Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn

Association mapping of haploid male fertility in sweet corn

KEY MESSAGE

Association mapping of a subset of the SweetCAP diversity panel revealed ten single-nucleotide polymorphisms (SNPs) associated with haploid male fertility (HMF), which provided four candidate genes. Doubled haploid (DH) technology using in vivo haploid induction has dramatically improved the efficiency of maize breeding programs worldwide. However, limitations from genome doubling create a bottleneck for DH line production. To overcome such limitations, spontaneous haploid genome doubling (SHGD) has gained prominence over the last decade, specifically in field corn materials. On the contrary, SHGD in sweet corn has been largely overlooked. A subset of 286 sweet corn genotypes from the SweetCAP diversity panel was evaluated for their ability to restore male fertility in the haploid state, otherwise known as haploid male fertility (HMF). Association mapping identified ten single-nucleotide polymorphisms (SNPs) associated with HMF, which provided four candidate genes. Our results highlight significant variation for HMF, with 11 genotypes having > 54% HMF. These genotypes demonstrate HMF naturally exists in sweet corn germplasm and can be used for population improvement.

Unveiling the heterosis pattern of modern maize breeding in Southwest China through population structure and genetic diversity analysis

Maize (Zea mays L.) is an important food crop throughout the world and is also one of the earliest crops to use heterosis. In this study, we evaluated the genetic diversity, population structure, and selective sweep of 100 elite inbred maize lines collected from the current breeding program in Sichuan province, Southwest China, using 5,261,175 high-quality single nucleotide polymorphisms (SNPs). We discovered an abundance of genetic diversities and classified them into four groups. By combining kinship relationships, these groups were further divided into Tropic-local A, Improved-tropic, Tropic-local B, and Improved-local. Genomic differentiation was assessed using Fst values (0.21-0.44) as well as genetic diversity (π = 6.07 × 10-4 - 6.61 × 10-4). We generated 900 (90 × 10) hybrids using 90 and 10 inbred maize lines from 100 diverse maize germplasms. All hybrids were evaluated for 10 traits in three replicate tests across two locations. We found that the patterns of G1 × G3, G1 × G4, G2 × G3, and G3 × G4 exhibited significant heterosis in yield-related traits and have been used in commercial breeding. In addition, we also explored the relationship between 10 traits of hybrid offspring and the number of heterozygous SNP. Under most heterosis modes, the best linear unbiased estimation (BLUE) value of the trait was highly consistent with the trend of deleterious SNPs, but there was a deviation in the G1 × G3 mode. Taken together, the results provide insight into the utilization of the current maize germplasm in Sichuan province to improve hybrid breeding.

Large-scale metabolomic landscape of edible maize reveals convergent changes in metabolite differentiation and facilitates its breeding improvement

Edible maize is an important food crop that provides energy and nutrients to meet human health and nutritional requirements. However, how environmental pressures and human activity have shaped the metabolome of edible maize remains unclear. In this study, we collected 452 diverse edible maize accessions worldwide, including waxy, sweet, and field maize. A total of 3020 non-redundant metabolites, including 802 annotated metabolites, were identified using a two-step optimized approach, which generated the most comprehensive annotated metabolite dataset in plants to date. Although specific metabolite differentiation was detected between field and sweet maize and between field and waxy maize, convergent metabolite differentiation was the dominant pattern. We identified hub genes in all metabolite classes by hotspot analysis in a metabolite genome-wide association study. Seventeen and 15 hub genes were selected as the key differentiation genes for flavonoids and lipids, respectively. Surprisingly, almost all of these genes were under diversifying selection, suggesting that diversifying selection was the main genetic mechanism of convergent metabolic differentiation. Further genetic and molecular studies revealed the roles and genetic diversifying selection mechanisms of ZmGPAT11 in convergent metabolite differentiation in the lipid pathway. On the basis of our research, we established the first edible maize metabolome database, EMMDB (https://www.maizemdb.site/home/). We successfully used EMMDB for precision improvement of nutritional and flavor traits and bred the elite inbred line 6644_2, with greatly increased contents of flavonoids, lysophosphatidylcholines, lysophosphatidylethanolamines, and vitamins. Collectively, our study sheds light on the genetic mechanisms of metabolite differentiation in edible maize and provides a database for breeding improvement of flavor and nutritional traits in edible maize by metabolome precision design.

Using genome-wide associations and host-by-pathogen predictions to identify allelic interactions that control disease resistance

Characterizing the molecular mechanisms underlying disease symptom expression has been used to improve human health and disease resistance in crops and animal breeds. Quantitative trait loci and genome-wide association studies (GWAS) are widely used to identify genomic regions that are involved in disease progression. This study extends traditional GWAS significance tests of host and pathogen marker main effects by utilizing dual-genome reaction norm models to evaluate the importance of host-single nucleotide polymorphism (SNP) by pathogen-SNP interactions. Disease symptom severity data from Fusarium ear rot (FER) on maize (Zea mays L.) is used to demonstrate the use of both genomes in genomic selection models for breeding and the identification of loci that interact across organisms to impact FER disease development. Dual genome prediction models improved heritability estimates, error variances, and model accuracy while providing predictions for host-by-pathogen interactions that may be used to test the significance of SNP-SNP interactions. Independent GWAS for maize and Fusarium populations identified significantly associated loci and predictions that were used to evaluate the importance of interactions using two different association tests. Predictions from dual genome models were used to evaluate the significance of the SNP-SNP interactions that may be associated with population structure or polygenic effects. As well, association tests incorporating host and pathogen markers in models that also included genomic relationship matrices were used to account for population structure. Subsequent evaluation of protein-protein interactions from candidate genes near the interacting SNPs provides a further in silico evaluation method to expedite the identification of interacting genes.

