Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops

Haplotype-based breeding: A new insight in crop improvement

Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.

Haplotype-based association mapping of genomic regions associated with Zymoseptoria tritici resistance using 217 diverse wheat genotypes

BACKGROUND

Septoria tritici blotch (STB) is considered to be one of the most destructive foliar wheat diseases and is caused by Zymoseptoria tritici. The yield losses are severe and in Northwestern Europe can reach up to 50%. The efficacy of fungicides is diminishing due to changes in the genetic structure of the pathogen. Therefore, resistance breeding is the most effective strategy of disease management. Recently, genome-wide association studies (GWAS) have become more popular due to their robustness in dissecting complex traits, including STB resistance in wheat. This was made possible by the use of large mapping populations and new sequencing technologies. High-resolution mapping benefits from historical recombination and greater allele numbers in GWAS.

RESULTS

In our study, 217 wheat genotypes of diverse origin were phenotyped against five Z. tritici isolates (IPO323, IPO88004, IPO92004, IPO86036 and St1-03) and genotyped on the DArTseq platform. In polytunnel tests two disease parameters were evaluated: the percentage of leaf area covered by necrotic lesions (NEC) and the percentage of leaf area covered by lesions bearing pycnidia (PYC). The disease escape parameters heading date (Hd) and plant height (Ht) were also measured. Pearson's correlation showed a positive effect between disease parameters, providing additional information. The Structure analysis indicated four subpopulations which included from 28 (subpopulation 2) to 79 genotypes (subpopulation 3). All of the subpopulations showed a relatively high degree of admixture, which ranged from 60% of genotypes with less than 80% of proportions of the genome attributed to assigned subpopulation for group 2 to 85% for group 4. Haplotype-based GWAS analysis allowed us to identify 27 haploblocks (HBs) significantly associated with analysed traits with a p-value above the genome-wide significance threshold (5%, which was -log10(p) > 3.64) and spread across the wheat genome. The explained phenotypic variation of identified significant HBs ranged from 0.2% to 21.5%. The results of the analysis showed that four haplotypes (HTs) associated with disease parameters cause a reduction in the level of leaf coverage by necrosis and pycnidia, namely: Chr3A_HB98_HT2, Chr5B_HB47_HT1, Chr7B_HB36_HT1 and Chr5D_HB10_HT3.

CONCLUSIONS

GWAS analysis enabled us to identify four significant chromosomal regions associated with a reduction in STB disease parameters. The list of valuable HBs and wheat varieties possessing them provides promising material for further molecular analysis of resistance loci and development of breeding programmes.

The Detection of a Functional 168 bp Deletion of the HOXB13 Gene Determining Short Tail and Its Association with Senior Growth Traits in Sheep Breeds Worldwide

In recent years, genome-wide association studies (GWAS) have uncovered that the HOXB13 gene is a key regulatory factor for the tail length trait of sheep. Further research has found that there is a functional 168 bp SINE element insertion upstream of the HOXB13 gene, which leads to the occurrence of long tails in sheep. However, the frequency of mutations in the 168 bp SINE element of the HOXB13 gene among different sheep breeds around the world and its relationship with growth traits are still unclear. This study used whole-genome sequencing (WGS) data, including 588 samples from 33 different sheep breeds around the world, to evaluate the frequency of HOXB13 gene mutations in different sheep breeds globally. At the same time, this study also selected 3392 sheep samples from six breeds. The genetic variation in the 168 bp InDel locus in the HOXB13 gene was determined through genotyping, and its association with the growth traits of Luxi black-headed sheep was analyzed. The research results indicate that the polymorphism of the 168 bp InDel locus is significantly correlated with the hip width of adult ewes in the Luxi black-headed sheep breed (p < 0.05) and that the hip width of adult ewes with the DD genotype is significantly larger than that of adult ewes with the ID genotype (p < 0.05). This study indicates that there is consistency between the research results on the sheep tail length trait and growth traits, which may contribute to the promotion of sheep breed improvement.

Dissection of quantitative trait nucleotides and candidate genes associated with agronomic and yield-related traits under drought stress in rapeseed varieties: integration of genome-wide association study and transcriptomic analysis

Introduction

An important strategy to combat yield loss challenge is the development of varieties with increased tolerance to drought to maintain production. Improvement of crop yield under drought stress is critical to global food security.

Methods

In this study, we performed multiomics analysis in a collection of 119 diverse rapeseed (Brassica napus L.) varieties to dissect the genetic control of agronomic traits in two watering regimes [well-watered (WW) and drought stress (DS)] for 3 years. In the DS treatment, irrigation continued till the 50% pod development stage, whereas in the WW condition, it was performed throughout the whole growing season.

Results

The results of the genome-wide association study (GWAS) using 52,157 single-nucleotide polymorphisms (SNPs) revealed 1,281 SNPs associated with traits. Six stable SNPs showed sequence variation for flowering time between the two irrigation conditions across years. Three novel SNPs on chromosome C04 for plant weight were located within drought tolerance-related gene ABCG16, and their pleiotropically effects on seed weight per plant and seed yield were characterized. We identified the C02 peak as a novel signal for flowering time, harboring 52.77% of the associated SNPs. The 288-kbps LD decay distance analysis revealed 2,232 candidate genes (CGs) associated with traits. The CGs BIG1-D, CAND1, DRG3, PUP10, and PUP21 were involved in phytohormone signaling and pollen development with significant effects on seed number, seed weight, and grain yield in drought conditions. By integrating GWAS and RNA-seq, 215 promising CGs were associated with developmental process, reproductive processes, cell wall organization, and response to stress. GWAS and differentially expressed genes (DEGs) of leaf and seed in the yield contrasting accessions identified BIG1-D, CAND1, and DRG3 genes for yield variation.

Discussion

The results of our study provide insights into the genetic control of drought tolerance and the improvement of marker-assisted selection (MAS) for breeding high-yield and drought-tolerant varieties.

Common signatures of selection reveal target loci for breeding across soybean populations

Understanding the underlying genetic bases of yield-related selection and distinguishing these changes from genetic drift are critical for both improved understanding and future success of plant breeding. Soybean [Glycine max (L.) Merr.] is a key species for world food security, yet knowledge of the mechanism of selective breeding in soybean, such as the century-long program of artificial selection in U.S. soybean germplasm, is currently limited to certain genes and loci. Here, we identify genome-wide signatures of selection in separate populations of soybean subjected to artificial selection for increased yield by multiple breeding programs in the United States. We compared the alternative soybean breeding population (AGP) created by USDA-ARS to the conventional public soybean lines (CGP) developed at three different stages of breeding (ancestral, intermediate, and elite) to identify shared signatures of selection and differentiate these from drift. The results showed a strong selection for specific haplotypes identified by single site frequency and haplotype homozygosity methods. A set of common selection signatures was identified in both AGP and CGP that supports the hypothesis that separate breeding programs within similar environments coalesce on the fixation of the same key haplotypes. Signatures unique to each breeding program were observed. These results raise the possibility that selection analysis can allow the identification of favorable alleles to enhance directed breeding approaches.

