Multi-environment multi-QTL association mapping identifies disease resistance QTL in barley germplasm from Latin America

Analysis of genome-wide association studies of low-temperature germination in Xian and Geng rice

Rice is the leading global staple crop. Low temperatures pose negative impacts on rice's optimal growth and development. Rice cultivars acclimating to low temperatures exhibited improved seedling emergence under direct-seeded sowing conditions, yet little is known about the genes that regulate germination at low temperatures (LTG). In this research investigation, we've performed whole genome sequencing for the 273 rice plant materials. Using the best linear unbiased prediction (BLUP) values for each rice material, we identified 7 LTG-related traits and performed the efficient genetic analysis and genome-wide association study (GWAS). As a result of this, 95 quantitative trait loci (QTLs) and 1001 candidate genes associated with LTG in rice were identified. Haplotype analysis and functional annotation of the candidate genes resulted in the identification of three promising candidate genes (LOC_Os08g30520 for regulating LTG4 and LTG5, LOC_Os10g02625 for regulating LTG6, LTg7 and LTG8, and LOC_Os12g31460 for regulating LTG7, LTg8 and LTG9) involving in the regulation of LTG in rice. This research provides a solid foundation for addressing the LTG issue in rice and will be valuable in future direct-seeded rice breeding programs.

Genome wide association study of seedling and adult plant leaf rust resistance in two subsets of barley genetic resources

Leaf rust (LR) caused by Puccinia hordei is a serious disease of barley worldwide, causing significant yield losses and reduced grain quality. Discovery and incorporation of new sources of resistance from gene bank accessions into barley breeding programs is essential for the development of leaf rust resistant varieties. To identify Quantitative Trait Loci (QTL) conferring LR resistance in the two barley subsets, the Generation Challenge Program (GCP) reference set of 142 accessions and the leaf rust subset constructed using the Focused Identification of Germplasm Strategy (FIGS) of 76 barley accessions, were genotyped to conduct a genome-wide association study (GWAS). The results revealed a total of 59 QTL in the 218 accessions phenotyped against barley leaf rust at the seedling stage using two P. hordei isolates (ISO-SAT and ISO-MRC), and at the adult plant stage in four environments in Morocco. Out of these 59 QTL, 10 QTL were associated with the seedling resistance (SR) and 49 QTL were associated with the adult plant resistance (APR). Four QTL showed stable effects in at least two environments for APR, whereas two common QTL associated with SR and APR were detected on chromosomes 2H and 7H. Furthermore, 39 QTL identified in this study were potentially novel. Interestingly, the sequences of 27 SNP markers encoded the candidate genes (CGs) with predicted protein functions in plant disease resistance. These results will provide new perspectives on the diversity of leaf rust resistance loci for fine mapping, isolation of resistance genes, and for marker-assisted selection for the LR resistance in barley breeding programs worldwide.

Genetic architecture of ear traits based on association mapping and co-expression networks in maize inbred lines and hybrids

Ear traits are key contributors to grain yield in maize; therefore, exploring their genetic basis facilitates the improvement of grain yield. However, the underlying molecular mechanisms of ear traits remain obscure in both inbred lines and hybrids. Here, two association panels, respectively, comprising 203 inbred lines (IP) and 246 F1 hybrids (HP) were employed to identify candidate genes for six ear traits. The IP showed higher phenotypic variation and lower phenotypic mean than the HP for all traits, except ear tip-barrenness length. By conducting a genome-wide association study (GWAS) across multiple environments, 101 and 228 significant single-nucleotide polymorphisms (SNPs) associated with six ear traits were identified in the IP and HP, respectively. Of these significant SNPs identified in the HP, most showed complete-incomplete dominance and over-dominance effects for each ear trait. Combining a gene co-expression network with GWAS results, 186 and 440 candidate genes were predicted in the IP and HP, respectively, including known ear development genes ids1 and sid1. Of these, nine candidate genes were detected in both populations and expressed in maize ear and spikelet tissues. Furthermore, two key shared genes (GRMZM2G143330 and GRMZM2G171139) in both populations were found to be significantly associated with ear traits in the maize Goodman diversity panel with high-density variations. These findings advance our knowledge of the genetic architecture of ear traits between inbred lines and hybrids and provide a valuable resource for the genetic improvement of ear traits in maize.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01426-9.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.)

