Improved multi-trait prediction of wheat end-product quality traits by integrating NIR-predicted phenotypes.

Historically, end-product quality testing has been costly and required large flour samples; therefore, it was generally implemented in the late phases of variety development, imposing a huge cost on the breeding effort and effectiveness. High genetic correlations of end-product quality traits with higher throughput and nondestructive testing technologies, such as near-infrared (NIR), could enable early-stage testing and effective selection of these highly valuable traits in a multi-trait genomic prediction model. We studied the impact on prediction accuracy in genomic best linear unbiased prediction (GBLUP) of adding NIR-predicted secondary traits for six end-product quality traits (crumb yellowness, water absorption, texture hardness, flour yield, grain protein, flour swelling volume). Bread wheat lines (1,400-1,900) were measured across 8 years (2012-2019) for six end-product quality traits with standard laboratory assays and with NIR, which were combined to generate predicted data for approximately 27,000 lines. All lines were genotyped with the Infinium™ Wheat Barley 40K BeadChip and imputed using exome sequence data. End-product and NIR phenotypes were genetically correlated (0.5-0.83, except for flour swelling volume 0.19). Prediction accuracies of end-product traits ranged between 0.28 and 0.64 and increased by 30% through the inclusion of NIR-predicted data compared to single-trait analysis. There was a high correlation between the multi-trait prediction accuracy and genetic correlations between end-product and NIR-predicted data (0.69-0.77). Our forward prediction validation revealed a gradual increase in prediction accuracy when adding more years to the multi-trait model. Overall, we achieved genomic prediction accuracy at a level that enables selection for end-product quality traits early in the breeding cycle.

Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat.

Soil salinity can impose substantial stress on plant growth and cause significant yield losses. Crop varieties tolerant to salinity stress are needed to sustain yields in saline soils. This requires effective genotyping and phenotyping of germplasm pools to identify novel genes and QTL conferring salt tolerance that can be utilised in crop breeding schemes. We investigated a globally diverse collection of 580 wheat accessions for their growth response to salinity using automated digital phenotyping performed under controlled environmental conditions. The results show that digitally collected plant traits, including digital shoot growth rate and digital senescence rate, can be used as proxy traits for selecting salinity-tolerant accessions. A haplotype-based genome-wide association study was conducted using 58,502 linkage disequilibrium-based haplotype blocks derived from 883,300 genome-wide SNPs and identified 95 QTL for salinity tolerance component traits, of which 54 were novel and 41 overlapped with previously reported QTL. Gene ontology analysis identified a suite of candidate genes for salinity tolerance, some of which are already known to play a role in stress tolerance in other plant species. This study identified wheat accessions that utilise different tolerance mechanisms and which can be used in future studies to investigate the genetic and genic basis of salinity tolerance. Our results suggest salinity tolerance has not arisen from or been bred into accessions from specific regions or groups. Rather, they suggest salinity tolerance is widespread, with small-effect genetic variants contributing to different levels of tolerance in diverse, locally adapted germplasm.

Genetic analysis of global faba bean diversity, agronomic traits and selection signatures.

KEY MESSAGE: We identified marker-trait associations for key faba bean agronomic traits and genomic signatures of selection within a global germplasm collection. Faba bean (Vicia faba L.) is a high-protein grain legume crop with great potential for sustainable protein production. However, little is known about the genetics underlying trait diversity. In this study, we used 21,345 high-quality SNP markers to genetically characterize 2678 faba bean genotypes. We performed genome-wide association studies of key agronomic traits using a seven-parent-MAGIC population and detected 238 significant marker-trait associations linked to 12 traits of agronomic importance. Sixty-five of these were stable across multiple environments. Using a non-redundant diversity panel of 685 accessions from 52 countries, we identified three subpopulations differentiated by geographical origin and 33 genomic regions subjected to strong diversifying selection between subpopulations. We found that SNP markers associated with the differentiation of northern and southern accessions explained a significant proportion of agronomic trait variance in the seven-parent-MAGIC population, suggesting that some of these traits were targets of selection during breeding. Our findings point to genomic regions associated with important agronomic traits and selection, facilitating faba bean genomics-based breeding.

The giant diploid faba genome unlocks variation in a global protein crop.

Increasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity1. However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value2. Faba bean (Vicia faba L.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13 Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the improvement of sustainable protein production across the Mediterranean, subtropical and northern temperate agroecological zones.

Benefit of Introgression Depends on Level of Genetic Trait Variation in Cereal Breeding Programmes.

