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Gaur A, Jindal Y, Singh V, Tiwari R, Juliana P, Kaushik D, Kumar KJY, Ahlawat OP, Singh G, Sheoran S. GWAS elucidated grain yield genetics in Indian spring wheat under diverse water conditions. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:177. [PMID: 38972024 DOI: 10.1007/s00122-024-04680-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 06/11/2024] [Indexed: 07/08/2024]
Abstract
KEY MESSAGE Underpinned natural variations and key genes associated with yield under different water regimes, and identified genomic signatures of genetic gain in the Indian wheat breeding program. A novel KASP marker for TKW under water stress was developed and validated. A comprehensive genome-wide association study was conducted on 300 spring wheat genotypes to elucidate the natural variations associated with grain yield and its eleven contributing traits under fully irrigated, restricted water, and simulated no water conditions. Utilizing the 35K Wheat Breeders' Array, we identified 1155 quantitative trait nucleotides (QTNs), with 207 QTNs exhibiting stability across diverse conditions. These QTNs were further delimited into 539 genomic regions using a genome-wide LD value of 3.0 Mbp, revealing pleiotropic control across traits and conditions. Sub-genome A was significantly associated with traits under irrigated conditions, while sub-genome B showed more QTNs under water stressed conditions. Favourable alleles with significantly associated QTNs were delineated, with a notable pyramiding effect for enhancing trait performance. Additionally, allele of only 921 QTNs significantly affected the population mean. Allele profiling highlighted C-306 as a most potential source of drought tolerance. Moreover, 762 genes overlapping significant QTNs were identified, narrowing down to 27 putative candidate genes overlapping 29 novel and functional SNPs expressing (≥ 0.5 tpm) relevance across various growth conditions. A new KASP assay was developed, targeting a gene TraesCS2A03G1123700 regulating thousand kernel weight under severe drought condition. Genomic selection models (GBLUP, BayesB, MxE, and R-Norm) demonstrated an average prediction accuracy of 0.06-0.58 across environments, indicating potential for trait selection. Retrospective analysis of the Indian wheat breeding program supported a genetic gain in GY at the rate of ca. 0.56% per breeding cycle, since 1960, supporting the identification of genomic signatures driving trait selection and genetic gain. These findings offer insight into improving the rate of genetic gain in wheat breeding programs globally.
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Affiliation(s)
- Arpit Gaur
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
- Crop Improvement, ICAR- Indian Institute of Wheat and Barley Research, Karnal, India
| | - Yogesh Jindal
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Vikram Singh
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | - Ratan Tiwari
- Crop Improvement, ICAR- Indian Institute of Wheat and Barley Research, Karnal, India
| | | | - Deepak Kaushik
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, India
| | | | - Om Parkash Ahlawat
- Crop Improvement, ICAR- Indian Institute of Wheat and Barley Research, Karnal, India
| | - Gyanendra Singh
- Crop Improvement, ICAR- Indian Institute of Wheat and Barley Research, Karnal, India
| | - Sonia Sheoran
- Crop Improvement, ICAR- Indian Institute of Wheat and Barley Research, Karnal, India.
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Sharma D, Budhlakoti N, Kumari A, Saini DK, Sharma A, Yadav A, Mir RR, Singh AK, Vikas VK, Singh GP, Kumar S. Exploring the genetic architecture of powdery mildew resistance in wheat through QTL meta-analysis. FRONTIERS IN PLANT SCIENCE 2024; 15:1386494. [PMID: 39022610 PMCID: PMC11251950 DOI: 10.3389/fpls.2024.1386494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 06/11/2024] [Indexed: 07/20/2024]
Abstract
Powdery mildew (PM), caused by Blumeria graminis f. sp. tritici, poses a significant threat to wheat production, necessitating the development of genetically resistant varieties for long-term control. Therefore, exploring genetic architecture of PM in wheat to uncover important genomic regions is an important area of wheat research. In recent years, the utilization of meta-QTL (MQTL) analysis has gained prominence as an essential tool for unraveling the complex genetic architecture underlying complex quantitative traits. The aim of this research was to conduct a QTL meta-analysis to pinpoint the specific genomic regions in wheat responsible for governing PM resistance. This study integrated 222 QTLs from 33 linkage-based studies using a consensus map with 54,672 markers. The analysis revealed 39 MQTLs, refined to 9 high-confidence MQTLs (hcMQTLs) with confidence intervals of 0.49 to 12.94 cM. The MQTLs had an average physical interval of 41.00 Mb, ranging from 0.000048 Mb to 380.71 Mb per MQTL. Importantly, 18 MQTLs co-localized with known resistance genes like Pm2, Pm3, Pm8, Pm21, Pm38, and Pm41. The study identified 256 gene models within hcMQTLs, providing potential targets for marker-assisted breeding and genomic prediction programs to enhance PM resistance. These MQTLs would serve as a foundation for fine mapping, gene isolation, and functional genomics studies, facilitating a deeper understanding of molecular mechanisms. The identification of candidate genes opens up exciting possibilities for the development of PM-resistant wheat varieties after validation.
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Affiliation(s)
- Divya Sharma
- Divison of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Neeraj Budhlakoti
- Centre for Agriculture Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Anita Kumari
- Department of Botany, University of Delhi, Delhi, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Punjab, Ludhiana, India
| | - Anshu Sharma
- Divison of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Aakash Yadav
- Divison of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Reyazul Rouf Mir
- Department of Genetics and Plant Breeding , Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - Amit Kumar Singh
- Divison of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - V. K. Vikas
- Divison of Crop Improvement, ICAR-Indian Agricultural Research Institute, Regional Station, Wellington, Tamilnadu, India
| | - Gyanendra Pratap Singh
- Divison of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Sundeep Kumar
- Divison of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
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Khojasteh M, Darzi Ramandi H, Taghavi SM, Taheri A, Rahmanzadeh A, Chen G, Foolad MR, Osdaghi E. Unraveling the genetic basis of quantitative resistance to diseases in tomato: a meta-QTL analysis and mining of transcript profiles. PLANT CELL REPORTS 2024; 43:184. [PMID: 38951262 DOI: 10.1007/s00299-024-03268-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 06/11/2024] [Indexed: 07/03/2024]
Abstract
KEY MESSAGE Whole-genome QTL mining and meta-analysis in tomato for resistance to bacterial and fungal diseases identified 73 meta-QTL regions with significantly refined/reduced confidence intervals. Tomato production is affected by a range of biotic stressors, causing yield losses and quality reductions. While sources of genetic resistance to many tomato diseases have been identified and characterized, stability of the resistance genes or quantitative trait loci (QTLs) across the resources has not been determined. Here, we examined 491 QTLs previously reported for resistance to tomato diseases in 40 independent studies and 54 unique mapping populations. We identified 29 meta-QTLs (MQTLs) for resistance to bacterial pathogens and 44 MQTLs for resistance to fungal pathogens, and were able to reduce the average confidence interval (CI) of the QTLs by 4.1-fold and 6.7-fold, respectively, compared to the average CI of the original QTLs. The corresponding physical length of the CIs of MQTLs ranged from 56 kb to 6.37 Mb, with a median of 921 kb, of which 27% had a CI lower than 500 kb and 53% had a CI lower than 1 Mb. Comparison of defense responses between tomato and Arabidopsis highlighted 73 orthologous genes in the MQTL regions, which were putatively determined to be involved in defense against bacterial and fungal diseases. Intriguingly, multiple genes were identified in some MQTL regions that are implicated in plant defense responses, including PR-P2, NDR1, PDF1.2, Pip1, SNI1, PTI5, NSL1, DND1, CAD1, SlACO, DAD1, SlPAL, Ph-3, EDS5/SID1, CHI-B/PR-3, Ph-5, ETR1, WRKY29, and WRKY25. Further, we identified a number of candidate resistance genes in the MQTL regions that can be useful for both marker/gene-assisted breeding as well as cloning and genetic transformation.
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Affiliation(s)
- Moein Khojasteh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
- School of Agriculture and Biology/State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran
| | - Hadi Darzi Ramandi
- Department of Plant Production and Genetics, Faculty of Agriculture, Bu-Ali Sina University, P.O. Box 657833131, Hamedan, Iran
- Department of Molecular Physiology, Agricultural Biotechnology Research Institute of Iran, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
| | - S Mohsen Taghavi
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran.
| | - Ayat Taheri
- Joint International Research Laboratory of Metabolic and Developmental Sciences, Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Asma Rahmanzadeh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran
| | - Gongyou Chen
- School of Agriculture and Biology/State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Majid R Foolad
- Department of Plant Science and the Intercollege Graduate Degree Program in Plant Biology, The Pennsylvania State University, University Park, PA, 16802, USA.
| | - Ebrahim Osdaghi
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran.
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Zheng J, Su H, Pu S, Chen H, El-Kassaby YA, Yang Z, Feng J. High-yield hybrid breeding of Camellia oleifolia based on ISSR molecular markers. BMC PLANT BIOLOGY 2024; 24:517. [PMID: 38851667 PMCID: PMC11162053 DOI: 10.1186/s12870-024-05218-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/29/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND C. Oleifera is among the world's largest four woody plants known for their edible oil production, yet the contribution rate of improved varieties is less than 20%. The species traditional breeding is lengthy cycle (20-30 years), occupation of land resources, high labor cost, and low accuracy and efficiency, which can be enhanced by molecular marker-assisted selection. However, the lack of high-quality molecular markers hinders the species genetic analysis and molecular breeding. RESULTS Through quantitative traits characterization, genetic diversity assessment, and association studies, we generated a selection population with wide genetic diversity, and identified five excellent high-yield parental combinations associated with four reliable high-yield ISSR markers. Early selection criteria were determined based on kernel fresh weight and cultivated 1-year seedling height, aided by the identification of these 4 ISSR markers. Specific assignment of selected individuals as paternal and maternal parents was made to capitalize on their unique attributes. CONCLUSIONS Our results indicated that molecular markers-assisted breeding can effectively shorten, enhance selection accuracy and efficiency and facilitate the development of a new breeding system for C. oleifera.
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Affiliation(s)
- Jinjia Zheng
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Haiqi Su
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Shaosheng Pu
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Hui Chen
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Yousry A El-Kassaby
- Department of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada.
| | - Zhijian Yang
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
| | - Jinling Feng
- College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
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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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Asins MJ, Carbonell EA. Meta-QTL and Candidate Gene Analyses of Agronomic Salt Tolerance and Related Traits in an RIL Population Derived from Solanum pimpinellifolium. Int J Mol Sci 2024; 25:6055. [PMID: 38892245 PMCID: PMC11172916 DOI: 10.3390/ijms25116055] [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: 04/22/2024] [Revised: 05/24/2024] [Accepted: 05/29/2024] [Indexed: 06/21/2024] Open
Abstract
Breeding salt-tolerant crops is necessary to reduce food insecurity. Prebreeding populations are fundamental for uncovering tolerance alleles from wild germplasm. To obtain a physiological interpretation of the agronomic salt tolerance and better criteria to identify candidate genes, quantitative trait loci (QTLs) governing productivity-related traits in a population of recombinant inbred lines (RIL) derived from S. pimpinellifolium were reanalyzed using an SNP-saturated linkage map and clustered using QTL meta-analysis to synthesize QTL information. A total of 60 out of 85 QTLs were grouped into 12 productivity MQTLs. Ten of them were found to overlap with other tomato yield QTLs that were found using various mapping populations and cultivation conditions. The MQTL compositions showed that fruit yield was genetically associated with leaf water content. Additionally, leaf Cl- and K+ contents were related to tomato productivity under control and salinity conditions, respectively. More than one functional candidate was frequently found, explaining most productivity MQTLs, indicating that the co-regulation of more than one gene within those MQTLs might explain the clustering of agronomic and physiological QTLs. Moreover, MQTL1.2, MQTL3 and MQTL6 point to the root as the main organ involved in increasing productivity under salinity through the wild allele, suggesting that adequate rootstock/scion combinations could have a clear agronomic advantage under salinity.
