Cross-species transcriptomics reveals differential regulation of essential photosynthesis genes in Hirschfeldia incana.

Photosynthesis is the only yield-related trait not yet substantially improved by plant breeding. Previously, we have established H. incana as the model plant for high photosynthetic light-use efficiency (LUE). Now we aim to unravel the genetic basis of this trait in H. incana, potentially contributing to the improvement of photosynthetic LUE in other species. Here, we compare its transcriptomic response to high light with that of Arabidopsis thaliana, Brassica rapa, and Brassica nigra, 3 fellow Brassicaceae members with lower photosynthetic LUE. We built a high-light, high-uniformity growing environment, in which the plants developed normally without signs of stress. We compared gene expression in contrasting light conditions across species, utilizing a panproteome to identify orthologous proteins. In-depth analysis of 3 key photosynthetic pathways showed a general trend of lower gene expression under high-light conditions for all 4 species. However, several photosynthesis-related genes in H. incana break this trend. We observed cases of constitutive higher expression (like antenna protein LHCB8), treatment-dependent differential expression (as for PSBE), and cumulative higher expression through simultaneous expression of multiple gene copies (like LHCA6). Thus, H. incana shows differential regulation of essential photosynthesis genes, with the light-harvesting complex as the first point of deviation. The effect of these expression differences on protein abundance and turnover, and ultimately the high photosynthetic LUE phenotype is relevant for further investigation. Furthermore, this transcriptomic resource of plants fully grown under, rather than briefly exposed to, a very high irradiance, will support the development of highly efficient photosynthesis in crops.

Crossover shortage in potato is caused by StMSH4 mutant alleles and leads to either highly uniform unreduced pollen or sterility.

The balanced segregation of homologous chromosomes during meiosis is essential for fertility and is mediated by crossovers (COs). A strong reduction of CO number leads to the unpairing of homologous chromosomes after the withdrawal of the synaptonemal complex. This results in the random segregation of univalents during meiosis I and ultimately to the production of unbalanced and sterile gametes. However, if CO shortage is combined with another meiotic alteration that restitutes the first meiotic division, then uniform and balanced unreduced male gametes, essentially composed of nonrecombinant homologs, are produced. This mitosis-like division is of interest to breeders because it transmits most of the parental heterozygosity to the gametes. In potato, CO shortage, a recessive trait previously referred to as desynapsis, was tentatively mapped to chromosome 8. In this article, we have fine-mapped the position of the CO shortage locus and identified StMSH4, an essential component of the class I CO pathway, as the most likely candidate gene. A 7 base-pair insertion in the second exon of StMSH4 was found to be associated with CO shortage in our mapping population. We also identified a second allele with a 3,820 base-pair insertion and confirmed that both alleles cannot complement each other. Such nonfunctional alleles appear to be common in potato cultivars. More than half of the varieties we tested are carriers of mutational load at the StMSH4 locus. With this new information, breeders can choose to remove alleles associated with CO shortage from their germplasm to improve fertility or to use them to produce highly uniform unreduced male gametes in alternative breeding schemes.

Genomic prediction of cereal crop architectural traits using models informed by gene regulatory circuitries from maize.

Plant architecture is a major determinant of planting density, which enhances productivity potential for crops per unit area. Genomic prediction is well positioned to expedite genetic gain of plant architectural traits since they are typically highly heritable. Additionally, the adaptation of genomic prediction models to query predictive abilities of markers tagging certain genomic regions could shed light on the genetic architecture of these traits. Here, we leveraged transcriptional networks from a prior study that contextually described developmental progression during tassel and leaf organogenesis in maize (Zea mays) to inform genomic prediction models for architectural traits. Since these developmental processes underlie tassel branching and leaf angle, 2 important agronomic architectural traits, we tested whether genes prioritized from these networks quantitatively contribute to the genetic architecture of these traits. We used genomic prediction models to evaluate the ability of markers in the vicinity of prioritized network genes to predict breeding values of tassel branching and leaf angle traits for 2 diversity panels in maize and diversity panels from sorghum (Sorghum bicolor) and rice (Oryza sativa). Predictive abilities of markers near these prioritized network genes were similar to those using whole-genome marker sets. Notably, markers near highly connected transcription factors from core network motifs in maize yielded predictive abilities that were significantly greater than expected by chance in not only maize but also closely related sorghum. We expect that these highly connected regulators are key drivers of architectural variation that are conserved across closely related cereal crop species.