Integration of genome-wide association studies, metabolomics, and transcriptomics reveals phenolic acid- and flavonoid-associated genes and their regulatory elements under drought stress in rapeseed flowers

Introduction

Biochemical and metabolic processes help plants tolerate the adverse effects of drought. In plants accumulating bioactive compounds, understanding the genetic control of the biosynthesis of biochemical pathways helps the discovery of candidate gene (CG)-metabolite relationships.

Methods

The metabolic profile of flowers in 119 rapeseed (Brassica napus) accessions was assessed over two irrigation treatments, one a well-watered (WW) condition and the other a drought stress (DS) regime. We integrated information gained from 52,157 single-nucleotide polymorphism (SNP) markers, metabolites, and transcriptomes to identify linked SNPs and CGs responsible for the genetic control of flower phenolic compounds and regulatory elements.

Results

In a genome-wide association study (GWAS), of the SNPs tested, 29,310 SNPs were qualified to assess the population structure and linkage disequilibrium (LD), of which several SNPs for radical scavenging activity (RSA) and total flavanol content (TFLC) were common between the two irrigation conditions and pleiotropic SNPs were found for chlorogenic and coumaric acids content. The principal component analysis (PCA) and stepwise regression showed that chlorogenic acid and epicatechin in WW and myricetin in DS conditions were the most important components for RSA. The hierarchical cluster analysis (HCA) showed that vanillic acid, myricetin, gallic acid, and catechin were closely associated in both irrigation conditions. Analysis of GWAS showed that 60 CGs were identified, of which 18 were involved in stress-induced pathways, phenylpropanoid pathway, and flavonoid modifications. Of the CGs, PAL1, CHI, UGT89B1, FLS3, CCR1, and CYP75B137 contributed to flavonoid biosynthetic pathways. The results of RNA sequencing (RNA-seq) revealed that the transcript levels of PAL, CHI, and CYP75B137 known as early flavonoid biosynthesis-related genes and FLS3, CCR1, and UGT89B1 related to the later stages were increased during drought conditions. The transcription factors (TFs) NAC035 and ERF119 related to flavonoids and phenolic acids were upregulated under drought conditions.

Discussion

These findings expand our knowledge on the response mechanisms to DS, particularly regarding the regulation of key phenolic biosynthetic genes in rapeseed. Our data also provided specific linked SNPs for marker-assisted selection (MAS) programs and CGs as resources toward realizing metabolomics-associated breeding of rapeseed.

Pilot-scale genome-wide association mapping in diverse sorghum germplasms identified novel genetic loci linked to major agronomic, root and stomatal traits

This genome-wide association studies (GWAS) used a subset of 96 diverse sorghum accessions, constructed from a large collection of 219 accessions for mining novel genetic loci linked to major agronomic, root morphological and physiological traits. The subset yielded 43,452 high quality single nucleotide polymorphic (SNP) markers exhibiting high allelic diversity. Population stratification showed distinct separation between caudatum and durra races. Linkage disequilibrium (LD) decay was rapidly declining with increasing physical distance across all chromosomes. The initial 50% LD decay was ~ 5 Kb and background level was within ~ 80 Kb. This study detected 42 significant quantitative trait nucleotide (QTNs) for different traits evaluated using FarmCPU, SUPER and 3VmrMLM which were in proximity with candidate genes related and were co-localized in already reported quantitative trait loci (QTL) and phenotypic variance (R2) of these QTNs ranged from 3 to 20%. Haplotype validation of the candidate genes from this study resulted nine genes showing significant phenotypic difference between different haplotypes. Three novel candidate genes associated with agronomic traits were validated including Sobic.001G499000, a potassium channel tetramerization domain protein for plant height, Sobic.010G186600, a nucleoporin-related gene for dry biomass, and Sobic.002G022600 encoding AP2-like ethylene-responsive transcription factor for plant yield. Several other candidate genes were validated and associated with different root and physiological traits including Sobic.005G104100, peroxidase 13-related gene with root length, Sobic.010G043300, homologous to Traes_5BL_8D494D60C, encoding inhibitor of apoptosis with iWUE, and Sobic.010G125500, encoding zinc finger, C3HC4 type domain with Abaxial stomatal density. In this study, 3VmrMLM was more powerful than FarmCPU and SUPER for detecting QTNs and having more breeding value indicating its reliable output for validation. This study justified that the constructed subset of diverse sorghums can be used as a panel for mapping other key traits to accelerate molecular breeding in sorghum.

Breeding effects on durum wheat traits detected using GWAS and haplotype block analysis

Introduction

The recent boosting of genomic data in durum wheat (Triticum turgidum subsp. durum) offers the opportunity to better understand the effects of breeding on the genetic structures that regulate the expression of traits of agronomic interest. Furthermore, the identification of DNA markers useful for marker-assisted selection could also improve the reliability of technical protocols used for variety protection and registration.

Methods

Within this motivation context, 123 durum wheat accessions, classified into three groups: landraces (LR), ancient (OC) and modern cultivars (MC), were evaluated in two locations, for 34 agronomic traits, including UPOV descriptors, to assess the impact of changes that occurred during modern breeding.

Results

The association mapping analysis, performed with 4,241 SNP markers and six multi-locus-GWAS models, revealed 28 reliable Quantitative Trait Nucleotides (QTNs) related to plant morphology and kernel-related traits. Some important genes controlling flowering time and plant height were in linkage disequilibrium (LD) decay with QTNs identified in this study. A strong association for yellow berry was found on chromosome 6A (Q.Yb-6A) in a region containing the nadh-ubiquinone oxidoreductase subunit, a gene involved in starch metabolism. The Q.Kcp-2A harbored the PPO locus, with the associated marker (Ku_c13700_1196) in LD decay with Ppo-A1 and Ppo-A2. Interestingly, the Q.FGSGls-2B.1, identified by RAC875_c34512_685 for flag leaf glaucosity, mapped less than 1 Mb from the Epistatic inhibitors of glaucousness (Iw1), thus representing a good candidate for supporting the morphological DUS traits also with molecular markers. LD haplotype block approach revealed a higher diversity, richness and length of haploblocks in MC than OC and LR (580 in LR, 585 in OC and 612 in MC), suggesting a possible effect exerted by breeding programs on genomic regions associated with the agronomic traits.

Discussion

Our findings pave new ways to support the phenotypic characterization necessary for variety registration by using a panel of cost-effectiveness SNP markers associated also to the UPOV descriptors. Moreover, the panel of associated SNPs might represent a reservoir of favourable alleles to use in durum wheat breeding and genetics.

Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes

Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.

Identifying genomic regions determining shoot and root traits related to nitrogen uptake efficiency in a multiparent advanced generation intercross (MAGIC) winter wheat population in a high-throughput phenotyping facility

In the context of a continuously increasing human population that needs to be fed, with environmental protection in mind, nitrogen use efficiency (NUE) improvement is becoming very important. To understand the natural variation of traits linked to nitrogen uptake efficiency (UPE), one component of NUE, the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting nitrogen (N) levels in a high-throughput phenotyping facility for six weeks. Three biomass-related, three root-related, and two reflectance-related traits were measured weekly under each treatment. Subsequently, the population was genetically analysed using a total of 13,060 polymorphic haplotypes and singular SNPs for a genome-wide association study (GWAS). In total, we detected 543 quantitative trait loci (QTL) across all time points and traits, which were pooled into 42 stable QTL (sQTL; present in at least three of the six weeks). Besides Rht-B1 and Rht-D1, candidate genes playing a role in gibberellic acid-regulated growth and nitrate transporter genes from the NPF gene family, like NRT 1.1, were linked to sQTL. Two novel sQTL on chromosomes 5 A and 6D showed pleiotropic effects on several traits. The high number of N-specific sQTL indicates that selection for UPE is useful specifically under N-limited conditions.

Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat

Linkage disequilibrium (LD)-based haplotyping with subsequent SNP tagging improved the genomic prediction accuracy up to 0.07 and 0.092 for Fusarium head blight resistance and spike width, respectively, across six different models. Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r² < 0.5), while stringent LD was required for spike length (SPL) and flag leaf area (FLA). Trait-linked SNPs identified only from training populations failed to improve the prediction accuracy of the four studied traits. Pre-selection of SNPs via LD-based haplotype-tagging could play a vital role in optimizing genomic selection and reducing genotyping costs. Furthermore, the method could pave the way for developing low-cost genotyping methods through customized genotyping platforms targeting key SNP markers tagged to essential haplotype blocks.

GWAS scans of cereal cyst nematode (Heterodera avenae) resistance in Indian wheat germplasm

Significant yield losses in major cereal-growing regions around the world have been linked to cereal cyst nematodes (Heterodera spp.). Identifying and deploying natural sources of resistance is of utmost importance due to increasing concerns associated with chemical methods over the years. We screened 141 diverse wheat genotypes collected from pan-Indian wheat cultivation states for nematode resistance over two years, alongside two resistant (Raj MR1, W7984 (M6)) and two susceptible (WH147, Opata M85) checks. We performed genome-wide association analysis using four single-locus models (GLM, MLM, CMLM, and ECMLM) and three multi-locus models (Blink, FarmCPU, and MLMM). Single locus models identified nine significant MTAs (-log10 (P) > 3.0) on chromosomes 2A, 3B, and 4B whereas, multi-locus models identified 11 significant MTAs on chromosomes 1B, 2A, 3B, 3D and 4B. Single and multi-locus models identified nine common significant MTAs. Candidate gene analysis identified 33 genes like F-box-like domain superfamily, Cytochrome P450 superfamily, Leucine-rich repeat, cysteine-containing subtype Zinc finger RING/FYVE/PHD-type, etc., having a putative role in disease resistance. Such genetic resources can help to reduce the impact of this disease on wheat production. Additionally, these results can be used to design new strategies for controlling the spread of H. avenae, such as the development of resistant varieties or the use of resistant cultivars. Finally, the obtained results can also be used to identify new sources of resistance to this pathogen and develop novel control methods.

Unraveling Genomic Regions Controlling Root Traits as a Function of Nitrogen Availability in the MAGIC Wheat Population WM-800

An ever-growing world population demands to be fed in the future and environmental protection and climate change need to be taken into account. An important factor here is nitrogen uptake efficiency (NUpE), which is influenced by the root system (the interface between plant and soil). To understand the natural variation of root system architecture (RSA) as a function of nitrogen (N) availability, a subset of the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting N treatments in a high-throughput phenotyping system at the seedling stage. Fourteen root and shoot traits were measured. Subsequently, these traits were genetically analyzed using 13,060 polymorphic haplotypes and SNPs in a genome-wide association study (GWAS). In total, 64 quantitative trait loci (QTL) were detected; 60 of them were N treatment specific. Candidate genes for the detected QTL included NRT1.1 and genes involved in stress signaling under N-, whereas candidate genes under N+ were more associated with general growth, such as mei2 and TaWOX11b. This finding may indicate (i) a disparity of the genetic control of root development under low and high N supply and, furthermore, (ii) the need for an N specific selection of genes and genotypes in breeding new wheat cultivars with improved NUpE.

A Haplotype-Based GWAS Identified Trait-Improving QTL Alleles Controlling Agronomic Traits under Contrasting Nitrogen Fertilization Treatments in the MAGIC Wheat Population WM-800

The multi-parent-advanced-generation-intercross (MAGIC) population WM-800 was developed by intercrossing eight modern winter wheat cultivars to enhance the genetic diversity present in breeding populations. We cultivated WM-800 during two seasons in seven environments under two contrasting nitrogen fertilization treatments. WM-800 lines exhibited highly significant differences between treatments, as well as high heritabilities among the seven agronomic traits studied. The highest-yielding WM-line achieved an average yield increase of 4.40 dt/ha (5.2%) compared to the best founder cultivar Tobak. The subsequent genome-wide-association-study (GWAS), which was based on haplotypes, located QTL for seven agronomic traits including grain yield. In total, 40, 51, and 46 QTL were detected under low, high, and across nitrogen treatments, respectively. For example, the effect of QYLD_3A could be associated with the haplotype allele of cultivar Julius increasing yield by an average of 4.47 dt/ha (5.2%). A novel QTL on chromosome 2B exhibited pleiotropic effects, acting simultaneously on three-grain yield components (ears-per-square-meter, grains-per-ear, and thousand-grain-weight) and plant-height. These effects may be explained by a member of the nitrate-transporter-1 (NRT1)/peptide-family, TaNPF5.34, located 1.05 Mb apart. The WM-800 lines and favorable QTL haplotypes, associated with yield improvements, are currently implemented in wheat breeding programs to develop advanced nitrogen-use efficient wheat cultivars.

Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.)