We investigated the benefit from introgression of external lines into a cereal breeding programme and strategies that accelerated introgression of the favourable alleles while minimising linkage drag using stochastic computer simulation. We simulated genomic selection for disease resistance and grain yield in two environments with a high level of genotype-by-environment interaction (G × E) for the latter trait, using genomic data of a historical barley breeding programme as the base generation. Two populations (existing and external) were created from this base population with different allele frequencies for few (N = 10) major and many (N ~ 990) minor simulated disease quantitative trait loci (QTL). The major disease QTL only existed in the external population and lines from the external population were introgressed into the existing population which had minor disease QTL with low, medium and high allele frequencies. The study revealed that the benefit of introgression depended on the level of genetic variation for the target trait in the existing cereal breeding programme. Introgression of external resources into the existing population was beneficial only when the existing population lacked variation in disease resistance or when minor disease QTL were already at medium or high frequency. When minor disease QTL were at low frequencies, no extra genetic gain was achieved from introgression. More benefit in the disease trait was obtained from the introgression if the major disease QTL had larger effect sizes, more selection emphasis was applied on disease resistance, or more external lines were introgressed. While our strategies to increase introgression of major disease QTL were generally successful, most were not able to completely avoid negative impacts on selection for grain yield with the only exception being when major introgression QTL effects were very large. Breeding programmes are advised to carefully consider the level of genetic variation in a trait available in their breeding programme before deciding to introgress germplasms.

Optical maps refine the bread wheat Triticum aestivum cv. Chinese Spring genome assembly.

Until recently, achieving a reference-quality genome sequence for bread wheat was long thought beyond the limits of genome sequencing and assembly technology, primarily due to the large genome size and > 80% repetitive sequence content. The release of the chromosome scale 14.5-Gb IWGSC RefSeq v1.0 genome sequence of bread wheat cv. Chinese Spring (CS) was, therefore, a milestone. Here, we used a direct label and stain (DLS) optical map of the CS genome together with a prior nick, label, repair and stain (NLRS) optical map, and sequence contigs assembled with Pacific Biosciences long reads, to refine the v1.0 assembly. Inconsistencies between the sequence and maps were reconciled and gaps were closed. Gap filling and anchoring of 279 unplaced scaffolds increased the total length of pseudomolecules by 168 Mb (excluding Ns). Positions and orientations were corrected for 233 and 354 scaffolds, respectively, representing 10% of the genome sequence. The accuracy of the remaining 90% of the assembly was validated. As a result of the increased contiguity, the numbers of transposable elements (TEs) and intact TEs have increased in IWGSC RefSeq v2.1 compared with v1.0. In total, 98% of the gene models identified in v1.0 were mapped onto this new assembly through development of a dedicated approach implemented in the MAGAAT pipeline. The numbers of high-confidence genes on pseudomolecules have increased from 105 319 to 105 534. The reconciled assembly enhances the utility of the sequence for genetic mapping, comparative genomics, gene annotation and isolation, and more general studies on the biology of wheat.

Meta-analysis of genome-wide association studies reveal common loci controlling agronomic and quality traits in a wide range of normal and heat stressed environments.

KEY MESSAGE: Several stable QTL were detected using metaGWAS analysis for different agronomic and quality traits under 26 normal and heat stressed environments. Heat stress, exacerbated by global warming, has a negative influence on wheat production worldwide and climate resilient cultivars can help mitigate these impacts. Selection decisions should therefore depend on multi-environment experiments representing a range of temperatures at critical stages of development. Here, we applied a meta-genome wide association analysis (metaGWAS) approach to detect stable QTL with significant effects across multiple environments. The metaGWAS was applied to 11 traits scored in 26 trials that were sown at optimal or late times of sowing (TOS1 and TOS2, respectively) at five locations. A total of 2571 unique wheat genotypes (13,959 genotypes across all environments) were included and the analysis conducted on TOS1, TOS2 and both times of sowing combined (TOS1&2). The germplasm was genotyped using a 90 k Infinium chip and imputed to exome sequence level, resulting in 341,195 single nucleotide polymorphisms (SNPs). The average accuracy across all imputed SNPs was high (92.4%). The three metaGWAS analyses revealed 107 QTL for the 11 traits, of which 16 were detected in all three analyses and 23 were detected in TOS1&2 only. The remaining QTL were detected in either TOS1 or TOS2 with or without TOS1&2, reflecting the complex interactions between the environments and the detected QTL. Eight QTL were associated with grain yield and seven with multiple traits. The identified QTL provide an important resource for gene enrichment and fine mapping to further understand the mechanisms of gene × environment interaction under both heat stressed and unstressed conditions.

Compact and evenly distributed k-mer binning for genomic sequences.

