Integration of omic networks in a developmental atlas of maize

The Zea mays PeptideAtlas: A New Maize Community Resource

This study presents the Maize PeptideAtlas resource (www.peptideatlas.org/builds/maize) to help solve questions about the maize proteome. Publicly available raw tandem mass spectrometry (MS/MS) data for maize collected from ProteomeXchange were reanalyzed through a uniform processing and metadata annotation pipeline. These data are from a wide range of genetic backgrounds and many sample types and experimental conditions. The protein search space included different maize genome annotations for the B73 inbred line from MaizeGDB, UniProtKB, NCBI RefSeq, and for the W22 inbred line. 445 million MS/MS spectra were searched, of which 120 million were matched to 0.37 million distinct peptides. Peptides were matched to 66.2% of proteins in the most recent B73 nuclear genome annotation. Furthermore, most conserved plastid- and mitochondrial-encoded proteins (NCBI RefSeq annotations) were identified. Peptides and proteins identified in the other B73 genome annotations will improve maize genome annotation. We also illustrate the high-confidence detection of unique W22 proteins. N-terminal acetylation, phosphorylation, ubiquitination, and three lysine acylations (K-acetyl, K-malonyl, and K-hydroxyisobutyryl) were identified and can be inspected through a PTM viewer in PeptideAtlas. All matched MS/MS-derived peptide data are linked to spectral, technical, and biological metadata. This new PeptideAtlas is integrated in MaizeGDB with a peptide track in JBrowse.

Genome-Wide Identification and Analysis of Maize DnaJ Family Genes in Response to Salt, Heat, and Cold at the Seedling Stage

DnaJ proteins, also known as HSP40s, play a key role in plant growth and development, and response to environmental stress. However, little comprehensive research has been conducted on the DnaJ gene family in maize. Here, we identify 91 ZmDnaJ genes from maize, which are likely distributed in the chloroplast, nucleus, and cytoplasm. Our analysis revealed that ZmDnaJs were classified into three types, with conserved protein motifs and gene structures within the same type, particularly among members of the same subfamily. Gene duplication events have likely contributed to the expansion of the ZmDnaJ family in maize. Analysis of cis-regulatory elements in ZmDnaJ promoters suggested involvement in stress responses, growth and development, and phytohormone sensitivity in maize. Specifically, four cis-acting regulatory elements associated with stress responses and phytohormone regulation indicated a role in adaptation. RNA-seq analysis showed constitutive expression of most ZmDnaJ genes, some specifically in pollen and endosperm. More importantly, certain genes also responded to salt, heat, and cold stresses, indicating potential interaction between stress regulatory networks. Furthermore, early responses to heat stress varied among five inbred lines, with upregulation of almost tested ZmDnaJ genes in B73 and B104 after 6 h, and fewer genes upregulated in QB1314, MD108, and Zheng58. After 72 h, most ZmDnaJ genes in the heat-sensitive inbred lines (B73 and B104) returned to normal levels, while many genes, including ZmDnaJ55, 79, 88, 90, and 91, remained upregulated in the heat-tolerant inbred lines (QB1314, MD108, and Zheng58) suggesting a synergistic function for prolonged protection against heat stress. In conclusion, our study provides a comprehensive analysis of the ZmDnaJ family in maize and demonstrates a correlation between heat stress tolerance and the regulation of gene expression within this family. These offer a theoretical basis for future functional validation of these genes.

COI1 F-box proteins regulate DELLA protein levels, growth, and photosynthetic efficiency in maize

The F-box protein Coronatine Insensitive (COI) is a receptor for the jasmonic acid signaling pathway in plants. To investigate the functions of the 6 maize (Zea mays) COI proteins (COI1a, COI1b, COI1c, COI1d, COI2a, and COI2b), we generated single, double, and quadruple loss-of-function mutants. The pollen of the coi2a coi2b double mutant was inviable. The coi1 quadruple mutant (coi1-4x) exhibited shorter internodes, decreased photosynthesis, leaf discoloration, microelement deficiencies, and accumulation of DWARF8 and/or DWARF9, 2 DELLA family proteins that repress the gibberellic acid (GA) signaling pathway. Coexpression of COI and DELLA in Nicotiana benthamiana showed that the COI proteins trigger proteasome-dependent DELLA degradation. Many genes that are downregulated in the coi1-4x mutant are GA-inducible. In addition, most of the proteins encoded by the downregulated genes are predicted to be bundle sheath- or mesophyll-enriched, including those encoding C4-specific photosynthetic enzymes. Heterologous expression of maize Coi genes in N. benthamiana showed that COI2a is nucleus-localized and interacts with maize jasmonate zinc-finger inflorescence meristem domain (JAZ) proteins, the canonical COI repressor partners. However, maize COI1a and COI1c showed only partial nuclear localization and reduced binding efficiency to the tested JAZ proteins. Together, these results show the divergent functions of the 6 COI proteins in regulating maize growth and defense pathways.

Genome-wide characterization and expression profiling of FARL (FHY3/FAR1) family genes in Zea mays

A significant role of the plant is played by the transcription factor FARL, which is light signal transduction as well as plant growth and development. Despite being transposases, FARL has developed a variety of dominant biological actions in evolution and speciation. On the other hand, little is known about the Zea mays FARL protein family. This study identifies and characterizes fifteen ZmFARL genes genome-wide, and RNA sequencing data was used to profile their expression. 105 FARL proteins from five plant species were classified into five groups based on sequence alignment and phylogeny. The ZmFARL genes' exon-intron and motif distribution were conserved based on their evolutionary group. The fifteen ZmFARL genes were distributed over seven of the ten Z. mays chromosomes, although no duplication was discovered. Cis-element analysis reveals that ZmFARL genes play a variety of activities, including tissue-specific, stress- and hormone-responsive expressions. Furthermore, the results of the RNA sequencing used to profile expression showed that the genes ZmFARL2 and ZmFARL5 were much more expressed than other genes in various tissues, particularly in leaf characteristics. The identification of likely genes involved in cellular activity in Z. mays and related species will be aided by the characterization of the FARL genes.

Teosinte Pollen Drive guides maize diversification and domestication by RNAi

Selfish genetic elements contribute to hybrid incompatibility and bias or 'drive' their own transmission1,2. Chromosomal drive typically functions in asymmetric female meiosis, whereas gene drive is normally post-meiotic and typically found in males. Here, using single-molecule and single-pollen genome sequencing, we describe Teosinte Pollen Drive, an instance of gene drive in hybrids between maize (Zea mays ssp. mays) and teosinte mexicana (Z. mays ssp. mexicana) that depends on RNA interference (RNAi). 22-nucleotide small RNAs from a non-coding RNA hairpin in mexicana depend on Dicer-like 2 (Dcl2) and target Teosinte Drive Responder 1 (Tdr1), which encodes a lipase required for pollen viability. Dcl2, Tdr1 and the hairpin are in tight pseudolinkage on chromosome 5, but only when transmitted through the male. Introgression of mexicana into early cultivated maize is thought to have been critical to its geographical dispersal throughout the Americas3, and a tightly linked inversion in mexicana spans a major domestication sweep in modern maize4. A survey of maize traditional varieties and sympatric populations of teosinte mexicana reveals correlated patterns of admixture among unlinked genes required for RNAi on at least four chromosomes that are also subject to gene drive in pollen from synthetic hybrids. Teosinte Pollen Drive probably had a major role in maize domestication and diversification, and offers an explanation for the widespread abundance of 'self' small RNAs in the germ lines of plants and animals.

