Browsing by Author "Hirsch, Candice N"
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Item Datasets to build marker effect networks(2023-01-23) Della Coletta, Rafael; Liese, Sharon E; Fernandes, Samuel B; Mikel, Mark A; Bohn, Martin O; Lipka, Alexander E; Hirsch, Candice N; cnhirsch@umn.edu; Hirsch, Candice N; Hirsch LabThis dataset contains the input files to build marker effect networks and identify markers associated with environmental adaptability. These networks are built by adapting commonly used software for building gene co-expression networks with marker effects across growth environments as the input data into the networks. Here, we provide grain yield data from 400 maize hybrids grown across nine environments in the U.S. Midwest, a set of ~10,000 non-redundant markers, and environmental data containing 17 weather parameters in 3-day intervals collected from planting date to the end of the season. For instructions on how to perform this analysis and analysis script, please see https://github.com/HirschLabUMN/meffs_networks. For more details on marker effect networks, please see preprint on https://www.biorxiv.org/content/10.1101/2023.01.19.524532v1.Item Datasets to test the importance of genetic architecture in marker selection decisions for genomic prediction(2023-03-01) Della Coletta, Rafael; Fernandes, Samuel B; Monnahan, Patrick J; Mikel, Mark A; Bohn, Martin O; Lipka, Alexander E; Hirsch, Candice N; cnhirsch@umn.edu; Hirsch, Candice N; Hirsch LabThis dataset contains the input files to simulate traits for maize recombinant inbred lines (RILs) and run genomic prediction models with different marker types. Using real genotypic information from 333 maize recombinant inbred lines with single nucleotide polymorphism (SNP) and structural variant (SV) information projected from their seven sequenced parental lines, we simulated traits with different genetic architectures in multiple environments using the R package simplePHENOTYPES. We varied the heritability, the number of quantitative trait loci (QTLs), the type of causative variant (SNPs or SVs), and the variant effect sizes. Weather data from five locations in the U.S. Midwest in 2020 was used to generate a residual correlation matrix among environments. After performing a two-stage analysis with multivariate GBLUP prediction model for each marker type and genetic architecture, we obtained prediction accuracies using two types of cross-validation (CV1 and CV2). For instructions on how to perform this analysis and analysis script, please see https://github.com/HirschLabUMN/genomic_prediction_svsItem Genomes to Fields Initiative Flight Data - Delaware 2020(2024-05-16) Sweet, Dorothy D; Hirsch, Candice N; Hirsch, Cory D; Sparks, Erin E; Miller, Jarrod O; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 1 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, digital elevation models, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Delaware 2020) all testers were used. A modified randomized complete block design was used for testing.Item Genomes to Fields Initiative Flight Data - Minnesota 2020(2024-05-16) Sweet, Dorothy D; Hirsch, Candice N; Hirsch, Cory D; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 2 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, digital elevation models, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Minnesota 2020) PHP02 was used. A modified randomized complete block design was used for testing.Item Genomes to Fields Initiative Flight Data - Minnesota 2021(2024-05-16) Sweet, Dorothy D; Hirsch, Candice N; Hirsch, Cory D; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 3 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, digital elevation models, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Minnesota 2021) PHP02 was used. A modified randomized complete block design was used for testing.Item Genomes to Fields Initiative Flight Data - Missouri C5A 2020(2024-05-16) Sweet, Dorothy D; Hirsch, Cory D; Hirsch, Candice N; Flint-Garcia, Sherry A; Washburn, Jacob D; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 4 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, digital elevation models, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Missouri 2020) all testers were used. A modified randomized complete block design was used for testing.Item Genomes to Fields Initiative Flight Data - Missouri C5B 2020 - Part 1(2024-05-16) Sweet, Dorothy D; Hirsch, Candice N; Hirsch, Cory D; Flint-Garcia, Sherry; Washburn, Jacob; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 5 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, digital elevation models, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Missouri 2020) all testers were used. A modified randomized complete block design was used for testing.Item Genomes to Fields Initiative Flight Data - Missouri C5B 2020 - Part 2(2024-05-16) Sweet, Dorothy D; Hirsch, Cory D; Hirsch, Candice N; Flint-Garcia, Sherry; Washburn, Jacob; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 6 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, DEMs, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Missouri 2020) all testers were used. A modified randomized complete block design was used for testing.Item Genomes to Fields Initiative Flight Data - Nebraska 2021(2024-05-16) Sweet, Dorothy D; Hirsch, Candice N; Hirsch, Cory D; Schnable, James; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 7 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, digital elevation models, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Nebraska 2021) PHZ51 was used. A modified randomized complete block design was used for testing.Item Genomes to Fields Initiative Flight Data - Texas 2020(2024-05-16) Sweet, Dorothy D; Hirsch, Cory D; Hirsch, Candice N; Murray, Seth; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset (DRUM 8 of 8) is a subset of the flight data collected through the Genomes to Fields Initiative in 2020 and 2021. In conjunction with equivalent datasets on similar material at alternate locations, this data provides a valuable resource for evaluating the performance and stability of hybrid maize across many environments. Many flights throughout the growing season were conducted at these locations (Delaware, Minnesota, Missouri, Nebraska, and Texas) and this dataset includes the orthomosaics, digital elevation models, plot shapefiles, and extracted plant height values for each of those flights following the pipeline from Anderson, Steven L., II, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, and J. Alex Thomasson. 