qTeller: a tool for comparative multi-genomic gene expression analysis

Tools and Resources at the Maize Genetics and Genomics Database (MaizeGDB)

The Maize Genetics and Genomics Database (MaizeGDB) is the community resource for maize researchers, offering a suite of tools, informatics resources, and curated data sets to support maize genetics, genomics, and breeding research. Here, we provide an overview of the key resources available at MaizeGDB, including maize genomes, comparative genomics, and pan-genomics tools. This review aims to familiarize users with the range of options available for maize research and highlights the importance of MaizeGDB as a central hub for the maize research community. By providing a detailed snapshot of the database's capabilities, we hope to enable researchers to make use of MaizeGDB's resources, ultimately assisting them to better study the evolution and diversity of maize.

A maize semi-dwarf mutant reveals a GRAS transcription factor involved in brassinosteroid signaling

Brassinosteroids (BR) and gibberellins (GA) regulate plant height and leaf angle in maize (Zea mays). Mutants with defects in BR or GA biosynthesis or signaling identify components of these pathways and enhance our knowledge about plant growth and development. In this study, we characterized three recessive mutant alleles of GRAS transcription factor 42 (gras42) in maize, a GRAS transcription factor gene orthologous to the DWARF AND LOW TILLERING (DLT) gene of rice (Oryza sativa). These maize mutants exhibited semi-dwarf stature, shorter and wider leaves, and more upright leaf angle. Transcriptome analysis revealed a role for GRAS42 as a determinant of BR signaling. Analysis of the expression consequences from loss of GRAS42 in the gras42-mu1021149 mutant indicated a weak loss of BR signaling in the mutant, consistent with its previously demonstrated role in BR signaling in rice. Loss of BR signaling was also evident by the enhancement of weak BR biosynthetic mutant alleles in double mutants of nana plant1-1 and gras42-mu1021149. The gras42-mu1021149 mutant had little effect on GA-regulated gene expression, suggesting that GRAS42 is not a regulator of core GA signaling genes in maize. Single-cell expression data identified gras42 expressed among cells in the G2/M phase of the cell cycle consistent with its previously demonstrated role in cell cycle gene expression in Arabidopsis (Arabidopsis thaliana). Cis-acting natural variation controlling GRAS42 transcript accumulation was identified by expression genome-wide association study (eGWAS) in maize. Our results demonstrate a conserved role for GRAS42/SCARECROW-LIKE 28 (SCL28)/DLT in BR signaling, clarify the role of this gene in GA signaling, and suggest mechanisms of tillering and leaf angle control by BR.

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

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

Unique genetic architecture of prolificacy in 'Sikkim Primitive' maize unraveled through whole-genome resequencing-based DNA polymorphism

KEY MESSAGE

'Sikkim Primitive' maize landrace, unique for prolificacy (7-9 ears per plant) possesses unique genomic architecture in branching and inflorescence-related gene(s), and locus Zm00001eb365210 encoding glycosyltransferases was identified as the putative candidate gene underlying QTL (qProl-SP-8.05) for prolificacy. The genotype possesses immense usage in breeding high-yielding baby-corn genotypes. 'Sikkim Primitive' is a native landrace of North Eastern Himalayas, and is characterized by having 7-9 ears per plant compared to 1-2 ears in normal maize. Though 'Sikkim Primitive' was identified in the 1960s, it has not been characterized at a whole-genome scale. Here, we sequenced the entire genome of an inbred (MGUSP101) derived from 'Sikkim Primitive' along with three non-prolific (HKI1128, UMI1200, and HKI1105) and three prolific (CM150Q, CM151Q and HKI323) inbreds. A total of 942,417 SNPs, 24,160 insertions, and 27,600 deletions were identified in 'Sikkim Primitive'. The gene-specific functional mutations in 'Sikkim Primitive' were classified as 10,847 missense (54.36%), 402 non-sense (2.015%), and 8,705 silent (43.625%) mutations. The number of transitions and transversions specific to 'Sikkim Primitive' were 666,021 and 279,950, respectively. Among all base changes, (G to A) was the most frequent (215,772), while (C to G) was the rarest (22,520). Polygalacturonate 4-α-galacturonosyltransferase enzyme involved in pectin biosynthesis, cell-wall organization, nucleotide sugar, and amino-sugar metabolism was found to have unique alleles in 'Sikkim Primitive'. The analysis further revealed the Zm00001eb365210 gene encoding glycosyltransferases as the putative candidate underlying QTL (qProl-SP-8.05) for prolificacy in 'Sikkim Primitive'. High-impact nucleotide variations were found in ramosa3 (Zm00001eb327910) and zeaxanthin epoxidase1 (Zm00001eb081460) genes having a role in branching and inflorescence development in 'Sikkim Primitive'. The information generated unraveled the genetic architecture and identified key genes/alleles unique to the 'Sikkim Primitive' genome. This is the first report of whole-genome characterization of the 'Sikkim Primitive' landrace unique for its high prolificacy.