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Characterization of Leaf Rust Resistance in International Barley Germplasm Using Genome-Wide Association Studies

A panel of 114 genetically diverse barley lines were assessed in the greenhouse and field for resistance to the pathogen Puccinia hordei, the causal agent of barley leaf rust. Multi-pathotype tests revealed that 16.6% of the lines carried the all-stage resistance (ASR) gene Rph3, followed by Rph2 (4.4%), Rph1 (1.7%), Rph12 (1.7%) or Rph19 (1.7%). Five lines (4.4%) were postulated to carry the gene combinations Rph2+9.am, Rph2+19 and Rph8+19. Three lines (2.6%) were postulated to carry Rph15 based on seedling rust tests and genotyping with a marker linked closely to this gene. Based on greenhouse seedling tests and adult-plant field tests, 84 genotypes (73.7%) were identified as carrying APR, and genotyping with molecular markers linked closely to three known APR genes (Rph20, Rph23 and Rph24) revealed that 48 of the 84 genotypes (57.1%) likely carry novel (uncharacterized) sources of APR. Seven lines were found to carry known APR gene combinations (Rph20+Rph23, Rph23+Rph24 and Rph20+Rph24), and these lines had higher levels of field resistance compared to those carrying each of these three APR genes singly. GWAS identified 12 putative QTLs; strongly associated markers located on chromosomes 1H, 2H, 3H, 5H and 7H. Of these, the QTL on chromosome 7H had the largest effect on resistance response to P. hordei. Overall, these studies detected several potentially novel genomic regions associated with resistance. The findings provide useful information for breeders to support the utilization of these sources of resistance to diversify resistance to leaf rust in barley and increase resistance durability.

Genome-Wide Association Study of Rice Grain Shape and Chalkiness in a Worldwide Collection of Xian Accessions

Rice (Oryza sativa L.) appearance quality, which is mainly defined by grain shape and chalkiness, is an important target in rice breeding. In this study, we first re-sequenced 137 indica accessions and then conducted a genome-wide association study (GWAS) for six agronomic traits with the 2,998,034 derived single nucleotide polymorphisms (SNPs) by using the best linear unbiased prediction (BLUP) values for each trait. The results revealed that 195 SNPs had significant associations with the six agronomic traits. Based on the genome-wide linkage disequilibrium (LD) blocks, candidate genes for the target traits were detected within 100 kb upstream and downstream of the relevant SNP loci. Results indicate that six quantitative trait loci (QTLs) significantly associated with six traits (qTGW4.1, qTGW4.2, qGL4.1, qGL12.1, qGL12.2, qGW2.1, qGW4.1, qGW6.1, qGW8.1, qGW8.2, qGW9.1, qGW11.1, qGLWR2.1, qGLWR2.2, qGLWR4.2, qPGWC5.1 and qDEC6.1) were identified for haplotype analysis. Among these QTLs, two (qTGW4.2 and qGW6.1), were overlapped with FLO19 and OsbZIP47, respectively, and the remaining four were novel QTLs. These candidate genes were further validated by haplotype block construction.

Developing high-quality value-added cereals for organic systems in the US Upper Midwest: hard red winter wheat (Triticum aestivum L.) breeding

There is an increased demand for food-grade grains grown sustainably. Hard red winter wheat has comparative advantages for organic farm rotations due to fall soil cover, weed competition, and grain yields. However, limitations of currently available cultivars such as poor disease resistance, winter hardiness, and baking quality, challenges its adoption and use. Our goal was to develop a participatory hard red winter wheat breeding program for the US Upper Midwest involving farmers, millers, and bakers. Specifically, our goals include (1) an evaluation of genotype-by-environment interaction (GEI) and genotypic stability for both agronomic and quality traits, and (2) the development of on-farm trials as well as baking and sensory evaluations of genotypes to include farmers, millers, and bakers' perspectives in the breeding process. Selection in early generations for diseases and protein content was followed by multi-environment evaluations for agronomic, disease, and quality traits in three locations during five years, on-farm evaluations, baking trials, and sensory evaluations. GEI was substantial for most traits, but no repeatable environmental conditions were significant contributors to GEI making selection for stability a critical trait. Breeding lines had similar performance in on-station and on-farm trials compared to commercial checks, but some breeding lines were more stable than the checks for agronomic, quality traits, and baking performance. These results suggest that stable lines can be developed using a participatory breeding approach under organic management. Crop improvement explicitly targeting sustainable agriculture practices for selection with farm to table participatory perspectives are critical to achieve long-term sustainable crop production. KEY MESSAGE: We describe a hard red winter wheat breeding program focused on developing genotypes adapted to organic systems in the US Upper Midwest for high-end artisan baking quality using participatory approaches.

