QTL mapping for stripe rust and powdery mildew resistance in <i>Triticum durum</i>–<i>Aegilops speltoides</i> backcross introgression lines

Dhillon, G. S.; Kaur, Satinder; Das, Niranjan; Singh, R. P.; Poland, Jesse; Kaur, Jaspal; Chhuneja, Parveen

doi:10.1017/s1479262120000222

Cited by 10 publications

(7 citation statements)

References 60 publications

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“…In the present study, the FarmCPU algorithm identified eight significant MTAs associated with stripe rust on chromosomes 2A, 2D, 5B, 6A, and 7A. Q.Yr.bisa-2A.3 on chromosome 2A at the physical position 753.3 Mb identified for YR resistance in this study was found in the vicinity of a Q.YrTd.pau.2A.2 mapped at 766.16 Mb by Dhillon et al (2020) . Another QTL mapped on chr2D ( Q.Yr.bisa-2D ) at a terminal end of 2DS was identified in the vicinity (∼70 Mb apart) of QYr.caas-2DS_Libellula ( Lu et al, 2009 ).…”

Section: Discussionsupporting

confidence: 49%

“…their possible functional roles in disease resistance. The genes identified were directly or indirectly involved in pathogenesis or plant-pathogen interaction ( Dhillon et al (2020). Another QTL mapped on chr2D (Q.Yr.bisa-2D) at a terminal end of 2DS was identified in the vicinity (∼70 Mb apart) of QYr.caas-2DS_Libellula (Lu et al, 2009).…”

Section: Candidate Resistance-associated Loci Identified By Genome-wide Association Studymentioning

confidence: 99%

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Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat (Triticum aestivum L.)

et al. 2021

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Stripe rust is one of the most destructive diseases of wheat (Triticum aestivum L.), caused by Puccinia striiformis f. sp. tritici (Pst), and responsible for significant yield losses worldwide. Single-nucleotide polymorphism (SNP) diagnostic markers were used to identify new sources of resistance at adult plant stage to wheat stripe rust (YR) in 141 CIMMYT advanced bread wheat lines over 3 years in replicated trials at Borlaug Institute for South Asia (BISA), Ludhiana. We performed a genome-wide association study and genomic prediction to aid the genetic gain by accumulating disease resistance alleles. The responses to YR in 141 advanced wheat breeding lines at adult plant stage were used to generate G × E (genotype × environment)-dependent rust scores for prediction and genome-wide association study (GWAS), eliminating variation due to climate and disease pressure changes. The lowest mean prediction accuracies were 0.59 for genomic best linear unbiased prediction (GBLUP) and ridge-regression BLUP (RRBLUP), while the highest mean was 0.63 for extended GBLUP (EGBLUP) and random forest (RF), using 14,563 SNPs and the G × E rust score results. RF and EGBLUP predicted higher accuracies (∼3%) than did GBLUP and RRBLUP. Promising genomic prediction demonstrates the viability and efficacy of improving quantitative rust tolerance. The resistance to YR in these lines was attributed to eight quantitative trait loci (QTLs) using the FarmCPU algorithm. Four (Q.Yr.bisa-2A.1, Q.Yr.bisa-2D, Q.Yr.bisa-5B.2, and Q.Yr.bisa-7A) of eight QTLs linked to the diagnostic markers were mapped at unique loci (previously unidentified for Pst resistance) and possibly new loci. The statistical evidence of effectiveness and distribution of the new diagnostic markers for the resistance loci would help to develop new stripe rust resistance sources. These diagnostic markers along with previously established markers would be used to create novel DNA biosensor-based microarrays for rapid detection of the resistance loci on large panels upon functional validation of the candidate genes identified in the present study to aid in rapid genetic gain in the future breeding programs.

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Section: Discussionsupporting

confidence: 49%

Section: Candidate Resistance-associated Loci Identified By Genome-wide Association Studymentioning

confidence: 99%

Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat (Triticum aestivum L.)

et al. 2021

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“…To counter the constraints from foliar diseases like SB, there is a need for constantly identifying and introgressing new sources of resistance. The DSBIL panel used in the present study showed wide range of variation for different traits and has already been reported to possess various QTLs for heat tolerance, stripe rust, and powdery mildew resistance (Awlachew et al, 2016;Dhillon et al, 2020). In the present study, during phenotypic evaluation of disease severity for SB, three DSBILs (DSBIL 13, 61, and 80) were identified to be highly resistant against SB.…”

Section: Discussionmentioning

confidence: 69%

Characterization and Mapping of Spot Blotch in Triticum durum–Aegilops speltoides Introgression Lines Using SNP Markers

Kaur

Dhillon

et al. 2021

Front. Plant Sci.