Integrating phenomic selection using single-kernel near-infrared spectroscopy and genomic selection for corn breeding improvement

KEY MESSAGE

Phenomic selection using intact seeds is a promising tool to improve gain and complement genomic selection in corn breeding. Models that combine genomic and phenomic data maximize the predictive ability. Phenomic selection (PS) is a cost-effective method proposed for predicting complex traits and enhancing genetic gain in breeding programs. The statistical procedures are similar to those utilized in genomic selection (GS) models, but molecular markers data are replaced with phenomic data, such as near-infrared spectroscopy (NIRS). However, the use of NIRS applied to PS typically utilized destructive sampling or collected data after the establishment of selection experiments in the field. Here, we explored the application of PS using nondestructive, single-kernel NIRS in a sweet corn breeding program, focusing on predicting future, unobserved field-based traits of economic importance, including ear and vegetative traits. Three models were employed on a diversity panel: genomic and phenomic best linear unbiased prediction models, which used relationship matrices based on SNP and NIRS data, respectively, and a combined model. The genomic relationship matrices were evaluated with varying numbers of SNPs. Additionally, the PS model trained on the diversity panel was used to select doubled haploid (DH) lines for germination before planting, with predictions validated using observed data. The findings indicate that PS generated good predictive ability (e.g., 0.46 for plant height) and distinguished between high and low germination rates in untested DH lines. Although GS generally outperformed PS, the model combining both information yielded the highest predictive ability, with higher accuracies than GS when low marker densities were used. This study highlights NIRS's potential to achieve genetic gain where GS may not be feasible and to maintain/improve accuracy with SNP-based information while reducing genotyping costs.

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.

Genetic diversity and population structure of sweet corn in China as revealed by mSNP

Corn is a widely grown cereal crop that serves as a model plant for genetic and evolutionary studies. However, the heterosis pattern of sweet corn remains unclear. Here, we analysed the genetic diversity and population structure of 514 sweet corn inbred lines and 181 field corn inbred lines. The population structure study enabled the classification of sweet corn into four groups: temperate sweet corns 1 and 2, tropical sweet corn, and subtropical sweet corn, in addition to the temperate and tropical field corn groups. Temperate sweet corn groups 1 and 2 were merged into the temperate sweet corn cluster in the phylogenetic trees. Principal component analysis divided sweet corn into four groups: temperate groups 1 and 2, tropical, and subtropical. Sweet corn exhibited lower levels of genetic diversity, polymorphism information content, and minor allele frequency than field corn. The average genetic distances and differentiation coefficients between inbreds within each sweet corn group were lower than those within field corn groups, indicating a relatively narrow genetic base in sweet corn. Taken together, the 514 sweet corn inbred lines can be divided into four groups: temperate 1, temperate 2, tropical, and subtropical. The classification of sweet corn groups in this study provides a reference for the breeding of sweet corn.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01533-1.

Mechanisms, Machinery, and Dynamics of Chromosome Segregation in Zea mays

Zea mays (maize) is both an agronomically important crop and a powerful genetic model system with an extensive molecular toolkit and genomic resources. With these tools, maize is an optimal system for cytogenetic study, particularly in the investigation of chromosome segregation. Here, we review the advances made in maize chromosome segregation, specifically in the regulation and dynamic assembly of the mitotic and meiotic spindle, the inheritance and mechanisms of the abnormal chromosome variant Ab10, the regulation of chromosome-spindle interactions via the spindle assembly checkpoint, and the function of kinetochore proteins that bridge chromosomes and spindles. In this review, we discuss these processes in a species-specific context including features that are both conserved and unique to Z. mays. Additionally, we highlight new protein structure prediction tools and make use of these tools to identify several novel kinetochore and spindle assembly checkpoint proteins in Z. mays.

Integrated Transcriptome and Metabolome Analysis Reveals Mechanism of Flavonoid Synthesis During Low-Temperature Storage of Sweet Corn Kernels

Sweet corn is a globally important food source and vegetable renowned for its rich nutritional content. However, post-harvest quality deterioration remains a significant challenge due to sweet corn's high sensitivity to environmental factors. Currently, low-temperature storage is the primary method for preserving sweet corn; however, the molecular mechanisms involved in this process remain unclear. In this study, kernels stored at different temperatures (28 °C and 4 °C) for 1, 3, and 5 days after harvest were collected for physiological and transcriptomic analysis. Low temperature storage significantly improved the PPO and SOD activity in sweet corn kernels compared to storage at a normal temperature. A total of 1993 common differentially expressed genes (DEGs) were identified in kernels stored at low temperatures across all three time points. Integrated analysis of transcriptomic and previous metabolomic data revealed that low temperature storage significantly affected flavonoid biosynthesis. Furthermore, 11 genes involved in flavonoid biosynthesis exhibited differential expression across the three storage periods, including CHI, HCT, ANS, F3'H, F3'5'H, FLS, and NOMT, with Eriodictyol, Myricetin, and Hesperetin-7-O-glucoside among the key flavonoids. Correlation analysis revealed three AP2/ERF-ERF transcription factors (EREB14, EREB182, and EREB200) as potential regulators of flavonoid biosynthesis during low temperature treatment. These results enhance our understanding of the mechanisms of flavonoid synthesis in sweet corn kernels during low-temperature storage.

Streamlined whole-genome genotyping through NGS-enhanced thermal asymmetric interlaced (TAIL)-PCR

Whole-genome genotyping (WGG) stands as a pivotal element in genomic-assisted plant breeding. Nevertheless, sequencing-based approaches for WGG continue to be costly, primarily owing to the high expenses associated with library preparation and the laborious protocol. During prior development of foreground and background integrated genotyping by sequencing (FBI-seq), we discovered that any sequence-specific primer (SP) inherently possesses the capability to amplify a massive array of stable and reproducible non-specific PCR products across the genome. Here, we further improved FBI-seq by replacing the adapter ligated by Tn5 transposase with an arbitrary degenerate (AD) primer. The protocol for the enhanced FBI-seq unexpectedly mirrors a simplified thermal asymmetric interlaced (TAIL)-PCR, a technique that is widely used for isolation of flanking sequences. However, the improved TAIL-PCR maximizes the primer-template mismatched annealing capabilities of both SP and AD primers. In addition, leveraging of next-generation sequencing enhances the ability of this technique to assay tens of thousands of genome-wide loci for any species. This cost-effective, user-friendly, and powerful WGG tool, which we have named TAIL-PCR by sequencing (TAIL-peq), holds great potential for widespread application in breeding programs, thereby facilitating genome-assisted crop improvement.

