Nov 8, 2018

Cis-regulatory code for predicting plant cell-type specific high salinity response

BioRxiv : the Preprint Server for Biology
Sahra UygunShin-Han Shiu


Multicellular organisms have diverse cell types with distinct roles in development and responses to the environment. At the transcriptional level, the differences in environmental response between cell types are due to differences in regulatory programs. In plants, although cell-type environmental responses have been examined, details on how these responses are regulated remain spotty. Here, we identify a set of putative cis-regulatory elements (pCREs) enriched in the promoters of genes responsive to high salinity stress in six Arabidopsis thaliana root cell types. Using machine learning with pCREs as predictors, we establish cis-regulatory codes, i.e. models predicting whether a gene is responsive to high salinity for each cell type. These pCRE-based models outperform models utilizing in vitro binding data of 758 A. thaliana transcription factors. Surprisingly, organ pCREs identified based on whole root high salinity response can predict cell-type responses as well as pCREs derived from cell-type data - because organ and cell-type pCREs predict complementary subsets of high salinity response genes. Our findings not only advance our understanding of the regulatory mechanisms of plant spatial transcriptional response through cis...Continue Reading

  • References
  • Citations


  • We're still populating references for this paper, please check back later.
  • References
  • Citations


  • This paper may not have been cited yet.

Mentioned in this Paper

Transcription, Genetic
Spatial Distribution
Notolabrus celidotus
Spots on Skin
Salinity Response
Genes, vif

About this Paper

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.