Mutations in DNA polymerase δ subunit 1 co-segregate with CMD2-type resistance to Cassava Mosaic Geminiviruses

Cassava mosaic disease (CMD) suppresses cassava yields across the tropics. The dominant CMD2 locus confers resistance to cassava mosaic geminiviruses. It has been reported that CMD2-type landraces lose resistance after regeneration through de novo morphogenesis. As full genome bisulfite sequencing failed to uncover an epigenetic mechanism for this loss of resistance, whole genome sequencing and genetic variant analysis was performed and the CMD2 locus was fine-mapped to a 190 kilobase interval. Collectively, these data indicate that CMD2-type resistance is caused by a nonsynonymous, single nucleotide polymorphism in DNA polymerase δ subunit 1 (MePOLD1) located within this region. Virus-induced gene silencing of MePOLD1 in a CMD-susceptible cassava variety produced a recovery phenotype typical of CMD2-type resistance. Analysis of other CMD2-type cassava varieties identified additional candidate resistance alleles within MePOLD1. Genetic variation of MePOLD1, therefore, could represent an important genetic resource for resistance breeding and/or genome editing, and elucidating mechanisms of resistance to geminiviruses.

Genome-wide association of rice response to blast fungus identifies loci for robust resistance under high nitrogen

BACKGROUND

Nitrogen fertilization is known to increase disease susceptibility, a phenomenon called Nitrogen-Induced Susceptibility (NIS). In rice, this phenomenon has been observed in infections with the blast fungus Magnaporthe oryzae. A previous classical genetic study revealed a locus (NIS1) that enhances susceptibility to rice blast under high nitrogen fertilization. In order to further address the underlying genetics of plasticity in susceptibility to rice blast after fertilization, we analyzed NIS under greenhouse-controlled conditions in a panel of 139 temperate japonica rice strains. A genome-wide association analysis was conducted to identify loci potentially involved in NIS by comparing susceptibility loci identified under high and low nitrogen conditions, an approach allowing for the identification of loci validated across different nitrogen environments. We also used a novel NIS Index to identify loci potentially contributing to plasticity in susceptibility under different nitrogen fertilization regimes.

RESULTS

A global NIS effect was observed in the population, with the density of lesions increasing by 8%, on average, under high nitrogen fertilization. Three new QTL, other than NIS1, were identified. A rare allele of the RRobN1 locus on chromosome 6 provides robust resistance in high and low nitrogen environments. A frequent allele of the NIS2 locus, on chromosome 5, exacerbates blast susceptibility under the high nitrogen condition. Finally, an allele of NIS3, on chromosome 10, buffers the increase of susceptibility arising from nitrogen fertilization but increases global levels of susceptibility. This allele is almost fixed in temperate japonicas, as a probable consequence of genetic hitchhiking with a locus involved in cold stress adaptation.

CONCLUSIONS

Our results extend to an entire rice subspecies the initial finding that nitrogen increases rice blast susceptibility. We demonstrate the usefulness of estimating plasticity for the identification of novel loci involved in the response of rice to the blast fungus under different nitrogen regimes.

Introgression Breeding in Barley: Perspectives and Case Studies

Changing production scenarios resulting from unstable climatic conditions are challenging crop improvement efforts. A deeper and more practical understanding of plant genetic resources is necessary if these assets are to be used effectively in developing improved varieties. In general, current varieties and potential varieties have a narrow genetic base, making them prone to suffer the consequences of new and different abiotic and biotic stresses that can reduce crop yield and quality. The deployment of genomic technologies and sophisticated statistical analysis procedures has generated a dramatic change in the way we characterize and access genetic diversity in crop plants, including barley. Various mapping strategies can be used to identify the genetic variants that lead to target phenotypes and these variants can be assigned coordinates in reference genomes. In this way, new genes and/or new alleles at known loci present in wild ancestors, germplasm accessions, land races, and un-adapted introductions can be located and targeted for introgression. In principle, the introgression process can now be streamlined and linkage drag reduced. In this review, we present an overview of (1) past and current efforts to identify diversity that can be tapped to improve barley yield and quality, and (2) case studies of our efforts to introgress resistance to stripe and stem rust from un-adapted germplasm. We conclude with a description of a modified Nested Association Mapping (NAM) population strategy that we are implementing for the development of multi-use naked barley for organic systems and share perspectives on the use of genome editing in introgression breeding.

