Access to RNA-sequencing data from 1,173 plant species: The 1000 Plant transcriptomes initiative (1KP)
AuthorCarpenter, Eric J
Jimenez Vieira, Fabio Rocha
Dorrell, Richard G
Gitzendanner, Matthew A
K Ullrich, Kristian
Wickett, Norman J
Barkmann, Todd J
Barker, Michael S
Leebens-Mack, James H
Wong, Gane Ka-Shu
AffiliationUniv Arizona, CyVerse
Univ Arizona, Dept Ecol Evolutionary Biol
MetadataShow full item record
PublisherOXFORD UNIV PRESS
CitationEric 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/giz126
RightsCopyright © 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/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Collection InformationThis 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 email@example.com.
AbstractBackground: 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.
NoteOpen access journal
VersionFinal published version