Publications by authors named "Guihua Bai"

113 Publications

Multi-Locus Genome-Wide Association Studies to Characterize Fusarium Head Blight (FHB) Resistance in Hard Winter Wheat.

Front Plant Sci 2022 25;13:946700. Epub 2022 Jul 25.

Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, SD, United States.

Fusarium head blight (FHB), caused by the fungus Schwabe is an important disease of wheat that causes severe yield losses along with serious quality concerns. Incorporating the host resistance from either wild relatives, landraces, or exotic materials remains challenging and has shown limited success. Therefore, a better understanding of the genetic basis of native FHB resistance in hard winter wheat (HWW) and combining it with major quantitative trait loci (QTLs) can facilitate the development of FHB-resistant cultivars. In this study, we evaluated a set of 257 breeding lines from the South Dakota State University (SDSU) breeding program to uncover the genetic basis of native FHB resistance in the US hard winter wheat. We conducted a multi-locus genome-wide association study (ML-GWAS) with 9,321 high-quality single-nucleotide polymorphisms (SNPs). A total of six distinct marker-trait associations (MTAs) were identified for the FHB disease index (DIS) on five different chromosomes including 2A, 2B, 3B, 4B, and 7A. Further, eight MTAs were identified for Fusarium-damaged kernels (FDK) on six chromosomes including 3B, 5A, 6B, 6D, 7A, and 7B. Out of the 14 significant MTAs, 10 were found in the proximity of previously reported regions for FHB resistance in different wheat classes and were validated in HWW, while four MTAs represent likely novel loci for FHB resistance. Accumulation of favorable alleles of reported MTAs resulted in significantly lower mean DIS and FDK score, demonstrating the additive effect of FHB resistance alleles. Candidate gene analysis for two important MTAs identified several genes with putative proteins of interest; however, further investigation of these regions is needed to identify genes conferring FHB resistance. The current study sheds light on the genetic basis of native FHB resistance in the US HWW germplasm and the resistant lines and MTAs identified in this study will be useful resources for FHB resistance breeding marker-assisted selection.
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http://dx.doi.org/10.3389/fpls.2022.946700DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359313PMC
July 2022

Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits.

Theor Appl Genet 2022 Aug 8. Epub 2022 Aug 8.

Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.

Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, most of these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practical wheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs) were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by the breeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.
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http://dx.doi.org/10.1007/s00122-022-04160-6DOI Listing
August 2022

TaHRC suppresses the calcium-mediated immune response and triggers wheat head blight susceptibility.

Plant Physiol 2022 Jul 28. Epub 2022 Jul 28.

Department of Agronomy, Kansas State University, Manhattan, KS 66506, USA.

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http://dx.doi.org/10.1093/plphys/kiac352DOI Listing
July 2022

The Black Necrotic Lesion Enhanced Resistance in Wheat.

Front Plant Sci 2022 30;13:926621. Epub 2022 Jun 30.

State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, College of Agronomy, Shandong Agricultural University, Tai'an, China.

Fusarium head blight, mainly incited by , is a devastating wheat disease worldwide. Diverse Fusarium head blight (FHB) resistant sources have been reported, but the resistance mechanisms of these sources remain to be investigated. FHB-resistant wheat germplasm often shows black necrotic lesions (BNLs) around the infection sites. To determine the relationship between BNL and FHB resistance, leaf tissue of a resistant wheat cultivar Sumai 3 was inoculated with four different isolates. Integrated metabolomic and transcriptomic analyses of the inoculated samples suggested that the phytohormone signaling, phenolamine, and flavonoid metabolic pathways played important roles in BNL formation that restricted extension. Exogenous application of flavonoid metabolites on wheat detached leaves revealed the possible contribution of flavonoids to BNL formation. Exogenous treatment of either salicylic acid (SA) or methyl jasmonate (MeJA) on wheat spikes significantly reduced the FHB severity. However, exogenous MeJA treatment prevented the BNL formation on the detached leaves of FHB-resistant wheat Sumai 3. SA signaling pathway influenced reactive oxygen species (ROS) burst to enhance BNL formation to reduce FHB severity. Three key genes in SA biosynthesis and signal transduction pathway, , , and , positively regulated FHB resistance in wheat. A complex temporal interaction that contributed to wheat FHB resistance was detected between the SA and JA signaling pathways. Knowledge of BNLs extends our understanding of the molecular mechanisms of FHB resistance in wheat and will benefit the genetic improvement of wheat FHB resistance.
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http://dx.doi.org/10.3389/fpls.2022.926621DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280303PMC
June 2022

Identification and characterization of the novel leaf rust resistance gene Lr81 in wheat.

Theor Appl Genet 2022 Aug 18;135(8):2725-2734. Epub 2022 Jun 18.

USDA-ARS Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA.