A Genome-Wide Association Study of Resistance to Puccinia striiformis f. sp. hordei and P. graminis f. sp. tritici in Barley and Development of Resistant Germplasm

Stripe rust (incited by Puccinia striiformis f. sp. hordei) and stem rust (incited by P. graminis f. sp. tritici) are two of the most important diseases affecting barley. Building on prior work involving the introgression of the resistance genes rpg4/Rpg5 into diverse genetic backgrounds and the discovery of additional quantitative trait locus (QTLs) for stem rust resistance, we generated an array of germplasm in which we mapped resistance to stripe rust and stem rust. Stem rust races TTKSK and QCCJB were used for resistance mapping at the seedling and adult plant stages, respectively. Resistance to stripe rust, at the adult plant stage, was determined by QTLs on chromosomes 1H, 4H, and 5H that were previously reported in the literature. The rpg4/Rpg5 complex was validated as a source of resistance to stem rust at the seedling stage. Some parental germplasm, selected as potentially resistant to stem rust or susceptible but having other positive attributes, showed resistance at the seedling stage, which appears to be allelic to rpg4/Rpg5. The rpg4/Rpg5 complex, and this new allele, were not sufficient for adult plant resistance to stem rust in one environment. A QTL on 5H, distinct from Rpg5 and a previously reported resistance QTL, was required for resistance at the adult plant stage in all environments. This QTL is coincident with the QTL for stripe rust resistance. Germplasm with mapped genes/QTLs conferring resistance to stripe and stem rust was identified and is available as a resource to the research and breeding communities.

Multi-trait Genomic Prediction Model Increased the Predictive Ability for Agronomic and Malting Quality Traits in Barley (Hordeum vulgare L.)

Plant breeders regularly evaluate multiple traits across multiple environments, which opens an avenue for using multiple traits in genomic prediction models. We assessed the potential of multi-trait (MT) genomic prediction model through evaluating several strategies of incorporating multiple traits (eight agronomic and malting quality traits) into the prediction models with two cross-validation schemes (CV1, predicting new lines with genotypic information only and CV2, predicting partially phenotyped lines using both genotypic and phenotypic information from correlated traits) in barley. The predictive ability was similar for single (ST-CV1) and multi-trait (MT-CV1) models to predict new lines. However, the predictive ability for agronomic traits was considerably increased when partially phenotyped lines (MT-CV2) were used. The predictive ability for grain yield using the MT-CV2 model with other agronomic traits resulted in 57% and 61% higher predictive ability than ST-CV1 and MT-CV1 models, respectively. Therefore, complex traits such as grain yield are better predicted when correlated traits are used. Similarly, a considerable increase in the predictive ability of malting quality traits was observed when correlated traits were used. The predictive ability for grain protein content using the MT-CV2 model with both agronomic and malting traits resulted in a 76% higher predictive ability than ST-CV1 and MT-CV1 models. Additionally, the higher predictive ability for new environments was obtained for all traits using the MT-CV2 model compared to the MT-CV1 model. This study showed the potential of improving the genomic prediction of complex traits by incorporating the information from multiple traits (cost-friendly and easy to measure traits) collected throughout breeding programs which could assist in speeding up breeding cycles.

Genome Wide Association Mapping of Spot Blotch Resistance at Seedling and Adult Plant Stages in Barley

