Differences in activity and stability drive transposable element variation in tropical and temperate maize.

Much of the profound interspecific variation in genome content has been attributed to transposable elements (TEs). To explore the extent of TE variation within species, we developed an optimized open-source algorithm, panEDTA, to de novo annotate TEs in a pangenome context. We then generated a unified TE annotation for a maize pangenome derived from 26 reference-quality genomes, which reveals an excess of 35.1 Mb of TE sequences per genome in tropical maize relative to temperate maize. A small number (n = 216) of TE families, mainly LTR retrotransposons, drive these differences. Evidence from the methylome, transcriptome, LTR age distribution, and LTR insertional polymorphisms reveals that 64.7% of the variability is contributed by LTR families that are young, less methylated, and more expressed in tropical maize, whereas 18.5% is driven by LTR families with removal or loss in temperate maize. Additionally, we find enrichment for Young LTR families adjacent to nucleotide-binding and leucine-rich repeat (NLR) clusters of varying copy number across lines, suggesting TE activity may be associated with disease resistance in maize.

Combined analysis of transposable elements and structural variation in maize genomes reveals genome contraction outpaces expansion.

Structural differences between genomes are a major source of genetic variation that contributes to phenotypic differences. Transposable elements, mobile genetic sequences capable of increasing their copy number and propagating themselves within genomes, can generate structural variation. However, their repetitive nature makes it difficult to characterize fine-scale differences in their presence at specific positions, limiting our understanding of their impact on genome variation. Domesticated maize is a particularly good system for exploring the impact of transposable element proliferation as over 70% of the genome is annotated as transposable elements. High-quality transposable element annotations were recently generated for de novo genome assemblies of 26 diverse inbred maize lines. We generated base-pair resolved pairwise alignments between the B73 maize reference genome and the remaining 25 inbred maize line assemblies. From this data, we classified transposable elements as either shared or polymorphic in a given pairwise comparison. Our analysis uncovered substantial structural variation between lines, representing both simple and complex connections between TEs and structural variants. Putative insertions in SNP depleted regions, which represent recently diverged identity by state blocks, suggest some TE families may still be active. However, our analysis reveals that within these recently diverged genomic regions, deletions of transposable elements likely account for more structural variation events and base pairs than insertions. These deletions are often large structural variants containing multiple transposable elements. Combined, our results highlight how transposable elements contribute to structural variation and demonstrate that deletion events are a major contributor to genomic differences.

Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits.

Plant height can be an indicator of plant health across environments and used to identify superior genotypes. Typically plant height is measured at a single timepoint when plants reach terminal height. Evaluating plant height using unoccupied aerial vehicles allows for measurements throughout the growing season, facilitating a better understanding of plant-environment interactions and the genetic basis of this complex trait. To assess variation throughout development, plant height data was collected from planting until terminal height at anthesis (14 flights 2018, 27 in 2019, 12 in 2020, and 11 in 2021) for a panel of ~500 diverse maize inbred lines. The percent variance explained in plant height throughout the season was significantly explained by genotype (9-48%), year (4-52%), and genotype-by-year interactions (14-36%) to varying extents throughout development. Genome-wide association studies revealed 717 significant single nucleotide polymorphisms associated with plant height and growth rate at different parts of the growing season specific to certain phases of vegetative growth. When plant height growth curves were compared to growth curves estimated from canopy cover, greater Fréchet distance stability was observed in plant height growth curves than for canopy cover. This indicated canopy cover may be more useful for understanding environmental modulation of overall plant growth and plant height better for understanding genotypic modulation of overall plant growth. This study demonstrated that substantial information can be gained from high temporal resolution data to understand how plants differentially interact with the environment and can enhance our understanding of the genetic basis of complex polygenic traits.

Genome-wide loss of CHH methylation with limited transcriptome changes in Setaria viridis DOMAINS REARRANGED METHYLTRANSFERASE (DRM) mutants.