Multi-layer molecular analysis reveals distinctive metabolomic and transcriptomic profiles of different sweet corn varieties

In plants, sugar metabolism involves a complex interplay of genetic, molecular and environmental factors. To better understand the molecular mechanisms underlying these processes, we utilized a multi-layered approach that integrated transcriptomic and metabolomic datasets generated from multiple different varieties of sweet corn. Through this analysis, we found 2533 genes that were differentially expressed in the immature kernel tissues of sweet corn, including genes involved in transcriptional regulation, sugar metabolism, primary metabolism, and other processes associated with adaptability of sweet corn. We also detected 31 differential metabolites among the three types of sweet corn. Utilizing an integrated approach encompassing transcriptomics and eGWAS, we elucidated the transcriptional regulatory patterns governing these differential metabolites. Specifically, we delved into the transcriptional modulation of malate- and ubiquitin-associated genes across a range of sweet corn varieties, shedding new light on the molecular mechanisms underlying their regulation. This study provides a framework for future research aimed at improving the current understanding of sugar metabolism and regulatory gene networks in sweet corn, which could ultimately lead to the development of novel strategies for crop improvement.

Prediction of resistance, virulence, and host-by-pathogen interactions using dual-genome prediction models

KEY MESSAGE

Integrating disease screening data and genomic data for host and pathogen populations into prediction models provides breeders and pathologists with a unified framework to develop disease resistance. Developing disease resistance in crops typically consists of exposing breeding populations to a virulent strain of the pathogen that is causing disease. While including a diverse set of pathogens in the experiments would be desirable for developing broad and durable disease resistance, it is logistically complex and uncommon, and limits our capacity to implement dual (host-by-pathogen)-genome prediction models. Data from an alternative disease screening system that challenges a diverse sweet corn population with a diverse set of pathogen isolates are provided to demonstrate the changes in genetic parameter estimates that result from using genomic data to provide connectivity across sparsely tested experimental treatments. An inflation in genetic variance estimates was observed when among isolate relatedness estimates were included in prediction models, which was moderated when host-by-pathogen interaction effects were incorporated into models. The complete model that included genomic similarity matrices for host, pathogen, and interaction effects indicated that the proportion of phenotypic variation in lesion size that is attributable to host, pathogen, and interaction effects was similar. Estimates of the stability of lesion size predictions for host varieties inoculated with different isolates and the stability of isolates used to inoculate different hosts were also similar. In this pathosystem, genetic parameter estimates indicate that host, pathogen, and host-by-pathogen interaction predictions may be used to identify crop varieties that are resistant to specific virulence mechanisms and to guide the deployment of these sources of resistance into pathogen populations where they will be more effective.

Seedling root system adaptation to water availability during maize domestication and global expansion

The maize root system has been reshaped by indirect selection during global adaptation to new agricultural environments. In this study, we characterized the root systems of more than 9,000 global maize accessions and its wild relatives, defining the geographical signature and genomic basis of variation in seminal root number. We demonstrate that seminal root number has increased during maize domestication followed by a decrease in response to limited water availability in locally adapted varieties. By combining environmental and phenotypic association analyses with linkage mapping, we identified genes linking environmental variation and seminal root number. Functional characterization of the transcription factor ZmHb77 and in silico root modeling provides evidence that reshaping root system architecture by reducing the number of seminal roots and promoting lateral root density is beneficial for the resilience of maize seedlings to drought.

Enhanced pan-genomic resources at the maize genetics and genomics database

Pan-genomes, encompassing the entirety of genetic sequences found in a collection of genomes within a clade, are more useful than single reference genomes for studying species diversity. This is especially true for a species like Zea mays, which has a particularly diverse and complex genome. Presenting pan-genome data, analyses, and visualization is challenging, especially for a diverse species, but more so when pan-genomic data is linked to extensive gene model and gene data, including classical gene information, markers, insertions, expression and proteomic data, and protein structures as is the case at MaizeGDB. Here, we describe MaizeGDB's expansion to include the genic subset of the Zea pan-genome in a pan-gene data center featuring the maize genomes hosted at MaizeGDB, and the outgroup teosinte Zea genomes from the Pan-Andropoganeae project. The new data center offers a variety of browsing and visualization tools, including sequence alignment visualization, gene trees and other tools, to explore pan-genes in Zea that were calculated by the pipeline Pandagma. Combined, these data will help maize researchers study the complexity and diversity of Zea, and to use the comparative functions to validate pan-gene relationships for a selected gene model.

Utilizing genomic prediction to boost hybrid performance in a sweet corn breeding program

Sweet corn breeding programs, like field corn, focus on the development of elite inbred lines to produce commercial hybrids. For this reason, genomic selection models can help the in silico prediction of hybrid crosses from the elite lines, which is hypothesized to improve the test cross scheme, leading to higher genetic gain in a breeding program. This study aimed to explore the potential of implementing genomic selection in a sweet corn breeding program through hybrid prediction in a within-site across-year and across-site framework. A total of 506 hybrids were evaluated in six environments (California, Florida, and Wisconsin, in the years 2020 and 2021). A total of 20 traits from three different groups were measured (plant-, ear-, and flavor-related traits) across the six environments. Eight statistical models were considered for prediction, as the combination of two genomic prediction models (GBLUP and RKHS) with two different kernels (additive and additive + dominance), and in a single- and multi-trait framework. Also, three different cross-validation schemes were tested (CV1, CV0, and CV00). The different models were then compared based on the correlation between the estimated breeding values/total genetic values and phenotypic measurements. Overall, heritabilities and correlations varied among the traits. The models implemented showed good accuracies for trait prediction. The GBLUP implementation outperformed RKHS in all cross-validation schemes and models. Models with additive plus dominance kernels presented a slight improvement over the models with only additive kernels for some of the models examined. In addition, models for within-site across-year and across-site performed better in the CV0 than the CV00 scheme, on average. Hence, GBLUP should be considered as a standard model for sweet corn hybrid prediction. In addition, we found that the implementation of genomic prediction in a sweet corn breeding program presented reliable results, which can improve the testcross stage by identifying the top candidates that will reach advanced field-testing stages.

Unveiling the sweetness: evaluating yield and quality attributes of early generation sweet corn (Zea mays subsp. sachharata) inbred lines through morphological, biochemical and marker-based approaches

BACKGROUND

Sweet corn is gaining tremendous demand worldwide due to urbanization and changing consumer preferences. However, genetic improvement in this crop is being limited by narrow genetic base and other undesirable agronomic traits that hinder the development of superior cultivars. The main requirement in this direction is the development of potentially promising parental lines. One of the most important strategies in this direction is to develop such lines from hybrid-oriented source germplasm which may provide diverse base material with desirable biochemical and agro-morphological attributes.