Barley spot blotch (SB) caused by Cochliobolus sativus is one of the major constrains to barley production in warmer regions worldwide. The study was undertaken to identify and estimate effects of loci underlying quantitative resistance to SB at the seedling and adult plant stages. A panel of 261 high input (HI-AM) barley genotypes consisting of released cultivars, advanced breeding lines, and landraces, was screened for resistance to SB. The seedling resistance screening was conducted using two virulent isolates from Morocco (ICSB3 and SB54) while the adult plant stage resistance was evaluated at two hot spot locations, Faizabad and Varanasi, in India under artificial inoculation using a mixture of prevalent virulent isolates. The HI-AM panel was genotyped using DArT-Seq high-throughput genotyping platform. Genome wide association mapping (GWAM) was conducted using 13,182 PAV and 6,311 SNP markers, for seedling and adult plant resistance. Both GLM and MLM model were employed in TASSEL (v 5.0) using principal component analysis and Kinship Matrix as covariates. Final disease rating and Area Under Disease Progress Curve (AUDPC) were used for the evaluation of adult stage plant resistance. The GWAM analysis indicated 23 QTL at the seedling stage (14 for isolate ICSB3 and 9 for isolate SB54), while 15 QTL were detected at the adult plant stage resistance (6 at Faizabad and 9 at Varanasi) and 5 for AUDPC based resistance at Varanasi. Common QTL at seedling and adult plant stages were found across all barley chromosomes. Seedling stage QTL explained together 73.24% of the variance for seedling resistance to isolate ICSB3 and 49.26% for isolate SB54, whereas, QTL for adult plant stage resistance explained together 38.32%, 44.09% and 26.42% of the variance at Faizabad and Varanasi and AUDPC at Varanasi, respectively. Several QTL identified in this study were also reported in previous studies using bi-parental and association mapping populations, corroborating our results. The promising QTL detected at both stages, once validated, can be used for marker assisted selection (MAS) in SB resistance barley breeding program.

Introgression of rpg4/Rpg5 Into Barley Germplasm Provides Insights Into the Genetics of Resistance to Puccinia graminis f. sp. tritici Race TTKSK and Resources for Developing Resistant Cultivars

Stem rust (incited by Puccinia graminis f. sp. tritici) is a devastating disease of wheat and barley in many production areas. The widely virulent African P. graminis f. sp. tritici race TTKSK is of particular concern, because most cultivars are susceptible. To prepare for the possible arrival of race TTKSK in North America, we crossed a range of barley germplasm-representing different growth habits and end uses-with donors of stem rust resistance genes Rpg1 and rpg4/Rpg5. The former confers resistance to prevalent races of P. graminis f. sp. tritici in North America, and the latter confers resistance to TTKSK and other closely related races from Africa. We produced doubled haploids from these crosses and determined their allele type at the Rpg loci and haplotype at 7,864 single-nucleotide polymorphism loci. The doubled haploids were phenotyped for TTKSK resistance at the seedling stage. Integration of genotype and phenotype data revealed that (i) Rpg1 was not associated with TTKSK resistance, (ii) rpg4/Rpg5 was necessary but was not sufficient for resistance, and (iii) specific haplotypes at two quantitative trait loci were required for rpg4/Rpg5 to confer resistance to TTKSK. To confirm whether lines found resistant to TTKSK at the seedling resistance were also resistant at the adult plant stage, a subset of doubled haploids was evaluated in Kenya. Additionally, adult plant resistance to leaf rust and stripe rust (incited by Puccinia hordei and Puccinia striiformis f. sp. hordei, respectively) was also assessed on the doubled haploids in field trials at three locations in the United States over a 2-year period. Doubled haploids were identified with adult plant resistance to all three rusts, and this germplasm is available to the research and breeding communities.

Integrating Molecular Markers and Environmental Covariates To Interpret Genotype by Environment Interaction in Rice (Oryza sativa L.) Grown in Subtropical Areas

Understanding the genetic and environmental basis of genotype × environment interaction (G×E) is of fundamental importance in plant breeding. If we consider G×E in the context of genotype × year interactions (G×Y), predicting which lines will have stable and superior performance across years is an important challenge for breeders. A better understanding of the factors that contribute to the overall grain yield and quality of rice (Oryza sativa L.) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. In this study, we used molecular marker data and environmental covariates (EC) simultaneously to predict rice yield, milling quality traits and plant height in untested environments (years), using both reaction norm models and partial least squares (PLS), in two rice breeding populations (indica and tropical japonica). We also sought to explain G×E by differential quantitative trait loci (QTL) expression in relation to EC. Our results showed that PLS models trained with both molecular markers and EC gave better prediction accuracies than reaction norm models when predicting future years. We also detected milling quality QTL that showed a differential expression conditional on humidity and solar radiation, providing insight for the main environmental factors affecting milling quality in subtropical and temperate rice growing areas.