Identifying the genetic components underlying yield-related traits in soybean is crucial for improving its production and productivity. Here, 211 soybean genotypes were evaluated across six environments for four yield-related traits, including seed yield per plant (SYP), number of pods per plant number of seeds per plant and 100-seed weight (HSW). Genome-wide association study (GWAS) and genomic prediction (GP) analyses were performed using 12,617 single nucleotide polymorphism markers from NJAU 355K SoySNP Array. A total of 57 SNPs were significantly associated with four traits across six environments and a combined environment using five Genome-wide association study models. Out of these, six significant SNPs were consistently identified in more than three environments using multiple GWAS models. The genomic regions (±670 kb) flanking these six consistent SNPs were considered stable QTL regions. Gene annotation and in silico expression analysis revealed 15 putative genes underlying the stable QTLs that might regulate soybean yield. Haplotype analysis using six significant SNPs revealed various allelic combinations regulating diverse phenotypes for the studied traits. Furthermore, the GP analysis revealed that accurate breeding values for the studied soybean traits is attainable at an earlier generation. Our study paved the way for increasing soybean yield performance within a short breeding cycle.

Harnessing adult-plant resistance genes to deploy durable disease resistance in crops

Adult-plant resistance (APR) is a type of genetic resistance in cereals that is effective during the later growth stages and can protect plants from a range of disease-causing pathogens. Our understanding of the functions of APR-associated genes stems from the well-studied wheat-rust pathosystem. Genes conferring APR can offer pathogen-specific resistance or multi-pathogen resistance, whereby resistance is activated following a molecular recognition event. The breeding community prefers APR to other types of resistance because it offers broad-spectrum protection that has proven to be more durable. In practice, however, deployment of new cultivars incorporating APR is challenging because there is a lack of well-characterised APRs in elite germplasm and multiple loci must be combined to achieve high levels of resistance. Genebanks provide an excellent source of genetic diversity that can be used to diversify resistance factors, but introgression of novel alleles into elite germplasm is a lengthy and challenging process. To overcome this bottleneck, new tools in breeding for resistance must be integrated to fast-track the discovery, introgression and pyramiding of APR genes. This review highlights recent advances in understanding the functions of APR genes in the well-studied wheat-rust pathosystem, the opportunities to adopt APR genes in other crops and the technology that can speed up the utilisation of new sources of APR in genebank accessions.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

Features and applications of haplotypes in crop breeding

Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications. This review article highlights ways to mine haplotypes and apply them for complex trait dissection and in GAB approaches including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior haplotypes to hasten breeding progress will be key to safeguarding global food security.

Direct introgression of untapped diversity into elite wheat lines

The effective utilization of natural variation has become essential in addressing the challenges that climate change and population growth pose to global food security. Currently adopted protracted approaches to introgress exotic alleles into elite cultivars need substantial transformation. Here, through a strategic three-way crossing scheme among diverse exotics and the best historical elites (exotic/elite1//elite2), 2,867 pre-breeding lines were developed, genotyped and screened for multiple agronomic traits in four mega-environments. A meta-genome-wide association study, selective sweeps and haplotype-block-based analyses unveiled selection footprints in the genomes of pre-breeding lines as well as exotic-specific associations with agronomic traits. A simulation with a neutrality assumption demonstrated that many pre-breeding lines had significant exotic contributions despite substantial selection bias towards elite genomes. National breeding programmes worldwide have adopted 95 lines for germplasm enhancement, and 7 additional lines are being advanced in varietal release trials. This study presents a great leap forwards in the mobilization of GenBank variation to the breeding pipelines.

Validation of Genes Affecting Rice Grain Zinc Content Through Candidate Gene-Based Association Analysis

Several key genes governing Zn homeostasis and grain zinc content (GZC) have been functionally characterized. However, the effects of these genes in diverse breeding populations have not been evaluated; thus, their availability in breeding is unclear. In this study, the effects of 65 genes related to rice zinc responses on GZC were evaluated using two panels of breeding lines, and the superior haplotypes were identified. One panel consisted of mega varieties from the International Rice Research Institute (IRRI), South Asia, and Southeast Asia (SEA), and the other panel is breeding lines/varieties from South China (SC). In addition, a multiparent advanced generation intercross (MAGIC) population, named as DC1, was also employed. Three analytical methods, single-locus mixed linear model (SL-MLM), multilocus random-SNP-effect mixed linear model (mrMLM), and haplotype-based association analysis (Hap-AA), were applied. OsIDEF1 (which explained 12.3% of the phenotypic variance) and OsZIFL7 (8.3-9.1%), OsZIP7 (18.9%), and OsIRT1 (17.9%) were identified by SL-MLM in SEA and SC, respectively, whereas no gene was significantly associated with GZC in DC1. In total, five (OsNRAMP6, OsYSL15, OsIRT1, OsIDEF1, and OsZIFL7, 7.70-15.39%), three (OsFRDL1, OsIRT1, and OsZIP7, 11.87-17.99%), and two (OsYSL7 and OsZIP7, 9.85-10.57%) genes were detected to be significantly associated with GZC in SEA, SC, and DC1 by mrMLM, respectively. Hap-AA indicated that Hap1-OsNRAMP5, Hap5-OsZIP4, Hap1-OsIRT1, Hap3-OsNRAMP6, Hap6-OsMTP1, and Hap6-OsYSL15 had the largest effects for GZC in SEA, whereas Hap3-OsOPT7, Hap4-OsIRT2, Hap4-OsZIP7, Hap5-OsIRT1, and Hap5-OsSAMS1 were the most significant in the SC population. Besides, superior alleles were also identified for the significant genes. The genes significantly associated with GZC and their superior haplotypes identified in different panels could be used in enhancing GZC through molecular breeding, which could further address the problem of Zn malnutrition among rice consumers.

Genome-Wide Association of Stem Carbohydrate Accumulation and Remobilization during Grain Growth in Bread Wheat (Triticum aestivum L.) in Mediterranean Environments

Water deficit represents an important challenge for wheat production in many regions of the world. Accumulation and remobilization of water-soluble carbohydrates (WSCs) in stems are part of the physiological responses regulated by plants to cope with water stress and, in turn, determine grain yield (GY). The genetic mechanisms underlying the variation in WSC are only partially understood. In this study, we aimed to identify Single Nucleotide Polymorphism (SNP) markers that account for variation in a suite of WSC and GY, evaluated in 225 cultivars and advanced lines of spring wheat. These genotypes were established in two sites in the Mediterranean region of Central Chile, under water-limited and full irrigation conditions, and assessed in two growing seasons, namely anthesis and maturity growth periods. A genome-wide association study (GWAS) was performed by using 3243 SNP markers. Genetic variance accounted for 5 to 52% of phenotypic variation of the assessed traits. A rapid linkage disequilibrium decay was observed across chromosomes (r² ≤ 0.2 at 2.52 kbp). Marker-trait association tests identified 96 SNPs related to stem weight (SW), WSCs, and GY, among other traits, at the different sites, growing seasons, and growth periods. The percentage of SNPs that were part of the gene-coding regions was 34%. Most of these genes are involved in the defensive response to drought and biotic stress. A complimentary analysis detected significant effects of different haplotypes on WSC and SW, in anthesis and maturity. Our results evidence both genetic and environmental influence on WSC dynamics in spring wheat. At the same time, they provide a series of markers suitable for supporting assisted selection approaches and functional characterization of genes.