METHODS AND RESULTS

The study was undertaken to carry out morphological and biochemical evaluation of 80 early generation inbred lines (S2) of sweet corn that were developed from a cross between two single cross sweet corn hybrids (Mithas and Sugar-75). Moreover, validation of favourable recessive alleles for sugar content was carried out using SSR markers. The 80 sweet corn inbreds evaluated for phenotypic characterization showed wide range of variability with respect to different traits studied. The highest content of total carotenoids was found in the inbred S27 (34 μg g-1) followed by the inbred S65 (31.1 μg g-1). The highest content for total sugars was found in S60 (8.54%) followed by S14 (8.34%). Molecular characterization of 80 inbred lines led to the identification of seven inbreds viz., S21, S28, S47, S48, S49, S53, and S54, carrying the alleles specific to the sugary gene (su1) with respect to the markers umc2061 and bnlg1937. Comparing the results of scatter plot for biochemical and morphological traits, it was revealed that inbreds S9, S23, S27 and S36 contain high levels of total sugars and total carotenoids along with moderate values for amylose and yield attributing traits.

CONCLUSION

The inbred lines identified with desirable biochemical and agro-morphological attributes in the study could be utilized as source of favourable alleles in sweet corn breeding programmes after further validation for disease resistance and other agronomic traits. Consequently, the study will not only enhance the genetic base of sweet corn germplasm but also has the potential to develop high-yielding hybrids with improved quality. The inbreds possessing su1 gene on the basis of umc2061 and bnlg1937 markers were also found to possess high sugar content. This indicates the potential of these lines as desirable candidates for breeding programs aimed at improving sweet corn yield and quality. These findings also demonstrate the effectiveness of the molecular markers in facilitating marker-assisted selection for important traits in sweet corn breeding.

Maize terpene synthase 1 impacts insect behavior via the production of monoterpene volatiles β-myrcene and linalool

Plant-derived volatiles are important mediators of plant-insect interactions as they can provide cues for host location and quality, or act as direct or indirect defense molecules. The volatiles produced by Zea mays (maize) include a range of terpenes, likely produced by several of the terpene synthases (TPS) present in maize. Determining the roles of specific terpene volatiles and individual TPSs in maize-insect interactions is challenging due to the promiscuous nature of TPSs in vitro and their potential for functional redundancy. In this study, we used metabolite GWAS of a sweetcorn diversity panel infested with Spodoptera frugiperda (fall armyworm) to identify genetic correlations between TPSs and individual volatiles. This analysis revealed a correlation between maize terpene synthase 1 (ZmTPS1) and emission of the monoterpene volatiles linalool and β-myrcene. Electroantennogram assays showed gravid S. frugiperda could detect both linalool and β-myrcene. Quantification of headspace volatiles in a maize tps1 loss-of-function mutant confirmed that ZmTPS1 is an important contributor to linalool and β-myrcene emission in maize. Furthermore, pairwise choice assays between tps1 mutant and wild-type plants showed that ZmTPS1, and by extension its volatile products, aid host location in the chewing insect S. frugiperda, yet repel the sap-sucking pest, Rhopalosiphum maidis (corn leaf aphid). On the other hand, ZmTPS1 had no impact on indirect defense via the recruitment of the parasitoid Cotesia marginiventris. ZmTPS1 is therefore an important mediator of the interactions between maize and its insect pests.

Preharvest 24-epibrassinolide treatment prolongs harvest duration and shelf life in sweet corn

Sweet corn is perishable and have limited harvest duration and shelf life due to their quality deterioration. Reactive oxygen species (ROS) are one of the most predominant factors for maintaining quality of sweet corn during and after harvest. Brassinosteroids (BRs) can enhance the activity of antioxidant enzymes and decrease the ROS level in plants. In this study, we found that a bioactive BR (24-epibrassinolide, EBR) treatment before harvest markedly inhibited change of quality indicators (MDA content, weight loss rate, and soluble sugar content) during and after harvest. Further analysis revealed that EBR promoted the activity and transcriptions of antioxidant enzymes, maintaining lower ROS level in kernels. Meanwhile, exogenous EBR increased the expression level of genes controlling sucrose transport in sweet corn kernels. Bioinformatics and binding analysis identified that BR transcription factor ZmBES1/ZmBZR1-10 might potentially bind to and upregulate transcriptions of antioxidant enzyme genes including SOD and POD genes, and sucrose transport-related genes including SUT and SWEET genes. These results indicated that exogenous application of EBR ameliorates quality during and after harvest by improving the antioxidant capacity and photosynthetic assimilates accumulation rate of sweet corn, thus prolonging harvest duration and shelf life in sweet corn.

Gene mining and genomics-assisted breeding empowered by the pangenome of tea plant Camellia sinensis

Tea is one of the world's oldest crops and is cultivated to produce beverages with various flavours. Despite advances in sequencing technologies, the genetic mechanisms underlying key agronomic traits of tea remain unclear. In this study, we present a high-quality pangenome of 22 elite cultivars, representing broad genetic diversity in the species. Our analysis reveals that a recent long terminal repeat burst contributed nearly 20% of gene copies, introducing functional genetic variants that affect phenotypes such as leaf colour. Our graphical pangenome improves the efficiency of genome-wide association studies and allows the identification of key genes controlling bud flush timing. We also identified strong correlations between allelic variants and flavour-related chemistries. These findings deepen our understanding of the genetic basis of tea quality and provide valuable genomic resources to facilitate its genomics-assisted breeding.

A complete telomere-to-telomere assembly of the maize genome

A complete telomere-to-telomere (T2T) finished genome has been the long pursuit of genomic research. Through generating deep coverage ultralong Oxford Nanopore Technology (ONT) and PacBio HiFi reads, we report here a complete genome assembly of maize with each chromosome entirely traversed in a single contig. The 2,178.6 Mb T2T Mo17 genome with a base accuracy of over 99.99% unveiled the structural features of all repetitive regions of the genome. There were several super-long simple-sequence-repeat arrays having consecutive thymine-adenine-guanine (TAG) tri-nucleotide repeats up to 235 kb. The assembly of the entire nucleolar organizer region of the 26.8 Mb array with 2,974 45S rDNA copies revealed the enormously complex patterns of rDNA duplications and transposon insertions. Additionally, complete assemblies of all ten centromeres enabled us to precisely dissect the repeat compositions of both CentC-rich and CentC-poor centromeres. The complete Mo17 genome represents a major step forward in understanding the complexity of the highly recalcitrant repetitive regions of higher plant genomes.