High-Density Mapping of Triple Rust Resistance in Barley Using DArT-Seq Markers

The recent availability of an assembled and annotated genome reference sequence for the diploid crop barley (Hordeum vulgare L.) provides new opportunities to study the genetic basis of agronomically important traits such as resistance to stripe [Puccinia striiformis f. sp. hordei (Psh)], leaf [P. hordei (Ph)], and stem [P. graminis f. sp. tritici (Pgt)] rust diseases. The European barley cultivar Pompadour is known to possess high levels of resistance to leaf rust, predominantly due to adult plant resistance (APR) gene Rph20. We developed a barley recombinant inbred line (RIL) population from a cross between Pompadour and the leaf rust and stripe rust susceptible selection Biosaline-19 (B-19), and genotyped this population using DArT-Seq genotyping by sequencing (GBS) markers. In the current study, we produced a high-density linkage map comprising 8,610 (SNP and in silico) markers spanning 5957.6 cM, with the aim of mapping loci for resistance to leaf rust, stem rust, and stripe rust. The RIL population was phenotyped in the field with Psh (Mexico and Ecuador) and Ph (Australia) and in the greenhouse at the seedling stage with Australian Ph and Pgt races, and at Wageningen University with a European variant of Psh race 24 (PshWUR). For Psh, we identified a consistent field QTL on chromosome 2H across all South American field sites and years. Two complementary resistance genes were mapped to chromosomes 1H and 4H at the seedling stage in response to PshWUR, likely to be the loci rpsEm1 and rpsEm2 previously reported from the cultivar Emir from which Pompadour was bred. For leaf rust, we determined that Rph20 in addition to two minor-effect QTL on 1H and 3H were effective at the seedling stage, whilst seedling resistance to stem rust was due to QTL on chromosomes 3H and 7H conferred by Pompadour and B-19, respectively.

Contribution of recent technological advances to future resistance breeding

The development of durable host resistance strategies to control crop diseases is a primary need for sustainable agricultural production in the future. This article highlights the potential of recent progress in the understanding of host resistance for future cereal breeding. Much of the novel work is based on advancements in large-scale sequencing and genomics, rapid gene isolation techniques and high-throughput molecular marker technologies. Moreover, emerging applications on the pathogen side like effector identification or field pathogenomics are discussed. The combination of knowledge from both sides of cereal pathosystems will result in new approaches for resistance breeding. We describe future applications and innovative strategies to implement effective and durable strategies to combat diseases of major cereal crops while reducing pesticide dependency.

Marker-trait associations in two-rowed spring barley accessions from Kazakhstan and the USA

In this study, phenotyping and single nucleotide polymorphism (SNP) genotyping data of 272 accessions of two-rowed spring barley from the USA along with 94 accessions from Kazakhstan were assessed in field trials at six breeding organizations in Kazakhstan to evaluate the performance of the USA samples over three years (2009-2011). The average grain yield over the six locations was not significantly higher in Kazakh accessions in comparison to the USA samples. Twenty four samples from Montana, Washington, the USDA station in Aberdeen Idaho, and the Anheuser-Busch breeding programs showed heavier average yield than the local standard cultivar "Ubagan". Principal Coordinate analysis based on two sets of SNP data suggested that Kazakh accessions were closest to the USA accessions among eight groups of samples from different parts of the World, and within five US barley origin groups the samples from Montana and Washington perfectly matched six groups of Kazakh breeding origins. A genome-wide association study (GWAS) using data from eighteen field trials allowed the identification of ninety one marker-trait associations (MTA) in two or more environments for nine traits, including key characters such as heading time (HT), number of kernels per spike (NKS), and thousand grain weight (TGW). Our GWAS allowed the identification of eight MTA for HT and NKS, and sixteen MTA for TGW, when those MTA were linked to mapped SNPs. Based on comparisons of chromosomal positions of MTA identified in this study, and positions of known genes and quantitative trait loci for HT, NKS and TGW, it was suggested that MTA for HT on chromosome 2H (at 158.2 cM, 11_21414), MTA for NKS on 5H (at 118.6 cM, 11_20298), and two MTA for TGW on chromosome 4H (at 94.7 cM, 12_30718, and at 129.3 cM, 11_20013) were potentially new associations in barley. GWAS suggested that six MTA for HT, including two on chromosome 1H, two on chromosome 3H, and one each on chromosomes 4H and 6H, had useful pleiotropic effects for improving barley spike traits.