MOTIVATION: The processing of k-mers (subsequences of length k) is at the foundation of many sequence processing algorithms in bioinformatics, including k-mer counting for genome size estimation, genome assembly, and taxonomic classification for metagenomics. Minimizers-ordered m-mers where m < k-are often used to group k-mers into bins as a first step in such processing. However, minimizers are known to generate bins of very different sizes, which can pose challenges for distributed and parallel processing, as well as generally increase memory requirements. Furthermore, although various minimizer orderings have been proposed, their practical value for improving tool efficiency has not yet been fully explored. RESULTS: We present Discount, a distributed k-mer counting tool based on Apache Spark, which we use to investigate the behaviour of various minimizer orderings in practice when applied to metagenomics data. Using this tool, we then introduce the universal frequency ordering, a new combination of frequency-sampled minimizers and universal k-mer hitting sets, which yields both evenly distributed binning and small bin sizes. We show that this ordering allows Discount to perform distributed k-mer counting on a large dataset in as little as 1/8 of the memory of comparable approaches, making it the most efficient out-of-core distributed k-mer counting method available. AVAILABILITY AND IMPLEMENTATION: Discount is GPL licensed and available at https://github.com/jtnystrom/discount. The data underlying this article are available in the article and in its online supplementary material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Novel Design of Imputation-Enabled SNP Arrays for Breeding and Research Applications Supporting Multi-Species Hybridization.

Array-based single nucleotide polymorphism (SNP) genotyping platforms have low genotype error and missing data rates compared to genotyping-by-sequencing technologies. However, design decisions used to create array-based SNP genotyping assays for both research and breeding applications are critical to their success. We describe a novel approach applicable to any animal or plant species for the design of cost-effective imputation-enabled SNP genotyping arrays with broad utility and demonstrate its application through the development of the Illumina Infinium Wheat Barley 40K SNP array Version 1.0. We show that the approach delivers high quality and high resolution data for wheat and barley, including when samples are jointly hybridised. The new array aims to maximally capture haplotypic diversity in globally diverse wheat and barley germplasm while minimizing ascertainment bias. Comprising mostly biallelic markers that were designed to be species-specific and single-copy, the array permits highly accurate imputation in diverse germplasm to improve the statistical power of genome-wide association studies (GWAS) and genomic selection. The SNP content captures tetraploid wheat (A- and B-genome) and Aegilops tauschii Coss. (D-genome) diversity and delineates synthetic and tetraploid wheat from other wheat, as well as tetraploid species and subgroups. The content includes SNP tagging key trait loci in wheat and barley, as well as direct connections to other genotyping platforms and legacy datasets. The utility of the array is enhanced through the web-based tool, Pretzel (https://plantinformatics.io/) which enables the content of the array to be visualized and interrogated interactively in the context of numerous genetic and genomic resources to be connected more seamlessly to research and breeding. The array is available for use by the international wheat and barley community.

Accurate calling of homeoallelic genotypes of iSelect markers using inbred structured populations.

MOTIVATION: Genetic map construction is a foundational step in the analysis of structured experimental populations. For markers that hybridize to several genetically similar locations, or where several alleles are present (such as in multiparental populations), current methods often discard the marker or incorrectly call the genotypes. These errors result in information loss, or incorrect genotypes that can corrupt map construction. RESULTS: We present a new approach for simultaneously performing genetic map construction and marker calling. Our new approach allows the calling of a larger number of markers, a larger number of unique alleles per marker and the correct use of markers which hybridize to multiple genetically similar locations. We demonstrate our new approach using simulations, a biparental wheat population and an eight-parent population of spring bread wheat. Applying our method to the eight-parent population increased the number of mapped markers by 71%. We show that the new genetic map allows the investigation of synteny in ways that were not previously possible in that dataset. AVAILABILITY AND IMPLEMENTATION: The method described in this article has been incorporated into R package mpMap2. It is available from CRAN and also from https://github.com/rohan-shah/mpMap2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Publisher Correction: Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

High-resolution mapping of rachis nodes per rachis, a critical determinant of grain yield components in wheat.