2019. “Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems.” The Plant Phenome Journal 2 (1): 1–15.. This maize experiment consisted of over 1000 maize hybrids grown in partial replication across 8 environments in 2 years. A set of common hybrids were grown in every location in order to establish a connection between environments, Within the partially replicated set, hybrids were produced by the cross of double haploids derived from the WI-SS-MAGIC population to the inbred testers PHK76, PHP02, and PHZ51 with the tester choice depending on the relative maturity zone of the location. For this location (Texas 2020) PHZ51 was used. A modified randomized complete block design was used for testing.Item Hirsch Lab UAV Commercial Maize Phenotyping Project at UMN SROC Waseca: 2020, 2021, and 2022(2024-04-22) Sweet, Dorothy D; Hirsch, Candice N; Hirsch, Cory D; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabThis dataset provides a valuable resource for evaluating the ability of unoccupied aerial vehicles to collect plant height information from commercial agricultural fields and predict within field variation in yield using temporal traits including plant height, growth rate, and vegetative indices. Many flights were conducted over commercial maize fields using an UAV equipped with an RGB camera and this dataset includes orthomosaics and digital elevation models generated from those flights as well as plot boundary shape files used for extraction of data from those flights. Data in this repository includes extracted plant height, extracted RGB vegetative indices, manual height measurements, weather data, soil data, and grain yield. This experiment consisted of three commercial fields containing single maize hybrids and is therefore useful in assessing the ability of UAV extracted values in identifying within field variation for prediction of yield. It can also be used to test different methods of extracting plant height values from commercial fields as it includes manual measurements of height to be used in evaluation.Item Maize 509 line TE PAV calls(2020-10-28) Springer, Nathan M; Noshay, Jaclyn M; Hirsch, Candice N; Marand, Alexandre P; Anderson, Sarah N; Zhou, Peng; O'Connor, Christine; Crisp, Peter A; Schmitz, Robert J; Lu, Zefu; nosha003@umn.edu; Noshay, Jaclyn; University of Minnesota Springer Research LabTransposable elements (TEs) have the potential to create regulatory variation both through disruption of existing DNA regulatory elements and through creation of novel DNA regulatory elements. In a species with a large genome, such as maize, the many TEs interspersed with genes creates opportunities for significant allelic variation due to TE presence/absence polymorphisms among individuals. We used information on putative regulatory elements in combination with knowledge about TE polymorphisms in maize to identify TE insertions that interrupt existing accessible chromatin regions (ACRs) in B73 as well as examples of polymorphic TEs that contain ACRs among four inbred lines of maize including B73, Mo17, W22, and PH207. The TE insertions in three other assembled maize genomes (Mo17, W22 or PH207) that interrupt ACRs that are present in the B73 genome can trigger changes to the chromatin suggesting the potential for both genetic and epigenetic influences of these insertions. Nearly 20% of the ACRs located over 2kb from the nearest gene are located within an annotated TE. These are regions of unmethylated DNA that show evidence for functional importance similar to ACRs that are not present within TEs. Using a large panel of maize genotypes we tested if there is an association between the presence of TE insertions that interrupt, or carry, an ACR and the expression of nearby genes. While most TE polymorphisms are not associated with expression for nearby genes the TEs that carry ACRs exhibit an enrichment for being associated with higher expression of nearby genes, suggesting that these TEs may contribute novel regulatory elements. These analyses highlight the potential for a subset of TEs to rewire transcriptional responses in eukaryotic genomes.Item Springer Lab UAV Maize Phenotyping Project at UMN StPaul: 2018 and 2019(2020-05-05) Tirado, Sara B; Hirsch, Candice N; Springer, Nathan M; springer@umn.edu; Springer, Nathan M; Springer LabThis dataset provides a valuable resource for evaluating the utility of unmanned aerial vehicles to collect phenotypic data in agricultural fields. Many flights throughout the growing season of a maize experiment were conducted and this dataset includes digital elevation models generated from images within these flights, the plot boundary shapefiles for plot identification, plant height values extracted following Tirado et al., 2019 procedure, hand measurement height values conducted following flights, and yield data for each plot. This maize experiment consisted of twelve hybrids planted at three different planting densities (low, medium and high) and two planting dates (early and late) across two years and therefore provides a valuable resource for evaluating how temporal data collected from UAVs can aid in assessing plant productivity. It can also be utilized to develop and test different protocols for plant height extraction from DEMs at different growth stages as the hand measurements can be used to test the accuracy.Item Supporting data for Development of a multi-parent population for genetic mapping and allele discovery in six-row barley(2019-08-12) Hemshrot, Alex; Poets, Ana