Key Message: The novel, leaf rust seedling resistance gene, Lr81, was identified in a Croatian breeding line and mapped to a genomic region of less than 100 Kb on chromosome 2AS. Leaf rust, caused by Puccinia triticina, is the most common and widespread rust disease in wheat. Races of Puccinia triticina evolve rapidly in the southern Great Plains of the USA, and leaf rust resistance genes often lose effectiveness shortly after deployment in wheat production. PI 470121, a wheat breeding line developed by the University of Zagreb in Croatia, showed high resistance to Puccinia triticina races collected from Oklahoma, suggesting that PI 470121 could be a leaf rust resistance source for the southern Great Plains of the USA. Genetic analysis based on an F population and F families derived from the cross PI 470121 × Stardust indicated that PI 470121 carries a dominant seedling resistance gene, designated as Lr81. Linkage mapping delimited Lr81 to a genomic region of 96,148 bp flanked by newly developed KASP markers Xstars-KASP320 and Xstars-KASP323 on the short arm of chromosome 2A, spanning 67,030,206-67,132,354 bp in the Chinese Spring reference assembly (IWGSC RefSeq v1.0). Deletion bin mapping assigned Lr81 to the terminal bin 2AS-0.78-1.00. Allelism tests indicated that Lr81 is a distinctive leaf rust resistance locus with the physical order Lr65-Lr17-Lr81. Marker-assisted selection based on a set of markers closely linked to leaf rust resistance genes in PI 470121 and Stardust enabled identification of a recombinant inbred line RIL92 carrying Lr81 only. Lr81 is a valuable leaf rust resistance source that can be rapidly introgressed into locally adapted cultivars using KASP markers Xstars-KASP320 and Xstars-KASP323.
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http://dx.doi.org/10.1007/s00122-022-04145-5DOI Listing
August 2022

Redox-engineering enhances maize thermotolerance and grain yield in the field.

Plant Biotechnol J 2022 Jun 2. Epub 2022 Jun 2.

Department of Horticulture and Natural Resources, Kansas State University, Manhattan, KS, USA.

Increasing populations and temperatures are expected to escalate food demands beyond production capacities, and the development of maize lines with better performance under heat stress is desirable. Here, we report that constitutive ectopic expression of a heterologous glutaredoxin S17 from Arabidopsis thaliana (AtGRXS17) can provide thermotolerance in maize through enhanced chaperone activity and modulation of heat stress-associated gene expression. The thermotolerant maize lines had increased protection against protein damage and yielded a sixfold increase in grain production in comparison to the non-transgenic counterparts under heat stress field conditions. The maize lines also displayed thermotolerance in the reproductive stages, resulting in improved pollen germination and the higher fidelity of fertilized ovules under heat stress conditions. Our results present a robust and simple strategy for meeting rising yield demands in maize and, possibly, other crop species in a warming global environment.
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http://dx.doi.org/10.1111/pbi.13866DOI Listing
June 2022

Cloning of the broadly effective wheat leaf rust resistance gene Lr42 transferred from Aegilops tauschii.

Nat Commun 2022 06 1;13(1):3044. Epub 2022 Jun 1.

Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506-5502, USA.

The wheat wild relative Aegilops tauschii was previously used to transfer the Lr42 leaf rust resistance gene into bread wheat. Lr42 confers resistance at both seedling and adult stages, and it is broadly effective against all leaf rust races tested to date. Lr42 has been used extensively in the CIMMYT international wheat breeding program with resulting cultivars deployed in several countries. Here, using a bulked segregant RNA-Seq (BSR-Seq) mapping strategy, we identify three candidate genes for Lr42. Overexpression of a nucleotide-binding site leucine-rich repeat (NLR) gene AET1Gv20040300 induces strong resistance to leaf rust in wheat and a mutation of the gene disrupted the resistance. The Lr42 resistance allele is rare in Ae. tauschii and likely arose from ectopic recombination. Cloning of Lr42 provides diagnostic markers and over 1000 CIMMYT wheat lines carrying Lr42 have been developed documenting its widespread use and impact in crop improvement.
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http://dx.doi.org/10.1038/s41467-022-30784-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160033PMC
June 2022

Genetics of Fusarium head blight resistance in soft red winter wheat using a genome-wide association study.

Plant Genome 2022 May 28:e20222. Epub 2022 May 28.

Dep. of Plant Pathology, Univ. of Georgia, Griffin Campus, Griffin, GA, 30223, USA.

Host resistance is an effective and sustainable approach to manage the negative impact of Fusarium head blight (FHB) on wheat (Triticum aestivum L.) grain yield and quality. The objective of this study was to characterize the phenotypic responses and identify quantitative trait loci (QTL) conditioning different FHB resistance types using a panel of 236 elite soft red winter wheat (SRWW) lines in a genome-wide association study (GWAS). The panel was phenotyped for five FHB and three morphological traits under two field and two greenhouse environments in 2018-2019 and 2019-2020. We identified 160 significant marker-trait associations (MTAs) for FHB traits and 11 MTAs for plant height. Eleven QTL showed major effects and explained >10% phenotypic variation (PV) for FHB resistance. Among these major loci, three QTL were stable and five QTL exhibited a pleiotropic effect. The QTL QFhb-3BL, QFhb-5AS, QFhb-5BL, QFhb-7AS.1, QFhb-7AS.2, and QFhb-7BS are presumed to be novel. Pyramiding multiple resistance alleles from all the major-effect QTL resulted in a significant reduction in FHB incidence, severity, index, deoxynivalenol (DON), and Fusarium-damaged kernel (FDK) by 17, 43, 45, 55, and 25%, respectively. Further validation of these QTL could potentially facilitate successful introgression of these resistance loci in new cultivars for improved FHB resistance in breeding programs.
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http://dx.doi.org/10.1002/tpg2.20222DOI Listing
May 2022

Genotyping-by-Sequencing Based Molecular Genetic Diversity of Pakistani Bread Wheat ( L.) Accessions.

Front Genet 2022 6;13:772517. Epub 2022 Apr 6.

Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan.