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011-2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5-21.1%, 3.7-14.7%, 3.5-20.6%, and 4.4- 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.

Evidence for the Accumulation of Nonsynonymous Mutations and Favorable Pleiotropic Alleles During Wheat Breeding

Plant breeding leads to the genetic improvement of target traits by selecting a small number of genotypes from among typically large numbers of candidate genotypes after careful evaluation. In this study, we first investigated how mutations at conserved nucleotide sites normally viewed as deleterious, such as nonsynonymous sites, accumulated in a wheat, Triticum aestivum, breeding lineage. By comparing a 150 year old ancestral and modern cultivar, we found recent nucleotide polymorphisms altered amino acids and occurred within conserved genes at frequencies expected in the absence of purifying selection. Mutations that are deleterious in other contexts likely had very small or no effects on target traits within the breeding lineage. Second, we investigated if breeders selected alleles with favorable effects on some traits and unfavorable effects on others and used different alleles to compensate for the latter. An analysis of a segregating population derived from the ancestral and modern parents provided one example of this phenomenon. The recent cultivar contains the Rht-B1b green revolution semi-dwarfing allele and compensatory alleles that reduce its negative effects. However, improvements in traits other than plant height were due to pleiotropic loci with favorable effects on traits and to favorable loci with no detectable pleiotropic effects. Wheat breeding appears to tolerate mutations at conserved nucleotide sites and to only select for alleles with both favorable and unfavorable effects on traits in exceptional situations.

Overcoming polyploidy pitfalls: a user guide for effective SNP conversion into KASP markers in wheat

Conversion of SNP chip assays into locus-specific KASP markers requires adapted strategies in polyploid species with high genome homeology. Procedures are exemplified by QTL-associated SNPs in hexaploid wheat. Kompetitive allele-specific PCR (KASP) markers are commonly used in marker-assisted commercial plant breeding due to their cost-effectiveness and throughput for high sample volumes. However, conversion of trait-linked SNP markers from array-based SNP detection technologies into KASP markers is particularly challenging in polyploid crop species, due to the presence of highly similar homeologous and paralogous genome sequences. We evaluated strategies and identified key requirements for successful conversion of Illumina Infinium assays from the wheat 90 K SNP array into robust locus-specific KASP markers. Numerous examples showed that commonly used software for semiautomated KASP primer design frequently fails to achieve locus-specificity of KASP assays in wheat. Instead, alignment of SNP probes with multiple reference genomes and Sanger sequencing of relevant genotypes, followed by visual KASP primer placement, was critical for locus-specificity. To identify KASP assays resulting in false calling of heterozygous individuals, validation of KASP assays using extended reference genotype sets including heterozygous genotypes is strongly advised for polyploid crop species. Applying this strategy, we developed highly reproducible, stable KASP assays that are predictive for root biomass QTL haplotypes from highly homoeologous wheat chromosome regions. Due to their locus-specificity, these assays predicted root biomass considerably better than the original trait-associated markers from the Illumina array.

Hap10: reconstructing accurate and long polyploid haplotypes using linked reads

BACKGROUND

Haplotype information is essential for many genetic and genomic analyses, including genotype-phenotype associations in human, animals and plants. Haplotype assembly is a method for reconstructing haplotypes from DNA sequencing reads. By the advent of new sequencing technologies, new algorithms are needed to ensure long and accurate haplotypes. While a few linked-read haplotype assembly algorithms are available for diploid genomes, to the best of our knowledge, no algorithms have yet been proposed for polyploids specifically exploiting linked reads.

RESULTS

The first haplotyping algorithm designed for linked reads generated from a polyploid genome is presented, built on a typical short-read haplotyping method, SDhaP. Using the input aligned reads and called variants, the haplotype-relevant information is extracted. Next, reads with the same barcodes are combined to produce molecule-specific fragments. Then, these fragments are clustered into strongly connected components which are then used as input of a haplotype assembly core in order to estimate accurate and long haplotypes.

CONCLUSIONS

Hap10 is a novel algorithm for haplotype assembly of polyploid genomes using linked reads. The performance of the algorithms is evaluated in a number of simulation scenarios and its applicability is demonstrated on a real dataset of sweet potato.

Haplotype diversity underlying quantitative traits in Canadian soybean breeding germplasm

KEY MESSAGE

Identification of marker-trait associations and trait-associated haplotypes in breeding germplasm identifies regions under selection and highlights changes in haplotype diversity over decades of soybean improvement in Canada. Understanding marker-trait associations using genome-wide association in soybean is typically carried out in diverse germplasm groups where identified loci are often not applicable to soybean breeding efforts. To address this challenge, this study focuses on defining marker-trait associations in breeding germplasm and studying the underlying haplotypes in these regions to assess genetic change through decades of selection. Phenotype data were generated for 175 accessions across multiple environments in Ontario, Canada. A set of 76,549 SNPs were used in the association analysis. A total of 23 genomic regions were identified as significantly associated with yield (5), days to maturity (5), seed oil (3), seed protein (5) and 100-seed weight (5), of which 14 are novel. Each significant region was haplotyped to assess haplotype diversity of the underlying genomic region, identifying ten regions with trait-associated haplotypes in the breeding germplasm. The range of genomic length for these regions (7.2 kb to 6.8 Mb) indicates variation in regional LD for the trait-associated regions. Six of these regions showed changes between eras of breeding, from historical to modern and experimental soybean accessions. Continued selection on these regions may necessitate introgression of novel parental genetic diversity as some haplotypes were fixed within the breeding germplasm. This finding highlights the importance of studying associations and haplotype diversity at a breeding program scale to understand breeders' selections and trends in soybean improvement over time. The haplotypes may also be used as a tool for selection of parental germplasm to inform breeder's decisions on further soybean improvement.

Molecular Markers Associated with Agro-Physiological Traits under Terminal Drought Conditions in Bread Wheat

Terminal drought stress poses a big challenge to sustain wheat grain production in rain-fed environments. This study aimed to utilize the genetically diverse pre-breeding lines for identification of genomic regions associated with agro-physiological traits at terminal stage drought stress in wheat. A total of 339 pre-breeding lines panel derived from three-way crosses of 'exotics × elite × elite' lines were evaluated in field conditions at Obregon, Mexico for two years under well irrigated as well as drought stress environments. Drought stress was imposed at flowering by skipping the irrigations at pre and post anthesis stage. Results revealed that drought significantly reduced grain yield (Y), spike length (SL), number of grains spikes-1 (NGS) and thousand kernel weight (TKW), while kernel abortion (KA) was increased. Population structure analysis in this panel uncovered three sub-populations. Genome wide linkage disequilibrium (LD) decay was observed at 2.5 centimorgan (cM). The haplotypes-based genome wide association study (GWAS) identified significant associations of Y, SL, and TKW on three chromosomes; 4A (HB10.7), 2D (HB6.10) and 3B (HB8.12), respectively. Likewise, associations on chromosomes 6B (HB17.1) and 3A (HB7.11) were found for NGS while on chromosome 3A (HB7.12) for KA. The genomic analysis information generated in the study can be efficiently utilized to improve Y and/or related parameters under terminal stage drought stress through marker-assisted breeding.