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/.

Genome-Wide Identification and Functional Analysis of Nitrate Transporter Genes (NPF, NRT2 and NRT3) in Maize

Nitrate is the primary form of nitrogen uptake in plants, mainly transported by nitrate transporters (NRTs), including NPF (NITRATE TRANSPORTER 1/PEPTIDE TRANSPORTER FAMILY), NRT2 and NRT3. In this study, we identified a total of 78 NPF, seven NRT2, and two NRT3 genes in maize. Phylogenetic analysis divided the NPF family into eight subgroups (NPF1-NPF8), consistent with the results in Arabidopsis thaliana and rice. The NRT2 family appears to have evolved more conservatively than the NPF family, as NRT2 genes contain fewer introns. The promoters of all NRTs are rich in cis-acting elements responding to biotic and abiotic stresses. The expression of NRTs varies in different tissues and developmental stages, with some NRTs only expressed in specific tissues or developmental stages. RNA-seq analysis using Xu178 revealed differential expression of NRTs in response to nitrogen starvation and nitrate resupply. Moreover, the expression patterns of six key NRTs genes (NPF6.6, NPF6.8, NRT2.1, NRT2.5 and NRT3.1A/B) varied in response to alterations in nitrogen levels across distinct maize inbred lines with different nitrogen uptake rates. This work enhances our understanding of the structure and expression of NRTs genes, and their roles in nitrate response, paving the way for improving maize nitrogen efficiency through molecular breeding.

A role for heritable transcriptomic variation in maize adaptation to temperate environments

Background

Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments.

Result

We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A GWAS for alternative splicing identified 49,897 splicing QTLs (sQTLs) for 7614 genes. Genes harboring both cis-eQTLs and cis-sQTLs in linkage disequilibrium were disproportionately likely to encode transcription factors or were annotated as responding to one or more stresses. Independent component analysis of gene expression data identified loci regulating co-expression modules involved in oxidation reduction, response to water deprivation, plastid biogenesis, protein biogenesis, and plant-pathogen interaction. Several genes involved in cell proliferation, flower development, DNA replication, and gene silencing showed lower gene expression variation explained by genetic factors between temperate and tropical maize lines. A GWAS of 27 previously published phenotypes identified several candidate genes overlapping with genomic intervals showing signatures of selection during adaptation to temperate environments.

Conclusion

Our results illustrate how maize transcriptional regulatory networks enable changes in transcriptional regulation to adapt to temperate regions.

Supplementary information

The online version contains supplementary material available at 10.1186/s13059-023-02891-3.

ZmCCT10-relayed photoperiod sensitivity regulates natural variation in the arithmetical formation of male germinal cells in maize

Extensive mutational screening studies have documented genes regulating anther and pollen development. Knowledge concerning how formation of male germinal cell is arithmetically controlled in natural populations, under different environmental conditions, is lacking. We counted pollen number within a single anther and a maize-teosinte BC₂ S₃ recombinant inbred line population to identify ZmCCT10 as a major determinant of pollen number variation. ZmCCT10 was originally identified as a photoperiod-sensitive negative regulator of flowering. ZmCCT10 inactivation, after transposon insertion within its promoter, is proposed to have accelerated maize spread toward higher latitudes, thus allowing temperate maize to flower under long-day conditions. We showed that the active ZmCCT10 allele decreased pollen formation. As different active and inactive ZmCCT10 alleles have been found in natural maize populations, this represents the first report of a gene controlling pollen number in a crop natural population. These findings suggest that higher pollen number, which provides a competitive advantage in open-pollinated populations, may have been one of the major driving forces for the selection of an inactive ZmCCT10 allele during tropical maize domestication. We provide evidence that ZmCCT10 has opposite effects on cell proliferation of archesporial and tapetum cells and it modulates expression of key regulators during early anther development.