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Affiliation(s)
- Maria J. Asins
- Instituto Valenciano de Investigaciones Agrarias (IVIA), 46113 Moncada, Valencia, Spain
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Xu H, Wang Z, Wang F, Hu X, Ma C, Jiang H, Xie C, Gao Y, Ding G, Zhao C, Qin R, Cui D, Sun H, Cui F, Wu Y. Genome-wide association study and genomic selection of spike-related traits in bread wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:131. [PMID: 38748046 DOI: 10.1007/s00122-024-04640-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 04/27/2024] [Indexed: 06/09/2024]
Abstract
KEY MESSAGE Identification of 337 stable MTAs for wheat spike-related traits improved model accuracy, and favorable alleles of MTA259 and MTA64 increased grain weight and yield per plant. Wheat (Triticum aestivum L.) is one of the three primary global, staple crops. Improving spike-related traits in wheat is crucial for optimizing spike and plant morphology, ultimately leading to increased grain yield. Here, we performed a genome-wide association study using a dataset of 24,889 high-quality unique single-nucleotide polymorphisms (SNPs) and phenotypic data from 314 wheat accessions across eight diverse environments. In total, 337 stable and significant marker-trait associations (MTAs) related to spike-related traits were identified. MTA259 and MTA64 were consistently detected in seven and six environments, respectively. The presence of favorable alleles associated with MTA259 and MTA64 significantly reduced wheat spike exsertion length and spike length, while enhancing thousand kernel weight and yield per plant. Combined gene expression and network analyses identified TraesCS6D03G0692300 and TraesCS6D03G0692700 as candidate genes for MTA259 and TraesCS2D03G0111700 and TraesCS2D03G0112500 for MTA64. The identified MTAs significantly improved the prediction accuracy of each model compared with using all the SNPs, and the random forest model was optimal for genome selection. Additionally, the eight stable and major MTAs, including MTA259, MTA64, MTA66, MTA94, MTA110, MTA165, MTA180, and MTA164, were converted into cost-effective and efficient detection markers. This study provided valuable genetic resources and reliable molecular markers for wheat breeding programs.
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Affiliation(s)
- Huiyuan Xu
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Zixu Wang
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Faxiang Wang
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Xinrong Hu
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Chengxue Ma
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Huijiao Jiang
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Chang Xie
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Yuhang Gao
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Guangshuo Ding
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Chunhua Zhao
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Ran Qin
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China
| | - Dezhou Cui
- Crop Research Institute, Shandong Academy of Agricultural Sciences/National Engineering Research Center of Wheat and Maize/Key Laboratory of Wheat Biology and Genetics and Breeding in Northern Huang-Huai River Plain, Ministry of Agriculture and Rural Affairs/Shandong Technology Innovation Center of Wheat/Jinan Key Laboratory of Wheat Genetic Improvement, Jinan, Shandong, China
| | - Han Sun
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China.
| | - Fa Cui
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China.
| | - Yongzhen Wu
- College of Agriculture, Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, Ludong University, Yantai, Shandong, China.
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Panigrahi S, Kumar U, Swami S, Singh Y, Balyan P, Singh KP, Dhankher OP, Varshney RK, Roorkiwal M, Amiri KM, Mir RR. Meta QTL analysis for dissecting abiotic stress tolerance in chickpea. BMC Genomics 2024; 25:439. [PMID: 38698307 PMCID: PMC11067088 DOI: 10.1186/s12864-024-10336-9] [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: 02/12/2023] [Accepted: 04/23/2024] [Indexed: 05/05/2024] Open
Abstract
BACKGROUND Chickpea is prone to many abiotic stresses such as heat, drought, salinity, etc. which cause severe loss in yield. Tolerance towards these stresses is quantitative in nature and many studies have been done to map the loci influencing these traits in different populations using different markers. This study is an attempt to meta-analyse those reported loci projected over a high-density consensus map to provide a more accurate information on the regions influencing heat, drought, cold and salinity tolerance in chickpea. RESULTS A meta-analysis of QTL reported to be responsible for tolerance to drought, heat, cold and salinity stress tolerance in chickpeas was done. A total of 1512 QTL responsible for the concerned abiotic stress tolerance were collected from literature, of which 1189 were projected on a chickpea consensus genetic map. The QTL meta-analysis predicted 59 MQTL spread over all 8 chromosomes, responsible for these 4 kinds of abiotic stress tolerance in chickpea. The physical locations of 23 MQTL were validated by various marker-trait associations and genome-wide association studies. Out of these reported MQTL, CaMQAST1.1, CaMQAST4.1, CaMQAST4.4, CaMQAST7.8, and CaMQAST8.2 were suggested to be useful for different breeding approaches as they were responsible for high per cent variance explained (PVE), had small intervals and encompassed a large number of originally reported QTL. Many putative candidate genes that might be responsible for directly or indirectly conferring abiotic stress tolerance were identified in the region covered by 4 major MQTL- CaMQAST1.1, CaMQAST4.4, CaMQAST7.7, and CaMQAST6.4, such as heat shock proteins, auxin and gibberellin response factors, etc. CONCLUSION: The results of this study should be useful for the breeders and researchers to develop new chickpea varieties which are tolerant to drought, heat, cold, and salinity stresses.
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Affiliation(s)
- Sourav Panigrahi
- Department of Molecular Biology & Biotechnology, College of Biotechnology, CCS Haryana Agricultural University, Hisar, 125004, India
| | - Upendra Kumar
- Department of Molecular Biology & Biotechnology, College of Biotechnology, CCS Haryana Agricultural University, Hisar, 125004, India.
- Department of Plant Science, Mahatma Jyotiba Phule Rohilkhand University, Bareilly, 243001, India.
| | - Sonu Swami
- Department of Molecular Biology & Biotechnology, College of Biotechnology, CCS Haryana Agricultural University, Hisar, 125004, India
- Department of Botany & Plant Physiology, College of Basic Sciences & Humanities, CCS Haryana Agricultural University, Hisar, 125004, India
| | - Yogita Singh
- Department of Molecular Biology & Biotechnology, College of Biotechnology, CCS Haryana Agricultural University, Hisar, 125004, India
| | - Priyanka Balyan
- Department of Botany, Deva Nagri P.G. College, CCS University, Meerut, 245206, India
| | - Krishna Pal Singh
- Biophysics Unit, College of Basic Sciences & Humanities, GB Pant University of Agriculture & Technology, Pantnagar, 263145, India
- Vice-Chancellor's Secretariat, Mahatma Jyotiba Phule Rohilkhand University, Bareilly, 243001, India
| | - Om Parkash Dhankher
- Stockbridge School of Agriculture, University of Massachusetts, Amherst, USA
| | - Rajeev K Varshney
- Centre for Crop & Food Innovation, State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, WA, Australia
| | - Manish Roorkiwal
- Khalifa Center for Genetic Engineering and Biotechnology, United Arab Emirates University, Al-Ain, United Arab Emirates.
| | - Khaled Ma Amiri
- Khalifa Center for Genetic Engineering and Biotechnology, United Arab Emirates University, Al-Ain, United Arab Emirates
- Department of Biology, College of Science, United Arab Emirates University, Al-Ain, United Arab Emirates
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-Kashmir), Srinagar, J&K, India.
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Lai D, Zhang K, He Y, Fan Y, Li W, Shi Y, Gao Y, Huang X, He J, Zhao H, Lu X, Xiao Y, Cheng J, Ruan J, Georgiev MI, Fernie AR, Zhou M. Multi-omics identification of a key glycosyl hydrolase gene FtGH1 involved in rutin hydrolysis in Tartary buckwheat (Fagopyrum tataricum). PLANT BIOTECHNOLOGY JOURNAL 2024; 22:1206-1223. [PMID: 38062934 PMCID: PMC11022807 DOI: 10.1111/pbi.14259] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/16/2023] [Accepted: 11/20/2023] [Indexed: 04/18/2024]
Abstract
Rutin, a flavonoid rich in buckwheat, is important for human health and plant resistance to external stresses. The hydrolysis of rutin to quercetin underlies the bitter taste of Tartary buckwheat. In order to identify rutin hydrolysis genes, a 200 genotypes mini-core Tartary buckwheat germplasm resource was re-sequenced with 30-fold coverage depth. By combining the content of the intermediate metabolites of rutin metabolism with genome resequencing data, metabolite genome-wide association analyses (GWAS) eventually identified a glycosyl hydrolase gene FtGH1, which could hydrolyse rutin to quercetin. This function was validated both in Tartary buckwheat overexpression hairy roots and in vitro enzyme activity assays. Mutation of the two key active sites, which were determined by molecular docking and experimentally verified via overexpression in hairy roots and transient expression in tobacco leaves, exhibited abnormal subcellular localization, suggesting functional changes. Sequence analysis revealed that mutation of the FtGH1 promoter in accessions of two haplotypes might be necessary for enzymatic activity. Co-expression analysis and GWAS revealed that FtbHLH165 not only repressed FtGH1 expression, but also increased seed length. This work reveals a potential mechanism behind rutin metabolism, which should provide both theoretical support in the study of flavonoid metabolism and in the molecular breeding of Tartary buckwheat.
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Affiliation(s)
- Dili Lai
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
- College of AgricultureGuizhou UniversityGuiyangChina
| | - Kaixuan Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yuqi He
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yu Fan
- School of Food and Biological EngineeringChengdu UniversityChengduChina
| | - Wei Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yaliang Shi
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yuanfen Gao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Xu Huang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Jiayue He
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Hui Zhao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Xiang Lu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yawen Xiao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | | | - Jingjun Ruan
- College of AgricultureGuizhou UniversityGuiyangChina
| | - Milen I. Georgiev
- Laboratory of Metabolomics, Institute of MicrobiologyBulgarian Academy of SciencesPlovdivBulgaria
- Center of Plant Systems Biology and BiotechnologyPlovdivBulgaria
| | - Alisdair R. Fernie
- Center of Plant Systems Biology and BiotechnologyPlovdivBulgaria
- Department of Molecular PhysiologyMax‐Planck‐Institute of Molecular Plant PhysiologyPotsdam‐GolmGermany
| | - Meiliang Zhou
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
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10
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Ding H, Wang C, Cai Y, Yu K, Zhao H, Wang F, Shi X, Cheng J, Sun H, Wu Y, Qin R, Liu C, Zhao C, Sun X, Cui F. Characterization of a wheat stable QTL for spike length and its genetic effects on yield-related traits. BMC PLANT BIOLOGY 2024; 24:292. [PMID: 38632554 PMCID: PMC11022484 DOI: 10.1186/s12870-024-04963-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 03/29/2024] [Indexed: 04/19/2024]
Abstract
Spike length (SL) is one of the most important agronomic traits affecting yield potential and stability in wheat. In this study, a major stable quantitative trait locus (QTL) for SL, i.e., qSl-2B, was detected in multiple environments in a recombinant inbred line (RIL) mapping population, KJ-RILs, derived from a cross between Kenong 9204 (KN9204) and Jing 411 (J411). The qSl-2B QTL was mapped to the 60.06-73.06 Mb region on chromosome 2B and could be identified in multiple mapping populations. An InDel molecular marker in the target region was developed based on a sequence analysis of the two parents. To further clarify the breeding use potential of qSl-2B, we analyzed its genetic effects and breeding selection effect using both the KJ-RIL population and a natural mapping population, which consisted of 316 breeding varieties/advanced lines. The results showed that the qSl-2B alleles from KN9204 showed inconsistent genetic effects on SL in the two mapping populations. Moreover, in the KJ-RILs population, the additive effects analysis of qSl-2B showed that additive effect was higher when both qSl-2D and qSl-5A harbor negative alleles under LN and HN. In China, a moderate selection utilization rate for qSl-2B was found in the Huanghuai winter wheat area and the selective utilization rate for qSl-2B continues to increase. The above findings provided a foundation for the genetic improvement of wheat SL in the future via molecular breeding strategies.