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Spot blotch (SB) of wheat is emerging as a major threat to successful wheat production in warm and humid areas of the world. SB, also called leaf blight, is caused by Bipolaris sorokiniana, and is responsible for high yield losses in Eastern Gangetic Plains Zone in India. More recently, SB is extending gradually toward cooler, traditional wheat-growing North-Western part of the country which is a major contributor to the national cereal basket. Deployment of resistant cultivars is considered as the most economical and ecologically sound measure to avoid losses due to this disease. In the present study, 89 backcross introgression lines (DSBILs) derived from Triticum durum (cv. PDW274-susceptible) × Aegilops speltoides (resistant) were evaluated against SB for four consecutive years, 2016–2020. Phenotypic evaluation of these lines showed a continuous variation in disease severity indicating that the resistance to SB is certainly quantitative in nature. Phenotypic data of DSBILs were further used for mapping QTLs using SNPs obtained by genotyping by sequencing. To identify QTLs stable across the environments, Best Linear Unbiased Estimates (BLUEs) and Predictions (BLUPs) were used for mapping QTLs based on stepwise regression-based Likelihood Ratio Test (RSTEP-LRT) for additive effect of markers and single marker analysis (SMA). Five QTLs, Q.Sb.pau-2A, Q.Sb.pau-2B, Q.Sb.pau-3B, Q.Sb.pau-5B, and Q.Sb.pau-6A, linked to SB resistance were mapped across chromosomes 2A, 2B, 3B, 5B, and 6A. Genes found adjacent to the SNP markers linked to these QTLs were literature mined to identify possible candidate genes by studying their role in plant pathogenesis. Further, highly resistant DSBIL (DSBIL-13) was selected to cross with a susceptible hexaploidy cultivar (HD3086) generating BC2F1 population. The QTL Q.Sb.pau-5B, linked to SNP S5B_703858864, was validated on this BC2F1 population and thus, may prove to be a potential diagnostic marker for SB resistance.

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“…Global climate change and ever-evolving pathogens are major causes of the reduction in crop production (Meehl and Tebaldi, 2004; Bebber et al ., 2013; Hua, 2013; Velásquez et al ., 2018; Dhillon et al ., 2020; Arora et al ., 2021). Temperature and rainfall fluctuations play a critical role in hindering successful crop cultivation (Dixon, 2012; Fischer and Knutti, 2015; Hatfield and Prueger, 2015; Dubey et al ., 2019, 2020; Sattar et al ., 2020).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Triticum durum–Aegilops tauschii derived primary synthetics as potential sources of heat stress tolerance for wheat improvement

Kaur

Chhuneja

Srivastava

et al. 2021

Plant Genet. Resour.

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Addressing the impact of heat stress during flowering and grain filling is critical to sustaining wheat productivity to meet a steadily increasing demand from a rapidly growing world population. Crop wild progenitor species of wheat possess a wealth of genetic diversity for several biotic and abiotic stresses, and morphological traits and can serve as valuable donors. The transfer of useful variation from the diploid progenitor, Aegilops tauschii, to hexaploid wheat can be done through the generation of synthetic hexaploid wheat (SHW). The present study targeted the identification of potential primary SHWs to introduce new genetic variability for heat stress tolerance. Selected SHWs were screened for different yield-associated traits along with three advanced breeding lines and durum parents as checks for assessing terminal heat stress tolerance under timely and late sown conditions for two consecutive seasons. Heat tolerance index based on the number of productive tillers and thousand grain weight indicated that three synthetics, syn9809 (64.32, 78.80), syn14128 (50.30, 78.28) and syn14135 (58.16, 76.03), were able to endure terminal heat stress better than other SHWs as well as checks. One of these synthetics, syn14128, recorded a minimum reduction in thousand kernel weight (21%), chlorophyll content (2.56%), grain width (1.07%) despite minimum grain-filling duration (36.15 d) and has been selected as a potential candidate for introducing the terminal heat stress tolerance in wheat breeding programmes. Breeding efforts using these candidate donors will help develop lines with a higher potential to express the desired heat stress-tolerant phenotype under field conditions.

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QTL mapping for stripe rust and powdery mildew resistance in Triticum durum–Aegilops speltoides backcross introgression lines

Cited by 10 publications

References 60 publications

Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat (Triticum aestivum L.)

Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat (Triticum aestivum L.)

Characterization and Mapping of Spot Blotch in Triticum durum–Aegilops speltoides Introgression Lines Using SNP Markers

Evaluation of Triticum durum–Aegilops tauschii derived primary synthetics as potential sources of heat stress tolerance for wheat improvement

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