MaizeGDB 2018: the maize multi-genome genetics and genomics database

Premeiotic 24-nt phasiRNAs are present in the Zea genus and unique in biogenesis mechanism and molecular function

Reproductive phasiRNAs (phased, small interfering RNAs) are broadly present in angiosperms and play crucial roles in sustaining male fertility. While the premeiotic 21-nt (nucleotides) phasiRNAs and meiotic 24-nt phasiRNA pathways have been extensively studied in maize (Zea mays) and rice (Oryza sativa), a third putative category of reproductive phasiRNAs-named premeiotic 24-nt phasiRNAs-have recently been reported in barley (Hordeum vulgare) and wheat (Triticum aestivum). To determine whether premeiotic 24-nt phasiRNAs are also present in maize and related species and begin to characterize their biogenesis and function, we performed a comparative transcriptome and degradome analysis of premeiotic and meiotic anthers from five maize inbred lines and three teosinte species/subspecies. Our data indicate that a substantial subset of the 24-nt phasiRNA loci in maize and teosinte are already highly expressed at the premeiotic phase. The premeiotic 24-nt phasiRNAs are similar to meiotic 24-nt phasiRNAs in genomic origin and dependence on DCL5 (Dicer-like 5) for biogenesis, however, premeiotic 24-nt phasiRNAs are unique in that they are likely i) not triggered by microRNAs, ii) not loaded by AGO18 proteins, and iii) not capable of mediating PHAS precursor cleavage. In addition, we also observed a group of premeiotic 24-nt phasiRNAs in rice using previously published data. Together, our results indicate that the premeiotic 24-nt phasiRNAs constitute a unique class of reproductive phasiRNAs and are present more broadly in the grass family (Poaceae) than previously known.

Genetic analysis and QTL mapping for pericarp thickness in maize (Zea mays L.)

Proper pericarp thickness protects the maize kernel against pests and diseases, moreover, thinner pericarp improves the eating quality in fresh corn. In this study, we aimed to investigate the dynamic changes in maize pericarp during kernel development and identified the major quantitative trait loci (QTLs) for maize pericarp thickness. It was observed that maize pericarp thickness first increased and then decreased. During the growth and formation stages, the pericarp thickness gradually increased and reached the maximum, after which it gradually decreased and reached the minimum during maturity. To identify the QTLs for pericarp thickness, a BC4F4 population was constructed using maize inbred lines B73 (recurrent parent with thick pericarp) and Baimaya (donor parent with thin pericarp). In addition, a high-density genetic map was constructed using maize 10 K SNP microarray. A total of 17 QTLs related to pericarp thickness were identified in combination with the phenotypic data. The results revealed that the heritability of the thickness of upper germinal side of pericarp (UG) was 0.63. The major QTL controlling UG was qPT1-1, which was located on chromosome 1 (212,215,145-212,948,882). The heritability of the thickness of upper abgerminal side of pericarp (UA) was 0.70. The major QTL controlling UA was qPT2-1, which was located on chromosome 2 (2,550,197-14,732,993). In addition, a combination of functional annotation, DNA sequencing analysis and quantitative real-time PCR (qPCR) screened two candidate genes, Zm00001d001964 and Zm00001d002283, that could potentially control maize pericarp thickness. This study provides valuable insights into the improvement of maize pericarp thickness during breeding.

Premeiotic 24-nt phasiRNAs are present in the Zea genus and unique in biogenesis mechanism and molecular function

Reproductive phasiRNAs are broadly present in angiosperms and play crucial roles in sustaining male fertility. While the premeiotic 21-nt phasiRNAs and meiotic 24-nt phasiRNA pathways have been extensively studied in maize (Zea mays) and rice (Oryza sativa), a third putative category of reproductive phasiRNAs-named premeiotic 24-nt phasiRNAs-have recently been reported in barley (Hordeum vulgare) and wheat (Triticum aestivum). To determine whether premeiotic 24-nt phasiRNAs are also present in maize and related species and begin to characterize their biogenesis and function, we performed a comparative transcriptome and degradome analysis of premeiotic and meiotic anthers from five maize inbred lines and three teosinte species/subspecies. Our data indicate that a substantial subset of the 24-nt phasiRNA loci in maize and teosinte are already highly expressed at premeiotic phase. The premeiotic 24-nt phasiRNAs are similar to meiotic 24-nt phasiRNAs in genomic origin and dependence on DCL5 for biogenesis, however, premeiotic 24-nt phasiRNAs are unique in that they are likely (i) not triggered by microRNAs, (ii) not loaded by AGO18 proteins, and (iii) not capable of mediating cis-cleavage. In addition, we also observed a group of premeiotic 24-nt phasiRNAs in rice using previously published data. Together, our results indicate that the premeiotic 24-nt phasiRNAs constitute a unique class of reproductive phasiRNAs and are present more broadly in the grass family (Poaceae) than previously known.

A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops

Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties. Predicting the associations between genes and traits requires the organization and analysis of multi-dimensional scientific data. The existing methods for establishing the relationships between genomic data and phenotypic data can only elucidate the associations between genes and individual traits. However, there are relatively few methods for detecting elite polyphenotype genes. In this study, a knowledge graph for traits regulating-genes was constructed by collecting data from the PubMed database and eight other databases related to the staple food crops rice, maize, and wheat as well as the model plant Arabidopsis thaliana. On the basis of the knowledge graph, a model for predicting traits regulating-genes was constructed by combining the data attributes of the gene nodes and the topological relationship attributes of the gene nodes. Additionally, a scoring method for predicting the genes regulating specific traits was developed to screen for elite polyphenotype genes. A total of 125,591 nodes and 547,224 semantic relationships were included in the knowledge graph. The accuracy of the knowledge graph-based model for predicting traits regulating-genes was 0.89, the precision rate was 0.91, the recall rate was 0.96, and the F1 value was 0.94. Moreover, 4,447 polyphenotype genes for 31 trait combinations were identified, among which the rice polyphenotype gene IPA1 and the A. thaliana polyphenotype gene CUC2 were verified via a literature search. Furthermore, the wheat gene TraesCS5A02G275900 was revealed as a potential polyphenotype gene that will need to be further characterized. Meanwhile, the result of venn diagram analysis between the polyphenotype gene datasets (consists of genes that are predicted by our model) and the transcriptome gene datasets (consists of genes that were differential expression in response to disease, drought or salt) showed approximately 70% and 54% polyphenotype genes were identified in the transcriptome datasets of Arabidopsis and rice, respectively. The application of the model driven by knowledge graph for predicting traits regulating-genes represents a novel method for detecting elite polyphenotype genes.

Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-023-00134-4.

Innovative computational tools provide new insights into the polyploid wheat genome

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

Plant pangenomes for crop improvement, biodiversity and evolution

Plant genome sequences catalogue genes and the genetic elements that regulate their expression. Such inventories further research aims as diverse as mapping the molecular basis of trait diversity in domesticated plants or inquiries into the origin of evolutionary innovations in flowering plants millions of years ago. The transformative technological progress of DNA sequencing in the past two decades has enabled researchers to sequence ever more genomes with greater ease. Pangenomes - complete sequences of multiple individuals of a species or higher taxonomic unit - have now entered the geneticists' toolkit. The genomes of crop plants and their wild relatives are being studied with translational applications in breeding in mind. But pangenomes are applicable also in ecological and evolutionary studies, as they help classify and monitor biodiversity across the tree of life, deepen our understanding of how plant species diverged and show how plants adapt to changing environments or new selection pressures exerted by human beings.

