Access to RNA-sequencing data from 1,173 plant species: The 1000 Plant transcriptomes initiative (1KP)
Author
Carpenter, Eric JMatasci, Naim
Ayyampalayam, Saravanaraj
Wu, Shuangxiu
Sun, Jing
Yu, Jun
Jimenez Vieira, Fabio Rocha
Bowler, Chris
Dorrell, Richard G
Gitzendanner, Matthew A
Li, Ling
Du, Wensi
K Ullrich, Kristian
Wickett, Norman J
Barkmann, Todd J
Barker, Michael S
Leebens-Mack, James H
Wong, Gane Ka-Shu
Affiliation
Univ Arizona, CyVerseUniv Arizona, Dept Ecol Evolutionary Biol
Issue Date
2019-10-23
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OXFORD UNIV PRESSCitation
Eric J Carpenter, Naim Matasci, Saravanaraj Ayyampalayam, Shuangxiu Wu, Jing Sun, Jun Yu, Fabio Rocha Jimenez Vieira, Chris Bowler, Richard G Dorrell, Matthew A Gitzendanner, Ling Li, Wensi Du, Kristian K. Ullrich, Norman J Wickett, Todd J Barkmann, Michael S Barker, James H Leebens-Mack, Gane Ka-Shu Wong, Access to RNA-sequencing data from 1,173 plant species: The 1000 Plant transcriptomes initiative (1KP), GigaScience, Volume 8, Issue 10, October 2019, giz126, https://doi.org/10.1093/gigascience/giz126Journal
GIGASCIENCERights
Copyright © The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Background: The 1000 Plant transcriptomes initiative (1KP) explored genetic diversity by sequencing RNA from 1,342 samples representing 1,173 species of green plants (Viridiplantae). Findings: This data release accompanies the initiative's final/capstone publication on a set of 3 analyses inferring species trees, whole genome duplications, and gene family expansions. These and previous analyses are based on de novo transcriptome assemblies and related gene predictions. Here, we assess their data and assembly qualities and explain how we detected potential contaminations. Conclusions: These data will be useful to plant and/or evolutionary scientists with interests in particular gene families, either across the green plant tree of life or in more focused lineages.Note
Open access journalISSN
2047-217XPubMed ID
31644802Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1093/gigascience/giz126
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).