The DOMAINS REARRANGED METHYLTRANSFERASEs (DRMs) are crucial for RNA-directed DNA methylation (RdDM) in plant species. Setaria viridis is a model monocot species with a relatively compact genome that has limited transposable element (TE) content. CRISPR-based genome editing approaches were used to create loss-of-function alleles for the two putative functional DRM genes in S. viridis to probe the role of RdDM. Double mutant (drm1ab) plants exhibit some morphological abnormalities but are fully viable. Whole-genome methylation profiling provided evidence for the widespread loss of methylation in CHH sequence contexts, particularly in regions with high CHH methylation in wild-type plants. Evidence was also found for the locus-specific loss of CG and CHG methylation, even in some regions that lack CHH methylation. Transcriptome profiling identified genes with altered expression in the drm1ab mutants. However, the majority of genes with high levels of CHH methylation directly surrounding the transcription start site or in nearby promoter regions in wild-type plants do not have altered expression in the drm1ab mutant, even when this methylation is lost, suggesting limited regulation of gene expression by RdDM. Detailed analysis of the expression of TEs identified several transposons that are transcriptionally activated in drm1ab mutants. These transposons are likely to require active RdDM for the maintenance of transcriptional repression.

Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions.

The regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent maps of potential transcriptional regulation. Here, we analyzed a large number of publically available maize (Zea mays) transcriptome data sets including >6000 RNA sequencing samples to generate 45 coexpression-based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, and tissue-and-genotype samples). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our coexpression-based GRNs to accurately predict covarying TF-target relationships in natural variation data sets, we found that presence/absence changes rather than quantitative changes in TF gene expression are more likely associated with changes in target gene expression. Integrating information from our TF-target predictions and previous expression quantitative trait loci (eQTL) mapping results provided support for 68 TFs underlying 74 previously identified trans-eQTL hotspots spanning a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species to detect putative regulators of important plant pathways and provides potential targets for breeding or biotechnological applications.

Importance of genetic architecture in marker selection decisions for genomic prediction.

KEY MESSAGE: We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait. Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.

Whole-genome assembly and annotation of northern wild rice, Zizania palustris L., supports a whole-genome duplication in the Zizania genus.

Zizania palustris L. (northern wild rice, NWR) is an aquatic grass native to North America that is notable for its nutritious grain. This is an important species with ecological, cultural and agricultural significance, specifically in the Great Lakes region of the USA. Using flow cytometry, we first estimated the NWR genome size to be 1.8 Gb. Using long- and short-range sequencing, Hi-C scaffolding and RNA-seq data from eight tissues, we generated an annotated whole-genome de novo assembly of NWR. The assembly was 1.29 Gb in length, highly repetitive (approx. 76.0%) and contained 46 421 putative protein-coding genes. The expansion of retrotransposons within the genome and a whole-genome duplication (WGD) after the Zizania-Oryza speciation event have both led to an increase in the genome size of NWR in comparison with Oryza sativa L. and Zizania latifolia. Both events depict a genome rapidly undergoing change over a short evolutionary time. Comparative analyses revealed the conservation of large syntenic blocks between NWR and O. sativa, which were used to identify putative seed-shattering genes. Estimates of divergence times revealed that the Zizania genus diverged from Oryza approximately 26-30 million years ago (26-30 MYA), whereas NWR and Z. latifolia diverged from one another approximately 6-8 MYA. Comparative genomics confirmed evidence of a WGD in the Zizania genus and provided support that the event occurred prior to the NWR-Z. latifolia speciation event. This genome assembly and annotation provides a valuable resource for comparative genomics in the Oryzeae tribe and provides an important resource for future conservation and breeding efforts of NWR.

Single-parent expression drives dynamic gene expression complementation in maize hybrids.