Data-driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well-studied major crops. Using 727 maize (Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre- and postanthesis maximum temperature, mid-season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well-studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Insights into maydis leaf blight resistance in maize: a comprehensive genome-wide association study in sub-tropics of India

BACKGROUND

In the face of contemporary climatic vulnerabilities and escalating global temperatures, the prevalence of maydis leaf blight (MLB) poses a potential threat to maize production. This study endeavours to discern marker-trait associations and elucidate the candidate genes that underlie resistance to MLB in maize by employing a diverse panel comprising 336 lines. The panel was screening for MLB across four environments, employing standard artificial inoculation techniques. Genome-wide association studies (GWAS) and haplotype analysis were conducted utilizing a total of 128,490 SNPs obtained from genotyping-by-sequencing (GBS).

RESULTS

GWAS identified 26 highly significant SNPs associated with MLB resistance, among the markers examined. Seven of these SNPs, reported in novel chromosomal bins (9.06, 5.01, 9.01, 7.04, 4.06, 1.04, and 6.05) were associated with genes: bzip23, NAGS1, CDPK7, aspartic proteinase NEP-2, VQ4, and Wun1, which were characterized for their roles in diminishing fungal activity, fortifying defence mechanisms against necrotrophic pathogens, modulating phyto-hormone signalling, and orchestrating oxidative burst responses. Gene mining approach identified 22 potential candidate genes associated with SNPs due to their functional relevance to resistance against necrotrophic pathogens. Notably, bin 8.06, which hosts five SNPs, showed a connection to defense-regulating genes against MLB, indicating the potential formation of a functional gene cluster that triggers a cascade of reactions against MLB. In silico studies revealed gene expression levels exceeding ten fragments per kilobase million (FPKM) for most genes and demonstrated coexpression among all candidate genes in the coexpression network. Haplotype regression analysis revealed the association of 13 common significant haplotypes at Bonferroni ≤ 0.05. The phenotypic variance explained by these significant haplotypes ranged from low to moderate, suggesting a breeding strategy that combines multiple resistance alleles to enhance resistance to MLB. Additionally, one particular haplotype block (Hap_8.3) was found to consist of two SNPs (S8_152715134, S8_152460815) identified in GWAS with 9.45% variation explained (PVE).

CONCLUSION

The identified SNPs/ haplotypes associated with the trait of interest contribute to the enrichment of allelic diversity and hold direct applicability in Genomics Assisted Breeding for enhancing MLB resistance in maize.

Engineering the future cereal crops with big biological data: toward intelligence-driven breeding by design

How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades, especially under an unpredicted climate change. Crop breeding, initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding, has played a critical role in securing the global food supply. However, regarding the changing environment and ever-increasing human population, can we breed outstanding crop varieties fast enough to achieve high productivity, good quality, and widespread adaptability? This review outlines the recent achievements in understanding cereal crop breeding, including the current knowledge about crop agronomic traits, newly developed techniques, crop big biological data research, and the possibility of integrating them for intelligence-driven breeding by design, which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops. This review focuses on the major cereal crops, including rice, maize, and wheat, to explain how intelligence-driven breeding by design is becoming a reality.

Prioritizing Maize Metabolic Gene Regulators through Multi-Omic Network Integration

Elucidating gene regulatory networks is a major area of study within plant systems biology. Phenotypic traits are intricately linked to specific gene expression profiles. These expression patterns arise primarily from regulatory connections between sets of transcription factors (TFs) and their target genes. Here, we integrated 46 co-expression networks, 283 protein-DNA interaction (PDI) assays, and 16 million SNPs used to identify expression quantitative trait loci (eQTL) to construct TF-target networks. In total, we analyzed ∼4.6M interactions to generate four distinct types of TF-target networks: co-expression, PDI, trans -eQTL, and cis -eQTL combined with PDIs. To functionally annotate TFs based on their target genes, we implemented three different network integration strategies. We evaluated the effectiveness of each strategy through TF loss-of function mutant inspection and random network analyses. The multi-network integration allowed us to identify transcriptional regulators of several biological processes. Using the topological properties of the fully integrated network, we identified potential functionally redundant TF paralogs. Our findings retrieved functions previously documented for numerous TFs and revealed novel functions that are crucial for informing the design of future experiments. The approach here-described lays the foundation for the integration of multi-omic datasets in maize and other plant systems.

GRAPHICAL ABSTRACT

A foundational large language model for edible plant genomes

Significant progress has been made in the field of plant genomics, as demonstrated by the increased use of high-throughput methodologies that enable the characterization of multiple genome-wide molecular phenotypes. These findings have provided valuable insights into plant traits and their underlying genetic mechanisms, particularly in model plant species. Nonetheless, effectively leveraging them to make accurate predictions represents a critical step in crop genomic improvement. We present AgroNT, a foundational large language model trained on genomes from 48 plant species with a predominant focus on crop species. We show that AgroNT can obtain state-of-the-art predictions for regulatory annotations, promoter/terminator strength, tissue-specific gene expression, and prioritize functional variants. We conduct a large-scale in silico saturation mutagenesis analysis on cassava to evaluate the regulatory impact of over 10 million mutations and provide their predicted effects as a resource for variant characterization. Finally, we propose the use of the diverse datasets compiled here as the Plants Genomic Benchmark (PGB), providing a comprehensive benchmark for deep learning-based methods in plant genomic research. The pre-trained AgroNT model is publicly available on HuggingFace at https://huggingface.co/InstaDeepAI/agro-nucleotide-transformer-1b  for future research purposes.

MTP family analysis and association study reveal the role of ZmMTP11 in lead (Pb) accumulation

The metal tolerance protein (MTP) gene family plays an essential role in the transport of heavy metals, however the function of the MTP family in transporting lead (Pb) was still unclear in plants. In this study, we identified and characterized 12 ZmMTPs in the whole genome of maize. These ZmMTP genes were divided into three subfamilies in evolution, namely Zn-CDF, Zn/Fe-CDF, Mn-CDF subfamilies, which showed diverse expression patterns in different tissues of maize. Using gene-based association analyses, we identified a Pb accumulation-related MTP member in maize, ZmMTP11, which was located in plasma membrane and had the potential of transporting Pb ion. Under the Pb treatment, ZmMTP11 showed a generally decreased expression relative to the normal conditions. Heterologous expressions of ZmMTP11 in yeast, Arabidopsis, and rice demonstrated that ZmMTP11 enhanced Pb accumulation in the cells without affecting yeast and plant growth under Pb stress. Remarkably, the increased Pb concentration in the plant roots did not cause changes in Pb content in the shoots. Our study provides new insights into the genetic improvement of heavy metal tolerance in plants and contributes to bioremediation of Pb-contaminant soils.

Comprehensive identification and expression analysis of FAR1/FHY3 genes under drought stress in maize (Zea mays L.)

Background

FAR1/FHY3 transcription factors are derived from transposase, which play important roles in light signal transduction, growth and development, and response to stress by regulating downstream gene expression. Although many FAR1/FHY3 members have been identified in various species, the FAR1/FHY3 genes in maize are not well characterized and their function in drought are unknown.

Method

The FAR1/FHY3 family in the maize genome was identified using PlantTFDB, Pfam, Smart, and NCBI-CDD websites. In order to investigate the evolution and functions of FAR1 genes in maize, the information of protein sequences, chromosome localization, subcellular localization, conserved motifs, evolutionary relationships and tissue expression patterns were analyzed by bioinformatics, and the expression patterns under drought stress were detected by quantitative real-time polymerase chain reaction (qRT-PCR).

