Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits.

The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein-protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.

PhosBoost: Improved phosphorylation prediction recall using gradient boosting and protein language models.

Protein phosphorylation is a dynamic and reversible post-translational modification that regulates a variety of essential biological processes. The regulatory role of phosphorylation in cellular signaling pathways, protein-protein interactions, and enzymatic activities has motivated extensive research efforts to understand its functional implications. Experimental protein phosphorylation data in plants remains limited to a few species, necessitating a scalable and accurate prediction method. Here, we present PhosBoost, a machine-learning approach that leverages protein language models and gradient-boosting trees to predict protein phosphorylation from experimentally derived data. Trained on data obtained from a comprehensive plant phosphorylation database, qPTMplants, we compared the performance of PhosBoost to existing protein phosphorylation prediction methods, PhosphoLingo and DeepPhos. For serine and threonine prediction, PhosBoost achieved higher recall than PhosphoLingo and DeepPhos (.78, .56, and .14, respectively) while maintaining a competitive area under the precision-recall curve (.54, .56, and .42, respectively). PhosphoLingo and DeepPhos failed to predict any tyrosine phosphorylation sites, while PhosBoost achieved a recall score of .6. Despite the precision-recall tradeoff, PhosBoost offers improved performance when recall is prioritized while consistently providing more confident probability scores. A sequence-based pairwise alignment step improved prediction results for all classifiers by effectively increasing the number of inferred positive phosphosites. We provide evidence to show that PhosBoost models are transferable across species and scalable for genome-wide protein phosphorylation predictions. PhosBoost is freely and publicly available on GitHub.

Maize Terpene Synthase 8 (ZmTPS8) Contributes to a Complex Blend of Fungal-Elicited Antibiotics.

In maize (Zea mays), fungal-elicited immune responses include the accumulation of terpene synthase (TPS) and cytochrome P450 monooxygenases (CYP) enzymes resulting in complex antibiotic arrays of sesquiterpenoids and diterpenoids, including α/ß-selinene derivatives, zealexins, kauralexins and dolabralexins. To uncover additional antibiotic families, we conducted metabolic profiling of elicited stem tissues in mapping populations, which included B73 × M162W recombinant inbred lines and the Goodman diversity panel. Five candidate sesquiterpenoids associated with a chromosome 1 locus spanning the location of ZmTPS27 and ZmTPS8. Heterologous enzyme co-expression studies of ZmTPS27 in Nicotiana benthamiana resulted in geraniol production while ZmTPS8 yielded α-copaene, δ-cadinene and sesquiterpene alcohols consistent with epi-cubebol, cubebol, copan-3-ol and copaborneol matching the association mapping efforts. ZmTPS8 is an established multiproduct α-copaene synthase; however, ZmTPS8-derived sesquiterpene alcohols are rarely encountered in maize tissues. A genome wide association study further linked an unknown sesquiterpene acid to ZmTPS8 and combined ZmTPS8-ZmCYP71Z19 heterologous enzyme co-expression studies yielded the same product. To consider defensive roles for ZmTPS8, in vitro bioassays with cubebol demonstrated significant antifungal activity against both Fusarium graminearum and Aspergillus parasiticus. As a genetically variable biochemical trait, ZmTPS8 contributes to the cocktail of terpenoid antibiotics present following complex interactions between wounding and fungal elicitation.

Plant signaling: Sustaining leaf electrical excitability protects against prolonged herbivory.

Electrical signaling is a critical initial trigger of systemic plant resistance to herbivory, but channels and pumps involved in signal maintenance are poorly understood. A new study identifies P-type calcium ATPases as necessary for both sustained vascular excitability during prolonged attack and physiological resilience.

A sorghum genome-wide association study (GWAS) identifies a WRKY transcription factor as a candidate gene underlying sugarcane aphid (Melanaphis sacchari) resistance.