Principal component analysis revisited: fast multitrait genetic evaluations with smooth convergence.

A cornerstone in breeding and population genetics is the genetic evaluation procedure, needed to make important decisions on population management. Multivariate mixed model analysis, in which many traits are considered jointly, utilizes genetic and environmental correlations between traits to improve the accuracy. However, the number of parameters in the multitrait model grows exponentially with the number of traits which reduces its scalability. Here, we suggest using principal component analysis to reduce the dimensions of the response variables, and then using the computed principal components as separate responses in the genetic evaluation analysis. As principal components are orthogonal to each other so that phenotypic covariance is abscent between principal components, a full multivariate analysis can be approximated by separate univariate analyses instead which should speed up computations considerably. We compared the approach to both traditional multivariate analysis and factor analytic approach in terms of computational requirement and rank lists according to predicted genetic merit on two forest tree datasets with 22 and 27 measured traits, respectively. Obtained rank lists of the top 50 individuals were in good agreement. Interestingly, the required computational time of the approach only took a few seconds without convergence issues, unlike the traditional approach which required considerably more time to run (7 and 10 h, respectively). The factor analytic approach took approximately 5-10 min. Our approach can easily handle missing data and can be used with all available linear mixed effect model softwares as it does not require any specific implementation. The approach can help to mitigate difficulties with multitrait genetic analysis in both breeding and wild populations.

Allelic combinations of Hd1, Hd16, and Ghd7 exhibit pleiotropic effects on agronomic traits in rice.

Heading date is a critical agronomic trait that significantly affects grain yield and quality in rice. As early heading is typically associated with reduced yield due to shorter growth duration, it is essential to harness optimum heading date genes and their allelic combinations to promote heading while minimizing yield penalties. In this study, we identified quantitative trait loci (QTLs) for heading date and other major agronomic traits in a recombinant inbred line (RIL) population derived from a cross between Koshihikari and Baegilmi. Analyses on 3 major QTLs for heading date and their underlying genes (Hd1, Hd16, and Ghd7) revealed their pleiotropic effects on culm length, panicle length, and head rice percentage. Additionally, Ghd7 exhibited pleiotropic effects on panicle number and grain size. Among 8 different types of allelic combinations of the 3 heading date genes, RILs carrying a single nonfunctional hd16 or ghd7 under the functional background of the other 2 genes (Hd1hd16Ghd7 and Hd1Hd16ghd7) showed potential for maintaining yield and quality-related traits while accelerating heading. These results provide valuable insights for fine-tuning heading dates in rice breeding programs.

High-density genetic linkage mapping in Sitka spruce advances the integration of genomic resources in conifers.

In species with large and complex genomes such as conifers, dense linkage maps are a useful resource for supporting genome assembly and laying the genomic groundwork at the structural, populational, and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, we developed a linkage map relying on 21,570 single nucleotide polymorphism (SNP) markers in Sitka spruce (Picea sitchensis [Bong.] Carr.), a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. We used a single-step mapping approach to efficiently combine RAD-seq and genotyping array SNP data for 528 individuals from 2 full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map for P. sitchensis and Picea glauca based on 27,052 markers and 11,609 gene sequences. Altogether, these 2 linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed, herein, open new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species.

A k-mer-based bulked segregant analysis approach to map seed traits in unphased heterozygous potato genomes.