Crop-GPA: an integrated platform of crop gene-phenotype associations

With the increasing availability of large-scale biology data in crop plants, there is an urgent demand for a versatile platform that fully mines and utilizes the data for modern molecular breeding. We present Crop-GPA ( https://crop-gpa.aielab.net ), a comprehensive and functional open-source platform for crop gene-phenotype association data. The current Crop-GPA provides well-curated information on genes, phenotypes, and their associations (GPAs) to researchers through an intuitive interface, dynamic graphical visualizations, and efficient online tools. Two computational tools, GPA-BERT and GPA-GCN, are specifically developed and integrated into Crop-GPA, facilitating the automatic extraction of gene-phenotype associations from bio-crop literature and predicting unknown relations based on known associations. Through usage examples, we demonstrate how our platform enables the exploration of complex correlations between genes and phenotypes in crop plants. In summary, Crop-GPA serves as a valuable multi-functional resource, empowering the crop research community to gain deeper insights into the biological mechanisms of interest.

PanEffect: a pan-genome visualization tool for variant effects in maize

SUMMARY

Understanding the effects of genetic variants is crucial for accurately predicting traits and functional outcomes. Recent approaches have utilized artificial intelligence and protein language models to score all possible missense variant effects at the proteome level for a single genome, but a reliable tool is needed to explore these effects at the pan-genome level. To address this gap, we introduce a new tool called PanEffect. We implemented PanEffect at MaizeGDB to enable a comprehensive examination of the potential effects of coding variants across 50 maize genomes. The tool allows users to visualize over 550 million possible amino acid substitutions in the B73 maize reference genome and to observe the effects of the 2.3 million natural variations in the maize pan-genome. Each variant effect score, calculated from the Evolutionary Scale Modeling (ESM) protein language model, shows the log-likelihood ratio difference between B73 and all variants in the pan-genome. These scores are shown using heatmaps spanning benign outcomes to potential functional consequences. In addition, PanEffect displays secondary structures and functional domains along with the variant effects, offering additional functional and structural context. Using PanEffect, researchers now have a platform to explore protein variants and identify genetic targets for crop enhancement.

AVAILABILITY AND IMPLEMENTATION

The PanEffect code is freely available on GitHub (https://github.com/Maize-Genetics-and-Genomics-Database/PanEffect). A maize implementation of PanEffect and underlying datasets are available at MaizeGDB (https://www.maizegdb.org/effect/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.

Insights into ZmWAKL in maize kernel development: genome-wide investigation and GA-mediated transcription

BACKGROUND

The functional roles of the Wall Associated Kinase (WAK) and Wall Associated Kinase Like (WAKL) families in cellular expansion and developmental processes have been well-established. However, the molecular regulation of these kinases in maize development is limited due to the absence of comprehensive genome-wide studies.

RESULTS

Through an in-depth analysis, we identified 58 maize WAKL genes, and classified them into three distinct phylogenetic clusters. Moreover, structural prediction analysis showed functional conservation among WAKLs across maize. Promoter analysis uncovered the existence of cis-acting elements associated with the transcriptional regulation of ZmWAKL genes by Gibberellic acid (GA). To further elucidate the role of WAKL genes in maize kernels, we focused on three highly expressed genes, viz ZmWAKL38, ZmWAKL42 and ZmWAKL52. Co-expression analyses revealed that their expression patterns exhibited a remarkable correlation with GA-responsive transcription factors (TF) TF5, TF6, and TF8, which displayed preferential expression in kernels. RT-qPCR analysis validated the upregulation of ZmWAKL38, ZmWAKL42, ZmWAKL52, TF5, TF6, and TF8 following GA treatment. Additionally, ZmWAKL52 showed significant increase of transcription in the present of TF8, with ZmWAKL52 localizing in both the plasma membrane and cell wall. TF5 positively regulated ZmWAKL38, while TF6 positively regulated ZmWAKL42.

CONCLUSIONS

Collectively, these findings provide novel insights into the characterization and regulatory mechanisms of specific ZmWAKL genes involved in maize kernel development, offering prospects for their utilization in maize breeding programs.

Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences

Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.

Biofortification of iron content by regulating a NAC transcription factor in maize

Iron (Fe) deficiency remains widespread among people in developing countries. To help solve this problem, breeders have been attempting to develop maize cultivars with high yields and high Fe concentrations in the kernels. We conducted a genome-wide association study and identified a gene, ZmNAC78 (NAM/ATAF/CUC DOMAIN TRANSCRIPTION FACTOR 78), that regulates Fe concentrations in maize kernels. We cultivated maize varieties with both high yield and high Fe concentrations in their kernels by using a molecular marker developed from a 42-base pair insertion or deletion (indel) in the promoter of ZmNAC78. ZmNAC78 expression is enriched in the basal endosperm transfer layer of kernels, and the ZmNAC78 protein directly regulates messenger RNA abundance of Fe transporters. Our results thus provide an approach to develop maize varieties with Fe-enriched kernels.

Genome-wide association analysis of plant architecture traits using doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic maize population

Selection in the Iowa Stiff Stalk Synthetic (BSSS) maize population for high yield, grain moisture, and root and stalk lodging has indirectly modified plant architecture traits that are important for adaptation to high plant density. In this study, we developed doubled haploid (DH) lines from the BSSS maize population in the earliest cycle of recurrent selection (BSSS), cycle 17 of reciprocal recurrent selection, [BSSS(R)17] and the cross between the two cycles [BSSS/BSSS(R)C17]. We aimed to determine the phenotypic variation and changes in agronomic traits that have occurred through the recurrent selection program in this population and to identify genes or regions in the genome associated with the plant architecture changes observed in the different cycles of selection. We conducted a per se evaluation of DH lines focusing on high heritability traits important for adaptation to high planting density and grain yield. Trends for reducing flowering time, anthesis-silking interval, ear height, and the number of primary tassel branches in BSSS(R)17 DH lines compared to BSSS and BSSS/BSSS(R)C17 DH lines were observed. Additionally, the BSSS(R)C17 DH lines showed more upright flag leaf angles. Using the entire panel of DH lines increased the number of SNP markers identified within candidate genes associated with plant architecture traits. The genomic regions identified for plant architecture traits in this study may help to elucidate the genetic basis of these traits and facilitate future work about marker-assisted selection or map-based cloning in maize breeding programs.

LHP1-mediated epigenetic buffering of subgenome diversity and defense responses confers genome plasticity and adaptability in allopolyploid wheat

Polyploidization is a major driver of genome diversification and environmental adaptation. However, the merger of different genomes may result in genomic conflicts, raising a major question regarding how genetic diversity is interpreted and regulated to enable environmental plasticity. By analyzing the genome-wide binding of 191 trans-factors in allopolyploid wheat, we identified like heterochromatin protein 1 (LHP1) as a master regulator of subgenome-diversified genes. Transcriptomic and epigenomic analyses of LHP1 mutants reveal its role in buffering the expression of subgenome-diversified defense genes by controlling H3K27me3 homeostasis. Stripe rust infection releases latent subgenomic variations by eliminating H3K27me3-related repression. The simultaneous inactivation of LHP1 homoeologs by CRISPR-Cas9 confers robust stripe rust resistance in wheat seedlings. The conditional repression of subgenome-diversified defenses ensures developmental plasticity to external changes, while also promoting neutral-to-non-neutral selection transitions and adaptive evolution. These findings establish an LHP1-mediated buffering system at the intersection of genotypes, environments, and phenotypes in polyploid wheat. Manipulating the epigenetic buffering capacity offers a tool to harness cryptic subgenomic variations for crop improvement.