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Affiliation(s)
- Hongke Ding
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Chenyang Wang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yibiao Cai
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Kai Yu
- Yantai Agricultural Technology Extension Center, Yantai, 264001, China
| | - Haibo Zhao
- Yantai Agricultural Technology Extension Center, Yantai, 264001, China
| | - Faxiang Wang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Xinyao Shi
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Jiajia Cheng
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Han Sun
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yongzhen Wu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Ran Qin
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Cheng Liu
- Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Chunhua Zhao
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
| | - Xiaohui Sun
- Yantai Academy of Agricultural Sciences, Yantai, Shandong, 265500, China.
| | - Fa Cui
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
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11
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Kartseva T, Aleksandrov V, Alqudah AM, Arif MAR, Kocheva K, Doneva D, Prokopova K, Börner A, Misheva S. GWAS in a Collection of Bulgarian Old and Modern Bread Wheat Accessions Uncovers Novel Genomic Loci for Grain Protein Content and Thousand Kernel Weight. PLANTS (BASEL, SWITZERLAND) 2024; 13:1084. [PMID: 38674493 PMCID: PMC11054703 DOI: 10.3390/plants13081084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/03/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024]
Abstract
Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits-grain protein content (GPC) and thousand kernel weight (TKW)-across 179 Bulgarian contemporary and historic varieties and landraces across three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, and genotypic data from the 25K Infinium iSelect array. As a result, we detected 16 quantitative trait nucleotides (QTNs) associated with GPC and 15 associated with TKW, all of which passed the false discovery rate threshold. Seven loci favorably influenced GPC, resulting in an increase of 1.4% to 8.1%, while four loci had a positive impact on TKW with increases ranging from 1.9% to 8.4%. While some loci confirmed previously published associations, four QTNs linked to GPC on chromosomes 2A, 7A, and 7B, as well as two QTNs related to TKW on chromosomes 1B and 6A, may represent novel associations. Annotations for proteins involved in the senescence-associated nutrient remobilization and in the following buildup of resources required for seed germination have been found for selected putative candidate genes. These include genes coding for storage proteins, cysteine proteases, cellulose-synthase, alpha-amylase, transcriptional regulators, and F-box and RWP-RK family proteins. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content.
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Affiliation(s)
- Tania Kartseva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Vladimir Aleksandrov
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Ahmad M. Alqudah
- Biological Science Program, Department of Biological and Environmental Sciences, College of Art and Science, Qatar University, Doha P.O. Box 2713, Qatar;
| | - Mian Abdur Rehman Arif
- Nuclear Institute for Agriculture and Biology College, Pakistan Institute of Engineering and Applied Sciences (NIAB-C, PIEAS), Jhang Road, Faisalabad 38000, Pakistan;
| | - Konstantina Kocheva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Dilyana Doneva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Katelina Prokopova
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Andreas Börner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben), OT Gatersleben, Corrensstraße 3, 06466 Seeland, Germany;
| | - Svetlana Misheva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
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12
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Li R, Wang Y, Li D, Guo Y, Zhou Z, Zhang M, Zhang Y, Würschum T, Liu W. Meta-Quantitative Trait Loci Analysis and Candidate Gene Mining for Drought Tolerance-Associated Traits in Maize ( Zea mays L.). Int J Mol Sci 2024; 25:4295. [PMID: 38673880 PMCID: PMC11049847 DOI: 10.3390/ijms25084295] [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: 03/07/2024] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
Drought is one of the major abiotic stresses with a severe negative impact on maize production globally. Understanding the genetic architecture of drought tolerance in maize is a crucial step towards the breeding of drought-tolerant varieties and a targeted exploitation of genetic resources. In this study, 511 quantitative trait loci (QTL) related to grain yield components, flowering time, and plant morphology under drought conditions, as well as drought tolerance index were collected from 27 published studies and then projected on the IBM2 2008 Neighbors reference map for meta-analysis. In total, 83 meta-QTL (MQTL) associated with drought tolerance in maize were identified, of which 20 were determined as core MQTL. The average confidence interval of MQTL was strongly reduced compared to that of the previously published QTL. Nearly half of the MQTL were confirmed by co-localized marker-trait associations from genome-wide association studies. Based on the alignment of rice proteins related to drought tolerance, 63 orthologous genes were identified near the maize MQTL. Furthermore, 583 candidate genes were identified within the 20 core MQTL regions and maize-rice homologous genes. Based on KEGG analysis of candidate genes, plant hormone signaling pathways were found to be significantly enriched. The signaling pathways can have direct or indirect effects on drought tolerance and also interact with other pathways. In conclusion, this study provides novel insights into the genetic and molecular mechanisms of drought tolerance in maize towards a more targeted improvement of this important trait in breeding.
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Affiliation(s)
- Ronglan Li
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
- Sanya Institute of China Agricultural University, Sanya 572025, China
| | - Yueli Wang
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Dongdong Li
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Yuhang Guo
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Zhipeng Zhou
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Mi Zhang
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
- Sanya Institute of China Agricultural University, Sanya 572025, China
| | - Yufeng Zhang
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
- Sanya Institute of China Agricultural University, Sanya 572025, China
| | - Tobias Würschum
- Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70599 Stuttgart, Germany
| | - Wenxin Liu
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education, Key Laboratory of Crop Genetic Improvement, Beijing Municipality, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
- Sanya Institute of China Agricultural University, Sanya 572025, China
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13
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Bi C, Wei C, Li J, Wen S, Zhao H, Yu J, Shi X, Zhang Y, Liu Q, Zhang Y, Li B, You M. A novel variation of TaGW2-6B increases grain weight without penalty in grain protein content in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:15. [PMID: 38362529 PMCID: PMC10864231 DOI: 10.1007/s11032-024-01455-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 01/23/2024] [Indexed: 02/17/2024]
Abstract
Yield and quality are two crucial breeding objects of wheat therein grain weight and grain protein content (GPC) are two key relevant factors correspondingly. Investigations of their genetic mechanisms represent special significance for breeding. In this study, 199 F2 plants and corresponding F2:3 families derived from Nongda3753 (ND3753) and its EMS-generated mutant 564 (M564) were used to investigate the genetic basis of larger grain and higher GPC of M564. QTL analysis identified a total of 33 environmentally stable QTLs related to thousand grain weight (TGW), grain area (GA), grain circle (GC), grain length (GL), grain width (GW), and GPC on chromosomes 1B, 2A, 2B, 4D, 6B, and 7D, respectively, among which QGw.cau-6B.1, QTgw.cau-6B.1, QGa.cau-6B.1, and QGc.cau-6B.1 shared overlap confidence interval on chromosome 6B. This interval contained the TaGW2 gene playing the same role as the QTLs, so TaGW2-6B was cloned and sequenced. Sequence alignment revealed two G/A SNPs between two parents, among which the SNP in the seventh exon led to a premature termination in M564. A KASP marker was developed based on the SNP, and single-marker analysis on biparental populations showed that the mutant allele could significantly increase GW and TGW, but had no effect on GPC. Distribution detection of the mutant allele through KASP marker genotyping and sequence alignment against databases ascertained that no materials harbored this allele within natural populations. This allele was subsequently introduced into three different varieties through molecular marker-assisted backcrossing, and it was revealed that the allele had a significant effect on simultaneously increasing GW, TGW, and even GPC in all of three backgrounds. Summing up the above, it could be concluded that a novel elite allele of TaGW2-6B was artificially created and might play an important role in wheat breeding for high yield and quality. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01455-y.
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Affiliation(s)
- Chan Bi
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Chaoxiong Wei
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Jinghui Li
- Wheat Center, Henan Institute of Science and Technology, Henan Provincial Key Laboratory of Hybrid Wheat, Xinxiang, 453003 China
| | - Shaozhe Wen
- Department of Landscape and Garden, Yangzhou Polytechnic College, Yangzhou, 225009 China
| | - Huanhuan Zhao
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Jiazheng Yu
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Xintian Shi
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Yuan Zhang
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Qiaofeng Liu
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Yufeng Zhang
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Baoyun Li
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Mingshan You
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
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14
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Du B, Wu J, Wang M, Wu J, Sun C, Zhang X, Ren X, Wang Q. Detection of consensus genomic regions and candidate genes for quality traits in barley using QTL meta-analysis. FRONTIERS IN PLANT SCIENCE 2024; 14:1319889. [PMID: 38283973 PMCID: PMC10811794 DOI: 10.3389/fpls.2023.1319889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/26/2023] [Indexed: 01/30/2024]
Abstract
Improving barley grain quality is a major goal in barley breeding. In this study, a total of 35 papers focusing on quantitative trait loci (QTLs) mapping for barley quality traits published since 2000 were collected. Among the 454 QTLs identified in these studies, 349 of them were mapped onto high-density consensus maps, which were used for QTL meta-analysis. Through QTL meta-analysis, the initial QTLs were integrated into 41 meta-QTLs (MQTLs) with an average confidence interval (CI) of 1. 66 cM, which is 88.9% narrower than that of the initial QTLs. Among the 41 identified MQTLs, 25 were subsequently validated in publications using genome-wide association study (GWAS). From these 25 validated MQTLs, ten breeder's MQTLs were selected. Synteny analysis comparing barley and wheat MQTLs revealed orthologous relationships between eight breeder's MQTLs and 45 wheat MQTLs. Additionally, 17 barley homologs associated with rice quality traits were identified within the regions of the breeder's MQTLs through comparative analysis. The findings of this study provide valuable insights for molecular marker-assisted breeding and the identification of candidate genes related to quality traits in barley.
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Affiliation(s)
- Binbin Du
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Jindong Wu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Meng Wang
- Xingtai Agriculture and Rural Bureau, Xingtai, Hebei, China
| | - Jia Wu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Chaoyue Sun
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Xingen Zhang
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Xifeng Ren
- Hubei Hongshan Laboratory, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Qifei Wang
- Institute of Crop and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang, China
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15
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Jiang C, Xu Z, Fan X, Zhou Q, Ji G, Liao S, Wang Y, Ma F, Zhao Y, Wang T, Feng B. Genetic dissection of major QTL for grain number per spike on chromosomes 5A and 6A in bread wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2024; 14:1305547. [PMID: 38259947 PMCID: PMC10800429 DOI: 10.3389/fpls.2023.1305547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 12/08/2023] [Indexed: 01/24/2024]
Abstract
Grain number per spike (GNS) is a crucial component of grain yield and plays a significant role in improving wheat yield. To identify quantitative trait loci (QTL) associated with GNS, a recombinant inbred line (RIL) population derived from the cross of Zhongkemai 13F10 and Chuanmai 42 was employed to conduct QTL mapping across eight environments. Based on the bulked segregant exome sequencing (BSE-Seq), genomic regions associated with GNS were detected on chromosomes 5A and 6A. According to the constructed genetic maps, two major QTL QGns.cib-5A (LOD = 4.35-8.16, PVE = 8.46-14.43%) and QGns.cib-6A (LOD = 3.82-30.80, PVE = 5.44-12.38%) were detected in five and four environments, respectively. QGns.cib-6A is a QTL cluster for other seven yield-related traits. QGns.cib-5A and QGns.cib-6A were further validated using linked Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. QGns.cib-5A exhibited pleiotropic effects on productive tiller number (PTN), spike length (SL), fertile spikelet number per spike (FSN), and ratio of grain length to grain width (GL/GW) but did not significantly affect thousand grain weight (TGW). Haplotype analysis revealed that QGns.cib-5A and QGns.cib-6A were the targets of artificial selection during wheat improvement. Candidate genes for QGns.cib-5A and QGns.cib-6A were predicted by analyzing gene annotation, spatiotemporal expression patterns, and orthologous and sequence differences. These findings will be valuable for fine mapping and map-based cloning of genes underlying QGns.cib-5A and QGns.cib-6A.
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Affiliation(s)
- Cheng Jiang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- College of Life Sciences, Sichuan University, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhibin Xu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Qiang Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Guangsi Ji
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Simin Liao
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yanlin Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fang Ma
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yun Zhao
- College of Life Sciences, Sichuan University, Chengdu, China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- The Innovative of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Bo Feng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
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16
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Sharma D, Kumari A, Sharma P, Singh A, Sharma A, Mir ZA, Kumar U, Jan S, Parthiban M, Mir RR, Bhati P, Pradhan AK, Yadav A, Mishra DC, Budhlakoti N, Yadav MC, Gaikwad KB, Singh AK, Singh GP, Kumar S. Meta-QTL analysis in wheat: progress, challenges and opportunities. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:247. [PMID: 37975911 DOI: 10.1007/s00122-023-04490-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 10/16/2023] [Indexed: 11/19/2023]
Abstract
Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.
