1
|
Aloryi KD, Okpala NE, Guo H, Karikari B, Amo A, Bello SF, Saini DK, Akaba S, Tian X. Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice. BMC Genomics 2024; 25:338. [PMID: 38575927 PMCID: PMC10993490 DOI: 10.1186/s12864-024-10219-z] [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: 11/13/2023] [Accepted: 03/13/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Due to rising costs, water shortages, and labour shortages, farmers across the globe now prefer a direct seeding approach. However, submergence stress remains a major bottleneck limiting the success of this approach in rice cultivation. The merger of accumulated rice genetic resources provides an opportunity to detect key genomic loci and candidate genes that influence the flooding tolerance of rice. RESULTS In the present study, a whole-genome meta-analysis was conducted on 120 quantitative trait loci (QTL) obtained from 16 independent QTL studies reported from 2004 to 2023. These QTL were confined to 18 meta-QTL (MQTL), and ten MQTL were successfully validated by independent genome-wide association studies from diverse natural populations. The mean confidence interval (CI) of the identified MQTL was 3.44 times narrower than the mean CI of the initial QTL. Moreover, four core MQTL loci with genetic distance less than 2 cM were obtained. By combining differentially expressed genes (DEG) from two transcriptome datasets with 858 candidate genes identified in the core MQTL regions, we found 38 common differentially expressed candidate genes (DECGs). In silico expression analysis of these DECGs led to the identification of 21 genes with high expression in embryo and coleoptile under submerged conditions. These DECGs encode proteins with known functions involved in submergence tolerance including WRKY, F-box, zinc fingers, glycosyltransferase, protein kinase, cytochrome P450, PP2C, hypoxia-responsive family, and DUF domain. By haplotype analysis, the 21 DECGs demonstrated distinct genetic differentiation and substantial genetic distance mainly between indica and japonica subspecies. Further, the MQTL7.1 was successfully validated using flanked marker S2329 on a set of genotypes with phenotypic variation. CONCLUSION This study provides a new perspective on understanding the genetic basis of submergence tolerance in rice. The identified MQTL and novel candidate genes lay the foundation for marker-assisted breeding/engineering of flooding-tolerant cultivars conducive to direct seeding.
Collapse
Grants
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- Key R&D Project in Hubei Province, China
Collapse
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
| | - Hong Guo
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Benjamin Karikari
- Département de phytologie, Université Laval, Québec, QC, Canada
- Department of Agricultural Biotechnology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Aduragbemi Amo
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, USA
- Texas A&M AgriLife Research and Extension Center, Weslaco, TX, USA
| | - Semiu Folaniyi Bello
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
- Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, USA
| | - 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.
| |
Collapse
|
2
|
Satasiya P, Patel S, Patel R, Raigar OP, Modha K, Parekh V, Joshi H, Patel V, Chaudhary A, Sharma D, Prajapati M. Meta-analysis of identified genomic regions and candidate genes underlying salinity tolerance in rice (Oryza sativa L.). Sci Rep 2024; 14:5730. [PMID: 38459066 PMCID: PMC10923909 DOI: 10.1038/s41598-024-54764-9] [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: 02/13/2023] [Accepted: 02/16/2024] [Indexed: 03/10/2024] Open
Abstract
Rice output has grown globally, yet abiotic factors are still a key cause for worry. Salinity stress seems to have the more impact on crop production out of all abiotic stresses. Currently one of the most significant challenges in paddy breeding for salinity tolerance with the help of QTLs, is to determine the QTLs having the best chance of improving salinity tolerance with the least amount of background noise from the tolerant parent. Minimizing the size of the QTL confidence interval (CI) is essential in order to primarily include the genes responsible for salinity stress tolerance. By considering that, a genome-wide meta-QTL analysis on 768 QTLs from 35 rice populations published from 2001 to 2022 was conducted to identify consensus regions and the candidate genes underlying those regions responsible for the salinity tolerance, as it reduces the confidence interval (CI) to many folds from the initial QTL studies. In the present investigation, a total of 65 MQTLs were extracted with an average CI reduced from 17.35 to 1.66 cM including the smallest of 0.01 cM. Identification of the MQTLs for individual traits and then classifying the target traits into correlated morphological, physiological and biochemical aspects, resulted in more efficient interpretation of the salinity tolerance, identifying the candidate genes and to understand the salinity tolerance mechanism as a whole. The results of this study have a huge potential to improve the rice genotypes for salinity tolerance with the help of MAS and MABC.
