Research output per year
Research output per year
Description
Abstract
Regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent a map of potential transcriptional regulation. A consistent analysis of a large number of public maize transcriptome datasets including >6000 RNA-Seq samples was used to generate 45 co- expression based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, tissue-and-genotype, etc). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes.
Description
These are the processed datasets used to create networks (raw and filtered expression tables) and predicted interactions
Funding information
Sponsorship: This study was funded by grants from the National Science Foundation (IOS-1546899 and IOS- 1733633). This work is supported in part by Michigan State University and the National Science Foundation Research Traineeship Program (DGE-1828149) to FGC. No conflict of interest declared.
Regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent a map of potential transcriptional regulation. A consistent analysis of a large number of public maize transcriptome datasets including >6000 RNA-Seq samples was used to generate 45 co- expression based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, tissue-and-genotype, etc). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes.
Description
These are the processed datasets used to create networks (raw and filtered expression tables) and predicted interactions
Funding information
Sponsorship: This study was funded by grants from the National Science Foundation (IOS-1546899 and IOS- 1733633). This work is supported in part by Michigan State University and the National Science Foundation Research Traineeship Program (DGE-1828149) to FGC. No conflict of interest declared.
| Date made available | 2020 |
|---|---|
| Publisher | Data Repository for the University of Minnesota |
| Date of data production | Jul 10 2019 - Jan 31 2020 |
Research output
- 1 Article
-
Meta gene regulatory networks in maize highlight functionally relevant regulatory interactions
Zhou, P., Li, Z., Magnusson, E., Cano, F. G., Crisp, P. A., Noshay, J. M., Grotewold, E., Hirsch, C. N., Briggs, S. P. & Springer, N. M., May 2020, In: Plant Cell. 32, 5, p. 1377-1396 20 p.Research output: Contribution to journal › Article › peer-review
Open Access48 Scopus citations