MAIN CONCLUSION: A WRKY transcription factor identified through forward genetics is associated with sorghum resistance to the sugarcane aphid and through heterologous expression reduces aphid populations in multiple plant species. Crop plant resistance to insect pests is based on genetically encoded traits which often display variability across diverse germplasm. In a comparatively recent event, a predominant sugarcane aphid (SCA: Melanaphis sacchari) biotype has become a significant agronomic pest of grain sorghum (Sorghum bicolor). To uncover candidate genes underlying SCA resistance, we used a forward genetics approach combining the genetic diversity present in the Sorghum Association Panel (SAP) and the Bioenergy Association Panel (BAP) for a genome-wide association study, employing an established SCA damage rating. One major association was found on Chromosome 9 within the WRKY transcription factor 86 (SbWRKY86). Transcripts encoding SbWRKY86 were previously identified as upregulated in SCA-resistant germplasm and the syntenic ortholog in maize accumulates following Rhopalosiphum maidis infestation. Analyses of SbWRKY86 transcripts displayed patterns of increased SCA-elicited accumulation in additional SCA-resistant sorghum lines. Heterologous expression of SbWRKY86 in both tobacco (Nicotiana benthamiana) and Arabidopsis resulted in reduced population growth of green peach aphid (Myzus persicae). Comparative RNA-Seq analyses of Arabidopsis lines expressing 35S:SbWRKY86-YFP identified changes in expression for a small network of genes associated with carbon-nitrogen metabolism and callose deposition, both contributing factors to defense against aphids. As a test of altered plant responses, 35S:SbWRKY86-YFP Arabidopsis lines were activated using the flagellin epitope elicitor, flg22, and displayed significant increases in callose deposition. Our findings indicate that both heterologous and increased native expression of the transcription factor SbWRKY86 contributes to reduced aphid levels in diverse plant models.

Comparative analyses of responses to exogenous and endogenous antiherbivore elicitors enable a forward genetics approach to identify maize gene candidates mediating sensitivity to herbivore-associated molecular patterns.

Crop damage by herbivorous insects remains a significant contributor to annual yield reductions. Following attack, maize (Zea mays) responds to herbivore-associated molecular patterns (HAMPs) and damage-associated molecular patterns (DAMPs), activating dynamic direct and indirect antiherbivore defense responses. To define underlying signaling processes, comparative analyses between plant elicitor peptide (Pep) DAMPs and fatty acid-amino acid conjugate (FAC) HAMPs were conducted. RNA sequencing analysis of early transcriptional changes following Pep and FAC treatments revealed quantitative differences in the strength of response yet a high degree of qualitative similarity, providing evidence for shared signaling pathways. In further comparisons of FAC and Pep responses across diverse maize inbred lines, we identified Mo17 as part of a small subset of lines displaying selective FAC insensitivity. Genetic mapping for FAC sensitivity using the intermated B73 × Mo17 population identified a single locus on chromosome 4 associated with FAC sensitivity. Pursuit of multiple fine-mapping approaches further narrowed the locus to 19 candidate genes. The top candidate gene identified, termed FAC SENSITIVITY ASSOCIATED (ZmFACS), encodes a leucine-rich repeat receptor-like kinase (LRR-RLK) that belongs to the same family as a rice (Oryza sativa) receptor gene previously associated with the activation of induced responses to diverse Lepidoptera. Consistent with reduced sensitivity, ZmFACS expression was significantly lower in Mo17 as compared to B73. Transient heterologous expression of ZmFACS in Nicotiana benthamiana resulted in a significantly increased FAC-elicited response. Together, our results provide useful resources for studying early elicitor-induced antiherbivore responses in maize and approaches to discover gene candidates underlying HAMP sensitivity in grain crops.

MutRank: an R shiny web-application for exploratory targeted mutual rank-based coexpression analyses integrated with user-provided supporting information.