Single-parent expression (SPE) is defined as gene expression in only one of the two parents. SPE can arise from differential expression between parental alleles, termed non-presence/absence (non-PAV) SPE, or from the physical absence of a gene in one parent, termed PAV SPE. We used transcriptome data of diverse Zea mays (maize) inbreds and hybrids, including 401 samples from five different tissues, to test for differences between these types of SPE genes. Although commonly observed, SPE is highly genotype and tissue specific. A positive correlation was observed between the genetic distance of the two inbred parents and the number of SPE genes identified. Regulatory analysis showed that PAV SPE and non-PAV SPE genes are mainly regulated by cis effects, with a small fraction under trans regulation. Polymorphic transposable element insertions in promoter sequences contributed to the high level of cis regulation for PAV SPE and non-PAV SPE genes. PAV SPE genes were more frequently expressed in hybrids than non-PAV SPE genes. The expression of parentally silent alleles in hybrids of non-PAV SPE genes was relatively rare but occurred in most hybrids. Non-PAV SPE genes with expression of the silent allele in hybrids are more likely to exhibit above high parent expression level than hybrids that do not express the silent allele, leading to non-additive expression. This study provides a comprehensive understanding of the nature of non-PAV SPE and PAV SPE genes and their roles in gene expression complementation in maize hybrids.

Monitoring the interplay between transposable element families and DNA methylation in maize.

DNA methylation and epigenetic silencing play important roles in the regulation of transposable elements (TEs) in many eukaryotic genomes. A majority of the maize genome is derived from TEs that can be classified into different orders and families based on their mechanism of transposition and sequence similarity, respectively. TEs themselves are highly methylated and it can be tempting to view them as a single uniform group. However, the analysis of DNA methylation profiles in flanking regions provides evidence for distinct groups of chromatin properties at different TE families. These differences among TE families are reproducible in different tissues and different inbred lines. TE families with varying levels of DNA methylation in flanking regions also show distinct patterns of chromatin accessibility and modifications within the TEs. The differences in the patterns of DNA methylation flanking TE families arise from a combination of non-random insertion preferences of TE families, changes in DNA methylation triggered by the insertion of the TE and subsequent selection pressure. A set of nearly 70,000 TE polymorphisms among four assembled maize genomes were used to monitor the level of DNA methylation at haplotypes with and without the TE insertions. In many cases, TE families with high levels of DNA methylation in flanking sequence are enriched for insertions into highly methylated regions. The majority of the >2,500 TE insertions into unmethylated regions result in changes in DNA methylation in haplotypes with the TE, suggesting the widespread potential for TE insertions to condition altered methylation in conserved regions of the genome. This study highlights the interplay between TEs and the methylome of a major crop species.

Maize sugary enhancer1 (se1) is a gene affecting endosperm starch metabolism.

sugary enhancer1 (se1) is a naturally occurring mutant allele involved in starch metabolism in maize endosperm. It is a recessive modifier of sugary1 (su1) and commercially important in modern sweet corn breeding, but its molecular identity and mode of action remain unknown. Here, we developed a pair of near-isogenic lines, W822Gse (su1-ref/su1-ref se1/se1) and W822GSe (su1-ref/su1-ref Se1/Se1), that Mendelize the se1 phenotype in an su1-ref background. W822Gse kernels have lower starch and higher water soluble polysaccharide and sugars than W822GSe kernels. Using high-resolution genetic mapping, we found that wild-type Se1 is a gene Zm00001d007657 on chromosome 2 and a deletion of this gene causes the se1 phenotype. Comparative metabolic profiling of seed tissue between these 2 isolines revealed the remarkable difference in carbohydrate metabolism, with sucrose and maltose highly accumulated in the mutant. Se1 is predominantly expressed in the endosperm, with low expression in leaf and root tissues. Differential expression analysis identified genes enriched in both starch biosynthesis and degradation processes, indicating a pleiotropic regulatory effect of se1 Repressed expression of Se1 and Su1 in RNA interference-mediated transgenic maize validates that deletion of the gene identified as Se1 is a true causal gene responsible for the se1 phenotype. The findings contribute to our understanding of starch metabolism in cereal crops.

Variation and Inheritance of Small RNAs in Maize Inbreds and F1 Hybrids.

