GrainGenes is an international, centralized crop database for peer-reviewed small grains data and information portal that serves the small grains research and breeding communities (wheat, barley, oat, and rye). The GrainGenes project ensures long-term data curation, accessibility, and sustainability so that small grains researchers can develop new, more nutritious, disease and pest resistant, high yielding cultivars. As a digital platform, GrainGenes houses peer-reviewed and curated genetic, genomic, and protein data. It has been hard-funded by the U.S. Department of Agriculture-Agricultural Research Service to ensure long-term data sustainability through a functional and integrated web interface for wheat, barley, oat, and rye.

GrainGenes is a popular repository for information about genetic maps, mapping probes and primers, genes, alleles and QTLs for the following crops: wheat, barley, rye and oat. Documentation includes such data as primer sequences, polymorphism descriptions, genotype and trait scoring data, experimental protocols used, and photographs of marker polymorphisms, disease symptoms and mutant phenotypes. These data, curated with the help of many members of the research community, are integrated with sequence and bibliographic records selected from external databases and results of BLAST searches of the ESTs. Records are linked to corresponding records in other important databases, e.g. Gramene's EST homologies to rice BAC/PACs, TIGR's Gene Indices and GenBank. In addition to this information within the GrainGenes database itself, the GrainGenes homepage at http://wheat.pw.usda.gov provides many other community resources including publications (the annual newsletters for wheat, barley and oat, monographs and articles), individual datasets (mapping and QTL studies, polymorphism surveys, variety performance evaluations), specialized databases (Triticeae repeat sequences, EST unigene sets) and pages to facilitate coordination of cooperative research efforts in specific areas such as SNP development, EST-SSRs and taxonomy. The goal is to serve as a central point for obtaining and contributing information about the genetics and biology of these cereal crops Resources in this dataset:Resource Title: GrainGenes, the genome database for small-grain crops (main web site). File Name: Web Page, url: http://wheat.pw.usda.gov/GG3/ GrainGenes is the primary repository for information about genetic maps, mapping probes and primers, genes, alleles and QTLs; crops are wheat, barley, rye and oat. Documentation includes such data as primer sequences, polymorphism descriptions, genotype and trait scoring data, experimental protocols used, and photographs of marker polymorphisms, disease symptoms and mutant phenotypes. These data, curated with the help of many members of the research community, are integrated with sequence and bibliographic records selected from external databases and results of BLAST searches of the ESTs. Records are linked to corresponding records in other important databases, e.g. Gramene's EST homologies to rice BAC/PACs, TIGR's Gene Indices and GenBank.

The TCP family genes are plant-specific transcription factors and play important roles in plant development. TCPs have been evolutionarily and functionally studied in several plants. Although common wheat (Triticum aestivum L.) is a major staple crop worldwide, no systematic analysis of TCPs in this important crop has been conducted. Here, we performed a genome-wide survey in wheat and found 66 TCP genes that belonged to 22 homoeologous groups. We then mapped these genes on wheat chromosomes and found that several TCP genes were duplicated in wheat including the ortholog of the maize TEOSINTE BRANCHED 1. Expression study using both RT-PCR and in situ hybridization assay showed that most wheat TCP genes were expressed throughout development of young spike and immature seed. Cis-acting element survey along promoter regions suggests that subfunctionalization may have occurred for homoeologous genes. Moreover, protein–protein interaction experiments of three TCP proteins showed that they can form either homodimers or heterodimers. Finally, we characterized two TaTCP9 mutants from tetraploid wheat. Each of these two mutant lines contained a premature stop codon in the A subgenome homoeolog that was dominantly expressed over the B subgenome homoeolog. We observed that mutation caused increased spike and grain lengths. Together, our analysis of the wheat TCP gene family provides a start point for further functional study of these important transcription factors in wheat.

A database for Triticeae and Avena gene symbols.

