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Deep Annotation of Populus trichocarpa microRNAs from Diverse Tissue Sets

Overview of attention for article published in PLOS ONE, March 2012
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Title
Deep Annotation of Populus trichocarpa microRNAs from Diverse Tissue Sets
Published in
PLOS ONE, March 2012
DOI 10.1371/journal.pone.0033034
Pubmed ID
Authors

Joshua R. Puzey, Amir Karger, Michael Axtell, Elena M. Kramer

Abstract

Populus trichocarpa is an important woody model organism whose entire genome has been sequenced. This resource has facilitated the annotation of microRNAs (miRNAs), which are short non-coding RNAs with critical regulatory functions. However, despite their developmental importance, P. trichocarpa miRNAs have yet to be annotated from numerous important tissues. Here we significantly expand the breadth of tissue sampling and sequencing depth for miRNA annotation in P. trichocarpa using high-throughput smallRNA (sRNA) sequencing. miRNA annotation was performed using three individual next-generation sRNA sequencing runs from separate leaves, xylem, and mechanically treated xylem, as well as a fourth run using a pooled sample containing vegetative apices, male flowers, female flowers, female apical buds, and male apical and lateral buds. A total of 276 miRNAs were identified from these datasets, including 155 previously unannotated miRNAs, most of which are P. trichocarpa specific. Importantly, we identified several xylem-enriched miRNAs predicted to target genes known to be important in secondary growth, including the critical reaction wood enzyme xyloglucan endo-transglycosylase/hydrolase and vascular-related transcription factors. This study provides a thorough genome-wide annotation of miRNAs in P. trichocarpa through deep sRNA sequencing from diverse tissue sets. Our data significantly expands the P. trichocarpa miRNA repertoire, which will facilitate a broad range of research in this major model system.

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Geographical breakdown

Country Count As %
Colombia 2 3%
Sweden 2 3%
Norway 2 3%
Unknown 63 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 36%
Researcher 16 23%
Professor > Associate Professor 5 7%
Professor 5 7%
Student > Master 5 7%
Other 8 12%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 67%
Biochemistry, Genetics and Molecular Biology 9 13%
Computer Science 3 4%
Mathematics 1 1%
Environmental Science 1 1%
Other 2 3%
Unknown 7 10%