Results

A total of 24 ZmFAR members in maize genome, which can be divided into five subfamilies, with large differences in protein and gene structures among subfamilies. The promoter regions of ZmFARs contain abundant abiotic stress-responsive and hormone-respovensive cis-elements. Among them, drought-responsive cis-elements are quite abundant. ZmFARs were expressed in all tissues detected, but the expression level varies widely. The expression of ZmFARs were mostly down-regulated in primary roots, seminal roots, lateral roots, and mesocotyls under water deficit. Most ZmFARs were down-regulated in root after PEG-simulated drought stress.

Conclusions

We performed a genome-wide and systematic identification of FAR1/FHY3 genes in maize. And most ZmFARs were down-regulated in root after drought stress. These results indicate that FAR1/FHY3 transcription factors have important roles in drought stress response, which can lay a foundation for further analysis of the functions of ZmFARs in response to drought stress.

Single-cell proteomics differentiates Arabidopsis root cell types

Single-cell proteomics (SCP) is an emerging approach to resolve cellular heterogeneity within complex tissues of multi-cellular organisms. Here, we demonstrate the feasibility of SCP on plant samples using the model plant Arabidopsis thaliana. Specifically, we focused on examining isolated single cells from the cortex and endodermis, which are two adjacent root cell types derived from a common stem cell lineage. From 756 root cells, we identified 3763 proteins and 1118 proteins/cell. Ultimately, we focus on 3217 proteins quantified following stringent filtering. Of these, we identified 596 proteins whose expression is enriched in either the cortex or endodermis and are able to differentiate these closely related plant cell types. Collectivity, this study demonstrates that SCP can resolve neighboring cell types with distinct functions, thereby facilitating the identification of biomarkers and candidate proteins to enable functional genomics.

Structural variants contribute to phenotypic variation in maize

Comprehensively identifying the loci shaping trait variation has been challenging, in part because standard approaches often miss many types of genetic variants. Structural variants, especially transposable elements are likely to affect phenotypic variation but we need better methods in maize for detecting polymorphic structural variants and TEs using short-read sequencing data. Here, we used a whole genome alignment between two maize genotypes to identify polymorphic structural variants and then genotyped a large maize diversity panel for these variants using short-read sequencing data. We characterized variation of SVs within the panel and identified SV polymorphisms that are associated with life history traits and genotype-by-environment interactions. While most of the SVs associated with traits contained TEs, only one of the SV's boundaries clearly matched TE breakpoints indicative of a TE insertion, whereas the other polymorphisms were likely caused by deletions. All of the SVs associated with traits were in linkage disequilibrium with nearby single nucleotide polymorphisms (SNPs), suggesting that this method did not identify variants that would have been missed in a SNP association study.

ZmNF-YA1 Contributes to Maize Thermotolerance by Regulating Heat Shock Response

Zea mays (maize) is a staple food, feed, and industrial crop. Heat stress is one of the major stresses affecting maize production and is usually accompanied by other stresses, such as drought. Our previous study identified a heterotrimer complex, ZmNF-YA1-YB16-YC17, in maize. ZmNF-YA1 and ZmNF-YB16 were positive regulators of the drought stress response and were involved in maize root development. In this study, we investigated whether ZmNF-YA1 confers heat stress tolerance in maize. The nf-ya1 mutant and overexpression lines were used to test the role of ZmNF-YA1 in maize thermotolerance. The nf-ya1 mutant was more temperature-sensitive than the wild-type (WT), while the ZmNF-YA1 overexpression lines showed a thermotolerant phenotype. Higher malondialdehyde (MDA) content and reactive oxygen species (ROS) accumulation were observed in the mutant, followed by WT and overexpression lines after heat stress treatment, while an opposite trend was observed for chlorophyll content. RNA-seq was used to analyze transcriptome changes in nf-ya1 and its wild-type control W22 in response to heat stress. Based on their expression profiles, the heat stress response-related differentially expressed genes (DEGs) in nf-ya1 compared to WT were grouped into seven clusters via k-means clustering. Gene Ontology (GO) enrichment analysis of the DEGs in different clades was performed to elucidate the roles of ZmNF-YA1-mediated transcriptional regulation and their contribution to maize thermotolerance. The loss function of ZmNF-YA1 led to the failure induction of DEGs in GO terms of protein refolding, protein stabilization, and GO terms for various stress responses. Thus, the contribution of ZmNF-YA1 to protein stabilization, refolding, and regulation of abscisic acid (ABA), ROS, and heat/temperature signaling may be the major reason why ZmNF-YA1 overexpression enhanced heat tolerance, and the mutant showed a heat-sensitive phenotype.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Dual-Model GWAS Analysis and Genomic Selection of Maize Flowering Time-Related Traits

An appropriate flowering period is an important selection criterion in maize breeding. It plays a crucial role in the ecological adaptability of maize varieties. To explore the genetic basis of flowering time, GWAS and GS analyses were conducted using an associating panel consisting of 379 multi-parent DH lines. The DH population was phenotyped for days to tasseling (DTT), days to pollen-shedding (DTP), and days to silking (DTS) in different environments. The heritability was 82.75%, 86.09%, and 85.26% for DTT, DTP, and DTS, respectively. The GWAS analysis with the FarmCPU model identified 10 single-nucleotide polymorphisms (SNPs) distributed on chromosomes 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. The GWAS analysis with the BLINK model identified seven SNPs distributed on chromosomes 1, 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. Three SNPs 3_198946071, 9_146646966, and 9_152140631 showed a pleiotropic effect, indicating a significant genetic correlation between DTT, DTP, and DTS. A total of 24 candidate genes were detected. A relatively high prediction accuracy was achieved with 100 significantly associated SNPs detected from GWAS, and the optimal training population size was 70%. This study provides a better understanding of the genetic architecture of flowering time-related traits and provides an optimal strategy for GS.

Factors specifying sex determination in maize

Plant architecture is an important feature for agronomic performance in crops. In maize, which is a monoecious plant, separation of floral organs to produce specific gametes has been studied from different perspectives including genetic, biochemical and physiological. Maize mutants affected in floral organ development have been key to identifying genes, hormones and other factors like miRNAs important for sex determination. In this review, we describe floral organ formation in maize, representative mutants and genes identified with a function in establishing sexual identity either classified as feminizing or masculinizing, and its relationship with hormones associated with sexual organ identity as jasmonic acid, brassinosteroid and gibberellin. Finally, we discuss the challenges and scopes of future research in maize sex determination.

Perfluorobutanoic acid triggers metabolic and transcriptional reprogramming in wheat seedlings

The environmental risks of fluorinated alternatives are of great concern with the phasing out of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate. Here, multi-omics (i.e., metabolomics and transcriptomics) coupled with physiological and biochemical analyses were employed to investigate the stress responses of wheat seedings (Triticum aestivum L.) to perfluorobutanoic acid (PFBA), one of the short-chain per- and polyfluoroalkyl substances (PFAS) and PFOA alternatives, at environmentally relevant concentrations (0.1-100 ng/g). After 28 days of soil exposure, PFBA boosted the generation of OH and O2- in wheat seedlings, resulting in lipid peroxidation, protein perturbation and impaired photosynthesis. Non-enzymatic antioxidant defense systems (e.g., glutathione, phenolics, and vitamin C) and enzymatic antioxidant copper/zinc superoxide dismutase were strikingly activated (p < 0.05). PFBA-triggered oxidative stress induced metabolic and transcriptional reprogramming, including carbon and nitrogen metabolisms, lipid metabolisms, immune responses, signal transduction processes, and antioxidant defense-related pathways. Down-regulation of genes related to plant-pathogen interaction suggested suppression of the immune-response, offering a novel understanding on the production of reactive oxygen species in plants under the exposure to PFAS. The identified MAPK signaling pathway illuminated a novel signal transduction mechanism in plant cells in response to PFAS. These findings provide comprehensive understandings on the phytotoxicity of PFBA to wheat seedlings and new insights into the impacts of PFAS on plants.