Genetic basis of the oil biosynthesis in ultra-high-oil maize grains with an oil content exceeding 20

Vegetable oil is an important part of the human diet and has multiple industrial uses. The rapid increase in vegetable oil consumption has necessitated the development of viable methods for optimizing the oil content of plants. The key genes regulating the biosynthesis of maize grain oil remain mostly uncharacterized. In this study, by analyzing oil contents and performing bulked segregant RNA sequencing and mapping analyses, we determined that su1 and sh2-R mediate the shrinkage of ultra-high-oil maize grains and contribute to the increase in the grain oil content. Functional kompetitive allele-specific PCR (KASP) markers developed for su1 and sh2-R detected su1su1Sh2Sh2, Su1Su1sh2sh2, and su1su1sh2sh2 mutants among 183 sweet maize inbred lines. An RNA sequencing (RNA-seq) analysis indicated that genes differentially expressed between two conventional sweet maize lines and two ultra-high-oil maize lines were significantly associated with linoleic acid metabolism, cyanoamino acid metabolism, glutathione metabolism, alanine, aspartate, and glutamate metabolism, and nitrogen metabolism. A bulk segregant analysis and sequencing (BSA-seq) analysis identified another 88 genomic intervals related to grain oil content, 16 of which overlapped previously reported maize grain oil-related QTLs. The combined analysis of BSA-seq and RNA-seq data enabled the identification of candidate genes. The KASP markers for GRMZM2G176998 (putative WD40-like beta propeller repeat family protein), GRMZM2G021339 (homeobox-transcription factor 115), and GRMZM2G167438 (3-ketoacyl-CoA synthase) were significantly related to maize grain oil content. Another candidate gene, GRMZM2G099802 (GDSL-like lipase/acylhydrolase), catalyzes the final step of the triacylglycerol synthesis pathway and was expressed at significantly higher levels in the two ultra-high-oil maize lines than in the two conventional sweet maize lines. These novel findings will help clarify the genetic basis of the increased oil production in ultra-high-oil maize lines with grain oil contents exceeding 20%. The KASP markers developed in this study may be useful for breeding new high-oil sweet maize varieties.

Chromosome-level genome assembly of Microplitis manilae Ashmead, 1904 (Hymenoptera: Braconidae)

Microplitis manilae Ashmead (Hymenoptera: Braconidae) is an important parasitoid of agricultural pests in lepidopteran species. So far, two extant genome assembles from the genus Microplitis are fragmented. Here, we offered a high-quality genome assembly of M. manilae at the chromosome level with high accuracy and contiguity, assembled by ONT long-read, MGI-SEQ short-read, and Hi-C sequencing methods. The final assembled genome size was 282.85 Mb, with 268.17 Mb assigned to 11 pseudochromosomes. The scaffold N50 length was 25.23 Mb, and the complete BUSCO score was 98.61%. The genome contained 152.37 Mb of repetitive elements, representing 53.87% of the total genome size. We predicted 15,689 protein-coding genes, of which 13,580 genes were annotated functionally. Gene family evolution investigations of M. manilae revealed 615 expanded and 635 contracted gene families. The high-quality genome of M. manilae reported in this paper will be a useful genomic resource for research on parasitoid wasps in the future.

Revisiting maize Brittle endosperm-2 reveals new insights in BETL development and starchy endosperm filling

Rerouting the starch biosynthesis pathway in maize can generate specialty types, like sweet corn and waxy corn, with a drastically increasing global demand. Hence, a fine-tuning of starch metabolism is relevant to create diverse maize cultivars for end-use applications. Here, we characterized a new maize brittle endosperm mutant, referred to as bt1774, which exhibited decreased starch content but a dramatic increase of soluble sugars at maturity. Both endosperm and embryo development was impaired in bt1774 relative to the wild-type (WT), with a prominently arrested basal endosperm transfer layer (BETL). Map-based cloning revealed that BRITTLE ENDOSPERM2 (Bt2), which encodes a small subunit of ADP-glucose pyrophosphorylase (AGPase), is the causal gene for bt1774. A MuA2 element was found to be inserted into intron 2 of Bt2, leading to a severe decrease of its expression, in bt1774. This is in line with the irregular and loosely packed starch granules in the mutant. Transcriptome of endosperm at grain filling stage identified 1, 013 differentially expressed genes in bt1774, which were notably enriched in the BETL compartment, including ZmMRP1, Miniature1, MEG1, and BETLs. Gene expression of the canonical starch biosynthesis pathway was marginally disturbed in Bt1774. Combined with the residual 60% of starch in this nearly null mutant of Bt2, this data strongly suggests that an AGPase-independent pathway compensates for starch synthesis in the endosperm. Consistent with the BETL defects, zein accumulation was impaired in bt1774. Co-expression network analysis revealed that Bt2 probably has a role in intracellular signal transduction, besides starch synthesis. Altogether, we propose that Bt2 is likely involved in carbohydrate flux and balance, thus regulating both the BETL development and the starchy endosperm filling.

New algorithms for accurate and efficient de novo genome assembly from long DNA sequencing reads

Building de novo genome assemblies for complex genomes is possible thanks to long-read DNA sequencing technologies. However, maximizing the quality of assemblies based on long reads is a challenging task that requires the development of specialized data analysis techniques. We present new algorithms for assembling long DNA sequencing reads from haploid and diploid organisms. The assembly algorithm builds an undirected graph with two vertices for each read based on minimizers selected by a hash function derived from the k-mer distribution. Statistics collected during the graph construction are used as features to build layout paths by selecting edges, ranked by a likelihood function. For diploid samples, we integrated a reimplementation of the ReFHap algorithm to perform molecular phasing. We ran the implemented algorithms on PacBio HiFi and Nanopore sequencing data taken from haploid and diploid samples of different species. Our algorithms showed competitive accuracy and computational efficiency, compared with other currently used software. We expect that this new development will be useful for researchers building genome assemblies for different species.