The study material in GWAS panel with 280 common bread wheat genotypes was selected from All India Coordinated Research Project on Wheat and Barley to map the genomic regions responsible for enhanced Grain Zinc Content (GZnC), Grain Iron Content (GZnC) and Thousand Kernel weight (TKW).

Phenotypic data:

The GWAS panel was evaluated at five different environments: E1-University of Agricultural Sciences, research farm, Dharwad (15°29'20.71"N, 74°59'3.35"E, 750m AMSL), E2-ICAR- Indian Agricultural Research Institute, New Delhi (28°38′30.5″N, 77°09′58.2″E, 228 m AMSL), E3-Indian Agricultural Research Institute, Jharkhand (24°16'58.4"N, 85°21'16.1"E, 651m AMSL), E4-ICAR-Indian Institute of Wheat and Barley, Karnal (29°41'8.2644''N, 76°59'25.9692''E, 250m AMSL), and E5-Punjab Agricultural University, Ludhiana (30o54' N, 75o48'E, 247m AMSL). Around 20 g of grain sample from each genotype were used for phenotyping GFeC and GZnC through high-throughput Energy Dispersive X-ray Fluorescence (ED-XRF) machine (model X-Supreme 8000; Oxford Instruments plc, Abingdon, United Kingdom) calibrated with glass beads-based values. To record TKW, the Numigral grain counter was used to count the grain number, the reading was set at 1000 grains and the weight of the grains was recorded in grams with an electronic balance. The GFeC, GZnC were expressed as milligram per kilogram (mg/kg), GPC in percentage (%), TKW in grams (gms).

Genotypic data:

Genomic DNA of the GWAS panel was extracted from the leaves of 21 days-old seedlings by Cetyl Trimethyl Ammonium Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder's Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143 genome-wide SNPs. The monomorphic, markers with minor allele frequency (MAF) of <5%, missing data of >20%, and heterozygote frequency >25% were removed from the analysis. The remaining set of 14,790 high-quality SNPs was used in GWAS analysis. The detailed information of the methods and software used, data analysis and GWAS is available at DOI: 10.1038/s41598-022-15992-z.

A spontaneous hybridization of the wild diploid grass Aegilops tauschii (2n=14, DD) with cultivated tetraploid wheat Triticum turgidum (2n=4x=28, AABB) 8,000~10,000 years ago in the Fertile Crescent resulted in the bread wheat (Triticum aestivum; 2n=6x=42, AABBDD), one of the earliest cultivated crops in modern agriculture. We sequenced the 4.36-gigabase (Gb) genome of Ae. tauschii by generating ~90x genome coverage of short reads from a series of libraries with various insert sizes. The assembled scaffolds of high quality sequences represent 83.4% of the genome, in which 65.9% comprised of repetitive elements. Assisted with comprehensive RNA-Seq data, we identified 43,150 protein-coding genes, with 30,697 (71.1%) of them uniquely anchored to chromosomes based on an integrated density genetic map. A number of agriculturally relevant gene families, such as disease resistance, abiotic stress tolerance, and grain quality genes, were found to expand in Ae. tauschii. The draft genome of Ae. tauschii hence provides novel insights into its role in enabling environmental adaptation of common wheat and in defining the large and complicated genomes of wheat species.

Wheat is a major source of nutrients for populations across the globe, but the amino acid composition of wheat grain does not provide optimal nutrition. The nutritional value of wheat grain is limited by low concentrations of lysine (the most limiting essential amino acid) and high concentrations of free asparagine (precursor to the processing contaminant acrylamide). There are currently few available solutions for asparagine reduction and lysine biofortification through breeding. In this study, we investigated the genetic architecture controlling grain-free amino acid composition and its relationship to other traits in a Robigus × Claire doubled haploid population. Multivariate analysis of amino acids and other traits showed that the two groups are largely independent of one another, with the largest effect on amino acids being from the environment. Linkage analysis of the population allowed the identification of QTL controlling free amino acids and other traits, and this was compared against genomic prediction methods. Following the identification of a QTL controlling free lysine content, wheat pangenome resources facilitated analysis of candidate genes in this region of the genome. These findings can be used to select appropriate strategies for lysine biofortification and free asparagine reduction in wheat breeding programmes.