KEY MESSAGE: Exploring large genomic data sets based on the latest reference genome assembly identifies the rice ortholog APO1 as a key candidate gene for number of rachis nodes per spike in wheat. Increasing grain yield in wheat is a key breeding objective worldwide. Several component traits contribute to grain yield with spike attributes being among the most important. In this study, we performed a genome-wide association analysis for 12 grain yield and component traits measured in field trials with contrasting agrochemical input levels in a panel of 220 hexaploid winter wheats. A highly significant, environmentally consistent QTL was detected for number of rachis nodes per rachis (NRN) on chromosome 7AL. The five most significant SNPs formed a strong linkage disequilibrium (LD) block and tagged a 2.23 Mb region. Using pairwise LD for exome SNPs located across this interval in a large worldwide hexaploid wheat collection, we reduced the genomic region for NRN to a 258 Kb interval containing four of the original SNP and six high-confidence genes. The ortholog of one (TraesCS7A01G481600) of these genes in rice was ABBERANT PANICLE ORGANIZATION1 (APO1), which is known to have significant effects on panicle attributes. The APO1 ortholog was the best candidate for NRN and was associated with a 115 bp promoter deletion and two amino acid (C47F and D384 N) changes. Using a large worldwide collection of tetraploid and hexaploid wheat, we found 12 haplotypes for the NRN QTL and evidence for positive enrichment of two haplotypes in modern germplasm. Comparison of five QTL haplotypes in Australian yield trials revealed their relative, context-dependent contribution to grain yield. Our study provides diagnostic SNPs and value propositions to support deployment of the NRN trait in wheat breeding.

Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome.

Introgression is a potential source of beneficial genetic diversity. The contribution of introgression to adaptive evolution and improvement of wheat as it was disseminated worldwide remains unknown. We used targeted re-sequencing of 890 diverse accessions of hexaploid and tetraploid wheat to identify wild-relative introgression. Introgression, and selection for improvement and environmental adaptation, each reduced deleterious allele burden. Introgression increased diversity genome wide and in regions harboring major agronomic genes, and contributed alleles explaining a substantial proportion of phenotypic variation. These results suggest that historic gene flow from wild relatives made a substantial contribution to the adaptive diversity of modern bread wheat.

Globular structures in roots accumulate phosphorus to extremely high concentrations following phosphorus addition.

Crops with improved uptake of fertilizer phosphorus (P) would reduce P losses and confer environmental benefits. We examined how P-sufficient 6-week-old soil-grown Trifolium subterraneum plants, and 2-week-old seedlings in solution culture, accumulated P in roots after inorganic P (Pi) addition. In contrast to our expectation that vacuoles would accumulate excess P, after 7 days, X-ray microanalysis showed that vacuolar [P] remained low (<12 mmol kg-1 ). However, in the plants after P addition, some cortex cells contained globular structures extraordinarily rich in P (often >3,000 mmol kg-1 ), potassium, magnesium, and sodium. Similar structures were evident in seedlings, both before and after P addition, with their [P] increasing threefold after P addition. Nuclear magnetic resonance (NMR) spectroscopy showed seedling roots accumulated Pi following P addition, and transmission electron microscopy (TEM) revealed large plastids. For seedlings, we demonstrated that roots differentially expressed genes after P addition using RNAseq mapped to the T. subterraneum reference genome assembly and transcriptome profiles. Among the most up-regulated genes after 4 hr was TSub_g9430.t1, which is similar to plastid envelope Pi transporters (PHT4;1, PHT4;4): expression of vacuolar Pi-transporter homologs did not change. We suggest that subcellular P accumulation in globular structures, which may include plastids, aids cytosolic Pi homeostasis under high-P availability.

Optical and physical mapping with local finishing enables megabase-scale resolution of agronomically important regions in the wheat genome.

BACKGROUND: Numerous scaffold-level sequences for wheat are now being released and, in this context, we report on a strategy for improving the overall assembly to a level comparable to that of the human genome. RESULTS: Using chromosome 7A of wheat as a model, sequence-finished megabase-scale sections of this chromosome were established by combining a new independent assembly using a bacterial artificial chromosome (BAC)-based physical map, BAC pool paired-end sequencing, chromosome-arm-specific mate-pair sequencing and Bionano optical mapping with the International Wheat Genome Sequencing Consortium RefSeq v1.0 sequence and its underlying raw data. The combined assembly results in 18 super-scaffolds across the chromosome. The value of finished genome regions is demonstrated for two approximately 2.5 Mb regions associated with yield and the grain quality phenotype of fructan carbohydrate grain levels. In addition, the 50 Mb centromere region analysis incorporates cytological data highlighting the importance of non-sequence data in the assembly of this complex genome region. CONCLUSIONS: Sufficient genome sequence information is shown to now be available for the wheat community to produce sequence-finished releases of each chromosome of the reference genome. The high-level completion identified that an array of seven fructosyl transferase genes underpins grain quality and that yield attributes are affected by five F-box-only-protein-ubiquitin ligase domain and four root-specific lipid transfer domain genes. The completed sequence also includes the centromere.