High-throughput sequencing-based methods for bulked segregant analysis (BSA) allow for the rapid identification of genetic markers associated with traits of interest. BSA studies have successfully identified qualitative (binary) and quantitative trait loci (QTLs) using QTL mapping. However, most require population structures that fit the models available and a reference genome. Instead, high-throughput short-read sequencing can be combined with BSA of k-mers (BSA-k-mer) to map traits that appear refractory to standard approaches. This method can be applied to any organism and is particularly useful for species with genomes diverged from the closest sequenced genome. It is also instrumental when dealing with highly heterozygous and potentially polyploid genomes without phased haplotype assemblies and for which a single haplotype can control a trait. Finally, it is flexible in terms of population structure. Here, we apply the BSA-k-mer method for the rapid identification of candidate regions related to seed spot and seed size in diploid potato. Using a mixture of F1 and F2 individuals from a cross between 2 highly heterozygous parents, candidate sequences were identified for each trait using the BSA-k-mer approach. Using parental reads, we were able to determine the parental origin of the loci. Finally, we mapped the identified k-mers to a closely related potato genome to validate the method and determine the genomic loci underlying these sequences. The location identified for the seed spot matches with previously identified loci associated with pigmentation in potato. The loci associated with seed size are novel. Both loci are relevant in future breeding toward true seeds in potato.

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

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

The chromosome-scale genome and the genetic resistance machinery against insect herbivores of the Mexican toloache, Datura stramonium.

Plant resistance refers to the heritable ability of plants to reduce damage caused by natural enemies, such as herbivores and pathogens, either through constitutive or induced traits like chemical compounds or trichomes. However, the genetic architecture-the number and genome location of genes that affect plant defense and the magnitude of their effects-of plant resistance to arthropod herbivores in natural populations remains poorly understood. In this study, we aimed to unveil the genetic architecture of plant resistance to insect herbivores in the annual herb Datura stramonium (Solanaceae) through quantitative trait loci mapping. We achieved this by assembling the species' genome and constructing a linkage map using an F2 progeny transplanted into natural habitats. Furthermore, we conducted differential gene expression analysis between undamaged and damaged plants caused by the primary folivore, Lema daturaphila larvae. Our genome assembly resulted in 6,109 scaffolds distributed across 12 haploid chromosomes. A single quantitative trait loci region on chromosome 3 was associated with plant resistance, spanning 0 to 5.17 cM. The explained variance by the quantitative trait loci was 8.44%. Our findings imply that the resistance mechanisms of D. stramonium are shaped by the complex interplay of multiple genes with minor effects. Protein-protein interaction networks involving genes within the quantitative trait loci region and overexpressed genes uncovered the key role of receptor-like cytoplasmic kinases in signaling and regulating tropane alkaloids and terpenoids, which serve as powerful chemical defenses against D. stramonium herbivores. The data generated in our study constitute important resources for delving into the evolution and ecology of secondary compounds mediating plant-insect interactions.

Somatic epigenetic drift during shoot branching: a cell lineage-based model.

Plant architecture is shaped by the production of new organs, most of which emerge postembryonically. This process includes the formation of new lateral branches along existing shoots. Current evidence supports a detached-meristem model as the cellular basis of lateral shoot initiation. In this model, a small number of undifferentiated cells are sampled from the periphery of the shoot apical meristem (SAM) to act as precursors for axillary buds, which eventually develop into new shoots. Repeated branching thus creates cellular bottlenecks (i.e. somatic drift) that affect how de novo (epi)genetic mutations propagate through the plant body during development. Somatic drift could be particularly relevant for stochastic DNA methylation gains and losses (i.e. spontaneous epimutations), as they have been shown to arise rapidly with each cell division. Here, we formalize a special case of the detached-meristem model, where precursor cells are randomly sampled from the SAM periphery in a way that maximizes cell lineage independence. We show that somatic drift during repeated branching gives rise to a mixture of cellular phylogenies within the SAM over time. This process is dependent on the number of branch points, the strength of drift as well as the epimutation rate. Our model predicts that cell-to-cell DNA methylation heterogeneity in the SAM converges to nonzero states during development, suggesting that epigenetic variation is an inherent property of the SAM cell population. Our insights have direct implications for empirical studies of somatic (epi)genomic diversity in long-lived perennial and clonal species using bulk or single-cell sequencing approaches.

Whole-genome analysis of recombinant inbred rice lines reveals a quantitative trait locus on chromosome 3 with genotype-by-environment interaction effects.