Spring wheat ( L.) is one of the most imperative staple food crops, with an annual production of 765 million tons globally to feed ∼40% world population. Genetic diversity in available germplasm is crucial for sustainable wheat improvement to ensure global food security. A diversity panel of 184 Pakistani wheat accessions was genotyped using 123,596 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing with 42% of the SNPs mapped on B, 36% on A, and 22% on D sub-genomes of wheat. Chromosome 2B contains the most SNPs (9,126), whereas 4D has the least (2,660) markers. The mean polymorphic information content, genetic diversity, and major allele frequency of the population were 0.157, 0.1844, and 0.87, respectively. Analysis of molecular variance revealed a higher genetic diversity (80%) within the sub-population than among the sub-populations (20%). The genome-wide linkage disequilibrium was 0.34 Mbp for the whole wheat genome. Among the three subgenomes, A has the highest LD decay value (0.29 Mbp), followed by B (0.2 Mbp) and D (0.07 Mbp) genomes, respectively. The results of population structure, principal coordinate analysis, phylogenetic tree, and kinship analysis also divided the whole population into three clusters comprising 31, 33, and 120 accessions in group 1, group 2, and group 3, respectively. All groups were dominated by the local wheat accessions. Estimation of genetic diversity will be a baseline for the selection of breeding parents for mutations and the genome-wide association and marker-assisted selection studies.
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http://dx.doi.org/10.3389/fgene.2022.772517DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9019749PMC
April 2022

Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat.

BMC Genomics 2022 Apr 12;23(1):298. Epub 2022 Apr 12.

Department of Agronomy, 3105 McCarty Hall B, Gainesville, FL, 32611, USA.

Background: Recently genomic selection (GS) has emerged as an important tool for plant breeders to select superior genotypes. Multi-trait (MT) prediction model provides an opportunity to improve the predictive ability of expensive and labor-intensive traits. In this study, we assessed the potential use of a MT genomic prediction model by incorporating two physiological traits (canopy temperature, CT and normalized difference vegetation index, NDVI) to predict 5 complex primary traits (harvest index, HI; grain yield, GY; grain number, GN; spike partitioning index, SPI; fruiting efiiciency, FE) using two cross-validation schemes CV1 and CV2.

Results: In this study, we evaluated 236 wheat genotypes in two locations in 2 years. The wheat genotypes were genotyped with genotyping by sequencing approach which generated 27,466 SNPs. MT-CV2 (multi-trait cross validation 2) model improved predictive ability by 4.8 to 138.5% compared to ST-CV1(single-trait cross validation 1). However, the predictive ability of MT-CV1 was not significantly different compared to the ST-CV1 model.

Conclusions: The study showed that the genomic prediction of complex traits such as HI, GN, and GY can be improved when correlated secondary traits (cheaper and easier phenotyping) are used. MT genomic selection could accelerate breeding cycles and improve genetic gain for complex traits in wheat and other crops.
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http://dx.doi.org/10.1186/s12864-022-08487-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004054PMC
April 2022

Identification of a novel major QTL from Chinese wheat cultivar Ji5265 for Fusarium head blight resistance in greenhouse.

Theor Appl Genet 2022 Jun 31;135(6):1867-1877. Epub 2022 Mar 31.

College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100083, China.

Key Message: A novel major QTL for FHB resistance was mapped to a 6.8 Mb region on chromosome 2D in a Chinese wheat cultivar Ji5265, and diagnostic KASP markers were developed for detecting it in a worldwide wheat collection. Fusarium head blight (FHB) is a serious disease in wheat (Triticum aestivum L.) and causes significant reductions in grain yield and quality worldwide. Breeding for FHB resistance is the most effective strategy to minimize the losses caused by FHB; therefore, identification of major quantitative trait loci (QTLs) conferring FHB resistance and development of diagnostic markers for the QTLs are prerequisites for marker-assisted selection (MAS). Ji5265 is a Chinese wheat cultivar resistant to FHB in multiple environments. An F population of 179 recombinant inbred lines (RILs) was developed from Ji5265 × Wheaton. The population was genotyped by genotyping-by-sequencing (GBS) and phenotyped for FHB Type II resistance in greenhouses. A major QTL, designated as QFhb-2DL, was mapped in a 6.8 Mb region between the markers GBS10238 and GBS12056 on the long arm of chromosome 2D in Ji5265 and explained ~ 30% of the phenotypic variation for FHB resistance. The effect of QFhb-2DL on FHB resistance was validated using near-isogenic lines (NILs) derived from residual heterozygotes from an F RIL of Ji5265 × Wheaton. The two flanking markers were converted into Kompetitive allele-specific PCR (KASP) markers (KASP10238 and KASP12056) and validated to be diagnostic in a collection of 2,065 wheat accessions. These results indicate that QFhb-2DL is a novel major QTL for resistance to FHB spread within a spike (Type II) and the two KASP markers can be used for MAS to improve wheat FHB resistance in wheat breeding programs.
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http://dx.doi.org/10.1007/s00122-022-04080-5DOI Listing
June 2022

A natural variation in Ribonuclease H-like gene underlies Rht8 to confer "Green Revolution" trait in wheat.

Mol Plant 2022 03 19;15(3):377-380. Epub 2022 Jan 19.

State Key Laboratory for Agrobiotechnology and Key Laboratory of Crop Heterosis and Utilization (MOE) and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, China. Electronic address:

Rht8 is a gibberellin-sensitive Reduced height (Rht) locus that has been widely used in crop wheat semi-dwarfing breeding. In this study, the authors reported the map-based cloning of Rht8 candidate gene, and confirmed that loss of Ribonuclease H-Like 1 (RNHL-D1) is responsible for Rht8 semi-dwarfing effect.
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http://dx.doi.org/10.1016/j.molp.2022.01.013DOI Listing
March 2022

Development of the Wheat Practical Haplotype Graph database as a resource for genotyping data storage and genotype imputation.