Teosinte Pollen Drive guides maize diversification and domestication by RNAi

Meiotic drivers subvert Mendelian expectations by manipulating reproductive development to bias their own transmission. Chromosomal drive typically functions in asymmetric female meiosis, while gene drive is normally postmeiotic and typically found in males. 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 (Zea mays ssp. mexicana), that depends on RNA interference (RNAi). 22nt 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 Americas, and a tightly linked inversion in mexicana spans a major domestication sweep in modern maize. A survey of maize landraces and sympatric populations of teosinte mexicana reveals correlated patterns of admixture among unlinked genes required for RNAi on at least 4 chromosomes that are also subject to gene drive in pollen from synthetic hybrids. Teosinte Pollen Drive likely played a major role in maize domestication and diversification, and offers an explanation for the widespread abundance of "self" small RNAs in the germlines of plants and animals.

Sequence variations associated with novel purple-pericarp super-sweetcorn compared to its purple-pericarp maize and white super-sweetcorn parents

Recently, a novel purple-pericarp super-sweetcorn line, 'Tim1' (A1A1.sh2sh2) was derived from the purple-pericarp maize 'Costa Rica' (A1Sh2.A1Sh2) and white shrunken2 (sh2) super-sweetcorn 'Tims-white' (a1sh2.a1sh2), however, information regarding anthocyanin biosynthesis genes controlling purple colour and sweetness gene is lacking. Specific sequence differences in the CDS (coding DNA sequence) and promoter regions of the anthocyanin biosynthesis structural genes, anthocyanin1 (A1), purple aleurone1 (Pr1) and regulatory genes, purple plant1 (Pl1), plant colour1 (B1), coloured1 (R1), and the sweetcorn structural gene, shrunken2 (sh2) were investigated using the publicly available annotated yellow starchy maize, B73 (NAM5.0) as a reference genome. In the CDS region, the A1, Pl1 and R1 gene sequence differences of 'Tim1' and 'Costa Rica' were similar, as they control purple-pericarp pigmentation. However, the B1 gene showed similarity between the 'Tim1' and 'Tims-white' lines, which may indicate that it does not have a role in controlling pericarp colour, unlike the report of a previous study. In the case of the Pr1 gene, in contrast to 'Costa Rica', 6- and 8-bp dinucleotide (TA) repeats were observed in the promoter region of the 'Tims-white' and 'Tim1' lines, respectively, indicating the defective functionality (redder colour in 'Tim1' rather than purple in 'Costa Rica') of the recessive pr1 allele. In sweetcorn, the structural gene (sh2), sequence showed similarity between purple-sweet 'Tim1' and its white-sweet parent 'Tims-white', as both display a shrunken phenotype in their mature kernels. These findings revealed that the developed purple-sweet line is different to the reference yellow-nonsweet line in both the anthocyanin biosynthesis and sweetcorn genes.

Phenotypic and genome-wide association analyses for nitrogen use efficiency related traits in maize (Zea mays L.) exotic introgression lines

Nitrogen (N) limits crop production, yet more than half of N fertilizer inputs are lost to the environment. Developing maize hybrids with improved N use efficiency can help minimize N losses and in turn reduce adverse ecological, economical, and health consequences. This study aimed to identify single nucleotide polymorphisms (SNPs) associated with agronomic traits (plant height, grain yield, and anthesis to silking interval) under high and low N conditions. A genome-wide association study (GWAS) was conducted using 181 doubled haploid (DH) lines derived from crosses between landraces from the Germplasm Enhancement of Maize (BGEM lines) project and two inbreds, PHB47 and PHZ51. These DH lines were genotyped using 62,077 SNP markers. The same lines from the per se trials were used as parental lines for the testcross field trials. Plant height, anthesis to silking interval, and grain yield were collected from high and low N conditions in three environments for both per se and testcross trials. We used three GWAS models, namely, general linear model (GLM), mixed linear model (MLM), and Fixed and Random model Circulating Probability Unification (FarmCPU) model. We observed significant genetic variation among the DH lines and their derived testcrosses. Interestingly, some testcrosses of exotic introgression lines were superior under high and low N conditions compared to the check hybrid, PHB47/PHZ51. We detected multiple SNPs associated with agronomic traits under high and low N, some of which co-localized with gene models associated with stress response and N metabolism. The BGEM panel is, thus, a promising source of allelic diversity for genes controlling agronomic traits under different N conditions.

Pangenome-based trajectories of intracellular gene transfers in Poaceae unveil high cumulation in Triticeae

Intracellular gene transfers (IGTs) between the nucleus and organelles, including plastids and mitochondria, constantly reshape the nuclear genome during evolution. Despite the substantial contribution of IGTs to genome variation, the dynamic trajectories of IGTs at the pangenomic level remain elusive. Here, we developed an approach, IGTminer, that maps the evolutionary trajectories of IGTs using collinearity and gene reannotation across multiple genome assemblies. We applied IGTminer to create a nuclear organellar gene (NOG) map across 67 genomes covering 15 Poaceae species, including important crops. The resulting NOGs were verified by experiments and sequencing data sets. Our analysis revealed that most NOGs were recently transferred and lineage specific and that Triticeae species tended to have more NOGs than other Poaceae species. Wheat (Triticum aestivum) had a higher retention rate of NOGs than maize (Zea mays) and rice (Oryza sativa), and the retained NOGs were likely involved in photosynthesis and translation pathways. Large numbers of NOG clusters were aggregated in hexaploid wheat during 2 rounds of polyploidization, contributing to the genetic diversity among modern wheat accessions. We implemented an interactive web server to facilitate the exploration of NOGs in Poaceae. In summary, this study provides resources and insights into the roles of IGTs in shaping interspecies and intraspecies genome variation and driving plant genome evolution.

Identification and functional analysis of ZmDLS associated with the response to biotic stress in maize

Terpenes are the main class of secondary metabolites produced in response to pest and germ attacks. In maize (Zea mays L.), they are the essential components of the herbivore-induced plant volatile mixture, which functioned as a direct or indirect defense against pest and germ attacks. In this study, 43 maize terpene synthase gene (ZmTPS) family members were systematically identified and analyzed through the whole genomes of maize. Nine genes, including Zm00001d032230, Zm00001d045054, Zm00001d024486, Zm00001d004279, Zm00001d002351, Zm00001d002350, Zm00001d053916, Zm00001d015053, and Zm00001d015054, were isolated for their differential expression pattern in leaves after corn borer (Ostrinia nubilalis) bite. Additionally, six genes (Zm00001d045054, Zm00001d024486, Zm00001d002351, Zm00001d002350, Zm00001d015053, and Zm00001d015054) were significantly upregulated in response to corn borer bite. Among them, Zm00001d045054 was cloned. Heterologous expression and enzyme activity assays revealed that Zm00001d045054 functioned as d-limonene synthase. It was renamed ZmDLS. Further analysis demonstrated that its expression was upregulated in response to corn borer bites and Fusarium graminearum attacks. The mutant of ZmDLS downregulated the expressions of Zm00001d024486, Zm00001d002351, Zm00001d002350, Zm00001d015053, and Zm00001d015054. It was more attractive to corn borer bites and more susceptible to F. graminearum infection. The yeast one-hybrid assay and dual-luciferase assay showed that ZmMYB76 and ZmMYB101 could upregulate the expression of ZmDLS by binding to the promoter region. This study may provide a theoretical basis for the functional analysis and transcriptional regulation of terpene synthase genes in crops.