Small RNAs (sRNAs) regulate gene expression, play important roles in epigenetic pathways, and are hypothesized to contribute to hybrid vigor in plants. Prior investigations have provided valuable insights into associations between sRNAs and heterosis, often using a single hybrid genotype or tissue, but our understanding of the role of sRNAs and their potential value to plant breeding are limited by an incomplete picture of sRNA variation between diverse genotypes and development stages. Here, we provide a deep exploration of sRNA variation and inheritance among a panel of 108 maize (Zea mays) samples spanning five tissues from eight inbred parents and 12 hybrid genotypes, covering a spectrum of heterotic groups, genetic variation, and levels of heterosis for various traits. We document substantial developmental and genotypic influences on sRNA expression, with varying patterns for 21-nucleotide (nt), 22-nt, and 24-nt sRNAs. We provide a detailed view of the distribution of sRNAs in the maize genome, revealing a complex makeup that also shows developmental plasticity, particularly for 22-nt sRNAs. sRNAs exhibited substantially more variation between inbreds as compared with observed variation for gene expression. In hybrids, we identify locus-specific examples of nonadditive inheritance, mostly characterized as partial or complete dominance, but rarely outside the parental range. However, the global abundance of 21-nt, 22-nt, and 24-nt sRNAs varies very little between inbreds and hybrids, suggesting that hybridization affects sRNA expression principally at specific loci rather than on a global scale. This study provides a valuable resource for understanding the potential role of sRNAs in hybrid vigor.

Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

KEY MESSAGE: Moisture content during nixtamalization can be accurately predicted from NIR spectroscopy when coupled with a support vector machine (SVM) model, is strongly modulated by the environment, and has a complex genetic architecture. Lack of high-throughput phenotyping systems for determining moisture content during the maize nixtamalization cooking process has led to difficulty in breeding for this trait. This study provides a high-throughput, quantitative measure of kernel moisture content during nixtamalization based on NIR scanning of uncooked maize kernels. Machine learning was utilized to develop models based on the combination of NIR spectra and moisture content determined from a scaled-down benchtop cook method. A linear support vector machine (SVM) model with a Spearman's rank correlation coefficient of 0.852 between wet laboratory and predicted values was developed from 100 diverse temperate genotypes grown in replicate across two environments. This model was applied to NIR spectra data from 501 diverse temperate genotypes grown in replicate in five environments. Analysis of variance revealed environment explained the highest percent of the variation (51.5%), followed by genotype (15.6%) and genotype-by-environment interaction (11.2%). A genome-wide association study identified 26 significant loci across five environments that explained between 5.04% and 16.01% (average = 10.41%). However, genome-wide markers explained 10.54% to 45.99% (average = 31.68%) of the variation, indicating the genetic architecture of this trait is likely complex and controlled by many loci of small effect. This study provides a high-throughput method to evaluate moisture content during nixtamalization that is feasible at the scale of a breeding program and provides important information about the factors contributing to variation of this trait for breeders and food companies to make future strategies to improve this important processing trait.

Transposable elements contribute to dynamic genome content in maize.

Transposable elements (TEs) are ubiquitous components of eukaryotic genomes and can create variation in genome organization and content. Most maize genomes are composed of TEs. We developed an approach to define shared and variable TE insertions across genome assemblies and applied this method to four maize genomes (B73, W22, Mo17 and PH207) with uniform structural annotations of TEs. Among these genomes we identified approximately 400 000 TEs that are polymorphic, encompassing 1.6 Gb of variable TE sequence. These polymorphic TEs include a combination of recent transposition events as well as deletions of older TEs. There are examples of polymorphic TEs within each of the superfamilies of TEs and they are found distributed across the genome, including in regions of recent shared ancestry among individuals. There are many examples of polymorphic TEs within or near maize genes. In addition, there are 2380 gene annotations in the B73 genome that are located within variable TEs, providing evidence for the role of TEs in contributing to the substantial differences in annotated gene content among these genotypes. TEs are highly variable in our survey of four temperate maize genomes, highlighting the major contribution of TEs in driving variation in genome organization and gene content. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://github.com/SNAnderson/maizeTE_variation; https://mcstitzer.github.io/maize_TEs.