M; Tyagi, Priyanka; Lei, Li; Carter, Corey; Hirsch, Candice N; Li, Lin; Brown-Guedira, Gina; Morrell, Peter L; Muehlbauer, Gary J; Smith, Kevin P; llei@umn.edu; Lei, Li; University of Minnesota Department of Plant and Microbial Biology; HuaZhong Agricultural University Department of Genetics, College of Plant Science and Technology; USDA Eastern Regional Small Grains Genotyping Laboratory; University of Minnesota Department of Agronomy & Plant GeneticsGermplasm collections hold valuable allelic diversity for crop improvement and genetic mapping of complex traits. To gain access to the genetic diversity within the USDA National Small Grain Collection (NSGC), we developed the Barley Recombinant Inbred Diverse Germplasm Population (BRIDG6), a six-row spring barley multi-parent population (MPP) with 88 cultivated accessions ranging from landrace to cultivars crossed to a common parent (Rasmusson). The parents were randomly selected from a core subset of the NSGC that represents the genetic diversity of landrace and breeding accessions. In total, we generated 6,160 F5 recombinant inbred lines (RILs) with an average of 69 and a range of 37-168 RILs per family genotyped with 7,773 SNPs. The number of segregating SNPs per family range from 956 to 6,775, with an average of 3,889 SNPs per family. Using BRIDG6, we detected 23 QTL contributing to flowering time. Five QTL were within five megabase pairs of previously described flowering time genes. For the major QTL detected near HvPpd-H1, a flowering time gene that affects photoperiod, we observed both positive and negative allele effects ranging from +4 to –3 days relative to Rasmusson among the 79 families segregating for the SNP. Haplotype-based analysis of HvPpd-H1 identified private alleles to families of Asian origin conferring both positive and negative effects, providing the first observation of flowering time-related alleles private to Asian accessions. We evaluate several subsampling strategies to determine their effect on the power of QTL detection and found that for flowering time in barley, a sample size larger than 50 families or 3,000 individuals results in the highest QTL detection. This MPP will be useful for uncovering large and small effect QTL for traits of interest and identifying and utilizing valuable alleles from the NSGC for barley improvement.Item Temporally resolved growth patterns in diverse maize panel(2023-01-27) Sweet, Dorothy D; Tirado, Sara B; Cooper, Julian S; Springer, Nathan M; Hirsch, Cory D; Hirsch, Candice N; cnhirsch@umn.edu; Hirsch, Candice N; Candice Hirsch Lab; Cory Hirsch LabPlant height is used in many breeding programs for assessing plant health across environments and predicting yield, which can be used in identifying superior hybrids or evaluating abiotic stress factors. This has often been measured at a single time point when plants have reached their terminal height for the season. Collection of plant height using unoccupied aerial vehicles (UAVs) is faster, allowing for measurements throughout the growing season which could facilitate a better understanding of plant-environment interaction and responses. To assess variation in plant height and growth rate throughout development, plant height data was collected weekly for a panel of ~500 diverse inbred lines over four growing seasons. The variation in plant height throughout the season was found to be significantly explained by genotype, year, and genotype-by-year interactions throughout vegetative growth. However, the relative contributions of these different sources of variation fluctuated throughout development. This variation was further captured by Fréchet distance values which identified genotypes with consistently high or low distances in each of the four years - high distance genotypes being more dissimilar between replications and therefore capturing more environmental variation. Genome-wide association studies revealed many significant SNPs associated with plant height and growth rate at different parts of the growing season that would not be identified by terminal height alone. When comparing growth rates estimated from plant height to growth rates estimated from another morphological characteristic, canopy cover, we found greater stability in growth curves estimated by plant height. This potentially makes canopy cover more useful for understanding environmental modulation of overall plant growth and plant height better for understanding genotypic modulation of overall plant growth. Overall, this suggests evaluations of plant growth throughout the season provide more information than terminal plant height alone.Item Whole Genome Assembly and Annotation of Northern Wild Rice (Zizania palustris L.), a North American Grain(2021-07-23) Haas, Matthew W; Kono, Thomas; Macchietto, Marissa; Millas, Reneth; McGilp, Lillian; Shao, Mingqin; Duquette, Jacques; Hirsch, Candice N; Kimball, Jennifer A; jkimball@umn.edu; Kimball, Jennifer A; University of Minnesota Cultivated Wild Rice Breeding and Genetics LabNorthern Wild Rice (NWR; Zizania palustris L.) 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 United States. Using long- and short-range sequencing, Hi-C scaffolding, and RNA-seq data from eight tissues, we generated a whole genome de novo assembly and annotation of NWR. The assembly is 1.29 Gb, highly repetitive (~76.0%), and contains 46,421 protein-coding genes. Comparative analyses revealed conservation of large syntenic blocks with Oryza sativa L., which were used to identify putative seed shattering genes. Estimates of divergence times revealed the Zizania genus diverged from Oryza ~26-30 million years ago (MYA), while NWR and Zizania latifolia diverged from one another ~6-8 MYA. Comparative genomics revealed evidence of a whole genome duplication in NWR ~5.3 MYA after the NWR-Z. latifolia speciation event. This high-quality genome assembly and annotation provides is a valuable resource for comparative genomics in the Oryzeae tribe and provides an important resource for future conservation and breeding efforts of NWR.