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Kaur B, Bai BK, Dhillon GS, Kaur J, Sharma A, Srivastava P, Chhuneja P, Kaur S. Mapping of Aegilops speltoides derived leaf rust and stripe rust resistance genes using 35K SNP array. BMC Genom Data 2024; 25:69. [PMID: 39009972 PMCID: PMC11247808 DOI: 10.1186/s12863-024-01247-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 06/19/2024] [Indexed: 07/17/2024] Open
Abstract
Wheat is an essential food commodity cultivated throughout the world. However, this crop faces continuous threats from fungal pathogens, leaf rust (LR) and stripe rust (YR). To continue feeding the growing population, these major destructors of wheat must be effectively countered by enhancing the genetic diversity of cultivated germplasm. In this study, an introgression line with hexaploid background (ILsp3603) carrying resistance against Pt pathotypes 77-5 (121R63-1), 77-9 (121R60-1) and Pst pathotypes 46S119 (46E159), 110S119 (110E159), 238S119 (238E159) was developed from donor wheat wild progenitor, Aegilops speltoides acc pau 3603. To understand the genetic basis of resistance and map these genes (named Lrsp3603 and Yrsp3603), inheritance studies were carried out in F6 and F7 mapping population, developed by crossing ILsp3603 with LR and YR susceptible cultivar WL711, which revealed a monogenic (single gene) inheritance pattern for each of these traits. Bulk segregant analysis combined with 35 K Axiom SNP array genotyping mapped both genes as separate entities on the short arm of chromosome 6B. A genetic linkage map, comprising five markers, 1 SNP, 1 PLUG and three gene based SSRs, covered a genetic distance of 12.65 cM. Lrsp3603 was flanked by markers Tag-SSR14 (located proximally at 2.42 cM) and SNP AX-94542331 (at 3.28 cM) while Yrsp3603 was mapped at one end closest to AX-94542331 at 6.62 cM distance. Functional annotation of Lrsp3603 target region (∼ 1 Mbp) revealed 10 gene IDs associated with disease resistance mechanisms including three encoding typical R gene domains.
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Affiliation(s)
- Balihar Kaur
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, 141004, India
| | - Bukke Kutti Bai
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, 141004, India
| | | | - Jaspal Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, India
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, India
| | - Parveen Chhuneja
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, 141004, India
| | - Satinder Kaur
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, 141004, India.
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Vasistha NK, Sharma V, Singh S, Kaur R, Kumar A, Ravat VK, Kumar R, Gupta PK. Meta-QTL analysis and identification of candidate genes for multiple-traits associated with spot blotch resistance in bread wheat. Sci Rep 2024; 14:13083. [PMID: 38844568 PMCID: PMC11156910 DOI: 10.1038/s41598-024-63924-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 06/03/2024] [Indexed: 06/09/2024] Open
Abstract
In bread wheat, a literature search gave 228 QTLs for six traits, including resistance against spot blotch and the following five other related traits: (i) stay green; (ii) flag leaf senescence; (iii) green leaf area duration; (iv) green leaf area of the main stem; and (v) black point resistance. These QTLs were used for metaQTL (MQTL) analysis. For this purpose, a consensus map with 72,788 markers was prepared; 69 of the above 228 QTLs, which were suitable for MQTL analysis, were projected on the consensus map. This exercise resulted in the identification of 16 meta-QTLs (MQTLs) located on 11 chromosomes, with the PVE ranging from 5.4% (MQTL7) to 21.8% (MQTL5), and the confidence intervals ranging from 1.5 to 20.7 cM (except five MQTLs with a range of 36.1-57.8 cM). The number of QTLs associated with individual MQTLs ranged from a maximum of 17 in MQTL3 to 8 each in MQTL5 and MQTL8 and 5 each in MQTL7 and MQTL14. The 16 MQTLs, included 12 multi-trait MQTLs; one of the MQTL also overlapped a genomic region carrying the major spot blotch resistance gene Sb1. Of the total 16 MQTLs, 12 MQTLs were also validated through marker-trait associations that were available from earlier genome-wide association studies. The genomic regions associated with MQTLs were also used for the identification of candidate genes (CGs) and led to the identification of 516 CGs encoding 508 proteins; 411 of these proteins are known to be associated with resistance against several biotic stresses. In silico expression analysis of CGs using transcriptome data allowed the identification of 71 differentially expressed CGs, which were examined for further possible studies. The findings of the present study should facilitate fine-mapping and cloning of genes, enabling Marker Assisted Selection.
