJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:2a02e88d-4d84-491d-ac48-89444819976eSymplectic Elements at Oxford2013Ilott, NPonting, CThe advent of next-generation sequencing, and in particular RNA-sequencing (RNA-seq), technologies has expanded our knowledge of the transcriptional capacity of human and other animal, genomes. In particular, recent RNA-seq studies have revealed that transcription is widespread across the mammalian genome, resulting in a large increase in the number of putative transcripts from both within, and intervening between, known protein-coding genes. Long transcripts that appear to lack protein-coding potential (long non-coding RNAs, lncRNAs) have been the focus of much recent research, in part owing to observations of their cell-type and developmental time-point restricted expression patterns. A variety of sequencing protocols are currently available for identifying lncRNAs including RNA polymerase II occupancy, chromatin state maps and - the focus of this review - deep RNA sequencing. In addition, there are numerous analytical methods available for mapping reads and assembling transcript models that predict the presence and structure of lncRNAs from RNA-seq data. Here we review current methods for identifying lncRNAs using large-scale sequencing data from RNA-seq experiments and highlight analytical considerations that are required when undertaking such projects. © 2013 Elsevier Inc. All rights reserved. |
| spellingShingle | Ilott, N Ponting, C Predicting long non-coding RNAs using RNA sequencing |
| title | Predicting long non-coding RNAs using RNA sequencing |
| title_full | Predicting long non-coding RNAs using RNA sequencing |
| title_fullStr | Predicting long non-coding RNAs using RNA sequencing |
| title_full_unstemmed | Predicting long non-coding RNAs using RNA sequencing |
| title_short | Predicting long non-coding RNAs using RNA sequencing |
| title_sort | predicting long non coding rnas using rna sequencing |
| work_keys_str_mv | AT ilottn predictinglongnoncodingrnasusingrnasequencing AT pontingc predictinglongnoncodingrnasusingrnasequencing |