Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing
Zea mays is an important genetic model for elucidating transcriptional networks. Uncertainties about the complete structure of mRNA transcripts limit the progress of research in this system. Here, using single-molecule sequencing technology, we produce 111,151 transcripts from 6 tissues capturing ∼7...
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Published in | Nature communications Vol. 7; no. 1; p. 11708 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
24.06.2016
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | Zea mays
is an important genetic model for elucidating transcriptional networks. Uncertainties about the complete structure of mRNA transcripts limit the progress of research in this system. Here, using single-molecule sequencing technology, we produce 111,151 transcripts from 6 tissues capturing ∼70% of the genes annotated in maize RefGen_v3 genome. A large proportion of transcripts (57%) represent novel, sometimes tissue-specific, isoforms of known genes and 3% correspond to novel gene loci. In other cases, the identified transcripts have improved existing gene models. Averaging across all six tissues, 90% of the splice junctions are supported by short reads from matched tissues. In addition, we identified a large number of novel long non-coding RNAs and fusion transcripts and found that DNA methylation plays an important role in generating various isoforms. Our results show that characterization of the maize B73 transcriptome is far from complete, and that maize gene expression is more complex than previously thought.
Zea mays
is an important crop species and genetic model but uncertainties remain regarding the structure of the transcriptome. Here Wang
et al
. use single-molecule sequencing and size-fractionated libraries to identify novel transcripts and isoforms illustrating the complexity of maize mRNA. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/ncomms11708 |