Roles of the MYB94/FUSED LEAVES1 (ZmFDL1) and GLOSSY2 (ZmGL2) genes in cuticle biosynthesis and potential impacts on Fusarium verticillioides growth on maize silks

Maize silks, the stigmatic portions of the female flowers, have an important role in reproductive development. Silks also provide entry points for pathogens into host tissues since fungal hyphae move along the surface of the silks to reach the site of infection, i.e., the developing kernel. The outer extracellular surface of the silk is covered by a protective hydrophobic cuticle, comprised of a complex array of long-chain hydrocarbons and small amounts of very long chain fatty acids and fatty alcohols. This work illustrates that two previously characterized cuticle-related genes separately exert roles on maize silk cuticle deposition and function. ZmMYB94/FUSED LEAVES 1 (ZmFDL1) MYB transcription factor is a key regulator of cuticle deposition in maize seedlings. The ZmGLOSSY2 (ZmGL2) gene, a putative member of the BAHD superfamily of acyltransferases with close sequence similarity to the Arabidopsis AtCER2 gene, is involved in the elongation of the fatty acid chains that serve as precursors of the waxes on young leaves. In silks, lack of ZmFDL1 action generates a decrease in the accumulation of a wide number of compounds, including alkanes and alkenes of 20 carbons or greater and affects the expression of cuticle-related genes. These results suggest that ZmFDL1 retains a regulatory role in silks, which might be exerted across the entire wax biosynthesis pathway. Separately, a comparison between gl2-ref and wild-type silks reveals differences in the abundance of specific cuticular wax constituents, particularly those of longer unsaturated carbon chain lengths. The inferred role of ZmGL2 is to control the chain lengths of unsaturated hydrocarbons. The treatment of maize silks with Fusarium verticillioides conidia suspension results in altered transcript levels of ZmFDL1 and ZmGL2 genes. In addition, an increase in fungal growth was observed on gl2-ref mutant silks 72 hours after Fusarium infection. These findings suggest that the silk cuticle plays an active role in the response to F. verticillioides infection.

Using knowledge graphs to infer gene expression in plants

Introduction

Climate change is already affecting ecosystems around the world and forcing us to adapt to meet societal needs. The speed with which climate change is progressing necessitates a massive scaling up of the number of species with understood genotype-environment-phenotype (G×E×P) dynamics in order to increase ecosystem and agriculture resilience. An important part of predicting phenotype is understanding the complex gene regulatory networks present in organisms. Previous work has demonstrated that knowledge about one species can be applied to another using ontologically-supported knowledge bases that exploit homologous structures and homologous genes. These types of structures that can apply knowledge about one species to another have the potential to enable the massive scaling up that is needed through in silico experimentation.

Methods

We developed one such structure, a knowledge graph (KG) using information from Planteome and the EMBL-EBI Expression Atlas that connects gene expression, molecular interactions, functions, and pathways to homology-based gene annotations. Our preliminary analysis uses data from gene expression studies in Arabidopsis thaliana and Populus trichocarpa plants exposed to drought conditions.

Results

A graph query identified 16 pairs of homologous genes in these two taxa, some of which show opposite patterns of gene expression in response to drought. As expected, analysis of the upstream cis-regulatory region of these genes revealed that homologs with similar expression behavior had conserved cis-regulatory regions and potential interaction with similar trans-elements, unlike homologs that changed their expression in opposite ways.

Discussion

This suggests that even though the homologous pairs share common ancestry and functional roles, predicting expression and phenotype through homology inference needs careful consideration of integrating cis and trans-regulatory components in the curated and inferred knowledge graph.

SoybeanGDB: A comprehensive genomic and bioinformatic platform for soybean genetics and genomics

Soybean (Glycine max (L.) Merr.) is a globally significant crop, widely cultivated for oilseed production and animal feeds. In recent years, the rapid growth of multi-omics data from thousands of soybean accessions has provided unprecedented opportunities for researchers to explore genomes, genetic variations, and gene functions. To facilitate the utilization of these abundant data for soybean breeding and genetic improvement, the SoybeanGDB database (https://venyao.xyz/SoybeanGDB/) was developed as a comprehensive platform. SoybeanGDB integrates high-quality de novo assemblies of 39 soybean genomes and genomic variations among thousands of soybean accessions. Genomic information and variations in user-specified genomic regions can be searched and downloaded from SoybeanGDB, in a user-friendly manner. To facilitate research on genetic resources and elucidate the biological significance of genes, SoybeanGDB also incorporates a variety of bioinformatics analysis modules with graphical interfaces, such as linkage disequilibrium analysis, nucleotide diversity analysis, allele frequency analysis, gene expression analysis, primer design, gene set enrichment analysis, etc. In summary, SoybeanGDB is an essential and valuable resource that provides an open and free platform to accelerate global soybean research.

A dolabralexin-deficient mutant provides insight into specialized diterpenoid metabolism in maize

Two major groups of specialized metabolites in maize (Zea mays), termed kauralexins and dolabralexins, serve as known or predicted diterpenoid defenses against pathogens, herbivores, and other environmental stressors. To consider the physiological roles of the recently discovered dolabralexin pathway, we examined dolabralexin structural diversity, tissue-specificity, and stress-elicited production in a defined biosynthetic pathway mutant. Metabolomics analyses support a larger number of dolabralexin pathway products than previously known. We identified dolabradienol as a previously undetected pathway metabolite and characterized its enzymatic production. Transcript and metabolite profiling showed that dolabralexin biosynthesis and accumulation predominantly occur in primary roots and show quantitative variation across genetically diverse inbred lines. Generation and analysis of CRISPR-Cas9-derived loss-of-function Kaurene Synthase-Like 4 (Zmksl4) mutants demonstrated dolabralexin production deficiency, thus supporting ZmKSL4 as the diterpene synthase responsible for the conversion of geranylgeranyl pyrophosphate precursors into dolabradiene and downstream pathway products. Zmksl4 mutants further display altered root-to-shoot ratios and root architecture in response to water deficit. Collectively, these results demonstrate dolabralexin biosynthesis via ZmKSL4 as a committed pathway node biochemically separating kauralexin and dolabralexin metabolism, and suggest an interactive role of maize dolabralexins in plant vigor during abiotic stress.