The rapid assignment of genotypes to phenotypes has been a historically challenging process. The discovery of genes encoding biosynthetic pathway enzymes for defined plant specialized metabolites has been informed and accelerated by the detection of gene clusters. Unfortunately, biosynthetic pathway genes are commonly dispersed across chromosomes or reside in genes clusters that provide little predictive value. More reliably, transcript abundance of genes underlying biochemical pathways for plant specialized metabolites display significant coregulation. By rapidly identifying highly coexpressed transcripts, it is possible to efficiently narrow candidate genes encoding pathway enzymes and more easily predict both functions and functional associations. Mutual Rank (MR)-based coexpression analyses in plants accurately demonstrate functional associations for many specialized metabolic pathways; however, despite the clear predictive value of MR analyses, the application is uncommonly used to drive new pathway discoveries. Moreover, many coexpression databases aid in the prediction of both functional associations and gene functions, but lack customizability for refined hypothesis testing. To facilitate and speed flexible MR-based hypothesis testing, we developed MutRank, an R Shiny web-application for coexpression analyses. MutRank provides an intuitive graphical user interface with multiple customizable features that integrates user-provided data and supporting information suitable for personal computers. Tabular and graphical outputs facilitate the rapid analyses of both unbiased and user-defined coexpression results that accelerate gene function predictions. We highlight the recent utility of MR analyses for functional predictions and discoveries in defining two maize terpenoid antibiotic pathways. Beyond applications in biosynthetic pathway discovery, MutRank provides a simple, customizable and user-friendly interface to enable coexpression analyses relating to a breadth of plant biology inquiries. Data and code are available at GitHub: https://github.com/eporetsky/MutRank.

Genetic elucidation of interconnected antibiotic pathways mediating maize innate immunity.

Specialized metabolites constitute key layers of immunity that underlie disease resistance in crops; however, challenges in resolving pathways limit our understanding of the functions and applications of these metabolites. In maize (Zea mays), the inducible accumulation of acidic terpenoids is increasingly considered to be a defence mechanism that contributes to disease resistance. Here, to understand maize antibiotic biosynthesis, we integrated association mapping, pan-genome multi-omic correlations, enzyme structure-function studies and targeted mutagenesis. We define ten genes in three zealexin (Zx) gene clusters that encode four sesquiterpene synthases and six cytochrome P450 proteins that collectively drive the production of diverse antibiotic cocktails. Quadruple mutants in which the ability to produce zealexins (ZXs) is blocked exhibit a broad-spectrum loss of disease resistance. Genetic redundancies ensuring pathway resiliency to single null mutations are combined with enzyme substrate promiscuity, creating a biosynthetic hourglass pathway that uses diverse substrates and in vivo combinatorial chemistry to yield complex antibiotic blends. The elucidated genetic basis of biochemical phenotypes that underlie disease resistance demonstrates a predominant maize defence pathway and informs innovative strategies for transferring chemical immunity between crops.

Differential activities of maize plant elicitor peptides as mediators of immune signaling and herbivore resistance.

Plant elicitor peptides (Peps) are conserved regulators of defense responses and models for the study of damage-associated molecular pattern-induced immunity. Although present as multigene families in most species, the functional relevance of these multigene families remains largely undefined. While Arabidopsis Peps appear largely redundant in function, previous work examining Pep-induced responses in maize (Zm) implied specificity of function. To better define the function of individual ZmPeps and their cognate receptors (ZmPEPRs), activities were examined by assessing changes in defense-associated phytohormones, specialized metabolites and global gene expression patterns, in combination with heterologous expression assays and analyses of CRISPR/Cas9-generated knockout plants. Beyond simply delineating individual ZmPep and ZmPEPR activities, these experiments led to a number of new insights into Pep signaling mechanisms. ZmPROPEP and other poaceous precursors were found to contain multiple active Peps, a phenomenon not previously observed for this family. In all, seven new ZmPeps were identified and the peptides were found to have specific activities defined by the relative magnitude of their response output rather than by uniqueness. A striking correlation was observed between individual ZmPep-elicited changes in levels of jasmonic acid and ethylene and the magnitude of induced defense responses, indicating that ZmPeps may collectively regulate immune output through rheostat-like tuning of phytohormone levels. Peptide structure-function studies and ligand-receptor modeling revealed structural features critical to the function of ZmPeps and led to the identification of ZmPep5a as a potential antagonist peptide able to competitively inhibit the activity of other ZmPeps, a regulatory mechanism not previously observed for this family.