Benchmarking of structural variant detection in the tetraploid potato genome using linked-read sequencing

It has recently been shown that structural variants (SV) can have a higher impact on gene expression variation compared to single nucleotide variants (SNV) in different plant species. Additionally, SV were associated with phenotypic variation in several crops. However, compared to the established SV detection based on short-read sequencing, less approaches were described for linked-read based SV calling. We therefore evaluated the performance of six linked-read SV callers compared to an established short-read SV caller based on simulated linked-reads in tetraploid potato. The objectives of our study were to i) compare the performance of SV callers based on linked-read sequencing to short-read sequencing, ii) examine the influence of SV type, SV length, haplotype incidence (HI), as well as sequencing coverage on the SV calling performance in the tetraploid potato genome, and iii) evaluate the accuracy of detecting insertions by linked-read compared to short-read sequencing. We observed high break point resolutions (BPR) detecting short SV and slightly lower BPR for large SV. Our observations highlighted the importance of short-read signals provided by Manta and LinkedSV to detect short SV. Manta and NAIBR performed well for detecting larger deletions, inversions, and duplications. Detected large SV were weakly influenced by the HI. Furthermore, we illustrated that large insertions can be assembled by Novel-X. Our results suggest the usage of the short-read and linked-read SV callers Manta, NAIBR, LinkedSV, and Novel-X based on at least 90x linked-read sequencing coverage to ensure the detection of a broad range of SV in the tetraploid potato genome.

Comparative transcriptome analyses shed light on the regulation of harvest duration and shelf life in sweet corn

Harvest duration and postharvest shelf life are two of the most important characters for sweet corn. However, the regulatory mechanism remains unclear. We performed a comparative transcriptome analysis of long harvest-duration and shelf-life sweet corn (LHS) and short harvest-duration and shelf-life field corn (SHS) at three stages, i.e. 10 days after pollination (10DAP), 22 days after pollination (22DAP), and 7 days after harvest (7DAH). We have observed the major transcriptome changes accompanying the harvest process in LHS corn. Gene expression pattern analysis and differentially expressed genes (DEGs) functional enrichments suggested an association between ROS metabolism in kernels with harvest duration and postharvest shelf life. The genes encoding cytochrome P450, peroxidase, peroxiredoxin, glutathione peroxidase, and glutathione S-transferase were upregulated specifically in LHS kernels during and after harvest compared to SHS kernels. These novel findings reveal a new regulatory mechanism of corn post-harvest shelf life and should be useful for extending harvest duration and shelf life for sweet corn.

Biocontrol endophytes Bacillus subtilis R31 influence the quality, transcriptome and metabolome of sweet corn

During colonization of soil and plants, biocontrol bacteria can effectively regulate the physiological metabolism of plants and induce disease resistance. To illustrate the influence of Bacillus subtilis R31 on the quality, transcriptome and metabolome of sweet corn, field studies were conducted at a corn experimental base in Zhuhai City. The results show that, after application of B. subtilis R31, sweet corn was more fruitful, with a 18.3 cm ear length, 5.0 cm ear diameter, 0.4 bald head, 403.9 g fresh weight of single bud, 272.0 g net weight of single ear, and 16.5 kernels sweetness. Combined transcriptomic and metabolomic analyses indicate that differentially expressed genes related to plant-pathogen interactions, MAPK signaling pathway-plant, phenylpropanoid biosynthesis, and flavonoid biosynthesis were significantly enriched. Moreover, the 110 upregulated DAMs were mainly involved in the flavonoid biosynthesis and flavone and flavonol biosynthesis pathways. Our study provides a foundation for investigating the molecular mechanisms by which biocontrol bacteria enhance crop nutrition and taste through biological means or genetic engineering at the molecular level.

Transcriptome Analysis Identifies Novel Genes Associated with Low-Temperature Seed Germination in Sweet Corn

Typically, sweet corn, particularly sh2 sweet corn, has low seed vigor owing to its high sugar and low starch content, which is a major problem in sweet corn production, particularly at low temperatures. There is considerable variation in the germination rates among sweet corn varieties under low-temperature conditions, and the underlying mechanisms behind this phenomenon remain unclear. In this study, we screened two inbred sweet corn lines (tolerant line L282 and sensitive line L693) differing in their low-temperature germination rates; while no difference was observed in their germination rates at normal temperatures. To identify the specifically induced genes influencing the germination capacity of sweet corn at low temperatures, a transcriptome analysis of the two lines was conducted at both normal and low temperatures. Compared to the lines at a normal temperature, 3926 and 1404 differently expressed genes (DEGs) were identified from L282 and L693, respectively, under low-temperature conditions. Of them, 830 DEGs were common DEGs (cDEGs) that were identified from both L282 and L693, which were majorly enriched in terms of microtubule-based processes, histone H3-K9 modification, single-organism cellular processes, and carbohydrate metabolic processes. In addition, 3096 special DEGs (sDEGs), with 2199 upregulated and 897 downregulated, were detected in the tolerant line L282, but not in the sensitive line L693. These sDEGs were primarily related to plasma membranes and oxygen-containing compounds. Furthermore, electric conductivity measurements demonstrated that the membrane of L282 experienced less damage, which is consistent with its strong tolerance at low temperatures. These results expand our understanding of the complex mechanisms involved in the cold germination of sweet corn and provide a set of candidate genes for further genetic analysis.

A high-quality chromosome-level genome assembly of Pelteobagrus vachelli provides insights into its environmental adaptation and population history

Pelteobagrus vachelli is a freshwater fish with high economic value, but the lack of genome resources has severely restricted its industrial development and population conservation. Here, we constructed the first chromosome-level genome assembly of P. vachelli with a total length of approximately 662.13 Mb and a contig N50 was 14.02 Mb, and scaffolds covering 99.79% of the assembly were anchored to 26 chromosomes. Combining the comparative genome results and transcriptome data under environmental stress (high temperature, hypoxia and Edwardsiella. ictaluri infection), the MAPK signaling pathway, PI3K-Akt signaling pathway and apelin signaling pathway play an important role in environmental adaptation of P. vachelli, and these pathways were interconnected by the ErbB family and involved in cell proliferation, differentiation and apoptosis. Population evolution analysis showed that artificial interventions have affected wild populations of P. vachelli. This study provides a useful genomic information for the genetic breeding of P. vachelli, as well as references for further studies on fish biology and evolution.