Incorporating Genome-Wide Association Mapping Results Into Genomic Prediction Models for Grain Yield and Yield Stability in CIMMYT Spring Bread Wheat

Untangling the genetic architecture of grain yield (GY) and yield stability is an important determining factor to optimize genomics-assisted selection strategies in wheat. We conducted in-depth investigation on the above using a large set of advanced bread wheat lines (4,302), which were genotyped with genotyping-by-sequencing markers and phenotyped under contrasting (irrigated and stress) environments. Haplotypes-based genome-wide-association study (GWAS) identified 58 associations with GY and 15 with superiority index Pi (measure of stability). Sixteen associations with GY were "environment-specific" with two on chromosomes 3B and 6B with the large effects and 8 associations were consistent across environments and trials. For Pi, 8 associations were from chromosomes 4B and 7B, indicating 'hot spot' regions for stability. Epistatic interactions contributed to an additional 5-9% variation on average. We further explored whether integrating consistent and robust associations identified in GWAS as fixed effects in prediction models improves prediction accuracy. For GY, the model accounting for the haplotype-based GWAS loci as fixed effects led to up to 9-10% increase in prediction accuracy, whereas for Pi this approach did not provide any advantage. This is the first report of integrating genetic architecture of GY and yield stability into prediction models in wheat.

Genome-Wide Associations and Transcriptional Profiling Reveal ROS Regulation as One Underlying Mechanism of Sheath Blight Resistance in Rice

Rice sheath blight, caused by the necrotrophic fungus Rhizoctonia solani Kühn, continues to be an important and challenging rice disease worldwide. Here, we used genome-wide association studies over a high-density rice array to facilitate the identification of potential novel genes and quantitative trait loci related to sheath blight resistance. We identified multiple regions that significantly associated with independent disease components in chromosomes 1, 4, and 11 under controlled condition. In particular, we investigated qLN11²⁸, a quantitative trait locus enriched with defense-related genes that reduce disease lesions in a near-isogenic line. RNA profiling of the line carrying qLN11²⁸ showed a number of differentially expressed genes related to the reactive oxygen species (ROS)-redox pathway. Histochemical staining revealed less ROS accumulation on the resistant line, suggesting efficient ROS deregulation that delays pathogen colonization. The detection of genomic regions controlling multiple mechanisms of resistance to sheath blight will provide tools to design effective breeding interventions in rice.

Haplotype block analysis of an Argentinean hexaploid wheat collection and GWAS for yield components and adaptation

BACKGROUND

Increasing wheat (Triticum aestivum L.) production is required to feed a growing human population. In order to accomplish this task a deeper understanding of the genetic structure of cultivated wheats and the detection of genomic regions significantly associated with the regulation of important agronomic traits are necessary steps. To better understand the genetic basis and relationships of adaptation and yield related traits, we used a collection of 102 Argentinean hexaploid wheat cultivars genotyped with the 35k SNPs array, grown from two to six years in three different locations. Based on SNPs data and gene-related molecular markers, we performed a haplotype block characterization of the germplasm and a genome-wide association study (GWAS).

RESULTS

The genetic structure of the collection revealed four subpopulations, reflecting the origin of the germplasm used by the main breeding programs in Argentina. The haplotype block characterization showed 1268 blocks of different sizes spread along the genome, including highly conserved regions like the 1BS chromosome arm where the 1BL/1RS wheat/rye translocation is located. Based on GWAS we identified ninety-seven chromosome regions associated with heading date, plant height, thousand grain weight, grain number per spike and fruiting efficiency at harvest (FEh). In particular FEh stands out as a promising trait to raise yield potential in Argentinean wheats; we detected fifteen haplotypes/markers associated with increased FEh values, eleven of which showed significant effects in all three evaluated locations. In the case of adaptation, the Ppd-D1 gene is consolidated as the main determinant of the life cycle of Argentinean wheat cultivars.

CONCLUSION

This work reveals the genetic structure of the Argentinean hexaploid wheat germplasm using a wide set of molecular markers anchored to the Ref Seq v1.0. Additionally GWAS detects chromosomal regions (haplotypes) associated with important yield and adaptation components that will allow improvement of these traits through marker-assisted selection.

A strategy for building and using a human reference pangenome

In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript.

A strategy for building and using a human reference pangenome

In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript.

Genome-Wide Analyses Reveal Footprints of Divergent Selection and Drought Adaptive Traits in Synthetic-Derived Wheats

Crop-wild introgressions have long been exploited without knowing the favorable recombination points. Synthetic hexaploid wheats are one of the most exploited genetic resources for bread wheat improvement. However, despite some QTL with major effects, much less is known about genome-wide patterns of introgressions and their effects on phenotypes. We used two genome-wide association approaches: SNP-GWAS and haplotype-GWAS to identify SNPs and haplotypes associated with productivity under water-limited conditions in a synthetic-derived wheat (SYN-DER) population. Haplotype-GWAS further enriched and identified 20 more genomic regions associated with drought adaptability that did not overlap with SNP-GWAS. Since GWAS is biased to the phenotypes in the study and may fail to detect important genetic diversity during breeding, we used five complementary analytical approaches (t-test, Tajima’s D, nucleotide diversity (π), Fst, and EigenGWAS) to identify divergent selections in SYN-DER compared to modern bread wheat. These approaches consistently pinpointed 89 ‘selective sweeps’, out of which 30 selection loci were identified on D-genome. These key selections co-localized with important functional genes of adaptive traits such as TaElf3-D1 (1D) for earliness per se (Eps), TaCKX-D1 (3D), TaGS1a (6D) and TaGS-D1 (7D) for grain size, weight and morphology, TaCwi-D1 (5D) influencing drought tolerance, and Vrn-D3 (7D) for vernalization. Furthermore, 55 SNPs and 23 haplotypes of agronomic and physiological importance such as grain yield, relative water content and thousand grain weight in SYN-DER, were among the top 5% of divergent selections contributed by synthetic hexaploid wheats. These divergent selections associated with improved agronomic performance carry new alleles that have been introduced to wheat. Our results demonstrated that GWAS and selection sweep analyses are powerful approaches for investigating favorable introgressions under strong selection pressure and the use of crop-wild hybridization to assist the improvement of wheat yield and productivity under moisture limiting environments.