Linking discoveries, mechanisms, and technologies to develop a clearer perspective on plant long noncoding RNAs

Long noncoding RNAs (lncRNAs) are a large and diverse class of genes in eukaryotic genomes that contribute to a variety of regulatory processes. Functionally characterized lncRNAs play critical roles in plants, ranging from regulating flowering to controlling lateral root formation. However, findings from the past decade have revealed that thousands of lncRNAs are present in plant transcriptomes, and characterization has lagged far behind identification. In this setting, distinguishing function from noise is challenging. However, the plant community has been at the forefront of discovery in lncRNA biology, providing many functional and mechanistic insights that have increased our understanding of this gene class. In this review, we examine the key discoveries and insights made in plant lncRNA biology over the past two and a half decades. We describe how discoveries made in the pregenomics era have informed efforts to identify and functionally characterize lncRNAs in the subsequent decades. We provide an overview of the functional archetypes into which characterized plant lncRNAs fit and speculate on new avenues of research that may uncover yet more archetypes. Finally, this review discusses the challenges facing the field and some exciting new molecular and computational approaches that may help inform lncRNA comparative and functional analyses.

Comparative analysis of tissue-specific genes in maize based on machine learning models: CNN performs technically best, LightGBM performs biologically soundest

Introduction: With the advancement of RNA-seq technology and machine learning, training large-scale RNA-seq data from databases with machine learning models can generally identify genes with important regulatory roles that were previously missed by standard linear analytic methodologies. Finding tissue-specific genes could improve our comprehension of the relationship between tissues and genes. However, few machine learning models for transcriptome data have been deployed and compared to identify tissue-specific genes, particularly for plants. Methods: In this study, an expression matrix was processed with linear models (Limma), machine learning models (LightGBM), and deep learning models (CNN) with information gain and the SHAP strategy based on 1,548 maize multi-tissue RNA-seq data obtained from a public database to identify tissue-specific genes. In terms of validation, V-measure values were computed based on k-means clustering of the gene sets to evaluate their technical complementarity. Furthermore, GO analysis and literature retrieval were used to validate the functions and research status of these genes. Results: Based on clustering validation, the convolutional neural network outperformed others with higher V-measure values as 0.647, indicating that its gene set could cover as many specific properties of various tissues as possible, whereas LightGBM discovered key transcription factors. The combination of three gene sets produced 78 core tissue-specific genes that had previously been shown in the literature to be biologically significant. Discussion: Different tissue-specific gene sets were identified due to the distinct interpretation strategy for machine learning models and researchers may use multiple methodologies and strategies for tissue-specific gene sets based on their goals, types of data, and computational resources. This study provided comparative insight for large-scale data mining of transcriptome datasets, shedding light on resolving high dimensions and bias difficulties in bioinformatics data processing.

Anthocyanins in metabolites of purple corn

Purple corn (Zea mays L.) is a special variety of corn, rich in a large amount of anthocyanins and other functional phytochemicals, and has always ranked high in the economic benefits of the corn industry. However, most studies on the stability of agronomic traits and the interaction between genotype and environment in cereal crops focus on yield. In order to further study the accumulation and stability of special anthocyanins in the growth process of purple corn, this review starts with the elucidation of anthocyanins in purple corn, the biosynthesis process and the gene regulation mechanism behind them, points out the influence of anthocyanin metabolism on anthocyanin metabolism, and introduces the influence of environmental factors on anthocyanin accumulation in detail, so as to promote the multi-field production of purple corn, encourage the development of color corn industry and provide new opportunities for corn breeders and growers.

IGTCM: An integrative genome database of traditional Chinese medicine plants

Fully understanding traditional Chinese medicines (TCMs) is still challenging because of the extreme complexity of their chemical components and mechanisms of action. The TCM Plant Genome Project aimed to obtain genetic information, determine gene functions, discover regulatory networks of herbal species, and elucidate the molecular mechanisms involved in the disease prevention and treatment, thereby accelerating the modernization of TCMs. A comprehensive database that contains TCM-related information will provide a vital resource. Here, we present an integrative genome database of TCM plants (IGTCM) that contains 14,711,220 records of 83 annotated TCM-related herb genomes, including 3,610,350 genes, 3,534,314 proteins and corresponding coding sequences, and 4,032,242 RNAs, as well as 1033 non-redundant component records for 68 herbs, downloaded and integrated from the GenBank and RefSeq databases. For minimal interconnectivity, each gene, protein, and component was annotated using the eggNOG-mapper tool and Kyoto Encyclopedia of Genes and Genomes database to acquire pathway information and enzyme classifications. These features can be linked across several species and different components. The IGTCM database also provides visualization and sequence similarity search tools for data analyses. These annotated herb genome sequences in IGTCM database are a necessary resource for systematically exploring genes related to the biosynthesis of compounds that have significant medicinal activities and excellent agronomic traits that can be used to improve TCM-related varieties through molecular breeding. It also provides valuable data and tools for future research on drug discovery and the protection and rational use of TCM plant resources. The IGTCM database is freely available at http://yeyn.group:96/.

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/β-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.

Comprehensive study of rice YABBY gene family: evolution, expression and interacting proteins analysis

As plant-specific transcription regulators, YABBYs are involved in plant growth, development and stress responses. However, little information is available about genome-wide screening and identification of OsYABBY-interacting proteins. In this study, phylogenetic relationship, gene structure, protein structure and gene expression profile of eight OsYABBYs were carried out, all of which indicated that OsYABBYs were involved in different developmental processes and had functional differentiation. More importantly, PPI (protein-protein interaction) analysis and molecular docking simulation predicted that WUSCHEL-related homeobox (WOX) proteins might be interacting proteins of OsYABBYs. Yeast two-hybrid (Y2H) and luciferase complementation imaging assays (LCI) further confirmed that OsYABBYs (except for OsYABBY7) could interact with OsWOX3A in vitro and in vivo. In addition, OsYABBY3 and OsYABBY5 also could interact with OsWUS. Taken together, our results provided valuable information for further elucidating OsYABBYs regulation mechanism in improving rice performance.

Genome-wide association study of quality traits and starch pasting properties of maize kernels

BACKGROUND

Starch are the main nutritional components of maize (Zea mays L.), and starch pasting properties are widely used as essential indicators for quality estimation. Based on the previous studies, various genes related to pasting properties have been identified in maize. However, the loci underlying variations in starch pasting properties in maize inbred lines remain to be identified.

RESULTS

To investigate the genetic architecture of these traits, the starch pasting properties were examined based on 292 maize inbred lines, which were genotyped with the MaizeSNP50 BeadChip composed of 55,126 evenly spaced, random SNPs. A genome-wide association study (GWAS) implemented in the software package FarmCPU was employed to identify genomic loci for the starch pasting properties. 48 SNPs were found to be associated with pasting properties. Moreover, 37 candidate genes were correlated with pasting properties. Among the candidate genes, GRMZM2G143646 and GRMZM2G166407 were associated with breakdown and final viscosity significantly, and both genes encode PPR (Pentatricopeptide repeat) protein. We used GWAS to explore candidate genes of maize starch pasting properties in this study. The identified candidate genes will be useful for further understanding of the genetic architecture of starch pasting properties in maize.

CONCLUSION

This study showed a complex regulation network about maize quality trait and starch pasting properties. It may provide some useful markers for marker assisted selection and a basis for cloning the genes behind these SNPs.

Confronting Secondary Metabolites with Water Uptake and Transport in Plants under Abiotic Stress

Phenolic compounds and glucosinolates are secondary plant metabolites that play fundamental roles in plant resistance to abiotic stress. These compounds have been found to increase in stress situations related to plant adaptive capacity. This review assesses the functions of phenolic compounds and glucosinolates in plant interactions involving abiotic stresses such as drought, salinity, high temperature, metals toxicity, and mineral deficiency or excess. Furthermore, their relation with water uptake and transport mediated through aquaporins is reviewed. In this way, the increases of phenolic compounds and glucosinolate synthesis have been related to primary responses to abiotic stress and induction of resistance. Thus, their metabolic pathways, root exudation, and external application are related to internal cell and tissue movement, with a lack of information in this latter aspect.