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Affiliation(s)
- Divya Sharma
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Anita Kumari
- Department of Botany, University of Delhi, Delhi, India
| | - Priya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Anupma Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Anshu Sharma
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Zahoor Ahmad Mir
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Uttam Kumar
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Sofora Jan
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - M Parthiban
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - Reyazul Rouf Mir
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - Pradeep Bhati
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Anjan Kumar Pradhan
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Aakash Yadav
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | | | - Neeraj Budhlakoti
- ICAR- Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mahesh C Yadav
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Kiran B Gaikwad
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
| | - Amit Kumar Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | | | - Sundeep Kumar
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
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López-Fernández M, García-Abadillo J, Uauy C, Ruiz M, Giraldo P, Pascual L. Genome wide association in Spanish bread wheat landraces identifies six key genomic regions that constitute potential targets for improving grain yield related traits. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:244. [PMID: 37957405 PMCID: PMC10643358 DOI: 10.1007/s00122-023-04492-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023]
Abstract
KEY MESSAGE Association mapping conducted in 189 Spanish bread wheat landraces revealed six key genomic regions that constitute stable QTLs for yield and include 15 candidate genes. Genetically diverse landraces provide an ideal population to conduct association analysis. In this study, association mapping was conducted in a collection of 189 Spanish bread wheat landraces whose genomic diversity had been previously assessed. These genomic data were combined with characterization for yield-related traits, including grain size and shape, and phenological traits screened across five seasons. The association analysis revealed a total of 881 significant marker trait associations, involving 434 markers across the genome, that could be grouped in 366 QTLs based on linkage disequilibrium. After accounting for days to heading, we defined 33 high density QTL genomic regions associated to at least four traits. Considering the importance of detecting stable QTLs, 6 regions associated to several grain traits and thousand kernel weight in at least three environments were selected as the most promising ones to harbour targets for breeding. To dissect the genetic cause of the observed associations, we studied the function and in silico expression of the 413 genes located inside these six regions. This identified 15 candidate genes that provide a starting point for future analysis aimed at the identification and validation of wheat yield related genes.
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Affiliation(s)
- Matilde López-Fernández
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain
| | - Julián García-Abadillo
- Department of Biotechnology and Plant Biology, Centre for Biotechnology and Plant Genomics (CBGP), Universidad Politécnica de Madrid (UPM), Madrid, Spain
| | - Cristobal Uauy
- John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, UK
| | - Magdalena Ruiz
- Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA), CSIC, Autovía A2, Km. 36.2. Finca La Canaleja, 28805, Alcalá de Henares, Madrid, Spain
| | - Patricia Giraldo
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain.
| | - Laura Pascual
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain
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18
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Qiao P, Li X, Liu D, Lu S, Zhi L, Rysbekova A, Chen L, Hu YG. Mining novel genomic regions and candidate genes of heading and flowering dates in bread wheat by SNP- and haplotype-based GWAS. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:76. [PMID: 37873506 PMCID: PMC10587053 DOI: 10.1007/s11032-023-01422-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 09/27/2023] [Indexed: 10/25/2023]
Abstract
Bread wheat (Triticum aestivum L.) is a global staple crop vital for human nutrition. Heading date (HD) and flowering date (FD) are critical traits influencing wheat growth, development, and adaptability to diverse environmental conditions. A comprehensive study were conducted involving 190 bread wheat accessions to unravel the genetic basis of HD and FD using high-throughput genotyping and multi-environment field trials. Seven independent quantitative trait loci (QTLs) were identified to be significantly associated with HD and FD using two GWAS methods, which explained a proportion of phenotypic variance ranging from 1.43% to 9.58%. Notably, QTLs overlapping with known vernalization genes Vrn-D1 were found, validating their roles in regulating flowering time. Moreover, novel QTLs on chromosome 2A, 5B, 5D, and 7B associated with HD and FD were identified. The effects of these QTLs on HD and FD were confirmed in an additional set of 74 accessions across different environments. An increase in the frequency of alleles associated with early flowering in cultivars released in recent years was also observed, suggesting the influence of molecular breeding strategies. In summary, this study enhances the understanding of the genetic regulation of HD and FD in bread wheat, offering valuable insights into crop improvement for enhanced adaptability and productivity under changing climatic conditions. These identified QTLs and associated markers have the potential to improve wheat breeding programs in developing climate-resilient varieties to ensure food security. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01422-z.
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Affiliation(s)
- Pengfang Qiao
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi China
| | - Xuan Li
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi China
| | - Dezheng Liu
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi China
| | - Shan Lu
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi China
| | - Lei Zhi
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi China
| | - Aiman Rysbekova
- S. Seifullin Kazakh Agro-Technical University, Astana, Kazakhstan
| | - Liang Chen
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi China
| | - Yin-gang Hu
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi China
- State Key Laboratory of Crop Stress Biology for Arid Areas, Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling, Shaanxi China
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19
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Valladares García AP, Desiderio F, Simeone R, Ravaglia S, Ciorba R, Fricano A, Guerra D, Blanco A, Cattivelli L, Mazzucotelli E. QTL mapping for kernel-related traits in a durum wheat x T. dicoccum segregating population. FRONTIERS IN PLANT SCIENCE 2023; 14:1253385. [PMID: 37849841 PMCID: PMC10577384 DOI: 10.3389/fpls.2023.1253385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/28/2023] [Indexed: 10/19/2023]
Abstract
Durum wheat breeding relies on grain yield improvement to meet its upcoming demand while coping with climate change. Kernel size and shape are the determinants of thousand kernel weight (TKW), which is a key component of grain yield, and the understanding of the genetic control behind these traits supports the progress in yield potential. The present study aimed to dissect the genetic network responsible for kernel size components (length, width, perimeter, and area) and kernel shape traits (width-to-length ratio and formcoefficient) as well as their relationships with kernel weight, plant height, and heading date in durum wheat. Quantitative Trait Locus (QTL) mapping was performed on a segregating population of 110 recombinant inbred lines, derived from a cross between the domesticated emmer wheat accession MG5323 and the durum wheat cv. Latino, evaluated in four different environments. A total of 24 QTLs stable across environments were found and further grouped in nine clusters on chromosomes 2A, 2B, 3A, 3B, 4B, 6B, and 7A. Among them, a QTL cluster on chromosome 4B was associated with kernel size traits and TKW, where the parental MG5323 contributed the favorable alleles, highlighting its potential to improve durum wheat germplasm. The physical positions of the clusters, defined by the projection on the T. durum reference genome, overlapped with already known genes (i.e., BIG GRAIN PROTEIN 1 on chromosome 4B). These results might provide genome-based guidance for the efficient exploitation of emmer wheat diversity in wheat breeding, possibly through yield-related molecular markers.
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Affiliation(s)
- Ana Paola Valladares García
- Instituto de Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universitat Politècnica de València, Valencia, Spain
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Francesca Desiderio
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Rosanna Simeone
- Department of Soil, Plant and Food Sciences (DiSSPA), Genetics and Plant Breeding Section, University of Bari Aldo Moro, Bari, Italy
| | | | - Roberto Ciorba
- Council for Agricultural Research and Economics (CREA) - Research Centre for Olive, Fruit and Citrus Crops, Rome, Italy
| | - Agostino Fricano
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Davide Guerra
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Antonio Blanco
- Department of Soil, Plant and Food Sciences (DiSSPA), Genetics and Plant Breeding Section, University of Bari Aldo Moro, Bari, Italy
| | - Luigi Cattivelli
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Elisabetta Mazzucotelli
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
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20
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Wei M, Huang Y, Mo C, Wang H, Zeng Q, Yang W, Chen J, Zhang X, Kong Q. Telomere-to-telomere genome assembly of melon ( Cucumis melo L. var. inodorus) provides a high-quality reference for meta-QTL analysis of important traits. HORTICULTURE RESEARCH 2023; 10:uhad189. [PMID: 37915500 PMCID: PMC10615816 DOI: 10.1093/hr/uhad189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 09/12/2023] [Indexed: 11/03/2023]
Abstract
Melon is an important horticultural crop with extensive diversity in many horticultural groups. To explore its genomic diversity, it is necessary to assemble more high-quality complete genomes from different melon accessions. Meanwhile, a large number of QTLs have been mapped in several studies. Integration of the published QTLs onto a complete genome can provide more accurate information for candidate gene cloning. To address these problems, a telomere-to-telomere (T2T) genome of the elite melon landrace Kuizilikjiz (Cucumis melo L. var. inodorus) was de novo assembled and all the published QTLs were projected onto it in this study. The results showed that a high-quality Kuizilikjiz genome with the size of 379.2 Mb and N50 of 31.7 Mb was de novo assembled using the combination of short reads, PacBio high-fidelity long reads, Hi-C data, and a high-density genetic map. Each chromosome contained the centromere and telomeres at both ends. A large number of structural variations were observed between Kuizilikjiz and the other published genomes. A total of 1294 QTLs published in 67 studies were collected and projected onto the T2T genome. Several clustered, co-localized, and overlapped QTLs were determined. Furthermore, 20 stable meta-QTLs were identified, which significantly reduced the mapping intervals of the initial QTLs and greatly facilitated identification of the candidate genes. Collectively, the T2T genome assembly together with the numerous projected QTLs will not only broaden the high-quality genome resources but also provide valuable and abundant QTL information for cloning the genes controlling important traits in melon.
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Affiliation(s)
- Minghua Wei
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China
| | - Ying Huang
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China
| | - Changjuan Mo
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China
| | - Haiyan Wang
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China
| | - Qingguo Zeng
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China
| | - Wenli Yang
- Hami-melon Research Center, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China
| | - Jihao Chen
- Hainan Sanya Experimental Center for Crop Breeding, Xinjiang Academy of Agricultural Sciences, Sanya 572014, China
| | - Xuejun Zhang
- Hami-melon Research Center, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China
- Hainan Sanya Experimental Center for Crop Breeding, Xinjiang Academy of Agricultural Sciences, Sanya 572014, China
| | - Qiusheng Kong
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China
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21
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Qin R, Ma T, Cai Y, Shi X, Cheng J, Dong J, Wang C, Li S, Pan G, Guan Y, Zhang L, Yang S, Xu H, Zhao C, Sun H, Li X, Wu Y, Li J, Cui F. Characterization and fine mapping analysis of a major stable QTL qKnps-4A for kernel number per spike in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:211. [PMID: 37737910 DOI: 10.1007/s00122-023-04456-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 08/28/2023] [Indexed: 09/23/2023]
Abstract
KEY MESSAGE A major stable QTL for kernel number per spike was narrowed down to a 2.19-Mb region containing two potential candidate genes, and its effects on yield-related traits were characterized. Kernel number per spike (KNPS) in wheat is a key yield component. Dissection and characterization of major stable quantitative trait loci (QTLs) for KNPS would be of considerable value for the genetic improvement of yield potential using molecular breeding technology. We had previously reported a major stable QTL controlling KNPS, qKnps-4A. In the current study, primary fine-mapping analysis, based on the primary mapping population, located qKnps-4A to an interval of approximately 6.8-Mb from 649.0 to 655.8 Mb on chromosome 4A refering to 'Kenong 9204' genome. Further fine-mapping analysis based on a secondary mapping population narrowed qKnps-4A to an approximately 2.19-Mb interval from 653.72 to 655.91 Mb. Transcriptome sequencing, gene function annotation analysis and homologous gene related reports showed that TraesKN4A01HG38570 and TraesKN4A01HG38590 were most likely to be candidate genes of qKnps-4A. Phenotypic analysis based on paired near-isogenic lines in the target region showed that qKnps-4A increased KNPS mainly by increasing the number of central florets per spike. We also evaluated the effects of qKnps-4A on other yield-related traits. Moreover, we dissected the QTL cluster of qKnps-4A and qTkw-4A and proved that the phenotypic effects were probably due to close linkage of two or more genes rather than pleiotropic effects of a single gene. This study provides molecular marker resource for wheat molecular breeding designed to improve yield potential, and lay the foundation for gene functional analysis of qKnps-4A.
