Laccases, as early as 1959, were proposed to catalyze the oxidative polymerization of monolignols. Genetic evidence in support of this hypothesis has been elusive due to functional redundancy of laccase genes. An Arabidopsis double mutant demonstrated the involvement of laccases in lignin biosynthesis. We previously identified a subset of laccase genes to be targets of a microRNA (miRNA) ptr-miR397a in Populus trichocarpa. To elucidate the roles of ptr-miR397a and its targets, we characterized the laccase gene family and identified 49 laccase gene models, of which 29 were predicted to be targets of ptr-miR397a. We overexpressed PtrMIR397a in transgenic P. trichocarpa. In each of all nine transgenic lines tested, 17 PtrLACs were down-regulated as analyzed by RNAseq. Transgenic lines with severe reduction in the expression of these laccase genes resulted in an ∼40% decrease in the total laccase activity. Overexpression of Ptr-MIR397a in these transgenic lines also reduced lignin content, whereas levels of all monolignol biosynthetic gene transcripts remained unchanged. A hierarchical genetic regulatory network (GRN) built by a bottom-up graphic Gaussian model algorithm provides additional support for a role of ptr-miR397a as a negative regulator of laccases for lignin biosynthesis. Full transcriptome-based differential gene expression in the overexpressed transgenics and protein domain analyses implicate previously unidentified transcription factors and their targets in an extended hierarchical GRN including ptr-miR397a and laccases that coregulate lignin biosynthesis in wood formation. Ptr-miR397a, laccases, and other regulatory components of this network may provide additional strategies for genetic manipulation of lignin content.L ignin, an abundant biological polymer affecting the ecology of the terrestrial biosphere, is vital for the integrity of plant cell walls, the strength of stems, and resistance against pests and pathogens (1). Lignin is also a major barrier in the pulping and biomass-to-ethanol processes (2-4). For extracting cellulose (pulping) or for enzymatic degradation of cellulose for bioethanol, harsh chemical or physical treatments are used to reduce interactions with lignin or other cell wall components (2-4). Reducing lignin content or altering lignin structure to reduce its recalcitrance are major goals for more efficient processing.Lignin is polymerized primarily from three monolignol precursors, p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol (1, 5). Over five decades, efforts have been made to understand the biosynthesis of the primary monolignols and to modify the quantity or composition of lignin. The polymerization of monolignols into a lignin polymer has long been thought to occur through oxidative polymerization catalyzed by either laccases or peroxidases (6). The mechanisms and specificity of the roles of the oxidative enzymes in lignin polymerization have been controversial (7).Laccases (EC. 1.10.3.2) are multicopper oxidoreductases. Plant laccase was the first enzyme sh...

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux, metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.

Plants develop tolerance to drought by activating genes with altered levels of epigenetic modifications. Specific transcription factors are involved in this activation, but the molecular connections within the regulatory system are unclear. Here, we analyzed genome-wide acetylated lysine residue 9 of histone H3 (H3K9ac) enrichment and examined its association with transcriptomes in Populus trichocarpa under drought stress. We revealed that abscisic acid-Responsive Element (ABRE) motifs in promoters of the drought-responsive genes PtrNAC006, PtrNAC007, and PtrNAC120 are involved in H3K9ac enhancement and activation of these genes. Overexpressing these PtrNAC genes in P. trichocarpa resulted in strong drought-tolerance phenotypes. We showed that the ABRE binding protein PtrAREB1-2 binds to ABRE motifs associated with these PtrNAC genes and recruits the histone acetyltransferase unit ADA2b-GCN5, forming AREB1-ADA2b-GCN5 ternary protein complexes. Moreover, this recruitment enables GCN5-mediated histone acetylation to enhance H3K9ac and enrich RNA polymerase II specifically at these PtrNAC genes for the development of drought tolerance. CRISPR editing or RNA interference-mediated downregulation of any of the ternary members results in highly drought-sensitive P. trichocarpa. Thus, the combinatorial function of the ternary proteins establishes a coordinated histone acetylation and transcription factormediated gene activation for drought response and tolerance in Populus species.

We established a predictive kinetic metabolic-flux model for the 21 enzymes and 24 metabolites of the monolignol biosynthetic pathway using Populus trichocarpa secondary differentiating xylem. To establish this model, a comprehensive study was performed to obtain the reaction and inhibition kinetic parameters of all 21 enzymes based on functional recombinant proteins. A total of 104 Michaelis-Menten kinetic parameters and 85 inhibition kinetic parameters were derived from these enzymes. Through mass spectrometry, we obtained the absolute quantities of all 21 pathway enzymes in the secondary differentiating xylem. This extensive experimental data set, generated from a single tissue specialized in wood formation, was used to construct the predictive kinetic metabolic-flux model to provide a comprehensive mathematical description of the monolignol biosynthetic pathway. The model was validated using experimental data from transgenic P. trichocarpa plants. The model predicts how pathway enzymes affect lignin content and composition, explains a longstanding paradox regarding the regulation of monolignol subunit ratios in lignin, and reveals novel mechanisms involved in the regulation of lignin biosynthesis. This model provides an explanation of the effects of genetic and transgenic perturbations of the monolignol biosynthetic pathway in flowering plants.

Wood is an essential renewable raw material for industrial products and energy. However, knowledge of the genetic regulation of wood formation is limited. We developed a genome-wide high-throughput system for the discovery and validation of specific transcription factor (TF)-directed hierarchical gene regulatory networks (hGRNs) in wood formation. This system depends on a new robust procedure for isolation and transfection of Populus trichocarpa stem differentiating xylem protoplasts. We overexpressed Secondary Wall-Associated NAC Domain 1s (Ptr-SND1-B1), a TF gene affecting wood formation, in these protoplasts and identified differentially expressed genes by RNA sequencing. Direct Ptr-SND1-B1-DNA interactions were then inferred by integration of timecourse RNA sequencing data and top-down Graphical Gaussian Modeling-based algorithms. These Ptr-SND1-B1-DNA interactions were verified to function in differentiating xylem by anti-PtrSND1-B1 antibody-based chromatin immunoprecipitation (97% accuracy) and in stable transgenic P. trichocarpa (90% accuracy). In this way, we established a Ptr-SND1-B1-directed quantitative hGRN involving 76 direct targets, including eight TF and 61 enzyme-coding genes previously unidentified as targets. The network can be extended to the third layer from the second-layer TFs by computation or by overexpression of a second-layer TF to identify a new group of direct targets (third layer). This approach would allow the sequential establishment, one two-layered hGRN at a time, of all layers involved in a more comprehensive hGRN. Our approach may be particularly useful to study hGRNs in complex processes in plant species resistant to stable genetic transformation and where mutants are unavailable.