Different Leaf Anatomical Responses to Water Deficit in Maize and Soybean

The stomata on leaf surfaces control gas exchange and water loss, closing during dry periods to conserve water. The distribution and size of stomatal complexes is determined by epidermal cell differentiation and expansion during leaf growth. Regulation of these processes in response to water deficit may result in stomatal anatomical plasticity as part of the plant acclimation to drought. We quantified the leaf anatomical plasticity under water-deficit conditions in maize and soybean over two experiments. Both species produced smaller leaves in response to the water deficit, partly due to the reductions in the stomata and pavement cell size, although this response was greater in soybean, which also produced thicker leaves under severe stress, whereas the maize leaf thickness did not change. The stomata and pavement cells were smaller with the reduced water availability in both species, resulting in higher stomatal densities. Stomatal development (measured as stomatal index, SI) was suppressed in both species at the lowest water availability, but to a greater extent in maize than in soybean. The result of these responses is that in maize leaves, the stomatal area fraction (f_gc) was consistently reduced in the plants grown under severe but not moderate water deficit, whereas the f_gc did not decrease in the water-stressed soybean leaves. The water deficit resulted in the reduced expression of one of two (maize) or three (soybean) SPEECHLESS orthologs, and the expression patterns were correlated with SI. The vein density (VD) increased in both species in response to the water deficit, although the effect was greater in soybean. This study establishes a mechanism of stomatal development plasticity that can be applied to other species and genotypes to develop or investigate stomatal development plasticity.

QTL mapping identifies novel major loci for kernel row number-associated ear fasciation, ear prolificacy and tillering in maize (Zea mays L.)

Maize ear fasciation originates from excessive or abnormal proliferation of the ear meristem and usually manifests as flattened multiple-tipped ear and/or disordered kernel arrangement. Ear prolificacy expresses as multiple ears per plant or per node. Both ear fasciation and prolificacy can affect grain yield. The genetic control of the two traits was studied using two recombinant inbred line populations (B73 × Lo1016 and Lo964 × Lo1016) with Lo1016 and Lo964 as donors of ear fasciation and prolificacy, respectively. Ear fasciation-related traits, number of kernel rows (KRN), ear prolificacy and number of tillers were phenotyped in multi-year field experiments. Ear fasciation traits and KRN showed relatively high heritability (h ² > 0.5) except ratio of ear diameters. For all ear fasciation-related traits, fasciation level positively correlated with KRN (0.30 ≤ r ≤ 0.68). Prolificacy and tillering were not correlated and their h ² ranged from 0.41 to 0.78. QTL mapping identified four QTLs for ear fasciation, on chromosomes 1 (two QTLs), 5 and 7, the latter two overlapping with QTLs for number of kernel rows. Notably, at these QTLs, the Lo1016 alleles increased both ear fasciation and KRN across populations, thus showing potential breeding applicability. Four and five non-overlapping QTLs were mapped for ear prolificacy and tillering, respectively. Two ear fasciation QTLs, qFas1.2 and qFas7, overlapped with fasciation QTLs mapped in other studies and spanned compact plant2 and ramosa1 candidate genes. Our study identified novel ear fasciation loci and alleles positively affecting grain yield components, and ear prolificacy and tillering loci which are unexpectedly still segregating in elite maize materials, contributing useful information for genomics-assisted breeding programs.

LettuceGDB: The community database for lettuce genetics and omics

As a globally popular leafy vegetable and a representative plant of the Asteraceae family, lettuce has great economic and academic significance. In the last decade, high-throughput sequencing, phenotyping, and other multi-omics data in lettuce have accumulated on a large scale, thus increasing the demand for an integrative lettuce database. Here, we report the establishment of a comprehensive lettuce database, LettuceGDB (https://www.lettucegdb.com/). As an omics data hub, the current LettuceGDB includes two reference genomes with detailed annotations; re-sequencing data from over 1000 lettuce varieties; a collection of more than 1300 worldwide germplasms and millions of accompanying phenotypic records obtained with manual and cutting-edge phenomics technologies; re-analyses of 256 RNA sequencing datasets; a complete miRNAome; extensive metabolite information for representative varieties and wild relatives; epigenetic data on the genome-wide chromatin accessibility landscape; and various lettuce research papers published in the last decade. Five hierarchically accessible functions (Genome, Genotype, Germplasm, Phenotype, and O-Omics) have been developed with a user-friendly interface to enable convenient data access. Eight built-in tools (Assembly Converter, Search Gene, BLAST, JBrowse, Primer Design, Gene Annotation, Tissue Expression, Literature, and Data) are available for data downloading and browsing, functional gene exploration, and experimental practice. A community forum is also available for information sharing, and a summary of current research progress on different aspects of lettuce is included. We believe that LettuceGDB can be a comprehensive functional database amenable to data mining and database-driven exploration, useful for both scientific research and lettuce breeding.

Toward a data infrastructure for the Plant Cell Atlas

We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms. The Human Cell Atlas has developed an extensive infrastructure for human and mouse single cell data, while the European Bioinformatics Institute has developed a Single Cell Expression Atlas, that currently houses several plant data sets. We discuss issues related to appropriate ontologies for describing a plant single cell experiment. We imagine how such an infrastructure will enable biologists and data scientists to glean new insights into plant biology in the coming decades, as long as such data are made accessible to the community in an open manner.

Maize cytolines as models to study the impact of different cytoplasms on gene expression under heat stress conditions

BACKGROUND

Crops are under constant pressure due to global warming, which unfolds at a much faster pace than their ability to adapt through evolution. Agronomic traits are linked to cytoplasmic-nuclear genome interactions. It thus becomes important to understand the influence exerted by the organelles on gene expression under heat stress conditions and profit from the available genetic diversity. Maize (Zea mays) cytolines allow us to investigate how the gene expression changes under heat stress conditions in three different cytoplasmic environments, but each having the same nucleus. Analyzing retrograde signaling in such an experimental set-up has never been done before. Here, we quantified the response of three cytolines to heat stress as differentially expressed genes (DEGs), and studied gene expression patterns in the context of existing polymorphism in their organellar genomes.

RESULTS

Our study unveils a plethora of new genes and GO terms that are differentially expressed or enriched, respectively, in response to heat stress. We report 19,600 DEGs as responding to heat stress (out of 30,331 analyzed), which significantly enrich 164 GO biological processes, 30 GO molecular functions, and 83 GO cell components. Our approach allowed for the discovery of a significant number of DEGs and GO terms that are not common in the three cytolines and could therefore be linked to retrograde signaling. Filtering for DEGs with a fold regulation > 2 (absolute values) that are exclusive to just one of the cytolines, we find a total of 391 up- and down-DEGs. Similarly, there are 19 GO terms with a fold enrichment > 2 that are cytoline-specific. Using GBS data we report contrasting differences in the number of DEGs and GO terms in each cytoline, which correlate with the genetic distances between the mitochondrial genomes (but not chloroplast) and the original nuclei of the cytolines, respectively.