Genome mapping of seed-borne allergens and immunoresponsive proteins in wheat.

Wheat is an important staple grain for humankind globally because of its end-use quality and nutritional properties and its adaptability to diverse climates. For a small proportion of the population, specific wheat proteins can trigger adverse immune responses and clinical manifestations such as celiac disease, wheat allergy, baker's asthma, and wheat-dependent exercise-induced anaphylaxis (WDEIA). Establishing the content and distribution of the immunostimulatory regions in wheat has been hampered by the complexity of the wheat genome and the lack of complete genome sequence information. We provide novel insights into the wheat grain proteins based on a comprehensive analysis and annotation of the wheat prolamin Pfam clan grain proteins and other non-prolamin allergens implicated in these disorders using the new International Wheat Genome Sequencing Consortium bread wheat reference genome sequence, RefSeq v1.0. Celiac disease and WDEIA genes are primarily expressed in the starchy endosperm and show wide variation in protein- and transcript-level expression in response to temperature stress. Nonspecific lipid transfer proteins and α-amylase trypsin inhibitor gene families, implicated in baker's asthma, are primarily expressed in the aleurone layer and transfer cells of grains and are more sensitive to cold temperature. The study establishes a new reference map for immunostimulatory wheat proteins and provides a fresh basis for selecting wheat lines and developing diagnostics for products with more favorable consumer attributes.

Transcriptome reprogramming due to the introduction of a barley telosome into bread wheat affects more barley genes than wheat.

Despite a long history, the production of useful alien introgression lines in wheat remains difficult mainly due to linkage drag and incomplete genetic compensation. In addition, little is known about the molecular mechanisms underlying the impact of foreign chromatin on plant phenotype. Here, a comparison of the transcriptomes of barley, wheat and a wheat-barley 7HL addition line allowed the transcriptional impact both on 7HL genes of a non-native genetic background and on the wheat gene complement as a result of the presence of 7HL to be assessed. Some 42% (389/923) of the 7HL genes assayed were differentially transcribed, which was the case for only 3% (960/35 301) of the wheat gene complement. The absence of any transcript in the addition line of a suite of chromosome 7A genes implied the presence of a 36 Mbp deletion at the distal end of the 7AL arm; this deletion was found to be in common across the full set of Chinese Spring/Betzes barley addition lines. The remaining differentially transcribed wheat genes were distributed across the whole genome. The up-regulated barley genes were mostly located in the proximal part of the 7HL arm, while the down-regulated ones were concentrated in the distal part; as a result, genes encoding basal cellular functions tended to be transcribed, while those encoding specific functions were suppressed. An insight has been gained into gene transcription in an alien introgression line, thereby providing a basis for understanding the interactions between wheat and exotic genes in introgression materials.

Climate Clever Clovers: New Paradigm to Reduce the Environmental Footprint of Ruminants by Breeding Low Methanogenic Forages Utilizing Haplotype Variation.

Mitigating methane production by ruminants is a significant challenge to global livestock production. This research offers a new paradigm to reduce methane emissions from ruminants by breeding climate-clever clovers. We demonstrate wide genetic diversity for the trait methanogenic potential in Australia's key pasture legume, subterranean clover (Trifolium subterraneum L.). In a bi-parental population the broadsense heritability in methanogenic potential was moderate (H2 = 0.4) and allelic variation in a region of Chr 8 accounted for 7.8% of phenotypic variation. In a genome-wide association study we identified four loci controlling methanogenic potential assessed by an in vitro fermentation system. Significantly, the discovery of a single nucleotide polymorphism (SNP) on Chr 5 in a defined haplotype block with an upstream putative candidate gene from a plant peroxidase-like superfamily (TSub_g18548) and a downstream lectin receptor protein kinase (TSub_g18549) provides valuable candidates for an assay for this complex trait. In this way haplotype variation can be tracked to breed pastures with reduced methanogenic potential. Of the quantitative trait loci candidates, the DNA-damage-repair/toleration DRT100-like protein (TSub_g26967), linked to avoid the severity of DNA damage induced by secondary metabolites, is considered central to enteric methane production, as are disease resistance (TSub_g26971, TSub_g26972, and TSub_g18549) and ribonuclease proteins (TSub_g26974, TSub_g26975). These proteins are good pointers to elucidate the genetic basis of in vitro microbial fermentability and enteric methanogenic potential in subterranean clover. The genes identified allow the design of a suite of markers for marker-assisted selection to reduce rumen methane emission in selected pasture legumes. We demonstrate the feasibility of a plant breeding approach without compromising animal productivity to mitigate enteric methane emissions, which is one of the most significant challenges to global livestock production.