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Affiliation(s)
- Ran Qin
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Tianhang Ma
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yibiao Cai
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Xinyao Shi
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Jiajia Cheng
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Jizi Dong
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Chenyang Wang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Shihui Li
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Guoqing Pan
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yuxiang Guan
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Lei Zhang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Shuang Yang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Huiyuan Xu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Chunhua Zhao
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Han Sun
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Ximei Li
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
- Shandong Key Laboratory of Dryland Farming Technology, Shandong Engineering Research Center of Germplasm Innovation and Utilization of Salt-Tolerant Crops, College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, China
| | - Yongzhen Wu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
| | - Junming Li
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Hebei Collaboration Innovation Center for Cell Signaling, Shijiazhuang, 050024, China.
| | - Fa Cui
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
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22
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Jin H, Tian Y, Zhang Y, Zhang R, Zhao H, Yang X, Song X, Dimitrov Y, Wu YE, Gao Q, Liu J, Zhang J, He Z. Genome-Wide Association Mapping of Processing Quality Traits in Common Wheat ( Triticum aestivum L.). Genes (Basel) 2023; 14:1816. [PMID: 37761956 PMCID: PMC10530800 DOI: 10.3390/genes14091816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 09/13/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023] Open
Abstract
Processing quality is an important economic wheat trait. The marker-assisted selection (MAS) method plays a vital role in accelerating genetic improvement of processing quality. In the present study, processing quality in a panel of 165 cultivars grown in four environments was evaluated by mixograph. An association mapping analysis using 90 K and 660 K single nucleotide polymorphism (SNP) arrays identified 24 loci in chromosomes 1A, 1B (4), 1D, 2A, 2B (2), 3A, 3B, 3D (2), 4A (3), 4B, 5D (2), 6A, 7B (2) and 7D (2), explaining 10.2-42.5% of the phenotypic variances. Totally, 15 loci were stably detected in two or more environments. Nine loci coincided with known genes or QTL, whereas the other fifteen were novel loci. Seven candidate genes encoded 3-ketoacyl-CoA synthase, lipoxygenase, pyridoxal phosphate-dependent decarboxylase, sucrose synthase 3 and a plant lipid transfer protein/Par allergen. SNPs significantly associated with processing quality and accessions with more favorable alleles can be used for marker-assisted selection.
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Affiliation(s)
- Hui Jin
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Yuanyuan Tian
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100000, China; (Y.T.); (Y.Z.); (J.L.)
| | - Yan Zhang
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100000, China; (Y.T.); (Y.Z.); (J.L.)
| | - Rui Zhang
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Haibin Zhao
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Xue Yang
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Xizhang Song
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Yordan Dimitrov
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Yu-e Wu
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Qiang Gao
- Horticultural Branch of Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China;
| | - Jindong Liu
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100000, China; (Y.T.); (Y.Z.); (J.L.)
| | - Jumei Zhang
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (H.J.); (X.Y.); (X.S.); (Y.D.); (Y.W.)
| | - Zhonghu He
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100000, China; (Y.T.); (Y.Z.); (J.L.)
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23
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Tyrka M, Krajewski P, Bednarek PT, Rączka K, Drzazga T, Matysik P, Martofel R, Woźna-Pawlak U, Jasińska D, Niewińska M, Ługowska B, Ratajczak D, Sikora T, Witkowski E, Dorczyk A, Tyrka D. Genome-wide association mapping in elite winter wheat breeding for yield improvement. J Appl Genet 2023; 64:377-391. [PMID: 37120451 PMCID: PMC10457411 DOI: 10.1007/s13353-023-00758-8] [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: 12/11/2022] [Revised: 03/19/2023] [Accepted: 04/03/2023] [Indexed: 05/01/2023]
Abstract
Increased grain yield (GY) is the primary breeding target of wheat breeders. We performed the genome-wide association study (GWAS) on 168 elite winter wheat lines from an ongoing breeding program to identify the main determinants of grain yield. Sequencing of Diversity Array Technology fragments (DArTseq) resulted in 19,350 single-nucleotide polymorphism (SNP) and presence-absence variation (PAV) markers. We identified 15 main genomic regions located in ten wheat chromosomes (1B, 2B, 2D, 3A, 3D, 5A, 5B, 6A, 6B, and 7B) that explained from 7.9 to 20.3% of the variation in grain yield and 13.3% of the yield stability. Loci identified in the reduced genepool are important for wheat improvement using marker-assisted selection. We found marker-trait associations between three genes involved in starch biosynthesis and grain yield. Two starch synthase genes (TraesCS2B03G1238800 and TraesCS2D03G1048800) and a sucrose synthase gene (TraesCS3D03G0024300) were found in regions of QGy.rut-2B.2, QGy.rut-2D.1, and QGy.rut-3D, respectively. These loci and other significantly associated SNP markers found in this study can be used for pyramiding favorable alleles in high-yielding varieties or to improve the accuracy of prediction in genomic selection.
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Affiliation(s)
- Mirosław Tyrka
- Department of Biotechnology and Bioinformatics, Rzeszow University of Technology, Powstańców Warszawy 6, 35-959, Rzeszów, Poland.
| | - Paweł Krajewski
- Institute of Plant Genetics, Polish Academy of Sciences, Strzeszyńska 34, 60-479, Poznań, Poland
| | - Piotr Tomasz Bednarek
- Plant Breeding and Acclimatization Institute - National Research Institute, Radzików, 05-870, Błonie, Poland
| | - Kinga Rączka
- Department of Biotechnology and Bioinformatics, Rzeszow University of Technology, Powstańców Warszawy 6, 35-959, Rzeszów, Poland
| | - Tadeusz Drzazga
- Małopolska Plant Breeding Ltd, Sportowa 21, 55-040, Kobierzyce, Poland
| | - Przemysław Matysik
- Plant Breeding Strzelce Group IHAR Ltd, Główna 20, 99-307, Strzelce, Poland
| | - Róża Martofel
- Poznań Plant Breeding Ltd, Kasztanowa 5, 63-004, Tulce, Poland
| | | | - Dorota Jasińska
- Poznań Plant Breeding Ltd, Kasztanowa 5, 63-004, Tulce, Poland
| | | | | | | | - Teresa Sikora
- DANKO Plant Breeders Ltd, Ks. Strzybnego 23, 47-411, Rudnik, Poland
| | - Edward Witkowski
- Plant Breeding Smolice Ltd, Smolice 146, 63-740, Kobylin, Poland
| | - Ada Dorczyk
- Plant Breeding Smolice Ltd, Smolice 146, 63-740, Kobylin, Poland
| | - Dorota Tyrka
- Department of Biotechnology and Bioinformatics, Rzeszow University of Technology, Powstańców Warszawy 6, 35-959, Rzeszów, Poland
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Zhang Y, Miao H, Xiao Y, Wang C, Zhang J, Shi X, Xie S, Wang C, Li T, Deng P, Chen C, Zhang H, Ji W. An intron-located single nucleotide variation of TaGS5-3D is related to wheat grain size through accumulating intron retention transcripts. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:193. [PMID: 37606787 DOI: 10.1007/s00122-023-04439-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/31/2023] [Indexed: 08/23/2023]
Abstract
KEY MESSAGE Thirty-three stable QTL for 13 yield-related traits across ten environments were identified in the PD34/MY47 RIL population, and a candidate gene TaGS5-3D in Qmt.nwafu.3D was preliminarily identified to affect grain-related traits through accumulation of specific transcripts. Dissecting the genetic basis of yield-related traits is pivotal for improvement of wheat yield potential. In this study, a recombinant inbred line (RIL) population genotyped by SNP markers was used to detect quantitative trait loci (QTL) related to yield-related traits in ten environments. A total of 102 QTL were detected, including 33 environmentally stable QTL and 69 putative QTL. Among them, Qmt.nwafu.3D was identified as a pleiotropic QTL in the physical interval of 149.77-154.11 Mb containing a potential candidate gene TaGS5-3D. An SNP (T > C) was detected in its ninth intron, and TaGS5-3D-C was validated as a superior allele associated with larger grains using a CAPS marker. Interestingly, we found that TaGS5-3D-C was closely related to significantly up-regulated expression of intron-retained transcript (TaGS5-3D-PD34.1), while TaGS5-3D-T was related to dominant expression of normal splicing transcript (TaGS5-3D-MY47.1). Our results indicated that alternative splicing associated with the SNP T/C could be involved in the regulation of grain-related traits, laying a foundation for the functional analysis of TaGS5-3D and its greater potential application in high-yield wheat breeding.
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Affiliation(s)
- Yaoyuan Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Hanxiao Miao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Yi Xiao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Chao Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Junjie Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Xiaoxi Shi
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Songfeng Xie
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Changyou Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Tingdong Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Pingchuan Deng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Chunhuan Chen
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Hong Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China.
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China.
| | - Wanquan Ji
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China.
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China.
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25
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Taranto F, Esposito S, De Vita P. Genomics for Yield and Yield Components in Durum Wheat. PLANTS (BASEL, SWITZERLAND) 2023; 12:2571. [PMID: 37447132 DOI: 10.3390/plants12132571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 06/29/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023]
Abstract
In recent years, many efforts have been conducted to dissect the genetic basis of yield and yield components in durum wheat thanks to linkage mapping and genome-wide association studies. In this review, starting from the analysis of the genetic bases that regulate the expression of yield for developing new durum wheat varieties, we have highlighted how, currently, the reductionist approach, i.e., dissecting the yield into its individual components, does not seem capable of ensuring significant yield increases due to diminishing resources, land loss, and ongoing climate change. However, despite the identification of genes and/or chromosomal regions, controlling the grain yield in durum wheat is still a challenge, mainly due to the polyploidy level of this species. In the review, we underline that the next-generation sequencing (NGS) technologies coupled with improved wheat genome assembly and high-throughput genotyping platforms, as well as genome editing technology, will revolutionize plant breeding by providing a great opportunity to capture genetic variation that can be used in breeding programs. To date, genomic selection provides a valuable tool for modeling optimal allelic combinations across the whole genome that maximize the phenotypic potential of an individual under a given environment.
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Affiliation(s)
- Francesca Taranto
- Institute of Biosciences and Bioresources (CNR-IBBR), 70126 Bari, Italy
| | - Salvatore Esposito
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA-Council for Agricultural Research and Economics, 71122 Foggia, Italy
| | - Pasquale De Vita
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA-Council for Agricultural Research and Economics, 71122 Foggia, Italy
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Song C, Xie K, Hu X, Zhou Z, Liu A, Zhang Y, Du J, Jia J, Gao L, Mao H. Genome wide association and haplotype analyses for the crease depth trait in bread wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1203253. [PMID: 37465391 PMCID: PMC10350514 DOI: 10.3389/fpls.2023.1203253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/14/2023] [Indexed: 07/20/2023]
Abstract
Wheat grain has a complex structure that includes a crease on one side, and tissues within the crease region play an important role in nutrient transportation during wheat grain development. However, the genetic architecture of the crease region is still unclear. In this study, 413 global wheat accessions were resequenced and a method was developed for evaluating the phenotypic data of crease depth (CD). The CD values exhibited continuous and considerable large variation in the population, and the broad-sense heritability was 84.09%. CD was found to be positively correlated with grain-related traits and negatively with quality-related traits. Analysis of differentiation of traits between landraces and cultivars revealed that grain-related traits and CD were simultaneously improved during breeding improvement. Moreover, 2,150.8-Mb genetic segments were identified to fall within the selective sweeps between the landraces and cultivars; they contained some known functional genes for quality- and grain-related traits. Genome-wide association study (GWAS) was performed using around 10 million SNPs generated by genome resequencing and 551 significant SNPs and 18 QTLs were detected significantly associated with CD. Combined with cluster analysis of gene expression, haplotype analysis, and annotated information of candidate genes, two promising genes TraesCS3D02G197700 and TraesCS5A02G292900 were identified to potentially regulate CD. To the best of our knowledge, this is the first study to provide the genetic basis of CD, and the genetic loci identified in this study may ultimately assist in wheat breeding programs.