G3 (Bethesda) 2022 02;12(2)

Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA.

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The Wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the Wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 92% imputation accuracy with 0.01× sequence coverage, which was slightly lower than the accuracy obtained using the 0.5× sequence coverage (96.6%). Compared to Beagle, on average, PHG imputation was ∼3.5% (P-value < 2 × 10-14) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. We found reduced accuracy of imputation with independent 2× GBS data (88.6%), which increases to 89.2% with the inclusion of parental haplotypes in the database. The accuracy reduction with GBS is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequilibrium and proportion of identity-by-descent regions among accessions in the PHG database. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.
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http://dx.doi.org/10.1093/g3journal/jkab390DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210282PMC
February 2022

Multi-Trait Multi-Environment Genomic Prediction of Agronomic Traits in Advanced Breeding Lines of Winter Wheat.

Front Plant Sci 2021 18;12:709545. Epub 2021 Aug 18.

Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, United States.

Genomic prediction is a promising approach for accelerating the genetic gain of complex traits in wheat breeding. However, increasing the prediction accuracy (PA) of genomic prediction (GP) models remains a challenge in the successful implementation of this approach. Multivariate models have shown promise when evaluated using diverse panels of unrelated accessions; however, limited information is available on their performance in advanced breeding trials. Here, we used multivariate GP models to predict multiple agronomic traits using 314 advanced and elite breeding lines of winter wheat evaluated in 10 site-year environments. We evaluated a multi-trait (MT) model with two cross-validation schemes representing different breeding scenarios (CV1, prediction of completely unphenotyped lines; and CV2, prediction of partially phenotyped lines for correlated traits). Moreover, extensive data from multi-environment trials (METs) were used to cross-validate a Bayesian multi-trait multi-environment (MTME) model that integrates the analysis of multiple-traits, such as G × E interaction. The MT-CV2 model outperformed all the other models for predicting grain yield with significant improvement in PA over the single-trait (ST-CV1) model. The MTME model performed better for all traits, with average improvement over the ST-CV1 reaching up to 19, 71, 17, 48, and 51% for grain yield, grain protein content, test weight, plant height, and days to heading, respectively. Overall, the empirical analyses elucidate the potential of both the MT-CV2 and MTME models when advanced breeding lines are used as a training population to predict related preliminary breeding lines. Further, we evaluated the practical application of the MTME model in the breeding program to reduce phenotyping cost using a sparse testing design. This showed that complementing METs with GP can substantially enhance resource efficiency. Our results demonstrate that multivariate GS models have a great potential in implementing GS in breeding programs.
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http://dx.doi.org/10.3389/fpls.2021.709545DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8416538PMC
August 2021

Precise mapping of QTL for Hessian fly resistance in the hard winter wheat cultivar 'Overland'.

Theor Appl Genet 2021 Dec 1;134(12):3951-3962. Epub 2021 Sep 1.

Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.

Key Message: A major QTL for Hessian fly resistance was precisely mapped to a 2.32 Mb region on chromosome 3B of the US hard winter wheat cultivar 'Overland'. The Hessian fly (HF, Mayetiola destructor) is a destructive insect pest of wheat in the USA and worldwide. Deploying HF-resistant cultivars is the most effective and economical approach to control this insect pest. A population of 186 recombinant inbred lines (RILs) was developed from 'Overland' × 'Overley' and phenotyped for responses to HF attack using the HF biotype 'Great Plains'. A high-density genetic linkage map was constructed using 1,576 single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). Two quantitative trait loci (QTLs) with a significant epistatic effect on HF resistance were mapped to chromosomes 3B (QHf.hwwg-3B) and 7A (QHf.hwwg-7A) in Overland, which are located in similar chromosome regions as found for H35 and H36 in the cultivar 'SD06165', respectively. QHf.hwwg-3B showed a much larger effect on HF resistance than QHf.hwwg-7A. Five and four GBS-SNPs, respectively, in the QHf.hwwg-3B and QHf.hwwg-7A QTL intervals were converted into Kompetitive allele specific polymerase chain reaction (KASP) markers. QHf.hwwg-3B was precisely mapped to a 2.32 Mb interval (2,479,314-4,799,538 bp) using near-isogenic lines (NILs) and RILs that have recombination within the QTL interval. The US winter wheat accessions carrying contrasting alleles at KASP markers KASP-3B4525164, KASP-7A47772047 and KASP-7A65090410 showed significant difference in HF resistance. The combination of the two KASP markers KASP-3B3797431 and KASP-3B4525164 is near-diagnostic for the detection of QHf.hwwg-3B in a US winter wheat panel and can be potentially used for screening the QTL in breeding programs.
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http://dx.doi.org/10.1007/s00122-021-03940-wDOI Listing
December 2021

Characterization of the genetic basis of local adaptation of wheat landraces from Iran and Pakistan using genome-wide association study.

Plant Genome 2021 11 18;14(3):e20096. Epub 2021 Jul 18.

Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), & CIMMYT-China office, 12 Zhongguancun South St., Beijing, 100081, China.