Establishing an optimized ATAC-seq protocol for the maize

The advent of next-generation sequencing in crop improvement offers unprecedented insights into the chromatin landscape closely linked to gene activity governing key traits in plant development and adaptation. Particularly in maize, its dynamic chromatin structure is found to collaborate with massive transcriptional variations across tissues and developmental stages, implying intricate regulatory mechanisms, which highlights the importance of integrating chromatin information into breeding strategies for precise gene controls. The depiction of maize chromatin architecture using Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) provides great opportunities to investigate cis-regulatory elements, which is crucial for crop improvement. In this context, we developed an easy-to-implement ATAC-seq protocol for maize with fewer nuclei and simple equipment. We demonstrate a streamlined ATAC-seq protocol with four key steps for maize in which nuclei purification can be achieved without cell sorting and using only a standard bench-top centrifuge. Our protocol, coupled with the bioinformatic analysis, including validation by read length periodicity, key metrics, and correlation with transcript abundance, provides a precise and efficient assessment of the maize chromatin landscape. Beyond its application to maize, our testing design holds the potential to be applied to other crops or other tissues, especially for those with limited size and amount, establishing a robust foundation for chromatin structure studies in diverse crop species.

ZmPILS6 is an auxin efflux carrier required for maize root morphogenesis

Plant root systems play a pivotal role in plant physiology and exhibit diverse phenotypic traits. Understanding the genetic mechanisms governing root growth and development in model plants like maize is crucial for enhancing crop resilience to drought and nutrient limitations. This study focused on identifying and characterizing ZmPILS6, an annotated auxin efflux carrier, as a key regulator of various crown root traits in maize. ZmPILS6-modified roots displayed reduced network area and suppressed lateral root formation, which are desirable traits for the "steep, cheap, and deep" ideotype. The research revealed that ZmPILS6 localizes to the endoplasmic reticulum and plays a vital role in controlling the spatial distribution of indole-3-acetic acid (IAA or "auxin") in primary roots. The study also demonstrated that ZmPILS6 can actively efflux IAA when expressed in yeast. Furthermore, the loss of ZmPILS6 resulted in significant proteome remodeling in maize roots, particularly affecting hormone signaling pathways. To identify potential interacting partners of ZmPILS6, a weighted gene coexpression analysis was performed. Altogether, this research contributes to the growing knowledge of essential genetic determinants governing maize root morphogenesis, which is crucial for guiding agricultural improvement strategies.

Dissection of Common Rust Resistance in Tropical Maize Multiparent Population through GWAS and Linkage Studies

Common rust (CR), caused by Puccina sorghi, is a major foliar disease in maize that leads to quality deterioration and yield losses. To dissect the genetic architecture of CR resistance in maize, this study utilized the susceptible temperate inbred line Ye107 as the male parent crossed with three resistant tropical maize inbred lines (CML312, D39, and Y32) to generate 627 F7 recombinant inbred lines (RILs), with the aim of identifying maize disease-resistant loci and candidate genes for common rust. Phenotypic data showed good segregation between resistance and susceptibility, with varying degrees of resistance observed across different subpopulations. Significant genotype effects and genotype × environment interactions were observed, with heritability ranging from 85.7% to 92.2%. Linkage and genome-wide association analyses across the three environments identified 20 QTLs and 62 significant SNPs. Among these, seven major QTLs explained 66% of the phenotypic variance. Comparison with six SNPs repeatedly identified across different environments revealed overlap between qRUST3-3 and Snp-203,116,453, and Snp-204,202,469. Haplotype analysis indicated two different haplotypes for CR resistance for both the SNPs. Based on LD decay plots, three co-located candidate genes, Zm00001d043536, Zm00001d043566, and Zm00001d043569, were identified within 20 kb upstream and downstream of these two SNPs. Zm00001d043536 regulates hormone regulation, Zm00001d043566 controls stomatal opening and closure, related to trichome, and Zm00001d043569 is associated with plant disease immune responses. Additionally, we performed candidate gene screening for five additional SNPs that were repeatedly detected across different environments, resulting in the identification of five candidate genes. These findings contribute to the development of genetic resources for common rust resistance in maize breeding programs.

Multiomics unravels potential molecular switches in the C3 to CAM transition of Mesembryanthemum crystallinum

Mesembryanthemum crystallinum (common ice plant), a facultative CAM plant, shifts from C3 to CAM photosynthesis under salt stress, enhancing water use efficiency. Here we used transcriptomics, proteomics, and targeted metabolomics to profile molecular changes during the diel cycle of C3 to CAM transition. The results confirmed expected changes associated with CAM photosynthesis, starch biosynthesis and degradation, and glycolysis/gluconeogenesis. Importantly, they yielded new discoveries: 1) Transcripts displayed greater circadian regulation than proteins. 2) Oxidative phosphorylation and inositol methylation may play important roles in initiating the transition. 3) V-type H+-ATPases showed consistent transcriptional regulation, aiding in vacuolar malate uptake. 4) A protein phosphatase 2C, a major component in the ABA signaling pathway, may trigger the C3 to CAM transition. Our work highlights the potential molecular switches in the C3 to CAM transition, including the potential role of ABA signaling. SIGNIFICANCE: The common ice plant is a model facultative CAM plant, and under stress conditions it can shift from C3 to CAM photosynthesis within a three-day period. However, knowledge about the molecular changes during the transition and the molecular switches enabling the transition is lacking. Multi-omic analyses not only revealed the molecular changes during the transition, but also highlighted the importance of ABA signaling, inositol methylation, V-type H+-ATPase in initiating the shift. The findings may explain physiological changes and nocturnal stomatal opening, and inform future synthetic biology effort in improving crop water use efficiency and stress resilience.

Genome-wide expression quantitative trait locus analysis reveals silk-preferential gene regulatory network in maize

Silk of maize (Zea mays L.) contains diverse metabolites with complicated structures and functions, making it a great challenge to explore the mechanisms of metabolic regulation. Genome-wide identification of silk-preferential genes and investigation of their expression regulation provide an opportunity to reveal the regulatory networks of metabolism. Here, we applied the expression quantitative trait locus (eQTL) mapping on a maize natural population to explore the regulation of gene expression in unpollinated silk of maize. We obtained 3,985 silk-preferential genes that were specifically or preferentially expressed in silk using our population. Silk-preferential genes showed more obvious expression variations compared with broadly expressed genes that were ubiquitously expressed in most tissues. We found that trans-eQTL regulation played a more important role for silk-preferential genes compared to the broadly expressed genes. The relationship between 38 transcription factors and 85 target genes, including silk-preferential genes, were detected. Finally, we constructed a transcriptional regulatory network around the silk-preferential gene Bx10, which was proposed to be associated with response to abiotic stress and biotic stress. Taken together, this study deepened our understanding of transcriptome variation in maize silk and the expression regulation of silk-preferential genes, enhancing the investigation of regulatory networks on metabolic pathways.

