Wheat and rice are important food crops with enormous biomass residues for biofuels. However, lignocellulosic recalcitrance becomes a crucial factor on biomass process. Plant cell walls greatly determine biomass recalcitrance, thus it is essential to identify their key factors on lignocellulose saccharification. Despite it has been reported about cell wall factors on biomass digestions, little is known in wheat and rice. In this study, we analyzed nine typical pairs of wheat and rice samples that exhibited distinct cell wall compositions, and identified three major factors of wall polymer features that affected biomass digestibility. Based on cell wall compositions, ten wheat accessions and three rice mutants were classified into three distinct groups each with three typical pairs. In terms of group I that displayed single wall polymer alternations in wheat, we found that three wall polymer levels (cellulose, hemicelluloses and lignin) each had a negative effect on biomass digestibility at similar rates under pretreatments of NaOH and H₂SO₄ with three concentrations. However, analysis of six pairs of wheat and rice samples in groups II and III that each exhibited a similar cell wall composition, indicated that three wall polymer levels were not the major factors on biomass saccharification. Furthermore, in-depth detection of the wall polymer features distinctive in rice mutants, demonstrated that biomass digestibility was remarkably affected either negatively by cellulose crystallinity (CrI) of raw biomass materials, or positively by both Ara substitution degree of non-KOH-extractable hemicelluloses (reverse Xyl/Ara) and p-coumaryl alcohol relative proportion of KOH-extractable lignin (H/G). Correlation analysis indicated that Ara substitution degree and H/G ratio negatively affected cellulose crystallinity for high biomass enzymatic digestion. It was also suggested to determine whether Ara and H monomer have an interlinking with cellulose chains in the future. Using nine typical pairs of wheat and rice samples having distinct cell wall compositions and wide biomass saccharification, Ara substitution degree and monolignin H proportion have been revealed to be the dominant factors positively determining biomass digestibility upon various chemical pretreatments. The results demonstrated the potential of genetic modification of plant cell walls for high biomass saccharification in bioenergy crops.

Plant cell walls are complex structures that full-fill many diverse functions during plant growth and development. It is therefore not surprising that thousands of gene products are involved in cell wall synthesis and maintenance. However, functional association for the majority of these gene products remains obscure. One useful approach to infer biological associations is via transcriptional coordination, or co-expression of genes. This approach has proved useful for several biological processes. Nevertheless, combining co-expression with other large-scale measurements may improve the biological inferences. In this study, we used a combined approach of co-expression and cell wall metabolomics to obtain new insight into cell wall synthesis in rice. We initially created a weighted gene co-expression network from publicly available datasets, and then established a comprehensive cell wall dataset by determining cell wall compositions from 29 tissues that almost cover the whole life cycle of rice. We subsequently combined the datasets through the conversion of co-expressed gene modules into eigen-vectors, representing expression profiles for the genes in the modules, and performed comparative analyses against the cell wall contents. Here, we made three major discoveries. First, we confirmed our approach by finding primary and secondary wall cellulose biosynthesis modules, respectively. Second, we found co-expressed modules that strongly correlated with re-organization of the secondary cell walls and with modifications and degradation of hemicellulosic structures. Third, we inferred that at least one module is likely to play a regulatory role in the production of G-rich lignification. Here, we integrated transcriptomic associations and cell wall metabolism and found that certain co-expressed gene modules are positively correlated with distinct cell wall characteristics. We propose that combining multiple data-types, such as coordinated transcription and cell wall analyses, may be a useful approach to glean new insight into biological processes. The combination of multiple datasets, as illustrated here, can further improve the functional inferences that typically are generated via a single type of datasets. In addition, our data extend the typical co-expression approach to allow deeper insight into cell wall biology in rice.