Using multiple reference genomes to identify and resolve annotation inconsistencies.

BACKGROUND: Advances in sequencing technologies have led to the release of reference genomes and annotations for multiple individuals within more well-studied systems. While each of these new genome assemblies shares significant portions of synteny between each other, the annotated structure of gene models within these regions can differ. Of particular concern are split-gene misannotations, in which a single gene is incorrectly annotated as two distinct genes or two genes are incorrectly annotated as a single gene. These misannotations can have major impacts on functional prediction, estimates of expression, and many downstream analyses. RESULTS: We developed a high-throughput method based on pairwise comparisons of annotations that detect potential split-gene misannotations and quantifies support for whether the genes should be merged into a single gene model. We demonstrated the utility of our method using gene annotations of three reference genomes from maize (B73, PH207, and W22), a difficult system from an annotation perspective due to the size and complexity of the genome. On average, we found several hundred of these potential split-gene misannotations in each pairwise comparison, corresponding to 3-5% of gene models across annotations. To determine which state (i.e. one gene or multiple genes) is biologically supported, we utilized RNAseq data from 10 tissues throughout development along with a novel metric and simulation framework. The methods we have developed require minimal human interaction and can be applied to future assemblies to aid in annotation efforts. CONCLUSIONS: Split-gene misannotations occur at appreciable frequency in maize annotations. We have developed a method to easily identify and correct these misannotations. Importantly, this method is generic in that it can utilize any type of short-read expression data. Failure to account for split-gene misannotations has serious consequences for biological inference, particularly for expression-based analyses.

Characterizing introgression-by-environment interactions using maize near isogenic lines.

KEY MESSAGE: Significant introgression-by-environment interactions are observed for traits throughout development from small introgressed segments of the genome. Relatively small genomic introgressions containing quantitative trait loci can have significant impacts on the phenotype of an individual plant. However, the magnitude of phenotypic effects for the same introgression can vary quite substantially in different environments due to introgression-by-environment interactions. To study potential patterns of introgression-by-environment interactions, fifteen near-isogenic lines (NILs) with > 90% B73 genetic background and multiple Mo17 introgressions were grown in 16 different environments. These environments included five geographical locations with multiple planting dates and multiple planting densities. The phenotypic impact of the introgressions was evaluated for up to 26 traits that span different growth stages in each environment to assess introgression-by-environment interactions. Results from this study showed that small portions of the genome can drive significant genotype-by-environment interaction across a wide range of vegetative and reproductive traits, and the magnitude of the introgression-by-environment interaction varies across traits. Some introgressed segments were more prone to introgression-by-environment interaction than others when evaluating the interaction on a whole plant basis throughout developmental time, indicating variation in phenotypic plasticity throughout the genome. Understanding the profile of introgression-by-environment interaction in NILs is useful in consideration of how small introgressions of QTL or transgene containing regions might be expected to impact traits in diverse environments.

The limited role of differential fractionation in genome content variation and function in maize (Zea mays L.) inbred lines.

Maize is a diverse paleotetraploid species with considerable presence/absence variation and copy number variation. One mechanism through which presence/absence variation can arise is differential fractionation. Fractionation refers to the loss of duplicate gene pairs from one of the maize subgenomes during diploidization. Differential fractionation refers to non-shared gene loss events between individuals following a whole-genome duplication event. We investigated the prevalence of presence/absence variation resulting from differential fractionation in the syntenic portion of the genome using two whole-genome de novo assemblies of the inbred lines B73 and PH207. Between these two genomes, syntenic genes were highly conserved with less than 1% of syntenic genes being subject to differential fractionation. The few variably fractionated syntenic genes that were identified are unlikely to contribute to functional phenotypic variation, as there is a significant depletion of these genes in annotated gene sets. In further comparisons of 60 diverse inbred lines, non-syntenic genes were six times more likely to be variable than syntenic genes, suggesting that comparisons among additional genome assemblies are not likely to result in the discovery of large-scale presence/absence variation among syntenic genes.