Should I stay or should I go? Trafficking of plant extra-nuclear transcription factors

At the heart of all biological processes lies the control of nuclear gene expression, which is primarily achieved through the action of transcription factors (TFs) that generally contain a nuclear localization signal (NLS) to facilitate their transport into the nucleus. However, some TFs reside in the cytoplasm in a transcriptionally inactive state and only enter the nucleus in response to specific signals, which in plants include biotic or abiotic stresses. These extra-nuclear TFs can be found in the cytosol or associated with various membrane systems, including the endoplasmic reticulum and plasma membrane. They may be integral proteins with transmembrane domains or associate peripherally with the lipid bilayer via acylation or membrane-binding domains. Although over 30 plant TFs, most of them involved in stress responses, have been experimentally shown to reside outside the nucleus, computational predictions suggest that this number is much larger. Understanding how extra-nuclear TFs are trafficked into the nucleus is essential for reconstructing transcriptional regulatory networks that govern major cellular pathways in response to biotic and abiotic signals. Here, we provide a perspective on what is known on plant extranuclear-nuclear TF retention, nuclear trafficking, and the post-translational modifications that ultimately enable them to regulate gene expression upon entering the nucleus.

Genome-wide investigation of the LARP gene family: focus on functional identification and transcriptome profiling of ZmLARP6c1 in maize pollen

BACKGROUND

The La-related proteins (LARPs) are a superfamily of RNA-binding proteins associated with regulation of gene expression. Evidence points to an important role for post-transcriptional control of gene expression in germinating pollen tubes, which could be aided by RNA-binding proteins.

RESULTS

In this study, a genome-wide investigation of the LARP proteins in eight plant species was performed. The LARP proteins were classified into three families based on a phylogenetic analysis. The gene structure, conserved motifs, cis-acting elements in the promoter, and gene expression profiles were investigated to provide a comprehensive overview of the evolutionary history and potential functions of ZmLARP genes in maize. Moreover, ZmLARP6c1 was specifically expressed in pollen and ZmLARP6c1 was localized to the nucleus and cytoplasm in maize protoplasts. Overexpression of ZmLARP6c1 enhanced the percentage pollen germination compared with that of wild-type pollen. In addition, transcriptome profiling analysis revealed that differentially expressed genes included PABP homologous genes and genes involved in jasmonic acid and abscisic acid biosynthesis, metabolism, signaling pathways and response in a Zmlarp6c1::Ds mutant and ZmLARP6c1-overexpression line compared with the corresponding wild type.

CONCLUSIONS

The findings provide a basis for further evolutionary and functional analyses, and provide insight into the critical regulatory function of ZmLARP6c1 in maize pollen germination.

Sugar transporters spatially organize microbiota colonization along the longitudinal root axis of Arabidopsis

Plant roots are functionally heterogeneous in cellular architecture, transcriptome profile, metabolic state, and microbial immunity. We hypothesized that axial differentiation may also impact spatial colonization by root microbiota along the root axis. We developed two growth systems, ArtSoil and CD-Rhizotron, to grow and then dissect Arabidopsis thaliana roots into three segments. We demonstrate that distinct endospheric and rhizosphere bacterial communities colonize the segments, supporting the hypothesis of microbiota differentiation along the axis. Root metabolite profiling of each segment reveals differential metabolite enrichment and specificity. Bioinformatic analyses and GUS histochemistry indicate microbe-induced accumulation of SWEET2, 4, and 12 sugar uniporters. Profiling of root segments from sweet mutants shows altered spatial metabolic profiles and reorganization of endospheric root microbiota. This work reveals the interdependency between root metabolites and microbial colonization and the contribution of SWEETs to spatial diversity and stability of microbial ecosystem.

Maize actin depolymerizing factor 1 (ZmADF1) negatively regulates pollen development

The normal development of pollen grains and the completion of double fertilization in embryos are crucial for both the sexual reproduction of angiosperms and grain production. Actin depolymerizing factor (ADF) regulates growth, development, and responses to biotic and abiotic stress by binding to actin in plants. In this study, the function of the ZmADF1 gene was validated through bioinformatic analysis, subcellular localization, overexpression in maize and Arabidopsis, and knockout via CRISPR/Cas9. The amino acid sequence of ZmADF1 exhibited high conservation and a similar tertiary structure to that of ADF homologs. Subcellular localization analysis revealed that ZmADF1 is localized mainly to the nucleus and cytoplasm. The ZmADF1 gene was specifically expressed in maize pollen, and overexpression of the ZmADF1 gene decreased the number of pollen grains in the anthers of transgenic Arabidopsis plants. The germination rate of pollen and the empty seed shell rate in the fruit pods of the overexpressing plants were significantly greater than those in the wild-type (WT) plants. In maize, the pollen viability of the knockout lines was significantly greater than that of both the WT and the overexpressing lines. Our results confirmed that the ZmADF1 gene was specifically expressed in pollen and negatively regulated pollen quantity, vigor, germination rate, and seed setting rate. This study provides insights into ADF gene function and possible pathways for improving high-yield maize breeding.

The maize PLASTID TERMINAL OXIDASE (PTOX) locus controls the carotenoid content of kernels

Carotenoids perform a broad range of important functions in humans; therefore, carotenoid biofortification of maize (Zea mays L.), one of the most highly produced cereal crops worldwide, would have a global impact on human health. PLASTID TERMINAL OXIDASE (PTOX) genes play an important role in carotenoid metabolism; however, the possible function of PTOX in carotenoid biosynthesis in maize has not yet been explored. In this study, we characterized the maize PTOX locus by forward- and reverse-genetic analyses. While most higher plant species possess a single copy of the PTOX gene, maize carries two tandemly duplicated copies. Characterization of mutants revealed that disruption of either copy resulted in a carotenoid-deficient phenotype. We identified mutations in the PTOX genes as being causal of the classic maize mutant, albescent1. Remarkably, overexpression of ZmPTOX1 significantly improved the content of carotenoids, especially β-carotene (provitamin A), which was increased by ~threefold, in maize kernels. Overall, our study shows that maize PTOX locus plays an important role in carotenoid biosynthesis in maize kernels and suggests that fine-tuning the expression of this gene could improve the nutritional value of cereal grains.

Maize multi-omics reveal leaf water status controlling of differential transcriptomes, proteomes and hormones as mechanisms of age-dependent osmotic stress response in leaves

Drought-induced osmotic stress severely affects the growth and yield of maize. However, the mechanisms underlying the different responses of young and old maize leaves to osmotic stress remain unclear. To gain a systematic understanding of age-related stress responses, we compared osmotic-stress-induced changes in maize leaves of different ages using multi-omics approaches. After short-term osmotic stress, old leaves suffered more severe water deficits than young leaves. The adjustments of transcriptomes, proteomes, and hormones in response to osmotic stress were more dynamic in old leaves. Metabolic activities, stress signaling pathways, and hormones (especially abscisic acid) responded to osmotic stress in an age-dependent manner. We identified multiple functional clusters of genes and proteins with potential roles in stress adaptation. Old leaves significantly accumulated stress proteins such as dehydrin, aquaporin, and chaperones to cope with osmotic stress, accompanied by senescence-like cellular events, whereas young leaves exhibited an effective water conservation strategy mainly by hydrolyzing transitory starch and increasing proline production. The stress responses of individual leaves are primarily determined by their intracellular water status, resulting in differential transcriptomes, proteomes, and hormones. This study extends our understanding of the mechanisms underlying plant responses to osmotic stress.