Characterization of genomic regions underlying adaptation of landraces can reveal a quantitative genetics framework for local wheat (Triticum aestivum L.) adaptability. A collection of 512 wheat landraces from the eastern edge of the Fertile Crescent in Iran and Pakistan were genotyped using genome-wide single nucleotide polymorphism markers generated by genotyping-by-sequencing. The minor allele frequency (MAF) and the heterozygosity (H) of Pakistani wheat landraces (MAF = 0.19, H = 0.008) were slightly higher than the Iranian wheat landraces (MAF = 0.17, H = 0.005), indicating that Pakistani landraces were slightly more genetically diverse. Population structure analysis clearly separated the Pakistani landraces from Iranian landraces, which indicates two separate adaptability trajectories. The large-scale agro-climatic data of seven variables were quite dissimilar between Iran and Pakistan as revealed by the correlation coefficients. Genome-wide association study identified 91 and 58 loci using agroclimatic data, which likely underpin local adaptability of the wheat landraces from Iran and Pakistan, respectively. Selective sweep analysis identified significant hits on chromosomes 4A, 4B, 6B, 7B, 2D, and 6D, which were colocalized with the loci associated with local adaptability and with some known genes related to flowering time and grain size. This study provides insight into the genetic diversity with emphasis on the genetic architecture of loci involved in adaptation to local environments, which has breeding implications.
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http://dx.doi.org/10.1002/tpg2.20096DOI Listing
November 2021

Expanding the range of editable targets in the wheat genome using the variants of the Cas12a and Cas9 nucleases.

Plant Biotechnol J 2021 12 28;19(12):2428-2441. Epub 2021 Jul 28.

Department of Plant Pathology, Kansas State University, Manhattan, KS, USA.

The development of CRISPR-based editors recognizing distinct protospacer-adjacent motifs (PAMs), or having different spacer length/structure requirements broadens the range of possible genomic applications. We evaluated the natural and engineered variants of Cas12a (FnCas12a and LbCas12a) and Cas9 for their ability to induce mutations in endogenous genes controlling important agronomic traits in wheat. Unlike FnCas12a, LbCas12a-induced mutations in the wheat genome, even though with a lower rate than that reported for SpCas9. The eight-fold improvement in the gene editing efficiency was achieved for LbCas12a by using the guides flanked by ribozymes and driven by the RNA polymerase II promoter from switchgrass. The efficiency of multiplexed genome editing (MGE) using LbCas12a was mostly similar to that obtained using the simplex RNA guides and showed substantial increase after subjecting transgenic plants to high-temperature treatment. We successfully applied LbCas12a-MGE for generating heritable mutations in a gene controlling grain size and weight in wheat. We showed that the range of editable loci in the wheat genome could be further expanded by using the engineered variants of Cas12a (LbCas12a-RVR) and Cas9 (Cas9-NG and xCas9) that recognize the TATV and NG PAMs, respectively, with the Cas9-NG showing higher editing efficiency on the targets with atypical PAMs compared to xCas9. In conclusion, our study reports a set of validated natural and engineered variants of Cas12a and Cas9 editors for targeting loci in the wheat genome not amenable to modification using the original SpCas9 nuclease.
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http://dx.doi.org/10.1111/pbi.13669DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633491PMC
December 2021

High-resolution genome-wide association study and genomic prediction for disease resistance and cold tolerance in wheat.

Theor Appl Genet 2021 Sep 1;134(9):2857-2873. Epub 2021 Jun 1.

State Key Laboratory of Crop Biology, College of Agronomy, Shandong Agricultural University, Tai'an 271018, China.

Key Message: High-resolution genome-wide association study (GWAS) facilitated QTL fine mapping and candidate gene identification, and the GWAS based genomic prediction models were highly predictive and valuable in wheat genomic breeding. Wheat is a major staple food crop and provides more than one-fifth of the daily calories and dietary proteins for humans. Genome-wide association study (GWAS) and genomic selection (GS) for wheat stress resistance and tolerance related traits are critical to understanding their genetic architecture for improvement of breeding selection efficiency. However, the insufficient marker density in previous studies limited the utility of GWAS and GS in wheat genomic breeding. Here, we conducted a high-resolution GWAS for wheat leaf rust (LR), yellow rust (YR), powdery mildew (PM), and cold tolerance (CT) by genotyping a panel of 768 wheat cultivars using genotyping-by-sequencing. Among 153 quantitative trait loci (QTLs) identified, 81 QTLs were delimited to ≤ 1.0 Mb intervals with three validated using bi-parental populations. Furthermore, 837 stress resistance-related genes were identified in the QTL regions with 12 showing induced expression by YR and PM pathogens. Genomic prediction using 2608, 4064, 3907, and 2136 pre-selected SNPs based on GWAS and genotypic correlations between the SNPs showed high prediction accuracies of 0.76, 0.73, and 0.78 for resistance to LR, YR, and PM, respectively, and 0.83 for resistance to cold damage. Our study laid a solid foundation for large-scale QTL fine mapping, candidate gene validation and GS in wheat.
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http://dx.doi.org/10.1007/s00122-021-03863-6DOI Listing
September 2021

Characterization of wheat curl mite resistance gene Cmc4 in OK05312.

Theor Appl Genet 2021 Apr 19;134(4):993-1005. Epub 2021 Feb 19.

Department of Agronomy, Kansas State University, 2004 Throckmorton Hall, Manhattan, KS, 66506, USA.