Genome Wide Association Mapping of Seedling and Adult Plant Resistance to Barley Stripe Rust (Puccinia striiformis f. sp. hordei) in India

Barley stripe rust is caused by Puccinia striiformis f.sp. hordei, (Psh), occurs worldwide, and is a major disease in South Asia. The aim of this work was to identify and estimate effects of loci underlying quantitative resistance to rust at seedling and adult plant stages. HI-AM panel of 261 barley genotypes consisting of released cultivars from North and South America, Europe, Australia, advanced breeding lines, and local landraces from ICARDA barley program were screened at seedling and adult plant stages for resistance to Psh. Seedling resistance was evaluated with the five prevalent Psh races in India. Screening for the adult plant stage resistance was also performed in two different locations by inoculating with a mixture of the five races used for seedling screeing. The panel was genotyped using DaRT-Seq high-throughput genotyping platform. The genome-wide association mapping (GWAM) showed a total of 45 QTL located across the seven barley chromosomes for seedling resistance to the five races and 18 QTL for adult plant stage resistance. Common QTL for different races at seedling stage were found on all chromosomes except on chromosome 1H. Four common QTL associated with seedling and adult plant stage resistance were found on chromosomes 2, 5, and 6H. Moreover, one of the QTL located on the long arm of chromosome 5H showed stable effects across environments for adult plant stage resistance. Several QTL identified in this study were also reported before in bi-parental and association mapping populations studies validating current GWAM. However 15 new QTL were found at adult plant stage on all chromosomes except the 4H, explaining up to 36.79% of the variance. The promising QTL detected at both stages, once validated, can be used for MAS in Psh resistance breeding program globally.

Identification of quantitative trait loci associated with resistance to net form net blotch in a collection of Nordic barley germplasm

Association mapping of resistance to Pyrenophora teres f. teres in a collection of Nordic barley germplasm at different developmental stages revealed 13 quantitative loci with mostly small effects. Net blotch, caused by the necrotrophic fungus Pyrenophora teres, is one of the major diseases in barley in Norway causing quantitative and qualitative yield losses. Resistance in Norwegian cultivars and germplasm is generally insufficient and resistance sources have not been extensively explored yet. In this study, we mapped quantitative trait loci (QTL) associated with resistance to net blotch in Nordic germplasm. We evaluated a collection of 209 mostly Nordic spring barley lines for reactions to net form net blotch (NFNB; Pyrenophora teres f. teres) in inoculations with three single conidia isolates at the seedling stage and in inoculated field trials at the adult stage in 4 years. Using 5669 SNP markers genotyped with the Illumina iSelect 9k Barley SNP Chip and a mixed linear model accounting for population structure and kinship, we found a total of 35 significant marker-trait associations for net blotch resistance, corresponding to 13 QTL, on all chromosomes. Out of these QTL, seven conferred resistance only in adult plants and four were only detectable in seedlings. Two QTL on chromosomes 3H and 6H were significant during both seedling inoculations and adult stage field trials. These are promising candidates for breeding programs using marker-assisted selection strategies. The results elucidate the genetic background of NFNB resistance in Nordic germplasm and suggest that NB resistance is conferred by a number of genes each with small-to-moderate effects, making it necessary to pyramid these genes to achieve sufficient levels of resistance.

Multi-task Gaussian process for imputing missing data in multi-trait and multi-environment trials

A method based on a multi-task Gaussian process using self-measuring similarity gave increased accuracy for imputing missing phenotypic data in multi-trait and multi-environment trials. Multi-environmental trial (MET) data often encounter the problem of missing data. Accurate imputation of missing data makes subsequent analysis more effective and the results easier to understand. Moreover, accurate imputation may help to reduce the cost of phenotyping for thinned-out lines tested in METs. METs are generally performed for multiple traits that are correlated to each other. Correlation among traits can be useful information for imputation, but single-trait-based methods cannot utilize information shared by traits that are correlated. In this paper, we propose imputation methods based on a multi-task Gaussian process (MTGP) using self-measuring similarity kernels reflecting relationships among traits, genotypes, and environments. This framework allows us to use genetic correlation among multi-trait multi-environment data and also to combine MET data and marker genotype data. We compared the accuracy of three MTGP methods and iterative regularized PCA using rice MET data. Two scenarios for the generation of missing data at various missing rates were considered. The MTGP performed a better imputation accuracy than regularized PCA, especially at high missing rates. Under the 'uniform' scenario, in which missing data arise randomly, inclusion of marker genotype data in the imputation increased the imputation accuracy at high missing rates. Under the 'fiber' scenario, in which missing data arise in all traits for some combinations between genotypes and environments, the inclusion of marker genotype data decreased the imputation accuracy for most traits while increasing the accuracy in a few traits remarkably. The proposed methods will be useful for solving the missing data problem in MET data.

