A systems biology approach uncovers a gene co-expression network associated with cell wall degradability in maize

Abstract

Understanding the mechanisms triggering variation of cell wall degradability is a prerequisite to improving the energy value of lignocellulosic biomass for animal feed or biorefinery. Here, we implemented a multiscale systems approach to shed light on the genetic basis of cell wall degradability in maize. We demonstrated that allele replacement in two pairs of near-isogenic lines at a region encompassing a major quantitative trait locus (QTL) for cell wall degradability led to phenotypic variation of a similar magnitude and sign to that expected from a QTL analysis of cell wall degradability in the F271 × F288 recombinant inbred line progeny. Using DNA sequences within the QTL interval of both F271 and F288 inbred lines and Illumina RNA sequencing datasets from internodes of the selected near-isogenic lines, we annotated the genes present in the QTL interval and provided evidence that allelic variation at the introgressed QTL region gives rise to coordinated changes in gene expression. The identification of a gene co-expression network associated with cell wall-related trait variation revealed that the favorable F288 alleles exploit biological processes related to oxidation-reduction, regulation of hydrogen peroxide metabolism, protein folding and hormone responses. Nested in modules of co-expressed genes, potential new cell-wall regulators were identified, including two transcription factors of the group VII ethylene response factor family, that could be exploited to fine-tune cell wall degradability. Overall, these findings provide new insights into the regulatory mechanisms by which a major locus influences cell wall degradability, paving the way for its map-based cloning in maize.

Identification of QTLs Controlling Resistance/Tolerance to Striga hermonthica in an Extra-Early Maturing Yellow Maize Population

“…Maize (Zea mays L.) is the most widely grown staple food crop in sub-Saharan Africa (SSA), and accounts for a large proportion of carbohydrates, proteins, lipids and vitamins for millions of people in the sub-region [1,2]. The root hemi-parasitic plant Striga hermonthica is an important biotic constraint limiting maize production in SSA.…”

Plant-PLMview: a database for identifyingcis-regulatory sequences with preferential positions in gene-proximal regions of plants

“…In this context, the in silico PLMdetect method [22,23] was developed to identify short DNA sequences that are overrepresented when the distance to the TSS or to the TTS is constrained, and are therefore referred to as preferentially located motifs (PLMs). Numerous applications are already showing interest in using PLMdetect to advance the characterization of the gene-proximal environment in targeted transcriptomic datasets and at the genome level for Arabidopsis and maize [21,[24][25][26][27][28]. To make PLMdetect available to the entire community, we introduce Plant-PLMview, a web database that allows all users to explore the proximal environment of genes by performing PLM searches for 20 plant species.…”