Genome-wide association mapping for resistance to leaf rust,stripe rust and tan spot in wheat reveals potential candidate genes

Key message

Genome-wide association mapping in conjunction with population sequencing map and Ensembl plants was used to identify markers/candidate genes linked to leaf rust, stripe rust and tan spot resistance in wheat.

Abstract

Leaf rust (LR), stripe rust (YR) and tan spot (TS) are some of the important foliar diseases in wheat (Triticum aestivum L.). To identify candidate resistance genes for these diseases in CIMMYT’s (International Maize and Wheat Improvement Center) International bread wheat screening nurseries, we used genome-wide association studies (GWAS) in conjunction with information from the population sequencing map and Ensembl plants. Wheat entries were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. Using a mixed linear model, we observed that seedling resistance to LR was associated with 12 markers on chromosomes 1DS, 2AS, 2BL, 3B, 4AL, 6AS and 6AL, and seedling resistance to TS was associated with 14 markers on chromosomes 1AS, 2AL, 2BL, 3AS, 3AL, 3B, 6AS and 6AL. Seedling and adult plant resistance (APR) to YR were associated with several markers at the distal end of chromosome 2AS. In addition, YR APR was also associated with markers on chromosomes 2DL, 3B and 7DS. The potential candidate genes for these diseases included several resistance genes, receptor-like serine/threonine-protein kinases and defense-related enzymes. However, extensive LD in wheat that decays at about 5?×?10⁷ bps, poses a huge challenge for delineating candidate gene intervals and candidates should be further mapped, functionally characterized and validated. We also explored a segment on chromosome 2AS associated with multiple disease resistance and identified seventeen disease resistance linked genes. We conclude that identifying candidate genes linked to significant markers in GWAS is feasible in wheat, thus creating opportunities for accelerating molecular breeding.

     

Genome-wide association study of stem rust resistance in a world collection of cultivated barley

Key message

QTL conferring a 14–40% reduction in adult plant stem rust severity to multiple races of Pgt were found on chromosome 5H and will be useful in barley breeding.

Abstract

Stem rust, caused by Puccinia graminis f. sp. tritici (Pgt) is an important disease of barley. The resistance gene Rpg1 has protected the crop against stem rust losses for over 70 years in North America, but is not effective against the African Pgt race TTKSK (and its variants) nor the domestic race QCCJB. To identify resistance to these Rpg1-virulent races, the Barley iCore Collection, held by the United States Department of Agriculture-Agricultural Research Service National Small Grains Collection was evaluated for adult plant resistance (APR) and seedling resistance to race TTKSK and APR to race QCCJB and the Pgt TTKSK composite of races TTKSK, TTKST, TTKTK, and TTKTT. Using a genome-wide association study approach based on 6224 single nucleotide polymorphic markers, seven significant loci for stem rust resistance were identified on chromosomes 1H, 2H, 3H, and 5H. The most significant markers detected were 11_11355 and SCRI_RS_177017 at 71–75 cM on chromosome 5H, conferring APR to QCCJB and TTKSK composite. Significant markers were also detected for TTKSK seedling resistance on chromosome 5H. All markers detected on 5H were independent of the rpg4/Rpg5 complex at 152–168 cM. This study verified the importance of the 11_11355 locus in conferring APR to races QCCJB and TTKSK and suggests that it may be effective against other races in the Ug99 lineage.

     

Unlocking new alleles for leaf rust resistance in the Vavilov wheat collection

Key message

Thirteen potentially new leaf rust resistance loci were identified in a Vavilov wheat diversity panel. We demonstrated the potential of allele stacking to strengthen resistance against this important pathogen.