Key Message: Cmc4, a wheat curl mite resistance gene, was delimited to a 523 kb region and a diagnostic marker haplotype was identified for selecting Cmc4 in breeding programs. Wheat curl mite (WCM, Aceria tosichella Keifer) is a disastrous wheat pest in many wheat-growing regions worldwide. WCM not only directly affects wheat yield, but also transmits wheat streak mosaic virus. Growing WCM resistant cultivars is the most economical and sustainable method to reduce its damage. A hard winter wheat breeding line OK05312 (PI 670019) carries Cmc4 gene resistance to A. tosichella and has many desirable agronomic traits. To finely map Cmc4 in OK05312, two recombinant inbred line populations were developed from crosses between OK05312 and two susceptible cultivars, SD06165 and Jerry, genotyped using single nucleotide polymorphism (SNP) markers generated from genotyping-by-sequencing (GBS), and phenotyped for WCM resistance. Gene mapping using the two SNP maps confirmed Cmc4 in OK05312 that explained up to 68% of the phenotypic variation. Further analysis delimited Cmc4 to a ~ 523 kb region between SNPs SDOKSNP6314 and SDOKSNP2805 based on the Ae. tauschii reference genome. We developed 18 polymorphic Kompetitive Allele Specific PCR (KASP) markers using the sequences of GBS-SNPs in this region and 23 additional KASP markers based on the SNPs between the parents derived from 90K SNP chips. The KASP markers SDOKSNP6314 and SDOKSNP9699 are closest to Cmc4 and can be used to diagnose the presence of Cmc4 in wheat breeding programs. Haplotype analysis suggested that Cmc in TAM112 might be the same gene as Cmc4.
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http://dx.doi.org/10.1007/s00122-020-03737-3DOI Listing
April 2021

Artificial selection in breeding extensively enriched a functional allelic variation in TaPHS1 for pre-harvest sprouting resistance in wheat.

Theor Appl Genet 2021 Jan 17;134(1):339-350. Epub 2020 Oct 17.

Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.

Pre-harvest sprouting (PHS) causes significant losses in wheat yield and quality worldwide. Previously, we cloned a PHS resistance gene, TaPHS1, and identified two causal mutations for reduced seed dormancy (SD) and increased PHS susceptibility. Here we identified a novel allelic variation of C to T transition in 3'-UTR of TaPHS1, which associated with reduced SD and PHS resistance. The T allele occurred in wild wheat progenitors and was likely the earliest functional mutation in TaPHS1 for PHS susceptibility. Allele frequency analysis revealed low frequency of the T allele in wild diploid and tetraploid wheat progenitors, but very high frequency in modern wheat cultivars and breeding lines, indicating that artificial selection quickly enriched the T allele during modern breeding. The T allele was significantly associated with short SD in both T. aestivum and T. durum, the two most cultivated species of wheat. This variation together with previously reported functional sequence variations co-regulated TaPHS1 expression levels and PHS resistance in different germplasms. Haplotype analysis of the four functional variations identified the best PHS resistance haplotype of TaPHS1. The resistance haplotype can be used in marker-assisted selection to transfer TaPHS1 to new wheat cultivars.
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http://dx.doi.org/10.1007/s00122-020-03700-2DOI Listing
January 2021

Genetic Diversity, Population Structure, and Linkage Disequilibrium of Pearl Millet.

Plant Genome 2019 11;12(3):1-12

Kansas State Univ., Agricultural Research Center-Hays, Hays, 1232 240th Avenue, Hays, KS, 67601, USA.

Core Ideas: Mapping of GBS reads of 398 accessions to the draft genome sequence identified 82,112 SNPs Model-based clustering analysis revealed a hierarchical genetic structure of six subgroups Greater LD decay in the west-African subpopulation is likely due to long history of recombination Genetic differentiation analysis among subpopulations revealed variation in selection signatures Pearl millet [Cenchrus americanus (L.) Morrone syn. Pennisetum glaucum (L.) R. Br.] is one of the most extensively cultivated cereals in the world, after wheat (Triticum aestivum L.), maize (Zea mays L.), rice (Oryza sativa L.), barley (Hordeum vulgare L.), and sorghum [Sorghum bicolor (L.) Moench]. It is the main component of traditional farming systems and a staple food in the arid and semiarid regions of Africa and southern Asia. However, its genetic improvement is lagging behind other major cereals and the yield is still low. Genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers were screened on a total of 398 accessions from different geographic regions to assess genetic diversity, population structure, and linkage disequilibrium (LD). By mapping the GBS reads to the reference genome sequence, 82,112 genome-wide SNPs were discovered. The telomeric regions of the chromosomes have the higher SNP density than in pericentromeric regions. Model-based clustering analysis of the population revealed a hierarchical genetic structure of six subgroups that mostly overlap with the geographic origins or sources of the genotypes but with differing levels of admixtures. A neighbor-joining phylogeny analysis revealed that germplasm from western Africa rooted the dendrogram with much diversity within each subgroup. Greater LD decay was observed in the west-African subpopulation than in the other subpopulations, indicating a long history of recombination among landraces. Also, genome scan of genetic differentiatation detected different selection histories among subpopulations. These results have potential application in the development of genomic-assisted breeding in pearl millet and heterotic grouping of the lines for improved hybrid performance.
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http://dx.doi.org/10.3835/plantgenome2018.11.0091DOI Listing
November 2019

Characterization of an Incomplete Leaf Rust Resistance Gene on Chromosome 1RS and Development of KASP Markers for in Wheat.

Phytopathology 2021 Apr 24;111(4):649-658. Epub 2021 Mar 24.

Kansas State University, Department of Plant Pathology, Manhattan, KS 66506.