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Affiliation(s)
- Chengxiang Song
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Kaidi Xie
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Zhihua Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Ankui Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yuwei Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jiale Du
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jizeng Jia
- Institute of Crop Sciences, Chinese Academy of Agriculture Sciences, Beijing, China
| | - Lifeng Gao
- Institute of Crop Sciences, Chinese Academy of Agriculture Sciences, Beijing, China
| | - Hailiang Mao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
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27
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Bilgrami S, Darzi Ramandi H, Farokhzadeh S, Rousseau-Gueutin M, Sobhani Najafabadi A, Ghaderian M, Huang P, Liu L. Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:161. [PMID: 37354229 DOI: 10.1007/s00122-023-04401-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 06/02/2023] [Indexed: 06/26/2023]
Abstract
KEY MESSAGE We report here the discovery of high-confidence MQTL regions and of putative candidate genes associated with seed weight in B. napus using a highly dense consensus genetic map and by comparing various large-scale multiomics datasets. Seed weight (SW) is a direct determinant of seed yield in Brassica napus and is controlled by many loci. To unravel the main genomic regions associated with this complex trait, we used 13 available genetic maps to construct a consensus and highly dense map, comprising 40,401 polymorphic markers and 9191 genetic bins, harboring a cumulative length of 3047.8 cM. Then, we performed a meta-analysis using 639 projected SW quantitative trait loci (QTLs) obtained from studies conducted since 1999, enabling the identification of 57 meta-QTLS (MQTLs). The confidence intervals of our MQTLs were 9.8 and 4.3 times lower than the average CIs of the original QTLs for the A and C subgenomes, respectively, resulting in the detection of some key genes and several putative novel candidate genes associated with SW. By comparing the genes identified in MQTL intervals with multiomics datasets and coexpression analyses of common genes, we defined a more reliable and shorter list of putative candidate genes potentially involved in the regulation of seed maturation and SW. As an example, we provide a list of promising genes with high expression levels in seeds and embryos (e.g., BnaA03g04230D, BnaC03g08840D, BnaA10g29580D and BnaA03g27410D) that can be more finely studied through functional genetics experiments or that may be useful for MQTL-assisted breeding for SW. The high-density genetic consensus map and the single nucleotide polymorphism (SNP) physical map generated from the latest B. napus cv. Darmor-bzh v10 assembly will be a valuable resource for further mapping and map-based cloning of other important traits.
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Affiliation(s)
- Sayedehsaba Bilgrami
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China
| | - Hadi Darzi Ramandi
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
| | - Sara Farokhzadeh
- Department of Plant Production, College of Agriculture and Natural Resources of Darab, Shiraz University, Darab, Iran
| | | | - Ahmad Sobhani Najafabadi
- Department of Biotechnology, Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), Isfahan, Iran
| | - Mostafa Ghaderian
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, 45220, USA
| | - Pu Huang
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China
| | - Liezhao Liu
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China.
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28
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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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Kumar A, Saini DK, Saripalli G, Sharma PK, Balyan HS, Gupta PK. Meta-QTLs, ortho-meta QTLs and related candidate genes for yield and its component traits under water stress in wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2023; 29:525-542. [PMID: 37187772 PMCID: PMC10172426 DOI: 10.1007/s12298-023-01301-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 03/25/2023] [Accepted: 03/28/2023] [Indexed: 05/17/2023]
Abstract
Meta-QTLs (MQTLs), ortho-MQTLs, and related candidate genes (CGs) for yield and its seven component traits evaluated under water deficit conditions were identified in wheat. For this purpose, a high density consensus map and 318 known QTLs were used for identification of 56 MQTLs. Confidence intervals (CIs) of the MQTLs were narrower (0.7-21 cM; mean = 5.95 cM) than the CIs of the known QTLs (0.4-66.6 cM; mean = 12.72 cM). Forty-seven MQTLs were co-located with marker trait associations reported in previous genome-wide association studies. Nine selected MQTLs were declared as 'breeders MQTLs' for use in marker-assisted breeding (MAB). Utilizing known MQTLs and synteny/collinearity among wheat, rice and maize, 12 ortho-MQTLs were also identified. A total of 1497 CGs underlying MQTLs were also identified, which were subjected to in-silico expression analysis, leading to identification of 64 differentially expressed CGs (DECGs) under normal and water deficit conditions. These DECGs encoded a variety of proteins, including the following: zinc finger, cytochrome P450, AP2/ERF domain-containing proteins, plant peroxidase, glycosyl transferase, glycoside hydrolase. The expression of 12 CGs at seedling stage (3 h stress) was validated using qRT-PCR in two wheat genotypes, namely Excalibur (drought tolerant) and PBW343 (drought sensitive). Nine of the 12 CGs were up-regulated and three down-regulated in Excalibur. The results of the present study should prove useful for MAB, for fine mapping of promising MQTLs and for cloning of genes across the three cereals studied. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-023-01301-z.
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Affiliation(s)
- Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | | | - Gautam Saripalli
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD 20742 USA
| | - P. K. Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - H. S. Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - P. K. Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
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30
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Karnatam KS, Chhabra G, Saini DK, Singh R, Kaur G, Praba UP, Kumar P, Goyal S, Sharma P, Ranjan R, Sandhu SK, Kumar R, Vikal Y. Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding. Int J Mol Sci 2023; 24:ijms24076135. [PMID: 37047112 PMCID: PMC10093813 DOI: 10.3390/ijms24076135] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/14/2023] [Accepted: 03/17/2023] [Indexed: 04/14/2023] Open
Abstract
Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.
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Affiliation(s)
- Krishna Sai Karnatam
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Gautam Chhabra
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana 141001, India
| | - Rajveer Singh
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Gurwinder Kaur
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Umesh Preethi Praba
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Pankaj Kumar
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Simran Goyal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Priti Sharma
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Rumesh Ranjan
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana 141001, India
| | - Surinder K Sandhu
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana 141001, India
| | - Ramesh Kumar
- Indian Institute of Maize Research, Ludhiana 141001, India
| | - Yogesh Vikal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
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Zhao J, Li X, Qiao L, Zheng X, Wu B, Guo M, Feng M, Qi Z, Yang W, Zheng J. Identification of structural variations related to drought tolerance in wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:37. [PMID: 36897407 DOI: 10.1007/s00122-023-04283-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 11/07/2022] [Indexed: 06/18/2023]
Abstract
Structural variations are common in plant genomes, affecting meiotic recombination and distorted segregation in wheat. And presence/absence variations can significantly affect drought tolerance in wheat. Drought is a major abiotic stress limiting wheat production. Common wheat has a complex genome with three sub-genomes, which host large numbers of structural variations (SVs). SVs play critical roles in understanding the genetic contributions of plant domestication and phenotypic plasticity, but little is known about their genomic characteristics and their effects on drought tolerance. In the present study, high-resolution karyotypes of 180 doubled haploids (DHs) were developed. Signal polymorphisms between the parents involved with 8 presence-absence variations (PAVs) of tandem repeats (TR) distributed on the 7 (2A, 4A, 5A, 7A, 3B, 7B, and 2D) of 21 chromosomes. Among them, PAV on chromosome 2D showed distorted segregation, others transmit normal conforming to a 1:1 segregation ration in the population; and a PAVs recombination occurred on chromosome 2A. Association analysis of PAV and phenotypic traits under different water regimes, we found PAVs on chromosomes 4A, 5A, and 7B showed negative effect on grain length (GL) and grain width (GW); PAV.7A had opposite effect on grain thickness (GT) and spike length (SL), with the effect on traits differing under different water regimes. PAVs on linkage group 2A, 4A, 7A, 2D, and 7B associated with the drought tolerance coefficients (DTCs), and significant negative effect on drought resistance values (D values) were detected in PAV.7B. Additionally, quantitative trait loci (QTL) associated with phenotypic traits using the 90 K SNP array showed QTL for DTCs and grain-related traits in chromosomes 4A, and 5A, 3B were co-localized in differential regions of PAVs. These PAVs can cause the differentiation of the target region of SNP and could be used for genetic improvement of agronomic traits under drought stress via marker-assisted selection (MAS) breeding.
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Affiliation(s)
- Jiajia Zhao
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Xiaohua Li
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Ling Qiao
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Xingwei Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Bangbang Wu
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Meijun Guo
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China
- Jinzhong University, Jinzhong, China
| | - Meichen Feng
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China
| | - Zengjun Qi
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Wude Yang
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China.
| | - Jun Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China.
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Rahimi Y, Khahani B, Jamali A, Alipour H, Bihamta MR, Ingvarsson PK. Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis. G3 (BETHESDA, MD.) 2023; 13:jkac320. [PMID: 36458966 PMCID: PMC10248217 DOI: 10.1093/g3journal/jkac320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022]
Abstract
A genome-wide association study (GWAS) was used to identify associated loci with early vigor under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published quantitative trait loci (QTL) from recombinant inbred lines, double haploids, back-crosses, and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis. Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75% were located within or closed to protein-coding genes. In the MQTL analysis, 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals associated with MQTLs. These findings provide important information on the genetic basis of early vigor traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.
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Affiliation(s)
- Yousef Rahimi
- Department of Plant Biology, Uppsala BioCenter, Linnean Centre for Plant Biology in Uppsala, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
| | - Bahman Khahani
- Department of Plant Genetics and Production, College of Agriculture, Shiraz University, 71441-65186 Shiraz, Iran
| | - Ali Jamali
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, 31587-77871 Karaj, Iran
| | - Hadi Alipour
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Urmia University, 5756151818 Urmia, Iran
| | - Mohammad Reza Bihamta
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, 31587-77871 Karaj, Iran
| | - Pär K Ingvarsson
- Department of Plant Biology, Uppsala BioCenter, Linnean Centre for Plant Biology in Uppsala, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
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Horváth Á, Kiss T, Berki Z, Horváth ÁD, Balla K, Cseh A, Veisz O, Karsai I. Effects of genetic components of plant development on yield-related traits in wheat ( Triticum aestivum L.) under stress-free conditions. FRONTIERS IN PLANT SCIENCE 2023; 13:1070410. [PMID: 36844908 PMCID: PMC9945125 DOI: 10.3389/fpls.2022.1070410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/14/2022] [Indexed: 06/18/2023]
Abstract
The dynamics of plant development not only has an impact on ecological adaptation but also contributes to the realization of genetically determined yield potentials in various environments. Dissecting the genetic determinants of plant development becomes urgent due to the global climate change, which can seriously affect and even disrupt the locally adapted developmental patterns. In order to determine the role plant developmental loci played in local adaptation and yield formation, a panel of 188 winter and facultative wheat cultivars from diverse geographic locations were characterized with the 15K Illumina Single Nucleotide Polymorphism (SNP) chip and functional markers of several plant developmental genes and included into a multiseason field experiment. Genome-wide association analyses were conducted on five consecutive developmental phases spanning from the first node appearance to full heading together with various grain yield-related parameters. The panel was balanced for the PPD-D1 photoperiod response gene, which facilitated the analyses in the two subsets of photoperiod-insensitive and -sensitive genotypes in addition to the complete panel. PPD-D1 was the single highest source, explaining 12.1%-19.0% of the phenotypic variation in the successive developmental phases. In addition, 21 minor developmental loci were identified, each one explaining only small portions of the variance, but, together, their effects amounted to 16.6%-50.6% of phenotypic variance. Eight loci (2A_27, 2A_727, 4A_570, 5B_315, 5B_520, 6A_26, 7A_1-(VRN-A3), and 7B_732) were independent of PPD-D1. Seven loci were only detectable in the PPD-D1-insensitive genetic background (1A_539, 1B_487, 2D_649, 4A_9, 5A_584-(VRN-A1), 5B_571-(VRN-B1), and 7B_3-(VRN-B3)), and six loci were only detectable in the sensitive background, specifically 2A_740, 2D_25, 3A_579, 3B_414, 7A_218, 7A_689, and 7B_538. The combination of PPD-D1 insensitivity and sensitivity with the extremities of early or late alleles in the corresponding minor developmental loci resulted in significantly altered and distinct plant developmental patterns with detectable outcomes on some yield-related traits. This study examines the possible significance of the above results in ecological adaptation.
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Affiliation(s)
- Ádám Horváth
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
| | - Tibor Kiss
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
- Food and Wine Research Institute, Eszterházy Károly Catholic University, Eger, Hungary
| | - Zita Berki
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
| | - Ádám D. Horváth
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
| | - Krisztina Balla
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
| | - András Cseh
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
| | - Ottó Veisz
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
| | - Ildikó Karsai
- Agricultural Institute, Centre of Agriculture, Eötvös Loránd Research Network (ELKH), Martonvásár, Hungary
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Kong B, Ma J, Zhang P, Chen T, Liu Y, Che Z, Shahinnia F, Yang D. Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment. BMC Genomics 2023; 24:33. [PMID: 36658498 PMCID: PMC9854125 DOI: 10.1186/s12864-023-09119-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/05/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Grain yield is a complex and polygenic trait influenced by the photosynthetic source-sink relationship in wheat. The top three leaves, especially the flag leaf, are considered the major sources of photo-assimilates accumulated in the grain. Determination of significant genomic regions and candidate genes affecting flag leaf size can be used in breeding for grain yield improvement. RESULTS With the final purpose of understanding key genomic regions for flag leaf size, a meta-analysis of 521 initial quantitative trait loci (QTLs) from 31 independent QTL mapping studies over the past decades was performed, where 333 loci eventually were refined into 64 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs was 5.28 times less than that of the initial QTLs. Thirty-three MQTLs overlapped the marker trait associations (MTAs) previously reported in genome-wide association studies (GWAS) for flag leaf traits in wheat. A total of 2262 candidate genes for flag leaf size, which were involved in the peroxisome, basal transcription factor, and tyrosine metabolism pathways were identified in MQTL regions by the in silico transcriptome assessment. Of these, the expression analysis of the available genes revealed that 134 genes with > 2 transcripts per million (TPM) were highly and specifically expressed in the leaf. These candidate genes could be critical to affect flag leaf size in wheat. CONCLUSIONS The findings will make further insight into the genetic determinants of flag leaf size and provide some reliable MQTLs and putative candidate genes for the genetic improvement of flag leaf size in wheat.