Genomic Dissection of Nonhost Resistance to Wheat Stem Rust in Brachypodium distachyon.

The emergence of new races of Puccinia graminis f. sp. tritici, the causal pathogen of wheat stem rust, has spurred interest in developing durable resistance to this disease in wheat. Nonhost resistance holds promise to help control this and other diseases because it is durable against nonadapted pathogens. However, the genetic and molecular basis of nonhost resistance to wheat stem rust is poorly understood. In this study, the model grass Brachypodium distachyon, a nonhost of P. graminis f. sp. tritici, was used to genetically dissect nonhost resistance to wheat stem rust. A recombinant inbred line (RIL) population segregating for response to wheat stem rust was evaluated for resistance. Evaluation of genome-wide cumulative single nucleotide polymorphism allele frequency differences between contrasting pools of resistant and susceptible RILs followed by molecular marker analysis identified six quantitative trait loci (QTL) that cumulatively explained 72.5% of the variation in stem rust resistance. Two of the QTLs explained 31.7% of the variation, and their interaction explained another 4.6%. Thus, nonhost resistance to wheat stem rust in B. distachyon is genetically complex, with both major and minor QTLs acting additively and, in some cases, interacting. These findings will guide future research to identify genes essential to nonhost resistance to wheat stem rust.

Genome-wide association analysis of stalk biomass and anatomical traits in maize.

BACKGROUND: Maize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area). RESULTS: Using a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes (Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22. CONCLUSION: Substantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Results of this study provide insights into the genetic control of maize stalk anatomy and biomass.

Draft Assembly of Elite Inbred Line PH207 Provides Insights into Genomic and Transcriptome Diversity in Maize.

Intense artificial selection over the last 100 years has produced elite maize (Zea mays) inbred lines that combine to produce high-yielding hybrids. To further our understanding of how genome and transcriptome variation contribute to the production of high-yielding hybrids, we generated a draft genome assembly of the inbred line PH207 to complement and compare with the existing B73 reference sequence. B73 is a founder of the Stiff Stalk germplasm pool, while PH207 is a founder of Iodent germplasm, both of which have contributed substantially to the production of temperate commercial maize and are combined to make heterotic hybrids. Comparison of these two assemblies revealed over 2500 genes present in only one of the two genotypes and 136 gene families that have undergone extensive expansion or contraction. Transcriptome profiling revealed extensive expression variation, with as many as 10,564 differentially expressed transcripts and 7128 transcripts expressed in only one of the two genotypes in a single tissue. Genotype-specific genes were more likely to have tissue/condition-specific expression and lower transcript abundance. The availability of a high-quality genome assembly for the elite maize inbred PH207 expands our knowledge of the breadth of natural genome and transcriptome variation in elite maize inbred lines across heterotic pools.

Natural variation for gene expression responses to abiotic stress in maize.

Plants respond to abiotic stress through a variety of physiological, biochemical, and transcriptional mechanisms. Many genes exhibit altered levels of expression in response to abiotic stress, which requires concerted action of both cis- and trans-regulatory features. In order to study the variability in transcriptome response to abiotic stress, RNA sequencing was performed using 14-day-old maize seedlings of inbreds B73, Mo17, Oh43, PH207 and B37 under control, cold and heat conditions. Large numbers of genes that responded differentially to stress between parental inbred lines were identified. RNA sequencing was also performed on similar tissues of the F1 hybrids produced by crossing B73 and each of the three other inbred lines. By evaluating allele-specific transcript abundance in the F1 hybrids, we were able to measure the abundance of cis- and trans-regulatory variation between genotypes for both steady-state and stress-responsive expression differences. Although examples of trans-regulatory variation were observed, cis-regulatory variation was more common for both steady-state and stress-responsive expression differences. The genes with cis-allelic variation for response to cold or heat stress provided an opportunity to study the basis for regulatory diversity.