CONCLUSIONS

The experimental design used here adds a new facet to the paradigm used to explain how gene expression changes in response to heat stress, capturing the influence exerted by different organelles upon one nucleus rather than investigating the response of several nuclei in their innate cytoplasmic environments.

Deciphering Macromolecular Interactions Involved in Abiotic Stress Signaling: A Review of Bioinformatics Analysis

Plant functioning and responses to abiotic stresses largely involve regulations at the transcriptomic level via complex interactions of signal molecules, signaling cascades, and regulators. Nevertheless, all the signaling networks involved in responses to abiotic stresses have not yet been fully established. The in-depth analysis of transcriptomes in stressed plants has become a relevant state-of-the-art methodology to study these regulations and signaling pathways that allow plants to cope with or attempt to survive abiotic stresses. The plant science and molecular biology community has developed databases about genes, proteins, protein-protein interactions, protein-DNA interactions and ontologies, which are valuable sources of knowledge for deciphering such regulatory and signaling networks. The use of these data and the development of bioinformatics tools help to make sense of transcriptomic data in specific contexts, such as that of abiotic stress signaling, using functional biological approaches. The aim of this chapter is to present and assess some of the essential online tools and resources that will allow novices in bioinformatics to decipher transcriptomic data in order to characterize the cellular processes and functions involved in abiotic stress responses and signaling. The analysis of case studies further describes how these tools can be used to conceive signaling networks on the basis of transcriptomic data. In these case studies, particular attention was paid to the characterization of abiotic stress responses and signaling related to chemical and xenobiotic stressors.

Coexpression network and trans-activation analyses of maize reproductive phasiRNA loci

The anther-enriched phased, small interfering RNAs (phasiRNAs) play vital roles in sustaining male fertility in grass species. Their long non-coding precursors are synthesized by RNA polymerase II and are likely regulated by transcription factors (TFs). A few putative transcriptional regulators of the 21- or 24-nucleotide phasiRNA loci (referred to as 21- or 24-PHAS loci) have been identified in maize (Zea mays), but whether any of the individual TFs or TF combinations suffice to activate any PHAS locus is unclear. Here, we identified the temporal gene coexpression networks (modules) associated with maize anther development, including two modules highly enriched for the 21- or 24-PHAS loci. Comparisons of these coexpression modules and gene sets dysregulated in several reported male sterile TF mutants provided insights into TF timing with regard to phasiRNA biogenesis, including antagonistic roles for OUTER CELL LAYER4 and MALE STERILE23. Trans-activation assays in maize protoplasts of individual TFs using bulk-protoplast RNA-sequencing showed that two of the TFs coexpressed with 21-PHAS loci could activate several 21-nucleotide phasiRNA pathway genes but not transcription of 21-PHAS loci. Screens for combinatorial activities of these TFs and, separately, the recently reported putative transcriptional regulators of 24-PHAS loci using single-cell (protoplast) RNA-sequencing, did not detect reproducible activation of either 21-PHAS or 24-PHAS loci. Collectively, our results suggest that the endogenous transcriptional machineries and/or chromatin states in the anthers are necessary to activate reproductive PHAS loci.

Leaf rolling in bread wheat (Triticum aestivum L.) is controlled by the upregulation of a pair of closely linked/duplicate zinc finger homeodomain class transcription factors during moisture stress conditions

Zinc finger-homeodomain (ZF-HDs) class IV transcriptional factors (TFs) is a plant-specific transcription factor and play a key role in stress responses, plant growth, development, and hormonal signaling. In this study, two new leaf rolling TFs genes, namely TaZHD1 and TaZHD10, were identified in wheat using comparative genomic analysis of the target region that carried a major QTL for leaf rolling identified through multi-environment phenotyping and high throughput genotyping of a RIL population. Structural and functional annotation of the candidate ZHD genes with its closest rice orthologs reflects the species-specific evolution and, undoubtedly, validates the notions of remote-distance homology concept. Meanwhile, the morphological analysis resulted in contrasting difference for leaf rolling in extreme RILs between parental lines HD2012 and NI5439 at booting and heading stages. Transcriptome-wide expression profiling revealed that TaZHD10 transcripts showed significantly higher expression levels than TaZHD1 in all leaf tissues upon drought stress. The relative expression of these genes was further validated by qRT-PCR analysis, which also showed consistent results across the studied genotypes at the booting and anthesis stage. The contrasting modulation of these genes under drought conditions and the available evidenced for its epigenetic behavior that might involve the regulation of metabolic and gene regulatory networks. Prediction of miRNAs resulted in five Tae-miRs that could be associated with RNAi mediated control of TaZHD1 and TaZHD10 putatively involved in the metabolic pathway controlling rolled leaf phenotype. Gene interaction network analysis indicated that TaZHD1 and TaZHD10 showed pleiotropic effects and might also involve other functions in wheat in addition to leaf rolling. Overall, the results increase our understanding of TaZHD genes and provide valuable information as robust candidate genes for future functional genomics research aiming for the breeding of wheat varieties tolerant to leaf rolling.

Application of crop wild relatives in modern breeding: An overview of resources, experimental and computational methodologies

Global agricultural industries are under pressure to meet the future food demand; however, the existing crop genetic diversity might not be sufficient to meet this expectation. Advances in genome sequencing technologies and availability of reference genomes for over 300 plant species reveals the hidden genetic diversity in crop wild relatives (CWRs), which could have significant impacts in crop improvement. There are many ex-situ and in-situ resources around the world holding rare and valuable wild species, of which many carry agronomically important traits and it is crucial for users to be aware of their availability. Here we aim to explore the available ex-/in- situ resources such as genebanks, botanical gardens, national parks, conservation hotspots and inventories holding CWR accessions. In addition we highlight the advances in availability and use of CWR genomic resources, such as their contribution in pangenome construction and introducing novel genes into crops. We also discuss the potential and challenges of modern breeding experimental approaches (e.g. de novo domestication, genome editing and speed breeding) used in CWRs and the use of computational (e.g. machine learning) approaches that could speed up utilization of CWR species in breeding programs towards crop adaptability and yield improvement.

Identification and Analysis of Stress-Associated Proteins (SAPs) Protein Family and Drought Tolerance of ZmSAP8 in Transgenic Arabidopsis

Stress-associated proteins (SAPs), a class of A20/AN1 zinc finger proteins, play vital roles in plant stress response. However, investigation of SAPs in maize has been very limited. Herein, to better trace the evolutionary history of SAPs in maize and plants, 415 SAPs were identified in 33 plant species and four species of other kingdoms. Moreover, gene duplication mode exploration showed whole genome duplication contributed largely to SAP gene expansion in angiosperms. Phylogeny reconstruction was performed with all identified SAPs by the maximum likelihood (ML) method and the SAPs were divided into five clades. SAPs within the same clades showed conserved domain composition. Focusing on maize, nine ZmSAPs were identified. Further promoter cis-elements and stress-induced expression pattern analysis of ZmSAPs indicated that ZmSAP8 was a promising candidate in response to drought stress, which was the only AN1-AN1-C2H2-C2H2 type SAP in maize and belonged to clade I. Additionally, ZmSAP8 was located in the nucleus and had no transactivation activity in yeast. Overexpressing ZmSAP8 enhanced the tolerance to drought stress in Arabidopsis thaliana, with higher seed germination and longer root length. Our results should benefit the further functional characterization of ZmSAPs.