Transcriptional Regulation of zma-MIR528a by Action of Nitrate and Auxin in Maize

In recent years, miR528, a monocot-specific miRNA, has been assigned multifaceted roles during development and stress response in several plant species. However, the transcription regulation and the molecular mechanisms controlling MIR528 expression in maize are still poorly explored. Here we analyzed the zma-MIR528a promoter region and found conserved transcription factor binding sites related to diverse signaling pathways, including the nitrate (TGA1/4) and auxin (AuxRE) response networks. Accumulation of both pre-miR528a and mature miR528 was up-regulated by exogenous nitrate and auxin treatments during imbibition, germination, and maize seedling establishment. Functional promoter analyses demonstrated that TGA1/4 and AuxRE sites are required for transcriptional induction by both stimuli. Overall, our findings of the nitrogen- and auxin-induced zma-MIR528a expression through cis-regulatory elements in its promoter contribute to the knowledge of miR528 regulome.

Association mapping across a multitude of traits collected in diverse environments in maize

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data-18M markers-from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

The Original Form of C4-Photosynthetic Phosphoenolpyruvate Carboxylase Is Retained in Pooids but Lost in Rice

Poaceae is the most prominent monocot family that contains the primary cereal crops wheat, rice, and maize. These cereal species exhibit physiological diversity, such as different photosynthetic systems and environmental stress tolerance. Phosphoenolpyruvate carboxylase (PEPC) in Poaceae is encoded by a small multigene family and plays a central role in C4-photosynthesis and dicarboxylic acid metabolism. Here, to better understand the molecular basis of the cereal species diversity, we analyzed the PEPC gene family in wheat together with other grass species. We could designate seven plant-type and one bacterial-type grass PEPC groups, ppc1a, ppc1b, ppc2a, ppc2b, ppc3, ppc4, ppcC4, and ppc-b, respectively, among which ppc1b is an uncharacterized type of PEPC. Evolutionary inference revealed that these PEPCs were derived from five types of ancient PEPCs (ppc1, ppc2, ppc3, ppc4, and ppc-b) in three chromosomal blocks of the ancestral Poaceae genome. C4-photosynthetic PEPC (ppcC4 ) had evolved from ppc1b, which seemed to be arisen by a chromosomal duplication event. We observed that ppc1b was lost in many Oryza species but preserved in Pooideae after natural selection. In silico analysis of cereal RNA-Seq data highlighted the preferential expression of ppc1b in upper ground organs, selective up-regulation of ppc1b under osmotic stress conditions, and nitrogen response of ppc1b. Characterization of wheat ppc1b showed high levels of gene expression in young leaves, transcriptional responses under nitrogen and abiotic stress, and the presence of a Dof1 binding site, similar to ppcC4 in maize. Our results indicate the evolving status of Poaceae PEPCs and suggest the functional association of ppc1-derivatives with adaptation to environmental changes.

The pho1;2a'-m1.1 allele of Phosphate1 conditions misregulation of the phosphorus starvation response in maize (Zea mays ssp. mays L.)