Dynamic regulation of Pep-induced immunity through post-translational control of defence transcript splicing.

The survival of all living organisms requires the ability to detect attacks and swiftly counter them with protective immune responses. Despite considerable mechanistic advances, the interconnectivity of signalling modules often remains unclear. A newly characterized protein, IMMUNOREGULATORY RNA-BINDING PROTEIN (IRR), negatively regulates immune responses in both maize and Arabidopsis, with disrupted function resulting in enhanced disease resistance. IRR associates with and promotes canonical splicing of transcripts encoding defence signalling proteins, including the key negative regulator of pattern-recognition receptor signalling complexes, CALCIUM-DEPENDENT PROTEIN KINASE 28 (CPK28). On immune activation by Plant Elicitor Peptides (Peps), IRR is dephosphorylated, disrupting interaction with CPK28 transcripts and resulting in the accumulation of an alternative splice variant encoding a truncated CPK28 protein with impaired kinase activity and diminished function as a negative regulator. We demonstrate a new mechanism linking Pep-induced post-translational modification of IRR with post-transcriptionally mediated attenuation of CPK28 function to dynamically amplify Pep signalling and immune output.

Multiple genes recruited from hormone pathways partition maize diterpenoid defences.

Duplication and divergence of primary pathway genes underlie the evolution of plant specialized metabolism; however, mechanisms partitioning parallel hormone and defence pathways are often speculative. For example, the primary pathway intermediate ent-kaurene is essential for gibberellin biosynthesis and is also a proposed precursor for maize antibiotics. By integrating transcriptional coregulation patterns, genome-wide association studies, combinatorial enzyme assays, proteomics and targeted mutant analyses, we show that maize kauralexin biosynthesis proceeds via the positional isomer ent-isokaurene formed by a diterpene synthase pair recruited from gibberellin metabolism. The oxygenation and subsequent desaturation of ent-isokaurene by three promiscuous cytochrome P450s and a new steroid 5α reductase indirectly yields predominant ent-kaurene-associated antibiotics required for Fusarium stalk rot resistance. The divergence and differential expression of pathway branches derived from multiple duplicated hormone-metabolic genes minimizes dysregulation of primary metabolism via the circuitous biosynthesis of ent-kaurene-related antibiotics without the production of growth hormone precursors during defence.

Calcium specificity signaling mechanisms in abscisic acid signal transduction in Arabidopsis guard cells.

A central question is how specificity in cellular responses to the eukaryotic second messenger Ca(2+) is achieved. Plant guard cells, that form stomatal pores for gas exchange, provide a powerful system for in depth investigation of Ca(2+)-signaling specificity in plants. In intact guard cells, abscisic acid (ABA) enhances (primes) the Ca(2+)-sensitivity of downstream signaling events that result in activation of S-type anion channels during stomatal closure, providing a specificity mechanism in Ca(2+)-signaling. However, the underlying genetic and biochemical mechanisms remain unknown. Here we show impairment of ABA signal transduction in stomata of calcium-dependent protein kinase quadruple mutant plants. Interestingly, protein phosphatase 2Cs prevent non-specific Ca(2+)-signaling. Moreover, we demonstrate an unexpected interdependence of the Ca(2+)-dependent and Ca(2+)-independent ABA-signaling branches and the in planta requirement of simultaneous phosphorylation at two key phosphorylation sites in SLAC1. We identify novel mechanisms ensuring specificity and robustness within stomatal Ca(2+)-signaling on a cellular, genetic, and biochemical level.