The transcriptional landscape of hexaploid wheat across tissues, cultivars, and stress conditions
Ricardo Ramirez-Gonzalez, Philippa Borrill, Cristobal Uauy
The coordinated expression of highly related homoeologous genes in polyploid species underlies the phenotypes of many of the world?s major crops. However, the balance of homoeolog expression across diverse tissues, stress conditions, and cultivars remains poorly understood. Here we combine extensive gene expression datasets with the fully annotated genome sequence to produce a comprehensive, genome-wide analysis of homoeolog expression patterns in hexaploid bread wheat. Bias in homoeolog expression varied between tissues, with ~30% of wheat homoeologs showing unbalanced expression. We found expression asymmetries along wheat chromosomes, with genes showing the largest inter-tissue, inter-cultivar, and coding sequence variation most often located in the high-recombination distal ends of chromosomes. These transcriptionally dynamic genes potentially represent the first steps towards neo/sub- functionalization of wheat homoeologs. Co-expression networks revealed extensive coordination of homoeologs throughout development and, alongside a detailed expression atlas, provide a framework to target candidate genes underpinning agronomic traits in polyploid wheat. Project Code: BB/P016855/1
This data is made available under the
Toronto Agreement
All of the data listed here is available under the prepublication data sharing principle of the
Toronto agreement.
By using this data, you agree to:
- respect the rights of the data producers and contributors to analyze and publish the first
global
analyses and certain other reserved analyses of this data set in a peer-reviewed publication.
- not redistribute, release, or otherwise provide access to the data to anyone outside of the
group, until
the data has been published & submitted to the public data repositories.
- contact the authors to discuss any plans to publish data or analyses that utilize this data to
avoid the
overlap of any planned analyses.
- fully cite the prepublication data along with any applicable versioning details.
- understand that this data as accessed is precompetitive and is not patentable in its present
state.
This agreement does not expire by time but only upon publication of the first global analysis by the
data
producers and contributors.