Plant PHO1 proteins play a central role in the translocation and sensing of inorganic phosphate. The maize (Zea mays ssp. mays) genome encodes two co-orthologs of the Arabidopsis PHO1 gene, designated ZmPho1;2a and ZmPho1;2b. Here, we report the characterization of the transposon footprint allele Zmpho1;2a'-m1.1, which we refer to hereafter as pho1;2a. The pho1;2a allele is a stable derivative formed by excision of an Activator transposable element from the ZmPho1;2a gene. The pho1;2a allele contains an 8-bp insertion at the point of transposon excision that disrupts the reading frame and is predicted to generate a premature translational stop. We show that the pho1;2a allele is linked to a dosage-dependent reduction in Pho1;2a transcript accumulation and a mild reduction in seedling growth. Characterization of shoot and root transcriptomes under full nutrient, low nitrogen, low phosphorus, and combined low nitrogen and low phosphorus conditions identified 1100 differentially expressed genes between wild-type plants and plants carrying the pho1;2a mutation. Of these 1100 genes, 966 were upregulated in plants carrying pho1;2a, indicating the wild-type PHO1;2a to predominantly impact negative gene regulation. Gene set enrichment analysis of the pho1;2a-misregulated genes revealed associations with phytohormone signaling and the phosphate starvation response. In roots, differential expression was broadly consistent across all nutrient conditions. In leaves, differential expression was largely specific to low phosphorus and combined low nitrogen and low phosphorus conditions. Of 276 genes upregulated in the leaves of pho1;2a mutants in the low phosphorus condition, 153 were themselves induced in wild-type plants with respect to the full nutrient condition. Our observations suggest that Pho1;2a functions in the fine-tuning of the transcriptional response to phosphate starvation through maintenance and/or sensing of plant phosphate status.

Meta-QTL analysis and candidate genes identification for various abiotic stresses in maize (Zea mays L.) and their implications in breeding programs

Global climate change leads to the concurrence of a number of abiotic stresses including moisture stress (drought, waterlogging), temperature stress (heat, cold), and salinity stress, which are the major factors affecting maize production. To develop abiotic stress tolerance in maize, many quantitative trait loci (QTL) have been identified, but very few of them have been utilized successfully in breeding programs. In this context, the meta-QTL analysis of the reported QTL will enable the identification of stable/real QTL which will pave a reliable way to introgress these QTL into elite cultivars through marker-assisted selection. In this study, a total of 542 QTL were summarized from 33 published studies for tolerance to different abiotic stresses in maize to conduct meta-QTL analysis using BiomercatorV4.2.3. Among those, only 244 major QTL with more than 10% phenotypic variance were preferably utilised to carry out meta-QTL analysis. In total, 32 meta-QTL possessing 1907 candidate genes were detected for different abiotic stresses over diverse genetic and environmental backgrounds. The MQTL2.1, 5.1, 5.2, 5.6, 7.1, 9.1, and 9.2 control different stress-related traits for combined abiotic stress tolerance. The candidate genes for important transcription factor families such as ERF, MYB, bZIP, bHLH, NAC, LRR, ZF, MAPK, HSP, peroxidase, and WRKY have been detected for different stress tolerances. The identified meta-QTL are valuable for future climate-resilient maize breeding programs and functional validation of candidate genes studies, which will help to deepen our understanding of the complexity of these abiotic stresses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01294-9.

Genome-Wide Association Study Reveals Genetic Architecture and Candidate Genes for Yield and Related Traits under Terminal Drought, Combined Heat and Drought in Tropical Maize Germplasm

Maize (Zea mays L.) production is constrained by drought and heat stresses. The combination of these two stresses is likely to be more detrimental. To breed for maize cultivars tolerant of these stresses, 162 tropical maize inbred lines were evaluated under combined heat and drought (CHD) and terminal drought (TD) conditions. The mixed linear model was employed for the genome-wide association study using 7834 SNP markers and several phenotypic data including, days to 50% anthesis (AD) and silking (SD), husk cover (HUSKC), and grain yield (GY). In total, 66, 27, and 24 SNPs were associated with the traits evaluated under CHD, TD, and their combined effects, respectively. Of these, four single nucleotide polymorphism (SNP) markers (SNP_161703060 on Chr01, SNP_196800695 on Chr02, SNP_195454836 on Chr05, and SNP_51772182 on Chr07) had pleiotropic effects on both AD and SD under CHD conditions. Four SNPs (SNP_138825271 (Chr03), SNP_244895453 (Chr04), SNP_168561609 (Chr05), and SNP_62970998 (Chr06)) were associated with AD, SD, and HUSKC under TD. Twelve candidate genes containing phytohormone cis-acting regulating elements were implicated in the regulation of plant responses to multiple stress conditions including heat and drought. The SNPs and candidate genes identified in the study will provide invaluable information for breeding climate smart maize varieties under tropical conditions following validation of the SNP markers.