The study material in the GWAS panel with 193 bread wheat genotypes from Indian and exotic collections was selected to map the genomic regions responsible for grain iron and Zinc content under drought and heat stress treatments.

Phenotypic data:

The GWAS panel was evaluated at IARI, New Delhi - DL (28.6550° N, 77.1888° E, MSL 228.61 m) under Irrigated (IR), Restricted Irrigated (RI) and Late sown (LS) treatment conditions over 2 years i.e. 2020 and 2021 with augmented RCBD design. Data was collected on Grain Iron and Grain zinc content along with thousand-grain weight. Around 20 g of grain sample from each of 282 genotypes from the GWAS panel under all three conditions were used for phenotyping GFeC and GZnC through high-throughput Energy Dispersive X-ray Fluorescence (ED-XRF) machine (model X-Supreme 8000; Oxford Instruments plc, Abingdon, United Kingdom) calibrated with glass beads-based values. To record TGW, manual counting of grains was followed and the weight of the grains was recorded in grams with an electronic balance.

Genotypic data:

Genomic DNA of the GWAS panel was extracted from the leaves of seedlings by Cetyl Trimethyl Ammonium Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder's Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143 genome-wide SNPs. The monomorphic, markers with minor allele frequency (MAF) of <5%, missing data of >10%, and heterozygote frequency >50% were removed from the analysis. The remaining set of 13,947 high-quality SNPs was used in GWAS analysis.

This is an Aegilops tauschii genome database containing genetic and physical maps, genetic markers and genomic sequences and up-to-date releases on Ae. tauschii genome mapping. Resources in this dataset:Resource Title: Web Page. File Name: Web Page, url: https://probes.pw.usda.gov/WheatDMarker/

Chromosome-scale genome assembly of bread wheat’s wild relative *Triticum timopheevii*

https://doi.org/10.5061/dryad.mpg4f4r6p

Assembly
Pseudomolecules assembled with Hifiasm and Salsa2 and organelle genome scaffolds assembled with Oatk (https://github.com/c-zhou/oatk)

• Timopheevii.final.pm.oriented.with_org.fasta.gz (assembly with organellar genomes)
• Timopheevii.final.pm.oriented.fasta.gz (assembly of only nuclear chromosomes)

Hi-C Contact map generated by mapping short-reads using the Arima pipeline (https://github.com/ArimaGenomics/mapping_pipeline) and scaffolds manually curated with Rapid Curation Pipeline (https://gitlab.com/wtsi-grit/rapid-curation)

• Timopheevii.final.pm.oriented.pretext
  • This is the final HiC contact map generated by mapping the HiC short reads onto the curated assembly. This file can be opened using PretextView v.0.2.5 (available at https://github.com/wtsi-hpag/PretextView/releases)

Annotation
Gene models were ge...

In the areas with wet climate of Eastern Asia, Fusarium head blight (FHB) is a major threat to bread wheat production. A source of FHB resistance (Fhb1) was identified in the Asian wheat germplasm and through classical breeding it was introduced in several varieties (https://doi.org/10.1186/s40066-017-0139-z ). The molecular determinant was identified as a deletion in an histidine-rich calcium-binding-protein gene on chromosome 3BS. (https://doi.org/10.1038/s41588-019-0426-7). The allele is common in many East Asia wheat varieties, but not in the reference assembly Chinese Spring (CS).

The whole-genome assembly of the Japanese variety Norin 61 allowed to confirm the sequence and structure of the haplotype surrounding Fhb1. Given the low amount of sequence conservation with CS at the locus, we noticed that the annotation based on projections of CS gene models (https://doi.org/10.1038/s41586-020-2961-x) did not identify all genes in the Norin 61 haplotype.