Abstract

Leaf rust (LR) caused by Puccinia triticina is an important disease of wheat (Triticum aestivum L.), and the deployment of genetically resistant cultivars is the most viable strategy to minimise yield losses. In this study, we evaluated a diversity panel of 295 bread wheat accessions from the N. I. Vavilov Institute of Plant Genetic Resources (St Petersburg, Russia) for LR resistance and performed genome-wide association studies (GWAS) using 10,748 polymorphic DArT-seq markers. The diversity panel was evaluated at seedling and adult plant growth stages using three P. triticina pathotypes prevalent in Australia. GWAS was applied to 11 phenotypic data sets which identified a total of 52 significant marker–trait associations representing 31 quantitative trait loci (QTL). Among them, 29 QTL were associated with adult plant resistance (APR). Of the 31 QTL, 13 were considered potentially new loci, whereas 4 co-located with previously catalogued Lr genes and 14 aligned to regions reported in other GWAS and genomic prediction studies. One seedling LR resistance QTL located on chromosome 3A showed pronounced levels of linkage disequilibrium among markers (r ² = 0.7), suggested a high allelic fixation. Subsequent haplotype analysis for this region found seven haplotype variants, of which two were strongly associated with LR resistance at seedling stage. Similarly, analysis of an APR QTL on chromosome 7B revealed 22 variants, of which 4 were associated with resistance at the adult plant stage. Furthermore, most of the tested lines in the diversity panel carried 10 or more combined resistance-associated marker alleles, highlighting the potential of allele stacking for long-lasting resistance.

     

Characterization and genome-wide association mapping of resistance to leaf rust,stem rust and stripe rust in a geographically diverse collection of spring wheat landraces

The challenge posed by rapidly changing wheat rust pathogens, both in virulence and in environmental adaptation, calls for the development and application of new techniques to accelerate the process of breeding for durable resistance. To expand the resistance gene pool available for germplasm improvement, a panel of 159 landraces plus old cultivars was evaluated for seedling and adult plant resistance (APR) to over 35 Australian pathotypes of Puccinia triticina, Puccinia graminis f. sp. tritici, and Puccinia striiformis f. sp. tritici. Known seedling resistance (SR) genes for leaf rust (Lr2a, Lr3a, Lr13, Lr23, Lr16, and Lr20), stem rust (Sr12, Sr13, Sr23, Sr30, and Sr36), and stripe rust (Yr3, Yr4, Yr5, Yr9, Yr10, Yr17, and Yr27) were postulated. The APR genes identified via field assessments and marker analyses included the pleiotropic genes (Lr34/Yr18/Sr57, Lr46/Yr29/Sr58, Lr67/Yr46/Sr55, and Sr2/Lr27/Yr30), Lr68, Lr74, and uncharacterized APR. A genome-wide association analysis using linear mixed models detected 79 single nucleotide polymorphism (SNP) markers significantly associated with rust resistance, which were mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 3A, 3B, 3D, 4A, 5A, 5B, 6A, 6B, 6D, 7A, 7B and 7D. SNPs associated with multiple rust resistances probably indicate the presence of new pleiotropic or closely linked genes. SNPs were mapped on chromosome positions (1AL, 1DS, 2AL, 4AS, 5BS, 6DL, and 7AL) that have not been known to carry APR genes. This study revealed the presence of a range of possibly unidentified effective seedling and APRs among the landraces, which might represent new sources of rust resistance for the ongoing effort to develop improved wheat cultivars.     

Characterization of Yr54 and other genes associated with adult plant resistance to yellow rust and leaf rust in common wheat Quaiu 3

Leaf rust (LR) and yellow rust (YR), caused by Puccinia triticina and Puccinia striiformis f. sp. tritici, respectively, are important diseases of wheat. Quaiu 3, a common wheat line developed at the International Maize and Wheat Improvement Center (CIMMYT), is immune to YR in Mexico despite seedling susceptibility to predominant races. Quaiu 3 also shows immunity to LR in field trials and is known to possess the race-specific gene Lr42. A mapping population of 182 recombinant inbred lines (RILs) was developed by crossing Quaiu 3 with susceptible Avocet-YrA and phenotyped with LR and YR in field trials for 2 years in Mexico. Quantitative trait loci (QTL) associated with YR and LR resistance in the RILs were identified using Diversity Arrays Technology and simple sequence repeat markers. A large-effect QTL on the long arm of chromosome 2D explained 49–54 % of the phenotypic variation in Quaiu 3 and was designated as Yr54. Two additional loci on 1BL and 3BS explained 8–17 % of the phenotypic variation for YR and coincided with previously characterized adult plant resistance (APR) genes Lr46/Yr29 and Sr2/Yr30, respectively. QTL on 1DS and 1BL corresponding to Lr42 and Lr46/Yr29, respectively, contributed 60–71 % of the variation for LR resistance. A locus on 3D associated with APR to both diseases explained up to 7 % of the phenotypic variance. Additional Avocet-YrA-derived minor QTL were also detected for YR on chromosomes 1A, 3D, 4A, and 6A. Yr54 is a newly characterized APR gene which can be combined with other genes by using closely linked molecular markers.     

