Regulatory motifs identified from a maize developmental coexpression network

• Published in: Genome Vol. 57; no. 3; pp. 181 - 184
• Main Authors: Downs, Gregory S., Liseron-Monfils, Christophe, Lukens, Lewis N.
• Format: Journal Article
• Language: English
• Published: Canada NRC Research Press 01.03.2014; Canadian Science Publishing NRC Research Press
• Subjects: 5' Untranslated Regions; 5′ upstream regulatory sequences; Botanical research; coexpression network; Corn; Development; développement de la plante; embryogenesis; Embryonic growth stage; Gene expression; gene expression regulation; Gene Expression Regulation, Developmental; Gene Expression Regulation, Plant; Gene Regulatory Networks; Genes; Genetic aspects; Genetic research; Growth; identification de motifs; motif identification; Nucleotide Motifs; plant development; Plant Development - genetics; Plants; Position-Specific Scoring Matrices; Promzea; regulatory sequences; réseau de coexpression; séquences régulatrices en 5; transcription (genetics); transcriptome; Zea mays; Zea mays - genetics; Zea mays - growth & development; United Kingdom; identification de motifs; plant development; Zea mays; réseau de coexpression; motif identification; développement de la plante; coexpression network; Promzea; 5′ upstream regulatory sequences; séquences régulatrices en 5
• ISSN: 1480-3321; 0831-2796; 1480-3321
• DOI: 10.1139/gen-2013-0177

Transcriptional control is an important determinant of plant development, and distinct modules of coordinated genes characterize the maize developmental transcriptome. Upstream regulatory sequences are often the primary factors that control gene expression pattern and abundance. Here, we identify 244 regulatory motifs that are significantly enriched within 24 gene expression modules previously constructed from transcript abundances of 34 876 Zea mays (maize) gene models from embryogenesis to senescence. Within modules, we identify motifs that have not been characterized. In addition, we identify motifs similar to experimentally verified motifs, and the functions of these motifs overlap with predicted module functions. This work demonstrates the power of transcript-level coexpression modules to identify both variants of known regulatory motifs and novel motifs that control a species’ developmental transcriptome.