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Affiliation(s)
- Neeraj Kumar Vasistha
- Department of Genetics and Plant Breeding, Rajiv Gandhi University, Rono Hills, Itanagar, India
- Department of Genetics-Plant Breeding and Biotechnology, Dr K. S. Gill, Akal College of Agriculture, Eternal University, Baru Sahib, Sirmour, India
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India
| | - Vaishali Sharma
- Department of Genetics-Plant Breeding and Biotechnology, Dr K. S. Gill, Akal College of Agriculture, Eternal University, Baru Sahib, Sirmour, India
| | - Sahadev Singh
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India
- Meerut Institute of Technology, NH-58 Baral Partapur Bypass Road, Meerut, India
| | - Ramandeep Kaur
- Department of Genetics-Plant Breeding and Biotechnology, Dr K. S. Gill, Akal College of Agriculture, Eternal University, Baru Sahib, Sirmour, India
| | - Anuj Kumar
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India
| | - Vikas Kumar Ravat
- Department of Plant Pathology, Rajiv Gandhi University, Rono Hills, Itanagar, India
| | - Rahul Kumar
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India
| | - Pushpendra K Gupta
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India.
- Murdoch's Centre for Crop and Food Innovation, Murdoch University, Murdoch, WA, Australia.
- Borlaug Institute for South Asia (BISA), National Agricultural Science Complex (NASC), Dev Prakash Shastri (DPS) Marg, New Delhi, India.
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Singh S, Gaurav SS, Vasistha NK, Kumar U, Joshi AK, Mishra VK, Chand R, Gupta PK. Genetics of spot blotch resistance in bread wheat ( Triticum aestivum L.) using five models for GWAS. FRONTIERS IN PLANT SCIENCE 2023; 13:1036064. [PMID: 36743576 PMCID: PMC9891466 DOI: 10.3389/fpls.2022.1036064] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 12/28/2022] [Indexed: 06/18/2023]
Abstract
Genetic architecture of resistance to spot blotch in wheat was examined using a Genome-Wide Association Study (GWAS) involving an association panel comprising 303 diverse genotypes. The association panel was evaluated at two different locations in India including Banaras Hindu University (BHU), Varanasi (Uttar Pradesh), and Borlaug Institute for South Asia (BISA), Pusa, Samastipur (Bihar) for two consecutive years (2017-2018 and 2018-2019), thus making four environments (E1, BHU 2017-18; E2, BHU 2018-19; E3, PUSA, 2017-18; E4, PUSA, 2018-19). The panel was genotyped for 12,196 SNPs based on DArT-seq (outsourced to DArT Ltd by CIMMYT); these SNPs included 5,400 SNPs, which could not be assigned to individual chromosomes and were therefore, described as unassigned by the vendor. Phenotypic data was recorded on the following three disease-related traits: (i) Area Under Disease Progress Curve (AUDPC), (ii) Incubation Period (IP), and (iii) Lesion Number (LN). GWAS was conducted using each of five different models, which included two single-locus models (CMLM and SUPER) and three multi-locus models (MLMM, FarmCPU, and BLINK). This exercise gave 306 MTAs, but only 89 MTAs (33 for AUDPC, 30 for IP and 26 for LN) including a solitary MTA detected using all the five models and 88 identified using four of the five models (barring SUPER) were considered to be important. These were used for further analysis, which included identification of candidate genes (CGs) and their annotation. A majority of these MTAs were novel. Only 70 of the 89 MTAs were assigned to individual chromosomes; the remaining 19 MTAs belonged to unassigned SNPs, for which chromosomes were not known. Seven MTAs were selected on the basis of minimum P value, number of models, number of environments and location on chromosomes with respect to QTLs reported earlier. These 7 MTAs, which included five main effect MTAs and two for epistatic interactions, were considered to be important for marker-assisted selection (MAS). The present study thus improved our understanding of the genetics of resistance against spot blotch in wheat and provided seven MTAs, which may be used for MAS after due validation.