Accuracy of genomic predictions in Bos indicus (Nellore) cattle

Background

Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population.

Methods

Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group.

Results

Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes C and BLASSO). Bayes C and BLASSO tended to produce deflated predictions (i.e. slope of the regression of dEBV on DGV greater than 1). Further analyses suggested that higher-than-expected accuracies were observed for traits for which EBV means differed significantly between two breeding subgroups that were identified in a principal component analysis based on genomic relationships.

Conclusions

Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions. Recurrent updates of the training population would be required to enable accurate prediction of the genetic merit of young animals. The technical feasibility of applying genomic prediction in a Bos indicus (Nellore) population was demonstrated. Further research is needed to permit cost-effective selection decisions using genomic information.     

Investigating successive Australian barley breeding populations for stable resistance to leaf rust

Key message

Genome-wide association studies of barley breeding populations identified candidate minor genes for pairing with the adult plant resistance gene Rph20 to provide stable leaf rust resistance across environments.

Abstract

Stable resistance to barley leaf rust (BLR, caused by Puccinia hordei) was evaluated across environments in barley breeding populations (BPs). To identify genomic regions that can be combined with Rph20 to improve adult plant resistance (APR), two BPs genotyped with the Diversity Arrays Technology genotyping-by-sequencing platform (DArT-seq) were examined for reaction to BLR at both seedling and adult growth stages in Australian environments. An integrated consensus map comprising both first- and second-generation DArT platforms was used to integrate QTL information across two additional BPs, providing a total of four interrelated BPs and 15 phenotypic data sets. This enabled identification of key loci underpinning BLR resistance. The APR gene Rph20 was the only active resistance region consistently detected across BPs. Of the QTL identified, RphQ27 on chromosome 6HL was considered the best candidate for pairing with Rph20. RphQ27 did not align or share proximity with known genes and was detected in three of the four BPs. The combination of RphQ27 and Rph20 was of low frequency in the breeding material; however, strong resistance responses were observed for the lines carrying this pairing. This suggests that the candidate minor gene RphQ27 can interact additively with Rph20 to provide stable resistance to BLR across diverse environments.

     

QTL mapping of adult-plant resistance to leaf rust in a RIL population derived from a cross of wheat cultivars Shanghai 3/Catbird and Naxos

Key message

Six QTL for adult plant resistance to leaf rust, including two QTL effective against additional diseases, were identified in a RIL population derived from a cross between Shanghai 3/Catbird and Naxos.

Abstract

Leaf rust is an important wheat disease and utilization of adult-plant resistance (APR) may be the best approach to achieve long-term protection from the disease. The CIMMYT spring wheat line Shanghai 3/Catbird (SHA3/CBRD) showed a high level of APR to Chinese Puccinia triticina pathotypes in the field. To identify APR genes in this line, a mapping population of 164 recombinant inbred lines (RILs) was developed from a cross of this line and Naxos, a moderately susceptible German cultivar. The RILs were evaluated for final disease severity (FDS) at Baoding, Hebei province, and Zhoukou, Henan province, in the 2010–2011 and 2011–2012 cropping seasons. QTL analysis detected one major QTL derived from SHA3/CBRD on chromosome 2BS explaining from 15 to 37 % of the phenotypic variance across environments. In addition one minor resistance QTL on chromosome 1AL from SHA3/CBRD and four minor QTL from Naxos on chromosomes 2DL, 5B, 7BS, and 7DS were also detected. SHA3/CBRD also possessed seedling resistance gene Lr26, and Naxos contained Lr1 based on gene postulation following tests with an array of P. triticina pathotypes and molecular marker assays. These seedling resistance and APR genes and their closely linked molecular markers are potentially useful for improving leaf rust resistance in wheat breeding programs.     