Low-Density Reference Fingerprinting SNP Dataset of CIMMYT Maize Lines for Quality Control and Genetic Diversity Analyses

CIMMYT maize lines (CMLs), which represent the tropical maize germplasm, are freely available worldwide. All currently released 615 CMLs and fourteen temperate maize inbred lines were genotyped with 180 kompetitive allele-specific PCR single nucleotide polymorphisms to develop a reference fingerprinting SNP dataset that can be used to perform quality control (QC) and genetic diversity analyses. The QC analysis identified 25 CMLs with purity, identity, or mislabeling issues. Further field observation, purification, and re-genotyping of these CMLs are required. The reference fingerprinting SNP dataset was developed for all of the currently released CMLs with 152 high-quality SNPs. The results of principal component analysis and average genetic distances between subgroups showed a clear genetic divergence between temperate and tropical maize, whereas the three tropical subgroups partially overlapped with one another. More than 99% of the pairs of CMLs had genetic distances greater than 0.30, showing their high genetic diversity, and most CMLs are distantly related. The heterotic patterns, estimated with the molecular markers, are consistent with those estimated using pedigree information in two major maize breeding programs at CIMMYT. These research findings are helpful for ensuring the regeneration and distribution of the true CMLs, via QC analysis, and for facilitating the effective utilization of the CMLs, globally.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

Transcriptional responses to gibberellin in the maize tassel and control by DELLA domain proteins

The plant hormone gibberellin (GA) impacts plant growth and development differently depending on the developmental context. In the maize (Zea mays) tassel, application of GA alters floral development, resulting in the persistence of pistils. GA signaling is achieved by the GA-dependent turnover of DELLA domain transcription factors, encoded by dwarf8 (d8) and dwarf9 (d9) in maize. The D8-Mpl and D9-1 alleles disrupt GA signaling, resulting in short plants and normal tassel floret development in the presence of excess GA. However, D9-1 mutants are unable to block GA-induced pistil development. Gene expression in developing tassels of D8-Mpl and D9-1 mutants and their wild-type siblings was determined upon excess GA₃ and mock treatments. Using GA-sensitive transcripts as reporters of GA signaling, we identified a weak loss of repression under mock conditions in both mutants, with the effect in D9-1 being greater. D9-1 was also less able to repress GA signaling in the presence of excess GA₃ . We treated a diverse set of maize inbred lines with excess GA₃ and measured the phenotypic consequences on multiple aspects of development (e.g., height and pistil persistence in tassel florets). Genotype affected all GA-regulated phenotypes but there was no correlation between any of the GA-affected phenotypes, indicating that the complexity of the relationship between GA and development extends beyond the two-gene epistasis previously demonstrated for GA and brassinosteroid biosynthetic mutants.

Natural alleles of the abscisic acid catabolism gene ZmAbh4 modulate water use efficiency and carbon isotope discrimination in maize

Altering plant water use efficiency (WUE) is a promising approach for achieving sustainable crop production in changing climate scenarios. Here, we show that WUE can be tuned by alleles of a single gene discovered in elite maize (Zea mays) breeding material. Genetic dissection of a genomic region affecting WUE led to the identification of the gene ZmAbh4 as causative for the effect. CRISPR/Cas9-mediated ZmAbh4 inactivation increased WUE without growth reductions in well-watered conditions. ZmAbh4 encodes an enzyme that hydroxylates the phytohormone abscisic acid (ABA) and initiates its catabolism. Stomatal conductance is regulated by ABA and emerged as a major link between variation in WUE and discrimination against the heavy carbon isotope (Δ13C) during photosynthesis in the C4 crop maize. Changes in Δ13C persisted in kernel material, which offers an easy-to-screen proxy for WUE. Our results establish a direct physiological and genetic link between WUE and Δ13C through a single gene with potential applications in maize breeding.

A genome for Cissus illustrates features underlying its evolutionary success in dry savannas

Cissus is the largest genus in Vitaceae and is mainly distributed in the tropics and subtropics. Crassulacean acid metabolism (CAM), a photosynthetic adaptation to the occurrence of succulent leaves or stems, indicates that convergent evolution occurred in response to drought stress during species radiation. Here we provide the chromosomal level assembly of Cissus rotundifolia (an endemic species in Eastern Africa) and a genome-wide comparison with grape to understand genome divergence within an ancient eudicot family. Extensive transcriptome data were produced to illustrate the genetics underpinning C. rotundifolia's ecological adaption to seasonal aridity. The modern karyotype and smaller genome of C. rotundifolia (n = 12, 350.69 Mb/1C), which lack further whole-genome duplication, were mainly derived from gross chromosomal rearrangements such as fusions and segmental duplications, and were sculpted by a very recent burst of retrotransposon activity. Bias in local gene amplification contributed to its remarkable functional divergence from grape, and the specific proliferated genes associated with abiotic and biotic responses (e.g. HSP-20, NBS-LRR) enabled C. rotundifolia to survive in a hostile environment. Reorganization of existing enzymes of CAM characterized as diurnal expression patterns of relevant genes further confer the ability to thrive in dry savannas.

Maize Flavonoid Biosynthesis, Regulation, and Human Health Relevance: A Review

Maize is one of the most important crops for human and animal consumption and contains a chemical arsenal essential for survival: flavonoids. Moreover, flavonoids are well known for their beneficial effects on human health. In this review, we decided to organize the information about maize flavonoids into three sections. In the first section, we include updated information about the enzymatic pathway of maize flavonoids. We describe a total of twenty-one genes for the flavonoid pathway of maize. The first three genes participate in the general phenylpropanoid pathway. Four genes are common biosynthetic early genes for flavonoids, and fourteen are specific genes for the flavonoid subgroups, the anthocyanins, and flavone C-glycosides. The second section explains the tissue accumulation and regulation of flavonoids by environmental factors affecting the expression of the MYB-bHLH-WD40 (MBW) transcriptional complex. The study of transcription factors of the MBW complex is fundamental for understanding how the flavonoid profiles generate a palette of colors in the plant tissues. Finally, we also include an update of the biological activities of C3G, the major maize anthocyanin, including anticancer, antidiabetic, and antioxidant effects, among others. This review intends to disclose and integrate the existing knowledge regarding maize flavonoid pigmentation and its relevance in the human health sector.

Bioinformatics approaches and applications in plant biotechnology

BACKGROUND

In recent years, major advance in molecular biology and genomic technologies have led to an exponential growth in biological information. As the deluge of genomic information, there is a parallel growth in the demands of tools in the storage and management of data, and the development of software for analysis, visualization, modelling, and prediction of large data set.

MAIN BODY

Particularly in plant biotechnology, the amount of information has multiplied exponentially with a large number of databases available from many individual plant species. Efficient bioinformatics tools and methodologies are also developed to allow rapid genome sequence and the study of plant genome in the 'omics' approach. This review focuses on the various bioinformatic applications in plant biotechnology, and their advantages in improving the outcome in agriculture. The challenges or limitations faced in plant biotechnology in the aspect of bioinformatics approach that explained the low progression in plant genomics than in animal genomics are also reviewed and assessed.

CONCLUSION

There is a critical need for effective bioinformatic tools, which are able to provide longer reads with unbiased coverage in order to overcome the complexity of the plant's genome. The advancement in bioinformatics is not only beneficial to the field of plant biotechnology and agriculture sectors, but will also contribute enormously to the future of humanity.