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Kumar S, Saini DK, Jan F, Jan S, Tahir M, Djalovic I, Latkovic D, Khan MA, Kumar S, Vikas VK, Kumar U, Kumar S, Dhaka NS, Dhankher OP, Rustgi S, Mir RR. Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat. BMC Genomics 2023; 24:259. [PMID: 37173660 PMCID: PMC10182688 DOI: 10.1186/s12864-023-09336-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 04/26/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. RESULTS Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker-trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development. CONCLUSION The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches.
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Affiliation(s)
- Sandeep Kumar
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, 193201, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, Punjab, India
| | - Farkhandah Jan
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, 193201, India
| | - Sofora Jan
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, 193201, India
| | - Mohd Tahir
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, 193201, India
| | - Ivica Djalovic
- Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Maxim Gorki 30, Novi Sad, Serbia
| | - Dragana Latkovic
- Department of Field and Vegetable Crops, Faculty of Agriculture, University of Novi Sad, Trg Dositeja Obradovića 8, 21000, Novi Sad, Serbia
| | - Mohd Anwar Khan
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, 193201, India
| | - Sundeep Kumar
- Indian Council of Agricultural Research-National Bureau of Plant Genetic Resources, New Delhi, India
| | - V K Vikas
- ICAR-IARI, Regional Station, Wellington, 643 231, The Nilgiris, India
| | - Upendra Kumar
- Department of Molecular Biology & Biotechnology., CCS Haryana Agriculture University, Hisar, India
| | - Sundip Kumar
- Department of Molecular Biology and Genetic Engineering, Molecular Cytogenetics Laboratory, College of Basic Science and Humanities, G. B. Pant University of Agriculture and Technology, Pantnagar-263145, U.S. Nagar, Uttarakhand, India
| | - Narendra Singh Dhaka
- Department of Genetics and Plant Breeding, College of Agriculture, G. B. Pant, University of Agriculture & Technology, Pantnagar-263145, U. S. Nagar, Uttarakhand, India
| | - Om Parkash Dhankher
- School of Agriculture, University of Massachusetts Amherst, Stockbridge Amherst, MA, 01003, USA
| | - Sachin Rustgi
- Department of Plant and Environmental Sciences, Clemson University, 2200 Pocket Road, Florence, SC, 29506, USA
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, 193201, India.
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Shafi S, Saini DK, Khan MA, Bawa V, Choudhary N, Dar WA, Pandey AK, Varshney RK, Mir RR. Delineating meta-quantitative trait loci for anthracnose resistance in common bean ( Phaseolus vulgaris L.). FRONTIERS IN PLANT SCIENCE 2022; 13:966339. [PMID: 36092444 PMCID: PMC9453441 DOI: 10.3389/fpls.2022.966339] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 08/01/2022] [Indexed: 05/03/2023]
Abstract
Anthracnose, caused by the fungus Colletotrichum lindemuthianum, is one of the devastating disease affecting common bean production and productivity worldwide. Several quantitative trait loci (QTLs) for anthracnose resistance have been identified. In order to make use of these QTLs in common bean breeding programs, a detailed meta-QTL (MQTL) analysis has been conducted. For the MQTL analysis, 92 QTLs related to anthracnose disease reported in 18 different earlier studies involving 16 mapping populations were compiled and projected on to the consensus map. This meta-analysis led to the identification of 11 MQTLs (each involving QTLs from at least two different studies) on 06 bean chromosomes and 10 QTL hotspots each involving multiple QTLs from an individual study on 07 chromosomes. The confidence interval (CI) of the identified MQTLs was found 3.51 times lower than the CI of initial QTLs. Marker-trait associations (MTAs) reported in published genome-wide association studies (GWAS) were used to validate nine of the 11 identified MQTLs, with MQTL4.1 overlapping with as many as 40 MTAs. Functional annotation of the 11 MQTL regions revealed 1,251 genes including several R genes (such as those encoding for NBS-LRR domain-containing proteins, protein kinases, etc.) and other defense related genes. The MQTLs, QTL hotspots and the potential candidate genes identified during the present study will prove useful in common bean marker-assisted breeding programs and in basic studies involving fine mapping and cloning of genomic regions associated with anthracnose resistance in common beans.
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Affiliation(s)
- Safoora Shafi
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Mohd Anwar Khan
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, India
| | - Vanya Bawa
- Division of Genetics & Plant Breeding, Faculty of Agriculture, SKUAST-Jammu, Chatha, Jammu and Kashmir, India
| | - Neeraj Choudhary
- Division of Genetics & Plant Breeding, Faculty of Agriculture, SKUAST-Jammu, Chatha, Jammu and Kashmir, India
| | - Waseem Ali Dar
- Mountain Agriculture Research and Extension Station, SKUAST-Kashmir, Bandipora, Jammu and Kashmir, India
| | - Arun K. Pandey
- College of Life Sciences, China Jiliang University, Hangzhou, China
| | - Rajeev Kumar Varshney
- State Agricultural Biotechnology Centre, Centre for Crop & Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia
- Rajeev Kumar Varshney,
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, India
- *Correspondence: Reyazul Rouf Mir,
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