Genetic analysis and mapping of adult plant resistance loci to leaf rust in durum wheat cultivar Bairds

Key message

New leaf rust adult plant resistance (APR) QTL QLr.cim - 6BL was mapped and confirmed the known pleotropic APR gene Lr46 effect on leaf rust in durum wheat line Bairds.

Abstract

CIMMYT-derived durum wheat line Bairds displays an adequate level of adult plant resistance (APR) to leaf rust in Mexican field environments. A recombinant inbred line (RIL) population developed from a cross of Bairds with susceptible parent Atred#1 was phenotyped for leaf rust response at Ciudad Obregon, Mexico, during 2013, 2014, 2015 and 2016 under artificially created epidemics of Puccinia triticina (Pt) race BBG/BP. The RIL population and its parents were genotyped with the 50 K diversity arrays technology (DArT) sequence system and simple sequence repeat (SSR) markers. A genetic map comprising 1150 markers was used to map the resistance loci. Four significant quantitative trait loci (QTLs) were detected on chromosomes 1BL, 2BC (centromere region), 5BL and 6BL. These QTLs, named Lr46, QLr.cim-2BC, QLr.cim-5BL and QLr.cim-6BL, respectively, explained 13.5–60.8%, 9.0–14.3%, 2.8–13.9%, and 11.6–29.4%, respectively, of leaf rust severity variation by the inclusive composite interval mapping method. All of these resistance loci were contributed by the resistant parent Bairds, except for QLr.cim-2BC, which came from susceptible parent Atred#1. Among these, the QTL on chromosome 1BL was the known pleiotropic APR gene Lr46, whereas QLr.cim-6BL, a consistently detected locus, should be a new leaf rust resistance locus in durum wheat. The mean leaf rust severity of RILs carrying all four QTLs ranged from 8.0 to 17.5%, whereas it ranged from 10.9 to 38.5% for three QTLs (Lr46 + 5BL + 6BL) derived from the resistant parent Bairds. Two RILs with four QTLs combinations can be used as sources of complex APR in durum wheat breeding.

     

Genomic prediction for rust resistance in diverse wheat landraces

Key message

We have demonstrated that genomic selection in diverse wheat landraces for resistance to leaf, stem and strip rust is possible, as genomic breeding values were moderately accurate. Markers with large effects in the Bayesian analysis confirmed many known genes, while also discovering many previously uncharacterised genome regions associated with rust scores.

Abstract

Genomic selection, where selection decisions are based on genomic estimated breeding values (GEBVs) derived from genome-wide DNA markers, could accelerate genetic progress in plant breeding. In this study, we assessed the accuracy of GEBVs for rust resistance in 206 hexaploid wheat (Triticum aestivum) landraces from the Watkins collection of phenotypically diverse wheat genotypes from 32 countries. The landraces were genotyped for 5,568 SNPs using an Illumina iSelect 9 K bead chip assay and phenotyped for field-based leaf rust (Lr), stem rust (Sr) and stripe rust (Yr) responses across multiple years. Genomic Best Linear Unbiased Prediction (GBLUP) and a Bayesian Regression method (BayesR) were used to predict GEBVs. Based on fivefold cross-validation, the accuracy of genomic prediction averaged across years was 0.35, 0.27 and 0.44 for Lr, Sr and Yr using GBLUP and 0.33, 0.38 and 0.30 for Lr, Sr and Yr using BayesR, respectively. Inclusion of PCR-predicted genotypes for known rust resistance genes increased accuracy more substantially when the marker was diagnostic (Lr34/Sr57/Yr18) for the presence-absence of the gene rather than just linked (Sr2). Investigation of the impact of genetic relatedness between validation and reference lines on accuracy of genomic prediction showed that accuracy will be higher when each validation line had at least one close relationship to the reference lines. Overall, the prediction accuracies achieved in this study are encouraging, and confirm the feasibility of genomic selection in wheat. In several instances, estimated marker effects were confirmed by published literature and results of mapping experiments using Watkins accessions.     