Leaf rust, caused by , is one of the most common wheat () diseases in the Great Plains of the United States. A population of recombinant inbred lines from CI 17884 × 'Bainong 418' was evaluated for responses to leaf rust race - and genotyped using single nucleotide polymorphism (SNP) markers. Quantitative trait locus analysis identified a minor gene for resistance to leaf rust, designated .-, on the 1BL.1RS translocation segment in 'Bainong 418', and another leaf rust resistance gene, , on chromosome 7A of CI 17884. , originally identified in CI 17884 and located in a wheat-. translocation segment 7S#1S, remains one of only a few race-specific resistance genes still effective in the Great Plains. A set of 7A-specific simple sequence repeat markers were developed and used to genotype CI 17884 and a pair of near-isogenic lines differing in the presence or absence of 7S#1S, PI 603918, and 'Pavon F76'. Haplotype analysis indicated that the estimated length of 7S#1S was 157.23 to 174.42 Megabases, accounting for ∼23% of the 7A chromosome. Two SNPs on 7S#1S and four SNPs on the 1RS chromosome arm were converted to Kompetitive allele-specific PCR (KASP) markers, which were subsequently validated in a panel of cultivars and elite breeding lines released within the last decade. Of these, one- and two-KASP markers are specific to the 1RS chromosome arm and 7S#1S, respectively, indicating that they can facilitate the introgression of and .- into locally adapted wheat cultivars and breeding lines.
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http://dx.doi.org/10.1094/PHYTO-07-20-0308-RDOI Listing
April 2021

High-Resolution Genome-wide Association Study Identifies Genomic Regions and Candidate Genes for Important Agronomic Traits in Wheat.

Mol Plant 2020 09 20;13(9):1311-1327. Epub 2020 Jul 20.

State Key Laboratory of Crop Biology, College of Agronomy, Shandong Agricultural University, Tai'an 271018, China. Electronic address:

Wheat (Triticum aestivum) is a major staple food crop worldwide. Genetic dissection of important agronomic traits is essential for continuous improvement of wheat yield to meet the demand of the world's growing population. We conducted a large-scale genome-wide association study (GWAS) using a panel of 768 wheat cultivars that were genotyped with 327 609 single-nucleotide polymorphisms generated by genotyping-by-sequencing and detected 395 quantitative trait loci (QTLs) for 12 traits under 7 environments. Among them, 273 QTLs were delimited to ≤1.0-Mb intervals and 7 of them are either known genes (Rht-D, Vrn-B1, and Vrn-D1) that have been cloned or known QTLs (TaGA2ox8, APO1, TaSus1-7B, and Rht12) that were previously mapped. Eight putative candidate genes were identified for three QTLs that enhance spike seed setting and grain size using gene expression data and were validated in three bi-parental populations. Protein sequence analysis identified 33 putative wheat orthologs that have high identity with rice genes in QTLs affecting similar traits. Large r values for additive effects observed among the QTLs for most traits indicated that the phenotypes of these identified QTLs were highly predictable. Results from this study demonstrated that significantly increasing GWAS population size and marker density greatly improves detection and identification of candidate genes underlying a QTL, solidifying the foundation for large-scale QTL fine mapping, candidate gene validation, and developing functional markers for genomics-based breeding in wheat.
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http://dx.doi.org/10.1016/j.molp.2020.07.008DOI Listing
September 2020

Genomic diversity in pearl millet inbred lines derived from landraces and improved varieties.

BMC Genomics 2020 Jul 8;21(1):469. Epub 2020 Jul 8.

Hard Winter Wheat Genetics Research Unit, USDA-ARS, Manhattan, KS, USA.

Background: Genetic improvement of pearl millet is lagging behind most of the major crops. Development of genomic resources is expected to expedite breeding for improved agronomic traits, stress tolerance, yield, and nutritional quality. Genotyping a breeding population with high throughput markers enables exploration of genetic diversity, population structure, and linkage disequilibrium (LD) which are important preludes for marker-trait association studies and application of genomic-assisted breeding.

Results: Genotyping-by-sequencing (GBS) libraries of 309 inbred lines derived from landraces and improved varieties from Africa and India generated 54,770 high quality single nucleotide polymorphism (SNP) markers. On average one SNP per 29 Kb was mapped in the reference genome, with the telomeric regions more densely mapped than the pericentromeric regions of the chromosomes. Population structure analysis using 30,208 SNPs evenly distributed in the genome divided 309 accessions into five subpopulations with different levels of admixture. Pairwise genetic distance (GD) between accessions varied from 0.09 to 0.33 with the average distance of 0.28. Rapid LD decay implied low tendency of markers inherited together. Genetic differentiation estimates were the highest between subgroups 4 and 5, and the lowest between subgroups 1 and 2.

Conclusions: Population genomic analysis of pearl millet inbred lines derived from diverse geographic and agroecological features identified five subgroups mostly following pedigree differences with different levels of admixture. It also revealed the prevalence of high genetic diversity in pearl millet, which is very useful in defining heterotic groups for hybrid breeding, trait mapping, and holds promise for improving pearl millet for yield and nutritional quality. The short LD decay observed suggests an absence of persistent haplotype blocks in pearl millet. The diverse genetic background of these lines and their low LD make this set of germplasm useful for traits mapping.
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http://dx.doi.org/10.1186/s12864-020-06796-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341570PMC
July 2020

The Hessian fly recessive resistance gene h4 mapped to chromosome 1A of the wheat cultivar 'Java' using genotyping-by-sequencing.