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Affiliation(s)
- Sahadev Singh
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
| | - Shailendra Singh Gaurav
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
| | - Neeraj Kumar Vasistha
- Department of Genetics-Plant Breeding and Biotechnology, Dr Khem Singh Gill, Akal College of Agriculture, Eternal University, Sirmaur, India
| | - Uttam Kumar
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Arun Kumar Joshi
- The International Maize and Wheat Improvement Center (CIMMYT), Borlaug Institute for South Asia (BISA), G-2, B-Block, NASC Complex, DPS Marg, New Delhi, India
| | - Vinod Kumar Mishra
- Department of Genetics and Plant Breeding, Indian Institute of Agricultural Science, Banaras Hindu University, Varanasi, India
| | - Ramesh Chand
- Department of Mycology and Plant Pathology, Indian Institute of Agricultural Science Banaras Hindu University, Varanasi, India
| | - Pushpendra Kumar Gupta
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
- Borlaug Institute for South Asia (BISA), Ludhiana, India
- Murdoch’s Centre for Crop & Food Innovation, Murdoch University, Murdoch, WA, Australia
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Luan P, Yi Y, Huang Y, Cui L, Hou Z, Zhu L, Ren X, Jia S, Liu Y. Biocontrol potential and action mechanism of Bacillus amyloliquefaciens DB2 on Bipolaris sorokiniana. Front Microbiol 2023; 14:1149363. [PMID: 37125175 PMCID: PMC10135310 DOI: 10.3389/fmicb.2023.1149363] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 03/16/2023] [Indexed: 05/02/2023] Open
Abstract
Introduction Bipolaris sorokiniana is the popular pathogenic fungi fungus which lead to common root rot and leaf spot on wheat. Generally, chemical fungicides are used to control diseases. However, the environmental pollution resulting from fungicides should not be ignored. It is important to study the mode of antagonistic action between biocontrol microbes and plant pathogens to design efficient biocontrol strategies. Results An antagonistic bacterium DB2 was isolated and identified as Bacillus amyloliquefaciens. The inhibition rate of cell-free culture filtrate (CF, 20%, v/v) of DB2 against B. sorokiniana reached 92.67%. Light microscopy and scanning electron microscopy (SEM) showed that the CF significantly altered the mycelial morphology of B. sorokiniana and disrupted cellular integrity. Fluorescence microscopy showed that culture filtrate destroyed mycelial cell membrane integrity, decreased the mitochondrial transmembrane potential, induced reactive oxygen species (ROS) accumulation, and nuclear damage which caused cell death in B. sorokiniana. Moreover, the strain exhibited considerable production of protease and amylase, and showed a significant siderophore and indole-3-acetic acid (IAA) production. In the detached leaves and potted plants control assay, B. amyloliquefacien DB2 had remarkable inhibition activity against B. sorokiniana and the pot control efficacy was 75.22%. Furthermore, DB2 suspension had a significant promotion for wheat seedlings growth. Conclusion B. amyloliquefaciens DB2 can be taken as a potential biocontrol agent to inhibit B. sorokiniana on wheat and promote wheat growth.
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Affiliation(s)
- Pengyu Luan
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
| | - Yanjie Yi
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
- *Correspondence: Yanjie Yi,
| | - Yifan Huang
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
| | - Liuqing Cui
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
| | - Zhipeng Hou
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
| | - Lijuan Zhu
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
| | - Xiujuan Ren
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
| | - Shao Jia
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
| | - Yang Liu
- School of Biological Engineering, Henan University of Technology, Zhengzhou, China
- Key Laboratory of Functional Molecules for Biomedical Research, Zhengzhou, China
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Navathe S, Pandey AK, Sharma S, Chand R, Mishra VK, Kumar D, Jaiswal S, Iquebal MA, Govindan V, Joshi AK, Singh PK. New Genomic Regions Identified for Resistance to Spot Blotch and Terminal Heat Stress in an Interspecific Population of Triticum aestivum and T. spelta. PLANTS (BASEL, SWITZERLAND) 2022; 11:2987. [PMID: 36365440 PMCID: PMC9657703 DOI: 10.3390/plants11212987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 10/28/2022] [Accepted: 11/03/2022] [Indexed: 06/16/2023]
Abstract
Wheat is one of the most widely grown and consumed food crops in the world. Spot blotch and terminal heat stress are the two significant constraints mainly in the Indo-Gangetic plains of South Asia. The study was undertaken using 185 recombinant lines (RILs) derived from the interspecific hybridization of 'Triticum aestivum (HUW234) × T. spelta (H+26)' to reveal genomic regions associated with tolerance to combined stress to spot blotch and terminal heat. Different physiological (NDVI, canopy temperature, leaf chlorophyll) and grain traits (TGW, grain size) were observed under stressed (spot blotch, terminal heat) and non-stressed environments. The mean maturity duration of RILs under combined stress was reduced by 12 days, whereas the normalized difference vegetation index (NDVI) was 46.03%. Similarly, the grain size was depleted under combined stress by 32.23% and thousand kernel weight (TKW) by 27.56% due to spot blotch and terminal heat stress, respectively. The genetic analysis using 6734 SNP markers identified 37 significant loci for the area under the disease progress curve (AUDPC) and NDVI. The genome-wide functional annotation of the SNP markers revealed gene functions such as plant chitinases, NB-ARC and NBS-LRR, and the peroxidase superfamily Cytochrome P450 have a positive role in the resistance through a hypersensitive response. Zinc finger domains, cysteine protease coding gene, F-box protein, ubiquitin, and associated proteins, play a substantial role in the combined stress of spot blotch and terminal heat in bread wheat, according to genomic domains ascribed to them. The study also highlights T. speltoides as a source of resistance to spot blotch and terminal heat tolerance.