To describe the complete set of coding regions in the Fhb1 allele, we de novo annotated the Norin 61 ~340 kb Fhb1 region with homology- and ab initio-based evidence. MAKER v2.31.9 was run on the Norin 61 genomic interval, with the Uniprot Liliopsida proteome, and the annotation from https://doi.org/10.1038/s41586-020-2961-x. Augustus was run with wheat as a species, and the output was parsed removing models that had >40% similarity over >50% of their length to TE proteins via BLASTP.

Our annotation identified 70 protein-coding genes, 50 more than the ones identified by homology only.A deletion in the start codon (third exon) of TaHRC gene was confirmed as the causal mutaiton conferring resistance, and it was present in other vaireties having the same resistance.

This resource highlights the importance of an appropriate characterization of the sequence in a non-reference genotype, especially when considering new variants with traits important for modern breeding programs.

Since the introduction of wheat into Australia by the First Fleet settlers, germplasm from different geographical origins has been used to adapt wheat to the Australian climate through selection and breeding. In this paper, we used 482 cultivars, representing the breeding history of bread wheat in Australia since 1840, to characterize their diversity and population structure and to define the geographical ancestral background of Australian wheat germplasm. This was achieved by comparing them to a global wheat collection using in-silico chromosome painting based on SNP genotyping. The global collection involved 2,335 wheat accessions which was divided into 23 different geographical subpopulations. However, the whole set was reduced to 1,544 accessions to increase the differentiation and decrease the admixture among different global subpopulations to increase the power of the painting analysis. Our analysis revealed that the structure of Australian wheat germplasm and its geographic ancestors have changed significantly through time, especially after the Green Revolution. Before 1920, breeders used cultivars from around the world, but mainly Europe and Africa, to select potential cultivars that could tolerate Australian growing conditions. Between 1921 and 1970, a dependence on African wheat germplasm became more prevalent. Since 1970, a heavy reliance on International Maize and Wheat Improvement Center (CIMMYT) germplasm has persisted. Combining the results from linkage disequilibrium, population structure and in-silico painting revealed that the dependence on CIMMYT materials has varied among different Australian Sstates, has shrunken the germplasm effective population size and produced larger linkage disequilibrium blocks. This study documents the evolutionary history of wheat breeding in Australia and provides an understanding for how the wheat genome has been adapted to local growing conditions. This information provides a guide for industry to assist with maintaining genetic diversity for long-term selection gains and to plan future breeding programs.

RenSeq assemblies of 907 diverse T. aestivum genotypes and two control genotypes. The assemblies were generated using CLC assembler (https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/analysis-and-visualization/qiagen-clc-assembly-cell/). The contigs from each accession were annotated with AUGUSTUS v3.3.1 using wheat gene models as training datasets and contigs with complete genes were identified. Amino acid (AA), coding sequence (CDS) and transcript sequence for each complete gene was extracted using getAnnoFasta.pl script from AUGUSTUS package. The files ending with “_updated_fasta” is the direct output of CLC assembler and contains contigs from each accession. The files ending with “_updated_complete.gff”, “_updated_complete.mrna”, “_updated_complete.aa” and “_updated_complete.codingseq” contain gene information in GFF3 format, transcript sequences, amino acid sequences and coding sequences respectively from each accession. Passport data and/or pedigree information and BioSamples IDs of RenSeq raw data are provided in the sample information file.