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Affiliation(s)
- Binxue Kong
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Jingfu Ma
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Peipei Zhang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
| | - Tao Chen
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Yuan Liu
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, 730000, China
| | - Fahimeh Shahinnia
- Bavarian State Research Centre for Agriculture, Institute for Crop Science and Plant Breeding, 85354, Freising, Germany
| | - Delong Yang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
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35
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Ma J, Liu Y, Zhang P, Chen T, Tian T, Wang P, Che Z, Shahinnia F, Yang D. Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.). BMC PLANT BIOLOGY 2022; 22:607. [PMID: 36550393 PMCID: PMC9784057 DOI: 10.1186/s12870-022-03989-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes. RESULTS The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites. CONCLUSIONS Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.
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Grants
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- Key Sci & Tech Special Project of Gansu Province
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Affiliation(s)
- Jingfu Ma
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Yuan Liu
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peipei Zhang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
| | - Tao Chen
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Tian Tian
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peng Wang
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, Gansu, China
| | - Fahimeh Shahinnia
- Institute for Crop Science and Plant Breeding, Bavarian State Research Centre for Agriculture, Freising, Germany
| | - Delong Yang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China.
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Zhao J, Zheng X, Qiao L, Yang C, Wu B, He Z, Tang Y, Li G, Yang Z, Zheng J, Qi Z. Genome-wide association study reveals structural chromosome variations with phenotypic effects in wheat (Triticum aestivum L.). THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 112:1447-1461. [PMID: 36345647 DOI: 10.1111/tpj.16023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 10/26/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
Structural chromosome variations (SCVs) are large-scale genomic variations that can be detected by fluorescence in situ hybridization (FISH). SCVs have played important roles in the genome evolution of wheat (Triticum aestivum L.), but little is known about their genetic effects. In this study, a total of 543 wheat accessions from the Chinese wheat mini-core collection and the Shanxi Province wheat collection were used for chromosome analysis using oligonucleotide probe multiplex FISH. A total of 139 SCVs including translocations, pericentric inversions, presence/absence variations (PAVs), and copy number variations (CNVs) in heterochromatin were identified at 230 loci. The distribution frequency of SCVs varied between ecological regions and between landraces and modern cultivars. Structural analysis using SCVs as markers clearly divided the landraces and modern cultivars into different groups. There are very clear instances illustrating alien introgression and wide application of foreign germplasms improved the chromosome diversity of Chinese modern wheat cultivars. A genome-wide association study (GWAS) identified 29 SCVs associated with 12 phenotypic traits, and five (RT4AS•4AL-1DS/1DL•1DS-4AL, Mg2A-3, Mr3B-10, Mr7B-13, and Mr4A-7) of them were further validated using a doubled haploid population and advanced sib-lines, implying the potential value of these SCVs. Importantly, the number of favored SCVs that were associated with agronomic trait improvement was significantly higher in modern cultivars compared to landraces, indicating positive selection in wheat breeding. This study demonstrates the significant effects of SCVs during wheat breeding and provides an efficient method of mining favored SCVs in wheat and other crops.
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Affiliation(s)
- Jiajia Zhao
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xingwei Zheng
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Ling Qiao
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Chenkang Yang
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Bangbang Wu
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Ziming He
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yuqing Tang
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Guangrong Li
- Center for Informational Biology, School of Life Science and Technology, University of Electronic and Technology of China, Chengdu, 611731, China
| | - Zujun Yang
- Center for Informational Biology, School of Life Science and Technology, University of Electronic and Technology of China, Chengdu, 611731, China
| | - Jun Zheng
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Zengjun Qi
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
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The Integration of Genome-Wide Association Study and Homology Analysis to Explore the Genomic Regions and Candidate Genes for Panicle-Related Traits in Foxtail Millet. Int J Mol Sci 2022; 23:ijms232314735. [PMID: 36499063 PMCID: PMC9741022 DOI: 10.3390/ijms232314735] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 10/26/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
Panicle traits are important factors affecting yield, and their improvement has long been a critical goal in foxtail millet breeding. In order to understand the genetic basis of panicle formation, a large-scale genome-wide association study (GWAS) was performed in this study for six panicle-related traits based on 706,646 high-polymorphism SNP loci in 407 accessions. As a result, 87 quantitative trait loci (QTL) regions with a physical distance of less than 100 kb were detected to be associated with these traits in three environments. Among them, 27 core regions were stably detected in at least two environments. Based on rice-foxtail millet homologous comparison, expression, and haplotype analysis, 27 high-confidence candidate genes in the QTL regions, such as Si3g11200 (OsDER1), Si1g27910 (OsMADS6), Si7g27560 (GS5), etc., affected panicle-related traits by involving multiple plant growth regulator pathways, a photoperiod response, as well as panicle and grain development. Most of these genes showed multiple effects on different panicle-related traits, such as Si3g11200 affecting all six traits. In summary, this study clarified a strategy based on the integration of GWAS, a homologous comparison, and haplotype analysis to discover the genomic regions and candidate genes for important traits in foxtail millet. The detected QTL regions and candidate genes could be further used for gene clone and marker-assisted selection in foxtail millet breeding.
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Aloryi KD, Okpala NE, Amo A, Bello SF, Akaba S, Tian X. A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice. FRONTIERS IN PLANT SCIENCE 2022; 13:1035851. [PMID: 36466247 PMCID: PMC9709451 DOI: 10.3389/fpls.2022.1035851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 10/19/2022] [Indexed: 06/17/2023]
Abstract
Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.
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Affiliation(s)
- Kelvin Dodzi Aloryi
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Nnaemeka Emmanuel Okpala
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Aduragbemi Amo
- Institute of Plant Breeding, Genetics and Genomics University of Georgia, Athens, GA, United States
| | - Semiu Folaniyi Bello
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Selorm Akaba
- School of Agriculture, University of Cape Coast, Cape Coast, Ghana
| | - Xiaohai Tian
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
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39
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Zia MAB, Yousaf MF, Asim A, Naeem M. An overview of genome-wide association mapping studies in Poaceae species (model crops: wheat and rice). Mol Biol Rep 2022; 49:12077-12090. [DOI: 10.1007/s11033-022-08036-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022]
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40
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Du B, Wu J, Islam MS, Sun C, Lu B, Wei P, Liu D, Chen C. Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat. PLoS One 2022; 17:e0276602. [PMID: 36279291 PMCID: PMC9591062 DOI: 10.1371/journal.pone.0276602] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 10/11/2022] [Indexed: 11/05/2022] Open
Abstract
Flag leaf is an important organ for photosynthesis of wheat plants, and a key factor affecting wheat yield. In this study, quantitative trait loci (QTL) for flag leaf morphological traits in wheat reported since 2010 were collected to investigate the genetic mechanism of these traits. Integration of 304 QTLs from various mapping populations into a high-density consensus map composed of various types of molecular markers as well as QTL meta-analysis discovered 55 meta-QTLs (MQTL) controlling morphological traits of flag leaves, of which 10 MQTLs were confirmed by GWAS. Four high-confidence MQTLs (MQTL-1, MQTL-11, MQTL-13, and MQTL-52) were screened out from 55 MQTLs, with an average confidence interval of 0.82 cM and a physical distance of 9.4 Mb, according to the definition of hcMQTL. Ten wheat orthologs from rice (7) and Arabidopsis (3) that regulated leaf angle, development and morphogenesis traits were identified in the hcMQTL region using comparative genomics, and were speculated to be potential candidate genes regulating flag leaf morphological traits in wheat. The results from this study provides valuable information for fine mapping and molecular markers assisted selection to improve morphological characters in wheat flag leaf.
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Affiliation(s)
- Binbin Du
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Jia Wu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Md. Samiul Islam
- Department of Plant Pathology, College of Plant Science and Technology and the Key Lab of Crop Disease Monitoring & Safety Control in Hubei Province, Huazhong Agricultural University, Wuhan, China
| | - Chaoyue Sun
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Baowei Lu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Peipei Wei
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Dong Liu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Cunwu Chen
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
- * E-mail:
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41
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Transcriptional signatures of wheat inflorescence development. Sci Rep 2022; 12:17224. [PMID: 36241895 PMCID: PMC9568521 DOI: 10.1038/s41598-022-21571-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/28/2022] [Indexed: 01/06/2023] Open
Abstract
In order to maintain global food security, it will be necessary to increase yields of the cereal crops that provide most of the calories and protein for the world's population, which includes common wheat (Triticum aestivum L.). An important wheat yield component is the number of grain-holding spikelets which form on the spike during inflorescence development. Characterizing the gene regulatory networks controlling the timing and rate of inflorescence development will facilitate the selection of natural and induced gene variants that contribute to increased spikelet number and yield. In the current study, co-expression and gene regulatory networks were assembled from a temporal wheat spike transcriptome dataset, revealing the dynamic expression profiles associated with the progression from vegetative meristem to terminal spikelet formation. Consensus co-expression networks revealed enrichment of several transcription factor families at specific developmental stages including the sequential activation of different classes of MIKC-MADS box genes. This gene regulatory network highlighted interactions among a small number of regulatory hub genes active during terminal spikelet formation. Finally, the CLAVATA and WUSCHEL gene families were investigated, revealing potential roles for TtCLE13, TtWOX2, and TtWOX7 in wheat meristem development. The hypotheses generated from these datasets and networks further our understanding of wheat inflorescence development.
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Rahmanzadeh A, Khahani B, Taghavi SM, Khojasteh M, Osdaghi E. Genome-wide meta-QTL analyses provide novel insight into disease resistance repertoires in common bean. BMC Genomics 2022; 23:680. [PMID: 36192697 PMCID: PMC9531352 DOI: 10.1186/s12864-022-08914-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 09/27/2022] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Common bean (Phaseolus vulgaris) is considered a staple food in a number of developing countries. Several diseases attack the crop leading to substantial economic losses around the globe. However, the crop has rarely been investigated for multiple disease resistance traits using Meta-analysis approach. RESULTS AND CONCLUSIONS In this study, in order to identify the most reliable and stable quantitative trait loci (QTL) conveying disease resistance in common bean, we carried out a meta-QTL (MQTL) analysis using 152 QTLs belonging to 44 populations reported in 33 publications within the past 20 years. These QTLs were decreased into nine MQTLs and the average of confidence interval (CI) was reduced by 2.64 folds with an average of 5.12 cM in MQTLs. Uneven distribution of MQTLs across common bean genome was noted where sub-telomeric regions carry most of the corresponding genes and MQTLs. One MQTL was identified to be specifically associated with resistance to halo blight disease caused by the bacterial pathogen Pseudomonas savastanoi pv. phaseolicola, while three and one MQTLs were specifically associated with resistance to white mold and anthracnose caused by the fungal pathogens Sclerotinia sclerotiorum and Colletotrichum lindemuthianum, respectively. Furthermore, two MQTLs were detected governing resistance to halo blight and anthracnose, while two MQTLs were detected for resistance against anthracnose and white mold, suggesting putative genes governing resistance against these diseases at a shared locus. Comparative genomics and synteny analyses provide a valuable strategy to identify a number of well‑known functionally described genes as well as numerous putative novels candidate genes in common bean, Arabidopsis and soybean genomes.
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Affiliation(s)
- Asma Rahmanzadeh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
| | - Bahman Khahani
- Department of Plant Genetics and Production, College of Agriculture, Shiraz University, Shiraz, Iran
| | - S Mohsen Taghavi
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
| | - Moein Khojasteh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran.
| | - Ebrahim Osdaghi
- Department of Plant Protection, College of Agriculture, University of Tehran, Karaj, 31587-77871, Iran.