Elucidating genotype-by-environment interactions is fundamental for understanding the interplay between genetic and environmental factors that shape complex traits in crops. Genotype-by-environment interactions are of practical importance, as they determine the performance of cultivars grown in different environments, prompting the need for an efficient approach for evaluating genotype-by-environment interactions. Here, we describe a method for genotype-by-environment detection that involves comparing linear mixed models. This method successfully detected genotype-by-environment interactions in rice (Oryza sativa) recombinant inbred lines grown at 3 locations. We identified a quantitative trait locus (QTL) on chromosome 3 that was associated with heading date, grain number, and leaf length. The effect of this QTL on plant growth-related traits varied with environmental conditions, indicating the presence of genotype-by-environment interactions. Therefore, our method enables a powerful genotype-by-environment detection pipeline that should facilitate the production of high-yielding crops in a given environment.

Identification of stable QTL controlling multiple yield components in a durum × cultivated emmer wheat population under field and greenhouse conditions.

Crop yield gains are needed to keep pace with a growing global population and decreasing resources to produce food. Cultivated emmer wheat is a progenitor of durum wheat and a useful source of genetic variation for trait improvement in durum. Here, we evaluated a recombinant inbred line population derived from a cross between the North Dakota durum wheat variety Divide and the cultivated emmer wheat accession PI 272527 consisting of 219 lines. The population was evaluated in 3 field environments and 2 greenhouse experiments to identify quantitative trait locus associated with 11 yield-related traits that were expressed in a consistent manner over multiple environments. We identified 27 quantitative trait locus expressed in at least 2 field environments, 17 of which were also expressed under greenhouse conditions. Seven quantitative trait locus regions on chromosomes 1B, 2A, 2B, 3A, 3B, 6A, and 7B had pleiotropic effects on multiple yield-related traits. The previously cloned genes Q and FT-B1, which are known to be associated with development and morphology, were found to consistently be associated with multiple traits across environments. PI 272527 contributed beneficial alleles for quantitative trait locus associated with multiple traits, especially for seed morphology quantitative trait locus on chromosomes 1B, 2B, and 6A. Three recombinant inbred lines with increased grain size and weight compared to Divide were identified and demonstrated the potential for improvement of durum wheat through deployment of beneficial alleles from the cultivated emmer parent. The findings from this study provide knowledge regarding stable and robust quantitative trait locus that breeders can use for improving yield in durum wheat.

Fine mapping and marker development for the wheat leaf rust resistance gene Lr32.

Wheat leaf rust is caused by the fungal pathogen Puccinia triticina and is one of the wheat diseases of concern globally. Among the known leaf rust resistance genes (Lr) genes, Lr32 is a broadly effective gene derived from the diploid species Aegilops tauschii coss. accession RL5497-1 and has been genetically mapped to chromosome arm 3DS. However, Lr32 resistance has not been utilized in current cultivars in part due to the lack of modern, predictive DNA markers. The goals of this study were to fine map the Lr32 region and develop SNP-based kompetitive allele-specific polymerase chain reaction markers. The genomic analysis was conducted by using doubled haploid and F2-derived mapping populations. For marker development, a 90K wheat chip array, 35K and 820K Axiom R SNPs, A. tauschii pseudomolecules v4.0 and International Wheat Genome Sequencing Consortium ReqSeq v2.1 reference genomes were used. Total 28 kompetitive allele-specific polymerase chain reaction and 2 simple sequence repeat markers were developed. The Lr32 region was fine mapped between kompetitive allele-specific polymerase chain reaction markers Kwh142 and Kwh355 that flanked 34-35 Mb of the diploid and hexaploid reference genomes. Leaf rust resistance mapped as a Mendelian trait that cosegregated with 20 markers, recombination restriction limited the further resolution of the Lr32 region. A total of 10-11 candidate genes associated with disease resistance were identified between the flanking regions on both reference genomes, with the majority belonging to the nucleotide-binding domain and leucine-rich repeat gene family. The validation analysis selected 2 kompetitive allele-specific polymerase chain reaction markers, Kwh147 and Kwh722, for marker-assisted selection. The presence of Lr32 along with other Lr genes such as Lr67 and Lr34 would increase the resistance in future wheat breeding lines and have a high impact on controlling wheat leaf rust.

Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis.

A genome-wide association study (GWAS) was used to identify associated loci with early vigor under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published quantitative trait loci (QTL) from recombinant inbred lines, double haploids, back-crosses, and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis. Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75% were located within or closed to protein-coding genes. In the MQTL analysis, 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals associated with MQTLs. These findings provide important information on the genetic basis of early vigor traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.

Insights into the domestication of avocado and potential genetic contributors to heterodichogamy.

The domestication history of the avocado (Persea americana) remains unclear. We created a reference genome from the Gwen varietal, which is closely related to the economically dominant Hass varietal. Our genome assembly had an N50 of 3.37 megabases, a BUSCO score of 91%, and was scaffolded with a genetic map, producing 12 pseudo-chromosomes with 49,450 genes. We used the Gwen genome as a reference to investigate population genomics, based on a sample of 34 resequenced accessions that represented the 3 botanical groups of P. americana. Our analyses were consistent with 3 separate domestication events; we estimated that the Mexican group diverged from the Lowland (formerly known as "West Indian") and Guatemalan groups >1 million years ago. We also identified putative targets of selective sweeps in domestication events; within the Guatemalan group, putative candidate genes were enriched for fruit development and ripening. We also investigated divergence between heterodichogamous flowering types, providing preliminary evidence for potential candidate genes involved in pollination and floral development.

Chromoanagenesis in the asy1 meiotic mutant of Arabidopsis.

Chromoanagenesis is a catastrophic event that involves localized chromosomal shattering and reorganization. In this study, we report a case of chromoanagenesis resulting from defective meiosis in the MEIOTIC ASYNAPTIC MUTANT 1 (asy1) background in Arabidopsis thaliana. We provide a detailed characterization of the genomic structure of this individual with a severely shattered segment of chromosome 1. We identified 260 novel DNA junctions in the affected region, most of which affect gene sequence on 1 or both sides of the junction. Our results confirm that asy1-related defective meiosis is a potential trigger for chromoanagenesis. This is the first example of chromoanagenesis associated with female meiosis and indicates the potential for genome evolution during oogenesis. PLAIN LANGUAGE SUMMARY: Chromoanagenesis is a complex and catastrophic event that results in severely restructured chromosomes. It has been identified in cancer cells and in some plant samples, after specific triggering events. Here, we identified this kind of genome restructuring in a mutant that exhibits defective meiosis in the model plant system Arabidopsis thaliana.

Extensive crop-wild hybridization during Brassica evolution and selection during the domestication and diversification of Brassica crops.

Adaptive genetic diversity in crop wild relatives (CWRs) can be exploited to develop improved crops with higher yield and resilience if phylogenetic relationships between crops and their CWRs are resolved. This further allows accurate quantification of genome-wide introgression and determination of regions of the genome under selection. Using broad sampling of CWRs and whole genome sequencing, we further demonstrate the relationships among two economically valuable and morphologically diverse Brassica crop species, their CWRs, and their putative wild progenitors. Complex genetic relationships and extensive genomic introgression between CWRs and Brassica crops were revealed. Some wild Brassica oleracea populations have admixed feral origins; some domesticated taxa in both crop species are of hybrid origin, while wild Brassica rapa is genetically indistinct from turnips. The extensive genomic introgression that we reveal could result in false identification of selection signatures during domestication using traditional comparative approaches used previously; therefore, we adopted a single-population approach to study selection during domestication. We used this to explore examples of parallel phenotypic selection in the two crop groups and highlight promising candidate genes for future investigation. Our analysis defines the complex genetic relationships between Brassica crops and their diverse CWRs, revealing extensive cross-species gene flow with implications for both crop domestication and evolutionary diversification more generally.

Mapping quantitative trait loci for biomass yield and yield-related traits in lowland switchgrass (Panicum virgatum L.) multiple populations.