Uncovering of natural allelic variants of key yield contributing genes by targeted resequencing in rice (Oryza sativa L.)

In rice (Oryza sativa L.), during the course of domestication, numerous beneficial alleles remain untapped in the progenitor wild species and landraces. This study aims at uncovering these promising alleles of six key genes influencing the yield, such as DEP1, Ghd7, Gn1a, GS3, qSW5 and sd1 by targeted resequencing of the 200 rice genotypes. In all, 543 nucleotide variations including single nucleotide polymorphisms and insertion and deletion polymorphisms were identified from the targeted genes. Of them, 225 were novel alleles, which identified in the present study only and 91 were beneficial alleles that showed significant association with the yield traits. Besides, we uncovered 128 population-specific alleles with indica being the highest of 79 alleles. The neutrality tests revealed that pleiotropic gene, Ghd7 and major grain size contributing gene, GS3 showed positive and balanced selection, respectively during the domestication. Further, the haplotype analysis revealed that some of the rice genotypes found to have rare haplotypes, especially the high yielding variety, BPT1768 has showed maximum of three genes such as Gn1a-8, qSW5-12 and GS3-29. The rice varieties with novel and beneficial alleles along with the rare haplotypes identified in the present study could be of immense value for yield improvement in the rice breeding programs.

Genome-wide haplotype analysis improves trait predictions in Brassica napus hybrids

Combining ability is crucial for parent selection in crop hybrid breeding. Many studies have attempted to provide reliable and quick methods to identify genome regions in parental lines correlating with improved hybrid performance. The local haplotype patterns surrounding densely spaced DNA markers include a large amount of genetic information, and analysis of the relationships between haplotypes and hybrid performance can provide insight into the underlying genome regions which might contribute to enhancing combining ability. Here, we generated 24,403 single-copy, genome-wide SNP loci and calculated the general combining ability (GCA) of 950 hybrids from a diverse panel of 475 pollinators of spring-type canola inbred lines crossed with two testers for days to flowering (DTF) and seed glucosinolate content (GSL). We performed a genome-wide analysis of the haplotypes and detected eight and seven haplotype regions that were significantly associated with the GCA values for DTF and seed GSL, respectively. Additionally, two haplotype blocks containing orthologs of flowering time genes FLOWERING LOCUS T (FT) and FLOWERING LOCUS C (FLC) on chromosome A02 showed additive epistatic interactions influencing flowering time. Moreover, two homoeologous haplotype regions on chromosomes A02 and C02 corresponded to major quantitative trait loci (QTL) for GSL which showed additive effects related to reduction of seed GSL in F1 hybrids. Our study showed that haplotype analysis has the potential to substantially improve the efficiency of hybrid breeding programs.

Apple whole genome sequences: recent advances and new prospects

In 2010, a major scientific milestone was achieved for tree fruit crops: publication of the first draft whole genome sequence (WGS) for apple (Malus domestica). This WGS, v1.0, was valuable as the initial reference for sequence information, fine mapping, gene discovery, variant discovery, and tool development. A new, high quality apple WGS, GDDH13 v1.1, was released in 2017 and now serves as the reference genome for apple. Over the past decade, these apple WGSs have had an enormous impact on our understanding of apple biological functioning, trait physiology and inheritance, leading to practical applications for improving this highly valued crop. Causal gene identities for phenotypes of fundamental and practical interest can today be discovered much more rapidly. Genome-wide polymorphisms at high genetic resolution are screened efficiently over hundreds to thousands of individuals with new insights into genetic relationships and pedigrees. High-density genetic maps are constructed efficiently and quantitative trait loci for valuable traits are readily associated with positional candidate genes and/or converted into diagnostic tests for breeders. We understand the species, geographical, and genomic origins of domesticated apple more precisely, as well as its relationship to wild relatives. The WGS has turbo-charged application of these classical research steps to crop improvement and drives innovative methods to achieve more durable, environmentally sound, productive, and consumer-desirable apple production. This review includes examples of basic and practical breakthroughs and challenges in using the apple WGSs. Recommendations for "what's next" focus on necessary upgrades to the genome sequence data pool, as well as for use of the data, to reach new frontiers in genomics-based scientific understanding of apple.

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High-throughput SNP arrays, or 'SNP chips', can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop-breeding activities.

Effect of breeding on nitrogen use efficiency-associated traits in oilseed rape

Oilseed rape is one of the most important dicotyledonous field crops in the world, where it plays a key role in productive cereal crop rotations. However, its production requires high nitrogen fertilization and its nitrogen footprint exceeds that of most other globally important crops. Hence, increased nitrogen use efficiency (NUE) in this crop is of high priority for sustainable agriculture. We report a comprehensive study of macrophysiological characteristics associated with breeding progress, conducted under contrasting nitrogen fertilization levels in a large panel of elite oilseed rape varieties representing breeding progress over the past 20 years. The results indicate that increased plant biomass at flowering, along with increases in primary yield components, have increased NUE in modern varieties. Nitrogen uptake efficiency has improved through breeding, particularly at high nitrogen. Despite low heritability, the number of seeds per silique is associated positively with increased yield in modern varieties. Seed weight remains unaffected by breeding progress; however, recent selection for high seed oil content and for high seed yields appears to have promoted a negative correlation (r= -0.39 at high and r= -0.49 at low nitrogen) between seed weight and seed oil concentration. Overall, our results reveal valuable breeding targets to improve NUE in oilseed rape.

Accelerating crop genetic gains with genomic selection

Genomic prediction based on additive genetic effects can accelerate genetic gain. There are opportunities for further improvement by including non-additive effects that access untapped sources of genetic diversity. Several studies have reported a worrying gap between the projected global future demand for plant-based products and the current annual rates of production increase, indicating that enhancing the rate of genetic gain might be critical for future food security. Therefore, new breeding technologies and strategies are required to significantly boost genetic improvement of future crop cultivars. Genomic selection (GS) has delivered considerable genetic gain in animal breeding and is becoming an essential component of many modern plant breeding programmes as well. In this paper, we review the lessons learned from implementing GS in livestock and the impact of GS on crop breeding, and discuss important features for the success of GS under different breeding scenarios. We highlight major challenges associated with GS including rapid genotyping, phenotyping, genotype-by-environment interaction and non-additivity and give examples for opportunities to overcome these issues. Finally, the potential of combining GS with other modern technologies in order to maximise the rate of crop genetic improvement is discussed, including the potential of increasing prediction accuracy by integration of crop growth models in GS frameworks.