RenSeq assemblies of 907 diverse T. aestivum genotypes and two control genotypes. The assemblies were generated using CLC assembler (https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/analysis-and-visualization/qiagen-clc-assembly-cell/). The contigs from each accession were annotated with AUGUSTUS v3.3.1 using wheat gene models as training datasets and contigs with complete genes were identified. Amino acid (AA), coding sequence (CDS) and transcript sequence for each complete gene was extracted using getAnnoFasta.pl script from AUGUSTUS package. The files ending with “_updated_fasta” is the direct output of CLC assembler and contains contigs from each accession. The files ending with “_updated_complete.gff”, “_updated_complete.mrna”, “_updated_complete.aa” and “_updated_complete.codingseq” contain gene information in GFF3 format, transcript sequences, amino acid sequences and coding sequences respectively from each accession. Passport data and/or pedigree information and BioSamples IDs of RenSeq raw data are provided in the sample information file.

Wheat immunotoxicity is associated with abnormal reaction to gluten-derived peptides. Attempts to reduce immunotoxicity using breeding and biotechnology often affect dough quality. Here, the multiplexed CRISPR-Cas9 editing of cultivar Fielder was used to modify gluten-encoding genes, specifically focusing on omega- and gamma-gliadin gene copies, which were identified to be abundant in immunoreactive peptides based on the analysis of wheat genomes assembled using the long-read sequencing technologies. The whole genome sequencing of an edited line showed mutation or deletion of nearly all omega-gliadin and half of the gamma-gliadin gene copies and confirmed the lack of editing in the alpha/beta-gliadin genes. The estimated 75% and 64% reduction in omega- and gamma-gliadin content, respectively, had no negative impact on the end-use quality characteristics of grain protein and dough. A 47-fold immunoreactivity reduction compared to non-edited line was demonstrated using antibodies against immunotoxic peptides. Our results indicate that the targeted CRISPR-based modification of the omega- and gamma-gliadin gene copies determined to be abundant in immunoreactive peptides by analyzing high-quality genome assemblies is an effective mean for reducing immunotoxicity of wheat cultivars while minimizing the impact of editing on protein quality.

Wild wheat relatives of bread wheat represent genetic diversity that can be used for wheat crop improvement. Here, we establish and analyse genomic resources for Tausch’s goatgrass, Aegilops tauschii, the donor of the bread wheat D genome. We determined 493 genetically non-redundant accessions from a diversity panel of over 900 sequenced accessions. We generated high-quality assemblies for 46 accessions, including annotated chromosome-scale assemblies for one accession from each of the three lineages of Ae. tauschii to serve a reference assemblies to anchor the genomic resources. This dataset was generated under the aegis of the Open Wild Wheat Consortium (www.openwildwheat.org). We also resequenced and analysed 60 wheat landraces and generated a chromosome-scale genome assembly for one of these to study the genetic composition and history of the bread wheat D genome. We determined the complexity and origin of the D genome across 17 hexaploid wheat lines by dividing the wheat genomes into 50-kb windows and assigned each window to an Ae. tauschii subpopulation based on identity-by-state. This dataset provides:

Pseudo-chromosome level genome assemblies, Hi-C contact maps and genome annotations for the Ae. tauschii lineage-reference accessions TA10171 (L1), TA1675 (L2) and TA2576 (L3), Contig-level and lineage reference-scaffolded assemblies for 43 Ae. tauschii accessions sequenced with PacBIO CCS Pseudo-chromosome level genome assembly, Omni-C contact map and genome annotation for bread wheat landrace accession CWI 86942, Variant call (SNP) vcf file for the Ae. tauschii diversity panel. SNP were called against the TA1675 (L2) reference assembly, Phylogenetic newick tree file for the non-redundant Ae. tauschii accessions, Structural variants (SV) vcf files for Ae. tauschii accessions sequenced with PacBIO CCS. SV were called against the TA1675 (L2) reference assembly, IBSpy variations across 17 hexaploid wheat genomes using Ae. tauschii k-mer sets

Methods The full methods are available in the related publication.