Association mapping of leaf rust resistance loci in a spring wheat core collection

Key message

We identified 15 potentially novel loci in addition to previously characterized leaf rust resistance genes from 1032 spring wheat accessions. Targeted AM subset panels were instrumental in revealing interesting loci.

Abstract

Leaf rust is a common disease of wheat, consistently reducing yields in many wheat-growing regions of the world. Although fungicides are commonly applied to wheat in the United States (US), genetic resistance can provide less expensive, yet effective control of the disease. Our objectives were to map leaf rust resistance genes in a large core collection of spring wheat accessions selected from the United States Department of Agriculture-Agricultural Research Service National Small Grains Collection (NSGC), determine whether previously characterized race-nonspecific resistance genes could be identified with our panel, and evaluate the use of targeted panels to identify seedling and adult plant resistance (APR) genes. Association mapping (AM) detected five potentially novel leaf rust resistance loci on chromosomes 2BL, 4AS, and 5DL at the seedling stage, and 2DL and 7AS that conditioned both seedling and adult plant resistance. In addition, ten potentially novel race-nonspecific resistance loci conditioned field resistance and lacked seedling resistance. Analyses of targeted subsets of the accessions identified additional loci not associated with resistance in the complete core panel. Using molecular markers, we also confirmed the presence and effectiveness of the race-nonspecific genes Lr34, Lr46, and Lr67 in our panel. Although most of the accessions in this study were susceptible to leaf rust in field and seedling tests, many resistance loci were identified with AM. Through the use of targeted subset panels, more loci were identified than in the larger core panels alone.

     

Genomic prediction based on data from three layer lines: a comparison between linear methods

Background

The prediction accuracy of several linear genomic prediction models, which have previously been used for within-line genomic prediction, was evaluated for multi-line genomic prediction.

Methods

Compared to a conventional BLUP (best linear unbiased prediction) model using pedigree data, we evaluated the following genomic prediction models: genome-enabled BLUP (GBLUP), ridge regression BLUP (RRBLUP), principal component analysis followed by ridge regression (RRPCA), BayesC and Bayesian stochastic search variable selection. Prediction accuracy was measured as the correlation between predicted breeding values and observed phenotypes divided by the square root of the heritability. The data used concerned laying hens with phenotypes for number of eggs in the first production period and known genotypes. The hens were from two closely-related brown layer lines (B1 and B2), and a third distantly-related white layer line (W1). Lines had 1004 to 1023 training animals and 238 to 240 validation animals. Training datasets consisted of animals of either single lines, or a combination of two or all three lines, and had 30 508 to 45 974 segregating single nucleotide polymorphisms.

Results

Genomic prediction models yielded 0.13 to 0.16 higher accuracies than pedigree-based BLUP. When excluding the line itself from the training dataset, genomic predictions were generally inaccurate. Use of multiple lines marginally improved prediction accuracy for B2 but did not affect or slightly decreased prediction accuracy for B1 and W1. Differences between models were generally small except for RRPCA which gave considerably higher accuracies for B2. Correlations between genomic predictions from different methods were higher than 0.96 for W1 and higher than 0.88 for B1 and B2. The greater differences between methods for B1 and B2 were probably due to the lower accuracy of predictions for B1 (~0.45) and B2 (~0.40) compared to W1 (~0.76).

Conclusions

Multi-line genomic prediction did not affect or slightly improved prediction accuracy for closely-related lines. For distantly-related lines, multi-line genomic prediction yielded similar or slightly lower accuracies than single-line genomic prediction. Bayesian variable selection and GBLUP generally gave similar accuracies. Overall, RRPCA yielded the greatest accuracies for two lines, suggesting that using PCA helps to alleviate the “n ≪ p” problem in genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0057-5) contains supplementary material, which is available to authorized users.     

Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation

Background

Genomic predictions can be applied early in life without impacting selection candidates. This is especially useful for meat quality traits in sheep. Carcass and novel meat quality traits were predicted in a multi-breed sheep population that included Merino, Border Leicester, Polled Dorset and White Suffolk sheep and their crosses.