From markers to genome-based breeding in wheat

Recent technological advances in wheat genomics provide new opportunities to uncover genetic variation in traits of breeding interest and enable genome-based breeding to deliver wheat cultivars for the projected food requirements for 2050. There has been tremendous progress in development of whole-genome sequencing resources in wheat and its progenitor species during the last 5 years. High-throughput genotyping is now possible in wheat not only for routine gene introgression but also for high-density genome-wide genotyping. This is a major transition phase to enable genome-based breeding to achieve progressive genetic gains to parallel to projected wheat production demands. These advances have intrigued wheat researchers to practice less pursued analytical approaches which were not practiced due to the short history of genome sequence availability. Such approaches have been successful in gene discovery and breeding applications in other crops and animals for which genome sequences have been available for much longer. These strategies include, (i) environmental genome-wide association studies in wheat genetic resources stored in genbanks to identify genes for local adaptation by using agroclimatic traits as phenotypes, (ii) haplotype-based analyses to improve the statistical power and resolution of genomic selection and gene mapping experiments, (iii) new breeding strategies for genome-based prediction of heterosis patterns in wheat, and (iv) ultimate use of genomics information to develop more efficient and robust genome-wide genotyping platforms to precisely predict higher yield potential and stability with greater precision. Genome-based breeding has potential to achieve the ultimate objective of ensuring sustainable wheat production through developing high yielding, climate-resilient wheat cultivars with high nutritional quality.

Genetic Dissection of Snow Mold Tolerance in US Pacific Northwest Winter Wheat Through Genome-Wide Association Study and Genomic Selection

Snow mold is a yield-limiting disease of wheat in the Pacific Northwest (PNW) region of the US, where there is prolonged snow cover. The objectives of this study were to identify genomic regions associated with snow mold tolerance in a diverse panel of PNW winter wheat lines in a genome-wide association study (GWAS) and to evaluate the usefulness of genomic selection (GS) for snow mold tolerance. An association mapping panel (AMP; N = 458 lines) was planted in Mansfield and Waterville, WA in 2017 and 2018 and genotyped using the Illumina^® 90K single nucleotide polymorphism (SNP) array. GWAS identified 100 significant markers across 17 chromosomes, where SNPs on chromosomes 5A and 5B coincided with major freezing tolerance and vernalization loci. Increased number of favorable alleles was related to improved snow mold tolerance. Independent predictions using the AMP as a training population (TP) to predict snow mold tolerance of breeding lines evaluated between 2015 and 2018 resulted in a mean accuracy of 0.36 across models and marker sets. Modeling nonadditive effects improved accuracy even in the absence of a close genetic relatedness between the TP and selection candidates. Selecting lines based on genomic estimated breeding values and tolerance scores resulted in a 24% increase in tolerance. The identified genomic regions associated with snow mold tolerance demonstrated the genetic complexity of this trait and the difficulty in selecting tolerant lines using markers. GS was validated and showed potential for use in PNW winter wheat for selecting on complex traits such tolerance to snow mold.

Discovering new alleles for yellow spot resistance in the Vavilov wheat collection

GWAS detected 11 yellow spot resistance QTL in the Vavilov wheat collection. Promising adult-plant resistance loci could provide a sustainable genetic solution to yellow spot in modern wheat varieties. Yellow spot, caused by the fungal pathogen Pyrenophora tritici-repentis (Ptr), is the most economically damaging foliar disease of wheat in Australia. Genetic resistance is considered to be the most sustainable means for disease management, yet the genomic regions underpinning resistance to Ptr, particularly adult-plant resistance (APR), remain vastly unknown. In this study, we report results of a genome-wide association study using 295 accessions from the Vavilov wheat collection which were extensively tested for response to Ptr infections in glasshouse and field trials at both seedling an adult growth stages. Combining phenotypic datasets from multiple experiments in Australia and Russia with 25,286 genome-wide, high-quality DArTseq markers, we detected a total of 11 QTL, of which 5 were associated with seedling resistance, 3 with all-stage resistance, and 3 with APR. Interestingly, the novel APR QTL were effective even in the presence of host sensitivity gene Tsn1. These genomic regions could offer broad-spectrum yellow spot protection, not just to ToxA but also other pathogenicity or virulence factors. Vavilov wheat accessions carrying APR QTL combinations displayed enhanced levels of resistance highlighting the potential for QTL stacking through breeding. We propose that the APR genetic factors discovered in our study could be used to improve resistance levels in modern wheat varieties and contribute to the sustainable control of yellow spot.

Genetic insights into underground responses to Fusarium graminearum infection in wheat

The ongoing global intensification of wheat production will likely be accompanied by a rising pressure of Fusarium diseases. While utmost attention was given to Fusarium head blight (FHB) belowground plant infections of the pathogen have largely been ignored. The current knowledge about the impact of soil borne Fusarium infection on plant performance and the underlying genetic mechanisms for resistance remain very limited. Here, we present the first large-scale investigation of Fusarium root rot (FRR) resistance using a diverse panel of 215 international wheat lines. We obtained data for a total of 21 resistance-related traits, including large-scale Real-time PCR experiments to quantify fungal spread. Association mapping and subsequent haplotype analyses discovered a number of highly conserved genomic regions associated with resistance, and revealed a significant effect of allele stacking on the stembase discoloration. Resistance alleles were accumulated in European winter wheat germplasm, implying indirect prior selection for improved FRR resistance in elite breeding programs. Our results give first insights into the genetic basis of FRR resistance in wheat and demonstrate how molecular parameters can successfully be explored in genomic prediction. Ongoing work will help to further improve our understanding of the complex interactions of genetic factors influencing FRR resistance.

Harnessing genetic potential of wheat germplasm banks through impact-oriented-prebreeding for future food and nutritional security

The value of exotic wheat genetic resources for accelerating grain yield gains is largely unproven and unrealized. We used next-generation sequencing, together with multi-environment phenotyping, to study the contribution of exotic genomes to 984 three-way-cross-derived (exotic/elite1//elite2) pre-breeding lines (PBLs). Genomic characterization of these lines with haplotype map-based and SNP marker approaches revealed exotic specific imprints of 16.1 to 25.1%, which compares to theoretical expectation of 25%. A rare and favorable haplotype (GT) with 0.4% frequency in gene bank identified on chromosome 6D minimized grain yield (GY) loss under heat stress without GY penalty under irrigated conditions. More specifically, the ‘T’ allele of the haplotype GT originated in Aegilops tauschii and was absent in all elite lines used in study. In silico analysis of the SNP showed hits with a candidate gene coding for isoflavone reductase IRL-like protein in Ae. tauschii. Rare haplotypes were also identified on chromosomes 1A, 6A and 2B effective against abiotic/biotic stresses. Results demonstrate positive contributions of exotic germplasm to PBLs derived from crosses of exotics with CIMMYT’s best elite lines. This is a major impact-oriented pre-breeding effort at CIMMYT, resulting in large-scale development of PBLs for deployment in breeding programs addressing food security under climate change scenarios.