Ascertainment bias from imputation methods evaluation in wheat

BACKGROUND

Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel.

RESULTS

In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between imputation methods were detected for QTL of major effect than QTL of minor effect. We also compared the different marker score matrices for GWAS analysis in a real wheat phenotype dataset, and we found minimal differences indicating that imputation did not improve the GWAS performance when a reference panel was not available.

CONCLUSIONS

Poorer performance was found in GWAS analysis when an imputed marker score matrix was used, no reference panel is available, in a wheat GBS panel.

Genome-wide association mapping of quantitative traits in a breeding population of sugarcane

BACKGROUND

Molecular markers associated with relevant agronomic traits could significantly reduce the time and cost involved in developing new sugarcane varieties. Previous sugarcane genome-wide association analyses (GWAS) have found few molecular markers associated with relevant traits at plant-cane stage. The aim of this study was to establish an appropriate GWAS to find molecular markers associated with yield related traits consistent across harvesting seasons in a breeding population. Sugarcane clones were genotyped with DArT (Diversity Array Technology) and TRAP (Target Region Amplified Polymorphism) markers, and evaluated for cane yield (CY) and sugar content (SC) at two locations during three successive crop cycles. GWAS mapping was applied within a novel mixed-model framework accounting for population structure with Principal Component Analysis scores as random component.

RESULTS

A total of 43 markers significantly associated with CY in plant-cane, 42 in first ratoon, and 41 in second ratoon were detected. Out of these markers, 20 were associated with CY in 2 years. Additionally, 38 significant associations for SC were detected in plant-cane, 34 in first ratoon, and 47 in second ratoon. For SC, one marker-trait association was found significant for the 3 years of the study, while twelve markers presented association for 2 years. In the multi-QTL model several markers with large allelic substitution effect were found. Sequences of four DArT markers showed high similitude and e-value with coding sequences of Sorghum bicolor, confirming the high gene microlinearity between sorghum and sugarcane.

CONCLUSIONS

In contrast with other sugarcane GWAS studies reported earlier, the novel methodology to analyze multi-QTLs through successive crop cycles used in the present study allowed us to find several markers associated with relevant traits. Combining existing phenotypic trial data and genotypic DArT and TRAP marker characterizations within a GWAS approach including population structure as random covariates may prove to be highly successful. Moreover, sequences of DArT marker associated with the traits of interest were aligned in chromosomal regions where sorghum QTLs has previously been reported. This approach could be a valuable tool to assist the improvement of sugarcane and better supply sugarcane demand that has been projected for the upcoming decades.

Genome-Wide Association Mapping of Acid Soil Resistance in Barley (Hordeum vulgare L.)

Genome-wide association studies (GWAS) based on linkage disequilibrium (LD) have been used to detect QTLs underlying complex traits in major crops. In this study, we collected 218 barley (Hordeum vulgare L.) lines including wild barley and cultivated barley from China, Canada, Australia, and Europe. A total of 408 polymorphic markers were used for population structure and LD analysis. GWAS for acid soil resistance were performed on the population using a general linkage model (GLM) and a mixed linkage model (MLM), respectively. A total of 22 QTLs (quantitative trait loci) were detected with the GLM and MLM analyses. Two QTLs, close to markers bPb-1959 (133.1 cM) and bPb-8013 (86.7 cM), localized on chromosome 1H and 4H respectively, were consistently detected in two different trials with both the GLM and MLM analyses. Furthermore, bPb-8013, the closest marker to the major Al(3+) resistance gene HvAACT1 in barley, was identified to be QTL5. The QTLs could be used in marker-assisted selection to identify and pyramid different loci for improved acid soil resistance in barley.