A genome-wide association study of folates in sweet corn kernels

Folate is commonly synthesized in natural plants and is an essential water-soluble vitamin of great importance inhuman health. Although the key genes involved in folate biosynthesis and transformation pathways have been identified in plants, the genetic architecture of folate in sweet corn kernels remain largely unclear. In this study, an association panel of 295 inbred lines of sweet corn was constructed. Six folate derivatives were quantified in sweet corn kernels at 20 days after pollination and a total of 95 loci were identified for eight folate traits using a genome-wide association study. A peak GWAS signal revealed that natural variation in ZmFCL, encoding a 5-formyltetrahydrofolate cyclo-ligase, accounted for 30.12% of phenotypic variation in 5-FTHF content. Further analysis revealed that two adjacent SNPs on the second exon resulting in an AA-to-GG in the gene and an Asn-to-Gly change in the protein could be the causative variant influencing 5-FTHF content. Meanwhile, 5-FTHF content was negatively correlated with ZmFCL expression levels in the population. These results extend our knowledge regarding the genetic basis of folate and provide molecular markers for the optimization of folate levels in sweet corn kernels.

GGDB: A Grameneae genome alignment database of homologous genes hierarchically related to evolutionary events

The genomes of Gramineae plants have been preferentially sequenced owing to their economic value. These genomes are often quite complex, for example harboring many duplicated genes, and are the main source of genetic innovation and often the result of recurrent polyploidization. Deciphering these complex genome structures and linking duplicated genes to specific polyploidization events are important for understanding the biology and evolution of plants. However, efforts have been hampered by the complexity of analyzing these genomes. Here, we analyzed 29 well-assembled and up-to-date Gramineae genome sequences by hierarchically relating duplicated genes in collinear regions to specific polyploidization or speciation events. We separated duplicated genes produced by each event, established lists of paralogous and orthologous genes, and ultimately constructed an online database, GGDB (http://www.grassgenome.com/). Homologous gene lists from each plant and between plants can be displayed, searched, and downloaded from the database. Interactive comparison tools are deployed to demonstrate homology among user-selected plants and to draw genome-scale or local alignment figures and gene-based phylogenetic trees corrected by exploiting gene collinearity. Using these tools and figures, users can easily detect structural changes in genomes and explore the effects of paleo-polyploidy on crop genome structure and function. The GGDB will provide a useful platform for improving our understanding of genome changes and functional innovation in Gramineae plants.

Genome-Wide Identification of Eucalyptus Heat Shock Transcription Factor Family and Their Transcriptional Analysis under Salt and Temperature Stresses

Heat shock transcription factors (HSFs) activate heat shock protein gene expression by binding their promoters in response to heat stress and are considered to be pivotal transcription factors in plants. Eucalyptus is a superior source of fuel and commercial wood. During its growth, high temperature or other abiotic stresses could impact its defense capability and growth. Hsf genes have been cloned and sequenced in many plants, but rarely in Eucalyptus. In this study, we used bioinformatics methods to analyze and identify Eucalyptus Hsf genes, their chromosomal localization and structure. The phylogenetic relationship and conserved domains of their encoded proteins were further analyzed. A total of 36 Hsf genes were identified and authenticated from Eucalyptus, which were scattered across 11 chromosomes. They could be classified into three classes (A, B and C). Additionally, a large number of stress-related cis-regulatory elements were identified in the upstream promoter sequence of HSF, and cis-acting element analysis indicated that the expression of EgHsf may be regulated by plant growth and development, metabolism, hormones and stress responses. The expression profiles of five representative Hsf genes, EgHsf4, EgHsf9, EgHsf13, EgHsf24 and EgHsf32, under salt and temperature stresses were examined by qRT-PCR. The results show that the expression pattern of class B genes (EgHsf4, EgHsf24 and EgHsf32) was more tolerant to abiotic stresses than that of class A genes (EgHsf9 and EgHsf13). However, the expressions of all tested Hsf genes in six tissues were at different levels. Finally, we investigated the network of interplay between genes, and the results suggest that there may be synergistic effects between different Hsf genes in response to abiotic stresses. We conclude that the Hsf gene family played an important role in the growth and developmental processes of Eucalyptus and could be vital for maintaining cell homeostasis against external stresses. This study provides basic information on the members of the Hsf gene family in Eucalyptus and lays the foundation for the functional identification of related genes and the further investigation of their biological functions in plant stress regulation.

Genetic Perturbation of the Starch Biosynthesis in Maize Endosperm Reveals Sugar-Responsive Gene Networks

In maize, starch mutants have facilitated characterization of key genes involved in endosperm starch biosynthesis such as large subunit of AGPase Shrunken2 (Sh2) and isoamylase type DBE Sugary1 (Su1). While many starch biosynthesis enzymes have been characterized, the mechanisms of certain genes (including Sugary enhancer1) are yet undefined, and very little is understood about the regulation of starch biosynthesis. As a model, we utilize commercially important sweet corn mutations, sh2 and su1, to genetically perturb starch production in the endosperm. To characterize the transcriptomic response to starch mutations and identify potential regulators of this pathway, differential expression and coexpression network analysis was performed on near-isogenic lines (NILs) (wildtype, sh2, and su1) in six genetic backgrounds. Lines were grown in field conditions and kernels were sampled in consecutive developmental stages (blister stage at 14 days after pollination (DAP), milk stage at 21 DAP, and dent stage at 28 DAP). Kernels were dissected to separate embryo and pericarp from the endosperm tissue and 3' RNA-seq libraries were prepared. Mutation of the Su1 gene led to minimal changes in the endosperm transcriptome. Responses to loss of sh2 function include increased expression of sugar (SWEET) transporters and of genes for ABA signaling. Key regulators of starch biosynthesis and grain filling were identified. Notably, this includes Class II trehalose 6-phosphate synthases, Hexokinase1, and Apetala2 transcription factor-like (AP2/ERF) transcription factors. Additionally, our results provide insight into the mechanism of Sugary enhancer1, suggesting a potential role in regulating GA signaling via GRAS transcription factor Scarecrow-like1.