Genetic improvements in heat tolerance of wheat provide a potential adaptation response to long-term warming trends, and may also boost yields in wheat-growing areas already subject to heat stress. Yet there have been few assessments of recent progress in breeding wheat for hot environments. Here, data from 25 years of wheat trials in 76 countries from the International Maize and Wheat Improvement Center (CIMMYT) are used to empirically model the response of wheat to environmental variation and assess the genetic gains over time in different environments and for different breeding strategies. Wheat yields exhibited the most sensitivity to warming during the grain-filling stage, typically the hottest part of the season. Sites with high vapour pressure deficit (VPD) exhibited a less negative response to temperatures during this period, probably associated with increased transpirational cooling. Genetic improvements were assessed by using the empirical model to correct observed yield growth for changes in environmental conditions and management over time. These 'climate-corrected' yield trends showed that most of the genetic gains in the high-yield-potential Elite Spring Wheat Yield Trial (ESWYT) were made at cooler temperatures, close to the physiological optimum, with no evidence for genetic gains at the hottest temperatures. In contrast, the Semi-Arid Wheat Yield Trial (SAWYT), a lower-yielding nursery targeted at maintaining yields under stressed conditions, showed the strongest genetic gains at the hottest temperatures. These results imply that targeted breeding efforts help us to ensure progress in building heat tolerance, and that intensified (and possibly new) approaches are needed to improve the yield potential of wheat in hot environments in order to maintain global food security in a warmer climate.

The TCP family genes are plant-specific transcription factors and play important roles in plant development. TCPs have been evolutionarily and functionally studied in several plants. Although common wheat (Triticum aestivum L.) is a major staple crop worldwide, no systematic analysis of TCPs in this important crop has been conducted. Here, we performed a genome-wide survey in wheat and found 66 TCP genes that belonged to 22 homoeologous groups. We then mapped these genes on wheat chromosomes and found that several TCP genes were duplicated in wheat including the ortholog of the maize TEOSINTE BRANCHED 1. Expression study using both RT-PCR and in situ hybridization assay showed that most wheat TCP genes were expressed throughout development of young spike and immature seed. Cis-acting element survey along promoter regions suggests that subfunctionalization may have occurred for homoeologous genes. Moreover, protein–protein interaction experiments of three TCP proteins showed that they can form either homodimers or heterodimers. Finally, we characterized two TaTCP9 mutants from tetraploid wheat. Each of these two mutant lines contained a premature stop codon in the A subgenome homoeolog that was dominantly expressed over the B subgenome homoeolog. We observed that mutation caused increased spike and grain lengths. Together, our analysis of the wheat TCP gene family provides a start point for further functional study of these important transcription factors in wheat.

The TCP family genes are plant-specific transcription factors and play important roles in plant development. TCPs have been evolutionarily and functionally studied in several plants. Although common wheat (Triticum aestivum L.) is a major staple crop worldwide, no systematic analysis of TCPs in this important crop has been conducted. Here, we performed a genome-wide survey in wheat and found 66 TCP genes that belonged to 22 homoeologous groups. We then mapped these genes on wheat chromosomes and found that several TCP genes were duplicated in wheat including the ortholog of the maize TEOSINTE BRANCHED 1. Expression study using both RT-PCR and in situ hybridization assay showed that most wheat TCP genes were expressed throughout development of young spike and immature seed. Cis-acting element survey along promoter regions suggests that subfunctionalization may have occurred for homoeologous genes. Moreover, protein–protein interaction experiments of three TCP proteins showed that they can form either homodimers or heterodimers. Finally, we characterized two TaTCP9 mutants from tetraploid wheat. Each of these two mutant lines contained a premature stop codon in the A subgenome homoeolog that was dominantly expressed over the B subgenome homoeolog. We observed that mutation caused increased spike and grain lengths. Together, our analysis of the wheat TCP gene family provides a start point for further functional study of these important transcription factors in wheat.

Detailed information of the 8891 differentially expressed genes between the natural and resynthesized allohexaploid wheats (TAA10 and XX329). (XLSX 473Â kb)