Methods

Prediction of breeding values by best linear unbiased prediction (BLUP) based on pedigree information was compared to prediction based on genomic BLUP (GBLUP) and a Bayesian prediction method (BayesR). Cross-validation of predictions across sire families was used to evaluate the accuracy of predictions based on the correlation of predicted and observed values and the regression of observed on predicted values was used to evaluate bias of methods. Accuracies and regression coefficients were calculated using either phenotypes or adjusted phenotypes as observed variables.

Results and conclusions

Genomic methods increased the accuracy of predicted breeding values to on average 0.2 across traits (range 0.07 to 0.31), compared to an average accuracy of 0.09 for pedigree-based BLUP. However, for some traits with smaller reference population size, there was no increase in accuracy or it was small. No clear differences in accuracy were observed between GBLUP and BayesR. The regression of phenotypes on breeding values was close to 1 for all methods, indicating little bias, except for GBLUP and adjusted phenotypes (regression = 0.78). Accuracies calculated with adjusted (for fixed effects) phenotypes were less variable than accuracies based on unadjusted phenotypes, indicating that fixed effects influence the latter. Increasing the reference population size increased accuracy, indicating that adding more records will be beneficial. For the Merino, Polled Dorset and White Suffolk breeds, accuracies were greater than for the Border Leicester breed due to the smaller sample size and limited across-breed prediction. BayesR detected only a few large marker effects but one region on chromosome 6 was associated with large effects for several traits. Cross-validation produced very similar variability of accuracy and regression coefficients for BLUP, GBLUP and BayesR, showing that this variability is not a property of genomic methods alone. Our results show that genomic selection for novel difficult-to-measure traits is a feasible strategy to achieve increased genetic gain.     

Association mapping of resistance to Puccinia hordei in Australian barley breeding germplasm

Key message

“To find stable resistance using association mapping tools, QTL with major and minor effects on leaf rust reactions were identified in barley breeding lines by assessing seedlings and adult plants.”

Abstract

Three hundred and sixty (360) elite barley (Hordeum vulgare L.) breeding lines from the Northern Region Barley Breeding Program in Australia were genotyped with 3,244 polymorphic diversity arrays technology markers and the results used to map quantitative trait loci (QTL) conferring a reaction to leaf rust (Puccinia hordei Otth). The F_3:5 (Stage 2) lines were derived or sourced from different geographic origins or hubs of international barley breeding ventures representing two breeding cycles (2009 and 2011 trials) and were evaluated across eight environments for infection type at both seedling and adult plant stages. Association mapping was performed using mean scores for disease reaction, accounting for family effects using the eigenvalues from a matrix of genotype correlations. In this study, 15 QTL were detected; 5 QTL co-located with catalogued leaf rust resistance genes (Rph1, Rph3/19, Rph8/14/15, Rph20, Rph21), 6 QTL aligned with previously reported genomic regions and 4 QTL (3 on chromosome 1H and 1 on 7H) were novel. The adult plant resistance gene Rph20 was identified across the majority of environments and pathotypes. The QTL detected in this study offer opportunities for breeding for more durable resistance to leaf rust through pyramiding multiple genomic regions via marker-assisted selection.     

Defeating the Warrior: genetic architecture of triticale resistance against a novel aggressive yellow rust race

Key message

Genome-wide association mapping of resistance against the novel, aggressive ‘Warrior’ race of yellow rust in triticale revealed a genetic architecture with some medium-effect QTL and a quantitative component, which in combination confer high levels of resistance on both leaves and ears.