The BulkECexplorer compiles endothelial bulk transcriptomes to predict functional versus leaky transcription

Transcriptomic data can be mined to understand the molecular activity of cell types. Yet, functional genes may remain undetected in RNA sequencing (RNA-seq) experiments for technical reasons, such as insufficient read depth or gene dropout. Conversely, RNA-seq experiments may detect lowly expressed mRNAs thought to be biologically irrelevant products of leaky transcription. To represent a cell type's functional transcriptome more accurately, we propose compiling many bulk RNA-seq datasets into a compendium and applying established classification models to predict whether detected transcripts are likely products of active or leaky transcription. Here, we present the BulkECexplorer (bulk RNA-seq endothelial cell explorer) compendium of 240 bulk RNA-seq datasets from five vascular endothelial cell subtypes. This resource reports transcript counts for genes of interest and predicts whether detected transcripts are likely the products of active or leaky gene expression. Beyond its usefulness for vascular biology research, this resource provides a blueprint for developing analogous tools for other cell types.

A review of artificial intelligence-assisted omics techniques in plant defense: current trends and future directions

Plants intricately deploy defense systems to counter diverse biotic and abiotic stresses. Omics technologies, spanning genomics, transcriptomics, proteomics, and metabolomics, have revolutionized the exploration of plant defense mechanisms, unraveling molecular intricacies in response to various stressors. However, the complexity and scale of omics data necessitate sophisticated analytical tools for meaningful insights. This review delves into the application of artificial intelligence algorithms, particularly machine learning and deep learning, as promising approaches for deciphering complex omics data in plant defense research. The overview encompasses key omics techniques and addresses the challenges and limitations inherent in current AI-assisted omics approaches. Moreover, it contemplates potential future directions in this dynamic field. In summary, AI-assisted omics techniques present a robust toolkit, enabling a profound understanding of the molecular foundations of plant defense and paving the way for more effective crop protection strategies amidst climate change and emerging diseases.

Evidence that variation in root anatomy contributes to local adaptation in Mexican native maize

Mexican native maize (Zea mays ssp. mays) is adapted to a wide range of climatic and edaphic conditions. Here, we focus specifically on the potential role of root anatomical variation in this adaptation. Given the investment required to characterize root anatomy, we present a machine-learning approach using environmental descriptors to project trait variation from a relatively small training panel onto a larger panel of genotyped and georeferenced Mexican maize accessions. The resulting models defined potential biologically relevant clines across a complex environment that we used subsequently for genotype-environment association. We found evidence of systematic variation in maize root anatomy across Mexico, notably a prevalence of trait combinations favoring a reduction in axial hydraulic conductance in varieties sourced from cooler, drier highland areas. We discuss our results in the context of previously described water-banking strategies and present candidate genes that are associated with both root anatomical and environmental variation. Our strategy is a refinement of standard environmental genome-wide association analysis that is applicable whenever a training set of georeferenced phenotypic data is available.

Genetic basis of maize stalk strength decoded via linkage and association mapping

Stalk lodging is a severe problem that limits maize production worldwide, although little attention has been given to its genetic basis. Here we measured rind penetrometer resistance (RPR), an effective index for stalk lodging, in a multi-parent population of 1948 recombinant inbred lines (RILs) and an association population of 508 inbred lines (AMP508). Linkage and association mapping identified 53 and 29 single quantitative trait loci (QTLs) and 50 and 19 pairs of epistatic interactions for RPR in the multi-parent population and AMP508 population, respectively. Phenotypic variation explained by all identified epistatic QTLs (up to ~5%) was much less than that explained by all single additive QTLs (up to ~33% in the multi-parent population and ~ 60% in the AMP508 population). Among all detected QTLs, only eight single QTLs explained >10% of phenotypic variation in single RIL populations. Alleles that increased RPR were enriched in tropical/subtropical (TST) groups from the AMP508 population. Based on genome-wide association studies in both populations, we identified 137 candidate genes affecting RPR, which were assigned to multiple biological processes, such as the biosynthesis of cell wall components. Sixty-six candidate genes were cross-validated by multiple methods or populations. Most importantly, 23 candidate genes were upregulated or downregulated in high-RPR lines relative to low-RPR lines, supporting the associations between candidate genes and RPR. These findings reveal the complex nature of the genetic basis underlying RPR and provide loci or candidate genes for developing elite varieties that are resistant to stalk lodging via molecular breeding.

iFLAS: positive-unlabeled learning facilitates full-length transcriptome-based identification and functional exploration of alternatively spliced isoforms in maize

The advent of full-length transcriptome sequencing technologies has accelerated the discovery of novel splicing isoforms. However, existing alternative splicing (AS) tools are either tailored for short-read RNA-Seq data or designed for human and animal studies. The disparities in AS patterns between plants and animals still pose a challenge to the reliable identification and functional exploration of novel isoforms in plants. Here, we developed integrated full-length alternative splicing analysis (iFLAS), a plant-optimized AS toolkit that introduced a semi-supervised machine learning method known as positive-unlabeled (PU) learning to accurately identify novel isoforms. iFLAS also enables the investigation of AS functions from various perspectives, such as differential AS, poly(A) tail length, and allele-specific AS (ASAS) analyses. By applying iFLAS to three full-length transcriptome sequencing datasets, we systematically identified and functionally characterized maize (Zea mays) AS patterns. We found intron retention not only introduces premature termination codons, resulting in lower expression levels of isoforms, but may also regulate the length of 3'UTR and poly(A) tail, thereby affecting the functional differentiation of isoforms. Moreover, we observed distinct ASAS patterns in two genes within heterosis offspring, highlighting their potential value in breeding. These results underscore the broad applicability of iFLAS in plant full-length transcriptome-based AS research.

The light and hypoxia induced gene ZmPORB1 determines tocopherol content in the maize kernel

Tocopherol is an important lipid-soluble antioxidant beneficial for both human health and plant growth. Here, we fine mapped a major QTL-qVE1 affecting γ-tocopherol content in maize kernel, positionally cloned and confirmed the underlying gene ZmPORB1 (por1), as a protochlorophyllide oxidoreductase. A 13.7 kb insertion reduced the tocopherol and chlorophyll content, and the photosynthetic activity by repressing ZmPORB1 expression in embryos of NIL-K22, but did not affect the levels of the tocopherol precursors HGA (homogentisic acid) and PMP (phytyl monophosphate). Furthermore, ZmPORB1 is inducible by low oxygen and light, thereby involved in the hypoxia response in developing embryos. Concurrent with natural hypoxia in embryos, the redox state has been changed with NO increasing and H2O2 decreasing, which lowered γ-tocopherol content via scavenging reactive nitrogen species. In conclusion, we proposed that the lower light-harvesting chlorophyll content weakened embryo photosynthesis, leading to fewer oxygen supplies and consequently diverse hypoxic responses including an elevated γ-tocopherol consumption. Our findings shed light on the mechanism for fine-tuning endogenous oxygen concentration in the maize embryo through a novel feedback pathway involving the light and low oxygen regulation of ZmPORB1 expression and chlorophyll content.

Dynamic transcriptome landscape of maize pericarp development

As a maternal tissue, the pericarp supports and protects for other components of seed, such as embryo and endosperm. Despite the importance of maize pericarp in seed, the genome-wide transcriptome pattern throughout maize pericarp development has not been well characterized. Here, we developed RNA-seq transcriptome atlas of B73 maize pericarp development based on 21 samples from 5 days before fertilization (DBP5) to 32 days after fertilization (DAP32). A total of 25 346 genes were detected in programming pericarp development, including 1887 transcription factors (TFs). Together with pericarp morphological changes, the global clustering of gene expression revealed four developmental stages: undeveloped, thickening, expansion and strengthening. Coexpression analysis provided further insights on key regulators in functional transition of four developmental stages. Combined with non-seed, embryo, endosperm, and nucellus transcriptome data, we identified 598 pericarp-specific genes, including 75 TFs, which could elucidate key mechanisms and regulatory networks of pericarp development. Cell wall related genes were identified that reflected their crucial role in the maize pericarp structure building. In addition, key maternal proteases or TFs related with programmed cell death (PCD) were proposed, suggesting PCD in the maize pericarp was mediated by vacuolar processing enzymes (VPE), and jasmonic acid (JA) and ethylene-related pathways. The dynamic transcriptome atlas provides a valuable resource for unraveling the genetic control of maize pericarp development.