Theor Appl Genet 2020 Oct 2;133(10):2927-2935. Epub 2020 Jul 2.

Department of Agronomy, Kansas State University, 2004 Throckmorton Hall, Manhattan, KS, 66506, USA.

Key Message: The recessive Hessian fly resistance gene h4 and flanking SNP markers were located to a 642 kb region in chromosome 1A of the wheat cultivar 'Java.' Hessian fly (HF), Mayetiola destructor, is one of the most destructive insect pests in wheat worldwide. The wheat cultivar 'Java' was reported to carry a recessive gene (h4) for HF resistance; however, its chromosome location has not been determined. To map the HF resistance gene in Java, two populations of recombinant inbred lines (RILs) were developed from 'Bobwhite' × Java and 'Overley' × Java, respectively, and were phenotyped for responses to infestation of HF Great Plains biotype. Analysis of phenotypic data from the F and the RIL populations confirmed that one recessive gene conditioned HF resistance in Java. Two linkage maps were constructed using single-nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The h4 gene was mapped to the distal end of the short arm of chromosome 1A, which explained 60.4 to 70.5% of the phenotypic variation for HF resistance in the two populations. The GBS-SNPs in the h4 candidate interval were converted into Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) markers to eliminate the missing data points in GBS-SNPs. Using the revised maps with KASP markers, h4 was further located to a 642 kb interval (6,635,984-7,277,935 bp). The two flanking KASP markers, KASP3299 and KASP1871, as well as four other closely linked KASP markers, may be useful for pyramiding h4 with other HF resistance genes in breeding.
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http://dx.doi.org/10.1007/s00122-020-03642-9DOI Listing
October 2020

Development of an Evaluation System for Resistance in Wheat Grains and Its Application in Assessment of the Corresponding Effects of .

Plant Dis 2020 Aug 8;104(8):2210-2216. Epub 2020 Jun 8.

Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Yangzhou University, Yangzhou 225009, China.

Fusarium head blight (FHB) caused by species is a globally important wheat disease. Host resistance to FHB is composed of multiple mechanisms, including resistance to initial infection (type I), disease spread (type II), toxin accumulation (type III), kernel infection (type IV), and yield loss (type V), of which the last three have been less studied. Traditionally, the -damaged kernel rate (FDK; percentage of -infected grains) from point- or spray-inoculated experiments was used as the parameter for type IV resistance, which may be problematic because of the influence of type II resistance. Here we propose a new definition for type IV resistance: that is, the resistance against infection expressed in wheat grains that have the same chance in contact with the pathogen, under favorable temperature and humidity for infection. confers strong type II resistance, leading to significantly reduced FHB severity and FDK. To investigate the role of in type IV resistance, a pair of near-isogenic lines, R22W ( carrier, resistant in terms of type II resistance) and S22V (non-, susceptible), along with eight wheat genotypes differing at were inoculated at different grain development stages with macrospores both in vivo and in vitro. The in vivo experiments with all florets inoculated demonstrated a significant reduction in thousand kernel weight (TKW) in inoculated grains, regardless of their status and developmental stages. Surprisingly, R22W showed more TKW reduction than S22V, which was supported by the scanning electron microscopy observation that confirmed the more severe degradation of starch granules in R22W grains. The in vitro experiments demonstrated that grains from both R22W and S22V promoted fungal colonization, but no significant difference was found between the two lines. In summary, our results indicated that the proposed type IV evaluation system is effective in determining different grain resistance levels, providing novel tools for FHB resistance breeding. The finding that is not associated with type IV resistance enriches our understanding of this gene.
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http://dx.doi.org/10.1094/PDIS-12-19-2584-REDOI Listing
August 2020

Identification of two novel Hessian fly resistance genes H35 and H36 in a hard winter wheat line SD06165.

Theor Appl Genet 2020 Aug 20;133(8):2343-2353. Epub 2020 May 20.

Department of Agronomy, Kansas State University, 2004 Throckmorton Hall, Manhattan, KS, 66506, USA.

Key Message: Two new Hessian fly resistance QTLs (H35 and H36) and tightly linked SNP markers were identified in a US hard winter wheat SD06165. Hessian fly (HF), Mayetiola destructor (Say), is one of the most destructive pests in wheat (Triticum aestivum L.) worldwide. Growing resistant cultivars is the most effective approach to minimize Hessian fly damage. To identify new quantitative trait loci (QTLs) for HF resistance, a recombinant inbred line population was developed by crossing HF resistant wheat line SD06165 to a susceptible line OK05312. The population was genotyped with 1709 single-nucleotide polymorphisms (SNPs) generated from genotyping-by-sequencing and phenotyped for HF resistance in greenhouses. Two novel QTLs for HF resistance were identified from SD06165. The major QTL, designated as H35, was closely linked to SNP marker SDOKSNP7679 on chromosome 3BS that explained 23.8% and 36.0% of the phenotypic variations; the minor QTL, designated as H36, was flanked by SNP markers SDOKSNP1618 and SDOKSNP8089 on chromosome 7AS and explained 8.5% and 13.1% of the phenotypic variation in the two experiments. Significant interaction was detected between the two QTLs. Seventeen SNPs that tightly link to H35 and eight SNPs that tightly link to H36 were converted to kompetitive allele specific polymerase chain reaction markers for selecting these QTLs in breeding programs.
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http://dx.doi.org/10.1007/s00122-020-03602-3DOI Listing
August 2020
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