Abstract

Yellow rust is an important destructive fungal disease in small grain cereals and the exotic ‘Warrior’ race has recently conquered Europe. The aim of this study was to investigate the genetic architecture of yellow rust resistance in hexaploid winter triticale as the basis for a successful resistance breeding. To this end, a diverse panel of 919 genotypes was evaluated for yellow rust infection on leaves and ears in multi-location field trials and genotyped by genotyping-by-sequencing as well as for known Yr resistance loci. Genome-wide association mapping identified ten quantitative trait loci (QTL) for yellow rust resistance on the leaves and seven of these also for ear resistance. The total genotypic variance explained by the QTL amounted to 44.0% for leaf and 26.0% for ear resistance. The same three medium-effect QTL were identified for both traits on chromosomes 1B, 2B, and 7B. Interestingly, plants pyramiding the resistance allele of all three medium-effect QTL were generally most resistant, but constitute less than 5% of the investigated triticale breeding material. Nevertheless, a genome-wide prediction yielded a higher predictive ability than prediction based on these three QTL. Taken together, our results show that yellow rust resistance in winter triticale is genetically complex, including both medium-effect QTL as well as a quantitative resistance component. Resistance to the novel ‘Warrior’ race of this fungal pathogen is consequently best achieved by recurrent selection in the field based on identified resistant lines and can potentially be assisted by genomic approaches.

     

Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat

Key message

A major stripe rust resistance QTL on chromosome 4BL was localized to a 4.5-Mb interval using comparative QTL mapping methods and validated in 276 wheat genotypes by haplotype analysis.

Abstract

CYMMIT-derived wheat line P10103 was previously identified to have adult plant resistance (APR) to stripe rust in the greenhouse and field. The conventional approach for QTL mapping in common wheat is laborious. Here, we performed QTL detection of APR using a combination of genome-wide scanning and extreme pool-genotyping. SNP-based genetic maps were constructed using the Wheat55 K SNP array to genotype a recombinant inbred line (RIL) population derived from the cross Mingxian 169?×?P10103. Five stable QTL were detected across multiple environments. After comparing SNP profiles from contrasting, extreme DNA pools of RILs six putative QTL were located to approximate chromosome positions. A major QTL on chromosome 4B was identified in F_2:4 contrasting pools from cross Zhengmai 9023?×?P10103. A consensus QTL (LOD?=?26–40, PVE?=?42–55%), named QYr.nwafu-4BL, was defined and localized to a 4.5-Mb interval flanked by SNP markers AX-110963704 and AX-110519862 in chromosome arm 4BL. Based on stripe rust response, marker genotypes, pedigree analysis and mapping data, QYr.nwafu-4BL is likely to be a new APR QTL. The applicability of the SNP-based markers flanking QYr.nwafu-4BL was validated on a diversity panel of 276 wheat lines. The additional minor QTL on chromosomes 4A, 5A, 5B and 6A enhanced the level of resistance conferred by QYr.nwafu-4BL. Marker-assisted pyramiding of QYr.nwafu-4BL and other favorable minor QTL in new wheat cultivars should improve the level of APR to stripe rust.

     

Genetic research as the valid base of strategies for breeding rust resistant wheats

It is known that few wheat cultivars maintain their resistance to rust diseases for a long period of time, particularly when crop populations become genetically more uniform. A number of genetically diverse, so far unexploited, sources of rust resistance in the natural as well as mutagenized population of wheat cultivars were identified. Several of these genes were placed in agronomically superior well-adapted backgrounds so that they could be used as pre-breeding stocks for introducing genetic diversity for resistance in a crop population. Some of these stocks when employed as parents in several cross combinations in a breeding programme have generated a number of promising cultivars with diversity for resistance.Many presently grown wheats in India, near-isogenic lines each with Lr14b, Lr14ab, Lr30 and certain international cultivars were identified as possessing diverse sources of adult plant resistance (APR) to leaf rust. Prolonged leaf rust resistance in some of the Indian cultivars was attributed to the likely presence of Lr34 either alone or in combination with other APR components. Tests of allelism carried out in certain cultivars that continue to show adequate levels of field resistance confirm the presence of Lr34, which explains the role that this gene has played in imparting durability for resistance to leaf rust. Also, Lr34 in combination with other APR components increases the levels of resistance, which suggests that combination of certain APR components should be another important strategy for breeding cultivars conferring durable and adequate levels of resistance. A new adult plant leaf rust resistance source that seems to be associated with durability in Arjun has been postulated. Likewise, cultivars possessing Sr2 in combination with certain other specific genes have maintained resistance to stem rust.Further, non-specific resistances that were transferred across widely different genotypes into two of the popular Indian wheats provided easily usable materials to the national breeding programmes for imparting durable resistance to stripe rust.     