Genome-wide identification and transcriptome profiling expression analysis of the U-box E3 ubiquitin ligase gene family related to abiotic stress in maize (Zea mays L.)

BACKGROUND

The U-box gene family encodes E3 ubiquitin ligases involved in plant hormone signaling pathways and abiotic stress responses. However, there has yet to be a comprehensive analysis of the U-box gene family in maize (Zea mays L.) and its responses to abiotic stress.

RESULTS

In this study, 85 U-box family proteins were identified in maize and were classified into four subfamilies based on phylogenetic analysis. In addition to the conserved U-box domain, we identified additional functional domains, including Pkinase, ARM, KAP and Tyr domains, by analyzing the conserved motifs and gene structures. Chromosomal localization and collinearity analysis revealed that gene duplications may have contributed to the expansion and evolution of the U-box gene family. GO annotation and KEGG pathway enrichment analysis identified a total of 105 GO terms and 21 KEGG pathways that were notably enriched, including ubiquitin-protein transferase activity, ubiquitin conjugating enzyme activity and ubiquitin-mediated proteolysis pathway. Tissue expression analysis showed that some ZmPUB genes were specifically expressed in certain tissues and that this could be due to their functions. In addition, RNA-seq data for maize seedlings under salt stress revealed 16 stress-inducible plant U-box genes, of which 10 genes were upregulated and 6 genes were downregulated. The qRT-PCR results for genes responding to abiotic stress were consistent with the transcriptome analysis. Among them, ZmPUB13, ZmPUB18, ZmPUB19 and ZmPUB68 were upregulated under all three abiotic stress conditions. Subcellular localization analysis showed that ZmPUB19 and ZmPUB59 were located in the nucleus.

CONCLUSIONS

Overall, our study provides a comprehensive analysis of the U-box gene family in maize and its responses to abiotic stress, suggesting that U-box genes play an important role in the stress response and providing insights into the regulatory mechanisms underlying the response to abiotic stress in maize.

Plant Reactome Knowledgebase: empowering plant pathway exploration and OMICS data analysis

Plant Reactome (https://plantreactome.gramene.org) is a freely accessible, comprehensive plant pathway knowledgebase. It provides curated reference pathways from rice (Oryza sativa) and gene-orthology-based pathway projections to 129 additional species, spanning single-cell photoautotrophs, non-vascular plants, and higher plants, thus encompassing a wide-ranging taxonomic diversity. Currently, Plant Reactome houses a collection of 339 reference pathways, covering metabolic and transport pathways, hormone signaling, genetic regulations of developmental processes, and intricate transcriptional networks that orchestrate a plant's response to abiotic and biotic stimuli. Beyond being a mere repository, Plant Reactome serves as a dynamic data discovery platform. Users can analyze and visualize omics data, such as gene expression, gene-gene interaction, proteome, and metabolome data, all within the rich context of plant pathways. Plant Reactome is dedicated to fostering data interoperability, upholding global data standards, and embracing the tenets of the Findable, Accessible, Interoperable and Re-usable (FAIR) data policy.

Multi-omics landscape to decrypt the distinct flavonoid biosynthesis of Scutellaria baicalensis across multiple tissues

Scutellaria baicalensis Georgi, also known as huang-qin in traditional Chinese medicine, is a widely used herbal remedy due to its anticancer, antivirus, and hepatoprotective properties. The S. baicalensis genome was sequenced many years ago; by contrast, the proteome as the executer of most biological processes of S. baicalensis in the aerial parts, as well as the secondary structure of the roots (xylem, phloem, and periderm), is far less comprehensively characterized. Here we attempt to depict the molecular landscape of the non-model plant S. baicalensis through a multi-omics approach, with the goal of constructing a highly informative and valuable reference dataset. Furthermore, we provide an in-depth characterization dissection to explain the two distinct flavonoid biosynthesis pathways that exist in the aerial parts and root, at the protein and phosphorylated protein levels. Our study provides detailed spatial proteomic and phosphoproteomic information in the context of secondary structures, with implications for the molecular profiling of secondary metabolite biosynthesis in non-model medicinal plants.

Dynamic transcriptome landscape of developing maize ear

Seed number and harvesting ability in maize (Zea mays L.) are primarily determined by the architecture of female inflorescence, namely the ear. Therefore, ear morphogenesis contributes to grain yield and as such is one of the key target traits during maize breeding. However, the molecular networks of this highly dynamic and complex grain-bearing inflorescence remain largely unclear. As a first step toward characterizing these networks, we performed a high-spatio-temporal-resolution investigation of transcriptomes using 130 ear samples collected from developing ears with length from 0.1 mm to 19.0 cm. Comparisons of these mRNA populations indicated that these spatio-temporal transcriptomes were clearly separated into four distinct stages stages I, II, III, and IV. A total of 23 793 genes including 1513 transcription factors (TFs) were identified in the investigated developing ears. During the stage I of ear morphogenesis, 425 genes were predicted to be involved in a co-expression network established by eight hub TFs. Moreover, 9714 ear-specific genes were identified in the seven kinds of meristems. Additionally, 527 genes including 59 TFs were identified as especially expressed in ear and displayed high temporal specificity. These results provide a high-resolution atlas of gene activity during ear development and help to unravel the regulatory modules associated with the differentiation of the ear in maize.

Overexpression of ZmEXPA5 reduces anthesis-silking interval and increases grain yield under drought and well-watered conditions in maize

Drought is one of the major abiotic stresses affecting the maize production worldwide. As a cross-pollination crop, maize is sensitive to water stress at flowering stage. Drought at this stage leads to asynchronous development of male and female flower organ and increased interval between anthesis and silking, which finally causes failure of pollination and grain yield loss. In the present study, the expansin gene ZmEXPA5 was cloned and its function in drought tolerance was characterized. An indel variant in promoter of ZmEXPA5 is significantly associated with natural variation in drought-induced anthesis-silking interval. The drought susceptible haplotypes showed lower expression level of ZmEXPA5 than tolerant haplotypes and lost the cis-regulatory activity of ZmDOF29. Increasing ZmEXPA5 expression in transgenic maize decreases anthesis-silking interval and improves grain yield under both drought and well-watered environments. In addition, the expression pattern of ZmEXPA5 was analyzed. These findings provide insights into the genetic basis of drought tolerance and a promising gene for drought improvement in maize breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01432-x.

Roles of auxin pathways in maize biology

Phytohormones play a central role in plant development and environmental responses. Auxin is a classical hormone that is required for organ formation, tissue patterning, and defense responses. Auxin pathways have been extensively studied across numerous land plant lineages, including bryophytes and eudicots. In contrast, our understanding of the roles of auxin in maize morphogenesis and immune responses is limited. Here, we review evidence for auxin-mediated processes in maize and describe promising areas for future research in the auxin field. Several recent transcriptomic and genetic studies have demonstrated that auxin is a key influencer of both vegetative and reproductive development in maize (namely roots, leaves, and kernels). Auxin signaling has been implicated in both maize shoot architecture and immune responses through genetic and molecular analyses of the conserved co-repressor RAMOSA ENHANCER LOCUS2. Polar auxin transport is linked to maize drought responses, root growth, shoot formation, and leaf morphogenesis. Notably, maize has been a key system for delineating auxin biosynthetic pathways and offers many opportunities for future investigations on auxin metabolism. In addition, crosstalk between auxin and other phytohormones has been uncovered through gene expression studies and is important for leaf and root development in maize. Collectively these studies point to auxin as a cornerstone for maize biology that could be leveraged for improved crop resilience and yield.

