A Developmental Transcriptional Network for Maize Defines Coexpression Modules      

Abstract

Here, we present a genome-wide overview of transcriptional circuits in the agriculturally significant crop species maize (Zea mays). We examined transcript abundance data at 50 developmental stages, from embryogenesis to senescence, for 34,876 gene models and classified genes into 24 robust coexpression modules. Modules were strongly associated with tissue types and related biological processes. Sixteen of the 24 modules (67%) have preferential transcript abundance within specific tissues. One-third of modules had an absence of gene expression in specific tissues. Genes within a number of modules also correlated with the developmental age of tissues. Coexpression of genes is likely due to transcriptional control. For a number of modules, key genes involved in transcriptional control have expression profiles that mimic the expression profiles of module genes, although the expression of transcriptional control genes is not unusually representative of module gene expression. Known regulatory motifs are enriched in several modules. Finally, of the 13 network modules with more than 200 genes, three contain genes that are notably clustered (P < 0.05) within the genome. This work, based on a carefully selected set of major tissues representing diverse stages of maize development, demonstrates the remarkable power of transcript-level coexpression networks to identify underlying biological processes and their molecular components.

Forest Tree Genomics: Review of Progress

“…Tissue differentiation has generally been linked to deep transcriptome reorganizations compared to that associated with developmental stages or environmental conditions in plants including Arabidopsis (Ma et al, 2005) and maize (Downs et al, 2013). The survey of forest tree transcriptome studies presented in Table 2 is consistent with this observation.…”

Maize maintains growth in response to decreased nitrate supply through a highly dynamic and developmental stage‐specific transcriptional response

“…It also indicated that N‐responsive transcriptional analyses could differ markedly, even from time points only a few days apart. It is well established that gene expression changes greatly between tissues and across the development of multiple plants including Arabidopsis (Ma et al ., ; Schmid et al ., ), soya bean (Libault et al ., ), Medicago truncatula (Benedito et al ., ), rice (Jiao et al ., ; Wang et al ., ), barley (Druka et al ., ), bread wheat (Schreiber et al ., ) and maize (Downs et al ., ; Liseron‐Monfils et al ., ; Sekhon et al ., ). Our analysis that builds on this work has revealed responsive transcription is highly dynamic across the life cycle, and proper interpretation of expression data requires knowledge of this variation under steady‐state conditions.…”

Genes and Co-Expression Modules Common to Drought and Bacterial Stress Responses in Arabidopsis and Rice

“…Recently, there has been an upsurge in the number of studies reporting global co-expression networks of plants based on genome wide transcriptome data [14,15,16]. A number of tools namely ATTED-II [17], CressExpress [18], RiceArrayNet [19], OryzaExpress [20] and RiceFREND [21] based on co-expression networks are available that can be explored to identify novel genes, predict gene functions and characterize gene regulatory networks.…”

“…Implemented in R as a package, WGCNA provides a vast array of functions to detect, analyze and export individual and consensus modules from diverse but related microarray studies. WGCNA has been utilized to detect coexpression modules in Arabidopsis , rice, maize, soybean and poplar [14,24,25] and also across species [26]. …”