Switchgrass can be used as an alternative source for bioenergy production. Many breeding programs focus on the genetic improvement of switchgrass for increasing biomass yield. Quantitative trait loci (QTL) mapping can help to discover marker-trait associations and accelerate the breeding process through marker-assisted selection. To identify significant QTL, this study mapped 7 hybrid populations and one combined of 2 hybrid populations (30-96 F1s) derived from Alamo and Kanlow genotypes. The populations were evaluated for biomass yield, plant height, and crown size in a simulated-sward plot with 2 replications at 2 locations in Tennessee from 2019 to 2021. The populations showed significant genetic variation for the evaluated traits and exhibited transgressive segregation. The 17,251 single nucleotide polymorphisms (SNPs) generated through genotyping-by-sequencing (GBS) were used to construct a linkage map using a fast algorithm for multiple outbred families. The linkage map spanned 1,941 cM with an average interval of 0.11 cM between SNPs. The QTL analysis was performed on evaluated traits for each and across environments (year and location) that identified 5 QTL for biomass yield (logarithm of the odds, LOD 3.12-4.34), 4 QTL for plant height (LOD 3.01-5.64), and 7 QTL for crown size (LOD 3.0-4.46) (P ≤ 0.05). The major QTL for biomass yield, plant height, and crown size resided on chromosomes 8N, 6N, and 8K explained phenotypic variations of 5.6, 5.1, and 6.6%, respectively. SNPs linked to QTL could be incorporated into marker-assisted breeding to maximize the selection gain in switchgrass breeding.

The Ga1 locus of the genus Zea is associated with novel genome structures derived from multiple, independent nonhomologous recombination events.

The Ga1 locus controls cross-incompatibility between field corn and popcorn. The Ga1-S haplotype contains 2 types of pectin methylesterase (PME) genes, ZmPme3 and several copies of ZmGa1P that are expressed in silk and pollen, respectively. The ga1 haplotype contains nonfunctional tandem repeat sequences related to ZmPme3 and ZmGa1P. This haplotype can cross-pollinate freely and is widely present in field corn. The primary objective of this study is to characterize the repeat sequences from a diverse collection of maize and teosinte lines and use this information to understand the evolution of the Ga1 locus. First, we characterized the complexity of the Ga1 genome region in high-quality maize genome assemblies that led to their categorization into 5 groups based on the number and type of PME-like sequences found at this region. Second, we studied duplication events that led to the ga1 and Ga1-S repeats using maximum likelihood phylogenetic reconstruction. Divergence estimates of the ga1 haplotype suggest that the duplication events occurred more than 600 KYA whereas those in Ga1-S occurred at 3 time points, i.e. >600, ∼260, and ∼100 KYA. These estimates suggest that the ga1 and Ga1-S tandem duplication events occurred independently. Finally, analysis of ZmPme3 and ZmGa1P homologs in Zea and Tripsacum genomes suggests that ga1 and Ga1-S repeats originated from an ancestral pair of PME genes that duplicated and diverged through 2 evolutionary branches prior to the domestication of maize.

The reference genome and abiotic stress responses of the model perennial grass Brachypodium sylvaticum.

Perennial grasses are important forage crops and emerging biomass crops and have the potential to be more sustainable grain crops. However, most perennial grass crops are difficult experimental subjects due to their large size, difficult genetics, and/or their recalcitrance to transformation. Thus, a tractable model perennial grass could be used to rapidly make discoveries that can be translated to perennial grass crops. Brachypodium sylvaticum has the potential to serve as such a model because of its small size, rapid generation time, simple genetics, and transformability. Here, we provide a high-quality genome assembly and annotation for B. sylvaticum, an essential resource for a modern model system. In addition, we conducted transcriptomic studies under 4 abiotic stresses (water, heat, salt, and freezing). Our results indicate that crowns are more responsive to freezing than leaves which may help them overwinter. We observed extensive transcriptional responses with varying temporal dynamics to all abiotic stresses, including classic heat-responsive genes. These results can be used to form testable hypotheses about how perennial grasses respond to these stresses. Taken together, these results will allow B. sylvaticum to serve as a truly tractable perennial model system.