A role for fermentation in aerobic conditions as revealed by computational analysis of maize root metabolism during growth by cell elongation

The root is a well-studied example of cell specialisation, yet little is known about the metabolism that supports the transport functions and growth of different root cell types. To address this, we used computational modelling to study metabolism in the elongation zone of a maize lateral root. A functional-structural model captured the cell-anatomical features of the root and modelled how they changed as the root elongated. From these data, we derived constraints for a flux balance analysis model that predicted metabolic fluxes of the 11 concentric rings of cells in the root. We discovered a distinct metabolic flux pattern in the cortical cell rings, endodermis and pericycle (but absent in the epidermis) that involved a high rate of glycolysis and production of the fermentation end-products lactate and ethanol. This aerobic fermentation was confirmed experimentally by metabolite analysis. The use of fermentation in the model was not obligatory but was the most efficient way to meet the specific demands for energy, reducing power and carbon skeletons of expanding cells. Cytosolic acidification was avoided in the fermentative mode due to the substantial consumption of protons by lipid synthesis. These results expand our understanding of fermentative metabolism beyond that of hypoxic niches and suggest that fermentation could play an important role in the metabolism of aerobic tissues.

miRNA-like secondary structures in maize (Zea mays) genes and transposable elements correlate with small RNAs, methylation, and expression

RNA molecules carry information in their primary sequence and also their secondary structure. Secondary structure can confer important functional information, but it is also a signal for an RNAi-like host epigenetic response mediated by small RNAs (smRNAs). In this study, we used two bioinformatic methods to predict local secondary structures across features of the maize genome, focusing on small regions that had similar folding properties to pre-miRNA loci. We found miRNA-like secondary structures to be common in genes and most, but not all, superfamilies of RNA and DNA transposable elements (TEs). The miRNA-like regions map to a higher diversity of smRNAs than regions without miRNA-like structure, explaining up to 27% of variation in smRNA mapping for some TE superfamilies. This mapping bias is more pronounced among putatively autonomous TEs relative to nonautonomous TEs. Genome-wide, miRNA-like regions are also associated with elevated methylation levels, particularly in the CHH context. Among genes, those with miRNA-like secondary structure are 1.5-fold more highly expressed, on average, than other genes. However, these genes are also more variably expressed across the 26 nested association mapping founder lines, and this variability positively correlates with the number of mapping smRNAs. We conclude that local miRNA-like structures are a nearly ubiquitous feature of expressed regions of the maize genome, that they correlate with higher smRNA mapping and methylation, and that they may represent a trade-off between functional requirements and the potentially negative consequences of smRNA production.

Characterization of Glycosyltransferase Family 1 (GT1) and Their Potential Roles in Anthocyanin Biosynthesis in Maize

Glycosyltransferase family 1 (GT1) is a large group of proteins that play critical roles in secondary metabolite biosynthesis in plants. However, the GT1 family is not well studied in maize. In this study, 107 GT1 unigenes were identified in the maize reference genome and classified into 16 groups according to their phylogenetic relationship. GT1s are unevenly distributed across all ten maize chromosomes, occurring as gene clusters in some chromosomes. Collinearity analysis revealed that gene duplication events, whole-genome or segmental duplication, and tandem duplication occurred at a similar frequency, indicating that both types of gene duplication play notable roles in the expansion of the GT1 gene family. Expression analysis showed GT1s expressing in all tissues with specific expression patterns of each GT1, suggesting that they might participate in multiple biological processes during the whole growth and development stages. Furthermore, 16 GT1s were identified to have similar expression patterns to those of anthocyanidin synthase (ANS), the critical enzyme in anthocyanin biosynthesis. Molecular docking was carried out to examine the affinity of GT1s with substrates in anthocyanin biosynthesis. This study provides valuable information on the GT1s of maize and will promote the development of research on their biological functions in the biosynthesis of other secondary metabolites.

GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize

Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.

Maize Feature Store: A centralized resource to manage and analyze curated maize multi-omics features for machine learning applications

The big-data analysis of complex data associated with maize genomes accelerates genetic research and improves agronomic traits. As a result, efforts have increased to integrate diverse datasets and extract meaning from these measurements. Machine learning models are a powerful tool for gaining knowledge from large and complex datasets. However, these models must be trained on high-quality features to succeed. Currently, there are no solutions to host maize multi-omics datasets with end-to-end solutions for evaluating and linking features to target gene annotations. Our work presents the Maize Feature Store (MFS), a versatile application that combines features built on complex data to facilitate exploration, modeling and analysis. Feature stores allow researchers to rapidly deploy machine learning applications by managing and providing access to frequently used features. We populated the MFS for the maize reference genome with over 14 000 gene-based features based on published genomic, transcriptomic, epigenomic, variomic and proteomics datasets. Using the MFS, we created an accurate pan-genome classification model with an AUC-ROC score of 0.87. The MFS is publicly available through the maize genetics and genomics database. Database URL  https://mfs.maizegdb.org/.

ZmEREB92 plays a negative role in seed germination by regulating ethylene signaling and starch mobilization in maize

Rapid and uniform seed germination is required for modern cropping system. Thus, it is important to optimize germination performance through breeding strategies in maize, in which identification for key regulators is needed. Here, we characterized an AP2/ERF transcription factor, ZmEREB92, as a negative regulator of seed germination in maize. Enhanced germination in ereb92 mutants is contributed by elevated ethylene signaling and starch degradation. Consistently, an ethylene signaling gene ZmEIL7 and an α-amylase gene ZmAMYa2 are identified as direct targets repressed by ZmEREB92. OsERF74, the rice ortholog of ZmEREB92, shows conserved function in negatively regulating seed germination in rice. Importantly, this orthologous gene pair is likely experienced convergently selection during maize and rice domestication. Besides, mutation of ZmEREB92 and OsERF74 both lead to enhanced germination under cold condition, suggesting their regulation on seed germination might be coupled with temperature sensitivity. Collectively, our findings uncovered the ZmEREB92-mediated regulatory mechanism of seed germination in maize and provide breeding targets for maize and rice to optimize seed germination performance towards changing climates.

Exploring the roles of ZmARM gene family in maize development and abiotic stress response

Armadillo (ARM) was a gene family important to plants, with crucial roles in regulating plant growth, development, and stress responses. However, the properties and functions of ARM family members in maize had received limited attention. Therefore, this study employed bioinformatics methods to analyze the structure and evolution of ARM-repeat protein family members in maize. The maize (Zea mays L.) genome contains 56 ARM genes distributed over 10 chromosomes, and collinearity analysis indicated 12 pairs of linkage between them. Analysis of the physicochemical properties of ARM proteins showed that most of these proteins were acidic and hydrophilic. According to the number and evolutionary analysis of the ARM genes, the ARM genes in maize can be divided into eight subgroups, and the gene structure and conserved motifs showed similar compositions in each group. The findings shed light on the significant roles of 56 ZmARM domain genes in development and abiotic stress, particularly drought stress. RNA-Seq and qRT-PCR analysis revealed that drought stress exerts an influence on specific members of the ZmARM family, such as ZmARM4, ZmARM12, ZmARM34 and ZmARM36. The comprehensive profiling of these genes in the whole genome, combined with expression analysis, establishes a foundation for further exploration of plant gene function in the context of abiotic stress and reproductive development.