Genome sequencing and population resequencing provide insights into the genetic basis of domestication and diversity of vegetable soybean

Vegetable soybean is one of the most important vegetables in China, and the demand for this vegetable has markedly increased worldwide over the past two decades. Here, we present a high-quality de novo genome assembly of the vegetable soybean cultivar Zhenong 6 (ZN6), which is one of the most popular cultivars in China. The 20 pseudochromosomes cover 94.57% of the total 1.01 Gb assembly size, with contig N50 of 3.84 Mb and scaffold N50 of 48.41 Mb. A total of 55 517 protein-coding genes were annotated. Approximately 54.85% of the assembled genome was annotated as repetitive sequences, with the most abundant long terminal repeat transposable elements. Comparative genomic and phylogenetic analyses with grain soybean Williams 82, six other Fabaceae species and Arabidopsis thaliana genomes highlight the difference of ZN6 with other species. Furthermore, we resequenced 60 vegetable soybean accessions. Alongside 103 previously resequenced wild soybean and 155 previously resequenced grain soybean accessions, we performed analyses of population structure and selective sweep of vegetable, grain, and wild soybean. They were clearly divided into three clades. We found 1112 and 1047 genes under selection in the vegetable soybean and grain soybean populations compared with the wild soybean population, respectively. Among them, we identified 134 selected genes shared between vegetable soybean and grain soybean populations. Additionally, we report four sucrose synthase genes, one sucrose-phosphate synthase gene, and four sugar transport genes as candidate genes related to important traits such as seed sweetness and seed size in vegetable soybean. This study provides essential genomic resources to promote evolutionary and functional genomics studies and genomically informed breeding for vegetable soybean.

The arches and spandrels of maize domestication, adaptation, and improvement

People living in the Balsas River basin in southwest México domesticated maize from the bushy grass teosinte. Nine thousand years later, in 2021, Ms. Deb Haaland - a member of the Pueblo of Laguna tribe of New Mexico - wore a dress adorned with a cornstalk when she was sworn in as the Secretary of Interior of the United States of America. This choice of garment highlights the importance of the coevolution of maize and the farmers who, through careful selection over thousands of years, domesticated maize and adapted the physiology and shoot architecture of maize to fit local environments and growth habits. Some traits such as tillering were directly selected on (arches), and others such as tassel size are the by-products (spandrels) of maize evolution. Here, we review current knowledge of the underlying cellular, developmental, physiological, and metabolic processes that were selected by farmers and breeders, which have positioned maize as a top global staple crop.

Genomic variation within the maize stiff-stalk heterotic germplasm pool

The stiff-stalk heterotic group in Maize (Zea mays L.) is an important source of inbreds used in U.S. commercial hybrid production. Founder inbreds B14, B37, B73, and, to a lesser extent, B84, are found in the pedigrees of a majority of commercial seed parent inbred lines. We created high-quality genome assemblies of B84 and four expired Plant Variety Protection (ex-PVP) lines LH145 representing B14, NKH8431 of mixed descent, PHB47 representing B37, and PHJ40, which is a Pioneer Hi-Bred International (PHI) early stiff-stalk type. Sequence was generated using long-read sequencing achieving highly contiguous assemblies of 2.13-2.18 Gbp with N50 scaffold lengths >200 Mbp. Inbred-specific gene annotations were generated using a core five-tissue gene expression atlas, whereas transposable element (TE) annotation was conducted using de novo and homology-directed methodologies. Compared with the reference inbred B73, synteny analyses revealed extensive collinearity across the five stiff-stalk genomes, although unique components of the maize pangenome were detected. Comparison of this set of stiff-stalk inbreds with the original Iowa Stiff Stalk Synthetic breeding population revealed that these inbreds represent only a proportion of variation in the original stiff-stalk pool and there are highly conserved haplotypes in released public and ex-Plant Variety Protection inbreds. Despite the reduction in variation from the original stiff-stalk population, substantial genetic and genomic variation was identified supporting the potential for continued breeding success in this pool. The assemblies described here represent stiff-stalk inbreds that have historical and commercial relevance and provide further insight into the emerging maize pangenome.

Towards population-scale long-read sequencing

Long-read sequencing technologies have now reached a level of accuracy and yield that allows their application to variant detection at a scale of tens to thousands of samples. Concomitant with the development of new computational tools, the first population-scale studies involving long-read sequencing have emerged over the past 2 years and, given the continuous advancement of the field, many more are likely to follow. In this Review, we survey recent developments in population-scale long-read sequencing, highlight potential challenges of a scaled-up approach and provide guidance regarding experimental design. We provide an overview of current long-read sequencing platforms, variant calling methodologies and approaches for de novo assemblies and reference-based mapping approaches. Furthermore, we summarize strategies for variant validation, genotyping and predicting functional impact and emphasize challenges remaining in achieving long-read sequencing at a population scale.

A pan-genomic approach to genome databases using maize as a model system

Research in the past decade has demonstrated that a single reference genome is not representative of a species' diversity. MaizeGDB introduces a pan-genomic approach to hosting genomic data, leveraging the large number of diverse maize genomes and their associated datasets to quickly and efficiently connect genomes, gene models, expression, epigenome, sequence variation, structural variation, transposable elements, and diversity data across genomes so that researchers can easily track the structural and functional differences of a locus and its orthologs across maize. We believe our framework is unique and provides a template for any genomic database poised to host large-scale pan-genomic data.

Chromosome-level genome assembly of a regenerable maize inbred line A188

BACKGROUND

The maize inbred line A188 is an attractive model for elucidation of gene function and improvement due to its high embryogenic capacity and many contrasting traits to the first maize reference genome, B73, and other elite lines. The lack of a genome assembly of A188 limits its use as a model for functional studies.

RESULTS

Here, we present a chromosome-level genome assembly of A188 using long reads and optical maps. Comparison of A188 with B73 using both whole-genome alignments and read depths from sequencing reads identify approximately 1.1 Gb of syntenic sequences as well as extensive structural variation, including a 1.8-Mb duplication containing the Gametophyte factor1 locus for unilateral cross-incompatibility, and six inversions of 0.7 Mb or greater. Increased copy number of carotenoid cleavage dioxygenase 1 (ccd1) in A188 is associated with elevated expression during seed development. High ccd1 expression in seeds together with low expression of yellow endosperm 1 (y1) reduces carotenoid accumulation, accounting for the white seed phenotype of A188. Furthermore, transcriptome and epigenome analyses reveal enhanced expression of defense pathways and altered DNA methylation patterns of the embryonic callus.

CONCLUSIONS

The A188 genome assembly provides a high-resolution sequence for a complex genome species and a foundational resource for analyses of genome variation and gene function in maize. The genome, in comparison to B73, contains extensive intra-species structural variations and other genetic differences. Expression and network analyses identify discrete profiles for embryonic callus and other tissues.