Mapping of stripe rust resistance gene in an <Emphasis Type="Italic">Aegilops caudata</Emphasis> introgression line in wheat and its genetic association with leaf rust resistance

A pair of stripe rust and leaf rust resistance genes was introgressed from Aegilops caudata, a nonprogenitor diploid species with the CC genome, to cultivated wheat. Inheritance and genetic mapping of stripe rust resistance gene in backcross-recombinant inbred line (BC-RIL) population derived from the cross of a wheat–Ae. caudata introgression line (IL) T291-2(pau16060) with wheat cv. PBW343 is reported here. Segregation of BC-RILs for stripe rust resistance depicted a single major gene conditioning adult plant resistance (APR) with stripe rust reaction varying from TR-20MS in resistant RILs signifying the presence of some minor genes as well. Genetic association with leaf rust resistance revealed that two genes are located at a recombination distance of 13%. IL T291-2 had earlier been reported to carry introgressions on wheat chromosomes 2D, 3D, 4D, 5D, 6D and 7D. Genetic mapping indicated the introgression of stripe rust resistance gene on wheat chromosome 5DS in the region carrying leaf rust resistance gene LrAc, but as an independent introgression. Simple sequence repeat (SSR) and sequence-tagged site (STS) markers designed from the survey sequence data of 5DS enriched the target region harbouring stripe and leaf rust resistance genes. Stripe rust resistance locus, temporarily designated as YrAc, mapped at the distal most end of 5DS linked with a group of four colocated SSRs and two resistance gene analogue (RGA)-STS markers at a distance of 5.3 cM. LrAc mapped at a distance of 9.0 cM from the YrAc and at 2.8 cM from RGA-STS marker Ta5DS_2737450, YrAc and LrAc appear to be the candidate genes for marker-assisted enrichment of the wheat gene pool for rust resistance.     

A mixed model to multiple harvest-location trials applied to genomic prediction in <Emphasis Type="Italic">Coffea canephora</Emphasis>

Genomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and genomic analysis was performed using a genotyping-by-sequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodness-of-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10–17% higher) and lower prediction errors than traditional GBLUP. The results may be used as basis for additional studies into the genus Coffea and can be expanded for similar perennial crops.     

Genome-wide association mapping for seedling and field resistance to <Emphasis Type="Italic">Puccinia striiformis</Emphasis> f. sp. <Emphasis Type="Italic">tritici</Emphasis> in elite durum wheat

Key message

Genome-wide association analysis in tetraploid wheat revealed novel and diverse loci for seedling and field resistance to stripe rust in elite spring durum wheat accessions from worldwide.

Abstract

Improving resistance to stripe rust, caused by Puccinia striiformis f. sp. tritici, is a major objective for wheat breeding. To identify effective stripe rust resistance loci, a genome-wide association study (GWAS) was conducted using 232 elite durum wheat (Triticum turgidum ssp. durum) lines from worldwide breeding programs. Genotyping with the 90 K iSelect wheat single nucleotide polymorphism (SNP) array resulted in 11,635 markers distributed across the genome. Response to stripe rust infection at the seedling stage revealed resistant and susceptible accessions present in rather balanced frequencies for the six tested races, with a higher frequency of susceptible responses to United States races as compared to Italian races (61.1 vs. 43.1% of susceptible accessions). Resistance at the seedling stage only partially explained adult plant resistance, which was found to be more frequent with 67.7% of accessions resistant across six nurseries in the United States. GWAS identified 82 loci associated with seedling stripe rust resistance, five of which were significant at the false discovery rate adjusted P value <0.1 and 11 loci were detected for the field response at the adult plant stages in at least two environments. Notably, Yrdurum-1BS.1 showed the largest effect for both seedling and field resistance, and is therefore considered as a major locus for resistance in tetraploid wheat. Our GWAS study is the first of its kind for stripe rust resistance in tetraploid wheat and provides an overview of resistance in elite germplasm and reports new loci that can be used in breeding resistant cultivars.