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Affiliation(s)
- Sudhir Navathe
- Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India
- Agharkar Research Institute, G.G. Agharkar Road, Pune 411004, India
| | - Ajeet Kumar Pandey
- Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India
| | - Sandeep Sharma
- Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India
| | - Ramesh Chand
- Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India
| | - Vinod Kumar Mishra
- Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India
| | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
- Department of Biotechnology, School of Interdisciplinary and Applied Sciences, Central University of Haryana, Mahendergarh 123031, India
| | - Sarika Jaiswal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
| | - Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
| | - Velu Govindan
- International Maize and Wheat Improvement Center (CIMMYT), Veracruz 56237, Mexico
| | - Arun Kumar Joshi
- Borlaug Institute for South Asia, NASC Complex, DPS Marg, New Delhi 110012, India
- International Maize and Wheat Improvement Center (CIMMYT), G-2, B-Block, NASC Complex, DPS Marg, New Delhi 110012, India
| | - Pawan Kumar Singh
- International Maize and Wheat Improvement Center (CIMMYT), Veracruz 56237, Mexico
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Tomar V, Dhillon GS, Singh D, Singh RP, Poland J, Chaudhary AA, Bhati PK, Joshi AK, Kumar U. Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat ( Triticum aestivum L.). Front Genet 2021; 12:710485. [PMID: 34650592 PMCID: PMC8505882 DOI: 10.3389/fgene.2021.710485] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 08/24/2021] [Indexed: 01/08/2023] Open
Abstract
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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Affiliation(s)
- Vipin Tomar
- Borlaug Institute for South Asia, Ludhiana, India.,International Maize and Wheat Improvement Center, New Delhi, India.,Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Guriqbal Singh Dhillon
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, India
| | - Daljit Singh
- Department of Plant Pathology, Kansas State University, Manhattan, KS, United States
| | - Ravi Prakash Singh
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Jesse Poland
- Department of Plant Pathology, Kansas State University, Manhattan, KS, United States
| | - Anis Ahmad Chaudhary
- Department of Biology, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | | | - Arun Kumar Joshi
- Borlaug Institute for South Asia, Ludhiana, India.,International Maize and Wheat Improvement Center, New Delhi, India.,Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Uttam Kumar
- Borlaug Institute for South Asia, Ludhiana, India.,International Maize and Wheat Improvement Center, New Delhi, India.,Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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Qu P, Wang J, Wen W, Gao F, Liu J, Xia X, Peng H, Zhang L. Construction of Consensus Genetic Map With Applications in Gene Mapping of Wheat ( Triticum aestivum L.) Using 90K SNP Array. FRONTIERS IN PLANT SCIENCE 2021; 12:727077. [PMID: 34512703 PMCID: PMC8424075 DOI: 10.3389/fpls.2021.727077] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 07/28/2021] [Indexed: 06/02/2023]
Abstract
Wheat is one of the most important cereal crops worldwide. A consensus map combines genetic information from multiple populations, providing an effective alternative to improve the genome coverage and marker density. In this study, we constructed a consensus map from three populations of recombinant inbred lines (RILs) of wheat using a 90K single nucleotide polymorphism (SNP) array. Phenotypic data on plant height (PH), spike length (SL), and thousand-kernel weight (TKW) was collected in six, four, and four environments in the three populations, and then used for quantitative trait locus (QTL) mapping. The mapping results obtained using the constructed consensus map were compared with previous results obtained using individual maps and previous studies on other populations. A simulation experiment was also conducted to assess the performance of QTL mapping with the consensus map. The constructed consensus map from the three populations spanned 4558.55 cM in length, with 25,667 SNPs, having high collinearity with physical map and individual maps. Based on the consensus map, 21, 27, and 19 stable QTLs were identified for PH, SL, and TKW, much more than those detected with individual maps. Four PH QTLs and six SL QTLs were likely to be novel. A putative gene called TraesCS4D02G076400 encoding gibberellin-regulated protein was identified to be the candidate gene for one major PH QTL located on 4DS, which may enrich genetic resources in wheat semi-dwarfing breeding. The simulation results indicated that the length of the confidence interval and standard errors of the QTLs detected using the consensus map were much smaller than those detected using individual maps. The consensus map constructed in this study provides the underlying genetic information for systematic mapping, comparison, and clustering of QTL, and gene discovery in wheat genetic study. The QTLs detected in this study had stable effects across environments and can be used to improve the wide adaptation of wheat cultivars through marker-assisted breeding.
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Affiliation(s)
- Pingping Qu
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Jiankang Wang
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weie Wen
- Department of Cell Biology, Zunyi Medical University, Zunyi, China
| | - Fengmei Gao
- Crop Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jindong Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xianchun Xia
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huiru Peng
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Luyan Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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