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Saini P, Sheikh I, Saini DK, Mir RR, Dhaliwal HS, Tyagi V. Consensus genomic regions associated with grain protein content in hexaploid and tetraploid wheat. Front Genet 2022; 13:1021180. [PMID: 36246648 PMCID: PMC9554612 DOI: 10.3389/fgene.2022.1021180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/13/2022] [Indexed: 11/13/2022] Open
Abstract
A meta-analysis of QTLs associated with grain protein content (GPC) was conducted in hexaploid and tetraploid wheat to identify robust and stable meta-QTLs (MQTLs). For this purpose, as many as 459 GPC-related QTLs retrieved from 48 linkage-based QTL mapping studies were projected onto the newly developed wheat consensus map. The analysis resulted in the prediction of 57 MQTLs and 7 QTL hotspots located on all wheat chromosomes (except chromosomes 1D and 4D) and the average confidence interval reduced 2.71-fold in the MQTLs and QTL hotspots compared to the initial QTLs. The physical regions occupied by the MQTLs ranged from 140 bp to 224.02 Mb with an average of 15.2 Mb, whereas the physical regions occupied by QTL hotspots ranged from 1.81 Mb to 36.03 Mb with a mean of 8.82 Mb. Nineteen MQTLs and two QTL hotspots were also found to be co-localized with 45 significant SNPs identified in 16 previously published genome-wide association studies in wheat. Candidate gene (CG) investigation within some selected MQTLs led to the identification of 705 gene models which also included 96 high-confidence CGs showing significant expressions in different grain-related tissues and having probable roles in GPC regulation. These significantly expressed CGs mainly involved the genes/gene families encoding for the following proteins: aminotransferases, early nodulin 93, glutamine synthetases, invertase/pectin methylesterase inhibitors, protein BIG GRAIN 1-like, cytochrome P450, glycosyl transferases, hexokinases, small GTPases, UDP-glucuronosyl/UDP-glucosyltransferases, and EamA, SANT/Myb, GNAT, thioredoxin, phytocyanin, and homeobox domains containing proteins. Further, eight genes including GPC-B1, Glu-B1-1b, Glu-1By9, TaBiP1, GSr, TaNAC019-A, TaNAC019-D, and bZIP-TF SPA already known to be associated with GPC were also detected within some of the MQTL regions confirming the efficacy of MQTLs predicted during the current study.
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Affiliation(s)
- Pooja Saini
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, India
| | - Imran Sheikh
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punajb Agricultural University, Ludhiana, India
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of Agriculture SKUAST-Kashmir, Srinagar, India
| | - Harcharan Singh Dhaliwal
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, India
| | - Vikrant Tyagi
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, India
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44
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Yang CJ, Ladejobi O, Mott R, Powell W, Mackay I. Analysis of historical selection in winter wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3005-3023. [PMID: 35864201 PMCID: PMC9482581 DOI: 10.1007/s00122-022-04163-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
KEY MESSAGE Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding.
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Affiliation(s)
- Chin Jian Yang
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - Olufunmilayo Ladejobi
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Richard Mott
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Wayne Powell
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - Ian Mackay
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK.
- IMplant Consultancy Ltd, Chelmsford, UK.
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45
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 PMCID: PMC9372038 DOI: 10.1038/s41598-022-18149-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 12/03/2022] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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46
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 DOI: 10.1101/2022.06.24.497482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 05/20/2023] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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47
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Bhinder G, Sharma S, Kaur H, Akhatar J, Mittal M, Sandhu S. Genomic Regions Associated With Seed Meal Quality Traits in Brassica napus Germplasm. FRONTIERS IN PLANT SCIENCE 2022; 13:882766. [PMID: 35909769 PMCID: PMC9333065 DOI: 10.3389/fpls.2022.882766] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 04/20/2022] [Indexed: 06/15/2023]
Abstract
The defatted Brassica napus (rapeseed) meal can be high-protein feed for livestock as the protein value of rapeseed meal is higher than that of the majority of other vegetable proteins. Extensive work has already been carried out on developing canola rapeseed where the focus was on reducing erucic acid and glucosinolate content, with less consideration to other antinutritional factors such as tannin, phytate, sinapine, crude fiber, etc. The presence of these antinutrients limits the use and marketing of rapeseed meals and a significant amount of it goes unused and ends up as waste. We investigated the genetic architecture of crude protein, methionine, tryptophan, total phenols, β-carotene, glucosinolates (GLSs), phytate, tannins, sinapine, and crude fiber content of defatted seed meal samples by conducting a genome-wide association study (GWAS), using a diversity panel comprising 96 B. napus genotypes. Genotyping by sequencing was used to identify 77,889 SNPs, spread over 19 chromosomes. Genetic diversity and phenotypic variations were generally high for the studied traits. A total of eleven genotypes were identified which showed high-quality protein, high antioxidants, and lower amount of antinutrients. A significant negative correlation between protein and limiting amino acids and a significant positive correlation between GLS and phytic acid were observed. General and mixed linear models were used to estimate the association between the SNP markers and the seed quality traits and quantile-quantile (QQ) plots were generated to allow the best-fit algorithm. Annotation of genomic regions around associated SNPs helped to predict various trait-related candidates such as ASP2 and EMB1027 (amino acid biosynthesis); HEMA2, GLU1, and PGM (tryptophan biosynthesis); MS3, CYSD1, and MTO1 (methionine biosynthesis); LYC (β-carotene biosynthesis); HDR and ISPF (MEP pathway); COS1 (riboflavin synthesis); UGT (phenolics biosynthesis); NAC073 (cellulose and hemicellulose biosynthesis); CYT1 (cellulose biosynthesis); BGLU45 and BGLU46 (lignin biosynthesis); SOT12 and UGT88A1 (flavonoid pathway); and CYP79A2, DIN2, and GSTT2 (GLS metabolism), etc. The functional validation of these candidate genes could confirm key seed meal quality genes for germplasm enhancement programs directed at improving protein quality and reducing the antinutritional components in B. napus.
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Affiliation(s)
| | - Sanjula Sharma
- Oilseeds Section, Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | | | - Javed Akhatar
- Oilseeds Section, Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
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48
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Pal N, Jan I, Saini DK, Kumar K, Kumar A, Sharma PK, Kumar S, Balyan HS, Gupta PK. Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2385-2405. [PMID: 35699741 DOI: 10.1007/s00122-022-04119-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 04/28/2022] [Indexed: 05/20/2023]
Abstract
In wheat, multiple disease resistance meta-QTLs (MDR-MQTLs) and underlying candidate genes for the three rusts were identified which may prove useful for development of resistant cultivars. Rust diseases in wheat are a major threat to global food security. Therefore, development of multiple disease-resistant cultivars (resistant to all three rusts) is a major goal in all wheat breeding programs worldwide. In the present study, meta-QTLs and candidate genes for multiple disease resistance (MDR) involving all three rusts were identified using 152 individual QTL mapping studies for resistance to leaf rust (LR), stem rust (SR), and yellow rust (YR). From these 152 studies, a total of 1,146 QTLs for resistance to three rusts were retrieved, which included 368 QTLs for LR, 291 QTLs for SR, and 487 QTLs for YR. Of these 1,146 QTLs, only 718 QTLs could be projected onto the consensus map saturated with 2, 34,619 markers. Meta-analysis of the projected QTLs resulted in the identification of 86 MQTLs, which included 71 MDR-MQTLs. Ten of these MDR-MQTLs were referred to as the 'Breeders' MQTLs'. Seventy-eight of the 86 MQTLs could also be anchored to the physical map of the wheat genome, and 54 MQTLs were validated by marker-trait associations identified during earlier genome-wide association studies. Twenty MQTLs (including 17 MDR-MQTLs) identified in the present study were co-localized with 44 known R genes. In silico expression analysis allowed identification of several differentially expressed candidate genes (DECGs) encoding proteins carrying different domains including the following: NBS-LRR, WRKY domains, F-box domains, sugar transporters, transferases, etc. The introgression of these MDR loci into high-yielding cultivars should prove useful for developing high yielding cultivars with resistance to all the three rusts.
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Affiliation(s)
- Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttrakhand, 263145, India
| | - Irfat Jan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India
| | - Kuldeep Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - P K Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Sundip Kumar
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttrakhand, 263145, India
| | - H S Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - P K Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India.
- Murdoch's Centre for Crop & Food Innovation, Murdoch University, Murdoch, Perth, WA 6150, Australia.
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49
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Identification and Validation of a Chromosome 4D Quantitative Trait Locus Hotspot Conferring Heat Tolerance in Common Wheat (Triticum aestivum L.). PLANTS 2022; 11:plants11060729. [PMID: 35336611 PMCID: PMC8949852 DOI: 10.3390/plants11060729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 03/03/2022] [Accepted: 03/07/2022] [Indexed: 11/24/2022]
Abstract
Understanding of the genetic mechanism of heat tolerance (HT) can accelerate and improve wheat breeding in dealing with a warming climate. This study identified and validated quantitative trait loci (QTL) responsible for HT in common wheat. The International Triticeae Mapping Initiative (ITMI) population, recombinant inbreed lines (RILs) derived from a cross between Synthetic W7984 and Opata M85, was phenotyped for shoot length, root length, whole plant length under heat stress and corresponding damage indices (DIs) to compare HT performances of individuals. Wide variations among the RILs were shown for all the traits. A total of 13 QTL including 9 major QTL and 4 minor QTL were identified, distributed on 6 wheat chromosomes. The six major QTL with the highest R2 were associated with different traits under heat stress. They were all from Opata M85 background and located within a 2.2 cm interval on chromosome 4D, making up a QTL hotspot conferring HT in common wheat. The QTL hotspot was validated by genotyping-phenotyping association analysis using single-nucleotide-polymorphism (SNP) assays. The QTL, especially the 4D QTL hotspot identified and validated in this study, are valuable for the further fine mapping and identification of key genes and exploring genetic mechanism of HT in wheat.
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Singh R, Saripalli G, Gautam T, Kumar A, Jan I, Batra R, Kumar J, Kumar R, Balyan HS, Sharma S, Gupta PK. Meta-QTLs, ortho-MetaQTLs and candidate genes for grain Fe and Zn contents in wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2022; 28:637-650. [PMID: 35465199 PMCID: PMC8986950 DOI: 10.1007/s12298-022-01149-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/09/2022] [Accepted: 02/15/2022] [Indexed: 05/06/2023]
Abstract
Majority of cereals are deficient in essential micronutrients including grain iron (GFe) and grain zinc (GZn), which are therefore the subject of research involving biofortification. In the present study, 11 meta-QTLs (MQTLs) including nine novel MQTLs for GFe and GZn contents were identified in wheat. Eight of these 11 MQTLs controlled both GFe and GZn. The confidence intervals of the MQTLs were narrower (0.51-15.75 cM) relative to those of the corresponding QTLs (0.6 to 55.1 cM). Two ortho-MQTLs involving three cereals (wheat, rice and maize) were also identified. Results of MQTLs were also compared with the results of earlier genome wide association studies (GWAS). As many as 101 candidate genes (CGs) underlying MQTLs were also identified. Twelve of these CGs were prioritized; these CGs encoded proteins with important domains (zinc finger, RING/FYVE/PHD type, flavin adenine dinucleotide linked oxidase, etc.) that are involved in metal ion binding, heme binding, iron binding, etc. qRT-PCR analysis was conducted for four of these 12 prioritized CGs using genotypes which have differed for GFe and GZn. Significant differential expression in these genotypes was observed at 14 and 28 days after anthesis. The MQTLs/CGs identified in the present study may be utilized in marker-assisted selection (MAS) for improvement of GFe/GZn contents and also for understanding the molecular basis of GFe/GZn homeostasis in wheat. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-022-01149-9.
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Affiliation(s)
- Rakhi Singh
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
- Department of Plant Science and Landscape Architecture, University of Maryland College Park, MD-20742 College Park, MD United States
| | - Tinku Gautam
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Irfat Jan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Ritu Batra
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Jitendra Kumar
- Dept. of Biotechnology, Govt. of India, National Agri-Food Biotechnology Institute (NABI), Sector 81 (Knowledge City), S.A.S. Nagar, 140306 Mohali, Punjab India
| | - Rahul Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Harindra Singh Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Shailendra Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
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