Collapse
Affiliation(s)
- Pratik Satasiya
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Sanyam Patel
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Ritesh Patel
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Om Prakash Raigar
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Kaushal Modha
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Vipul Parekh
- Department of Biotechnology, College of Forestry, Navsari Agricultural University, Navsari, Gujarat, India
| | - Haimil Joshi
- Coastal Soil Salinity Research Station Danti-Umbharat, Navsari Agricultural University, Navsari, Gujarat, India
| | - Vipul Patel
- Regional Rice Research Station, Vyara, Navsari Agricultural University, Navsari, Gujarat, India
| | - Ankit Chaudhary
- Kishorbhai Institute of Agriculture Sciences and Research Centre, Uka Tarsadia University, Bardoli, Gujarat, India.
| | - Deepak Sharma
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Maulik Prajapati
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| |
Collapse
|
3
|
Daryani P, Amirbakhtiar N, Soorni J, Loni F, Darzi Ramandi H, Shobbar ZS. Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach. RICE (NEW YORK, N.Y.) 2024; 17:7. [PMID: 38227151 DOI: 10.1186/s12284-024-00684-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 01/03/2024] [Indexed: 01/17/2024]
Abstract
The complex trait of yield is controlled by several quantitative trait loci (QTLs). Given the global water deficit issue, the development of rice varieties suitable for non-flooded cultivation holds significant importance in breeding programs. The powerful approach of Meta-QTL (MQTL) analysis can be used for the genetic dissection of complicated quantitative traits. In the current study, a comprehensive MQTL analysis was conducted to identify consistent QTL regions associated with drought tolerance and yield-related traits under water deficit conditions in rice. In total, 1087 QTLs from 134 rice populations, published between 2000 to 2021, were utilized in the analysis. Distinct MQTL analysis of the relevant traits resulted in the identification of 213 stable MQTLs. The confidence interval (CI) for the detected MQTLs was between 0.12 and 19.7 cM. The average CI of the identified MQTLs (4.68 cM) was 2.74 times narrower compared to the average CI of the initial QTLs. Interestingly, 63 MQTLs coincided with SNP peak positions detected by genome-wide association studies for yield and drought tolerance-associated traits under water deficit conditions in rice. Considering the genes located both in the QTL-overview peaks and the SNP peak positions, 19 novel candidate genes were introduced, which are associated with drought response index, plant height, panicle number, biomass, and grain yield. Moreover, an inclusive MQTL analysis was performed on all the traits to obtain "Breeding MQTLs". This analysis resulted in the identification of 96 MQTLs with a CI ranging from 0.01 to 9.0 cM. The mean CI of the obtained MQTLs (2.33 cM) was 4.66 times less than the mean CI of the original QTLs. Thirteen MQTLs fulfilling the criteria of having more than 10 initial QTLs, CI < 1 cM, and an average phenotypic variance explained greater than 10%, were designated as "Breeding MQTLs". These findings hold promise for assisting breeders in enhancing rice yield under drought stress conditions.
Collapse
Affiliation(s)
- Parisa Daryani
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Nazanin Amirbakhtiar
- National Plant Gene Bank of Iran, Seed and Plant Improvement Institute (SPII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Jahad Soorni
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Fatemeh Loni
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Hadi Darzi Ramandi
- Department of Plant Production and Genetics, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran.
| | - Zahra-Sadat Shobbar
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
| |
Collapse
|
4
|
Navea IP, Maung PP, Yang S, Han JH, Jing W, Shin NH, Zhang W, Chin JH. A meta-QTL analysis highlights genomic hotspots associated with phosphorus use efficiency in rice ( Oryza sativa L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1226297. [PMID: 37662146 PMCID: PMC10471825 DOI: 10.3389/fpls.2023.1226297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 07/31/2023] [Indexed: 09/05/2023]
Abstract
Phosphorus use efficiency (PUE) is a complex trait, governed by many minor quantitative trait loci (QTLs) with small effects. Advances in molecular marker technology have led to the identification of QTLs underlying PUE. However, their practical use in breeding programs remains challenging due to the unstable effects in different genetic backgrounds and environments, interaction with soil status, and linkage drag. Here, we compiled PUE QTL information from 16 independent studies. A total of 192 QTLs were subjected to meta-QTL (MQTL) analysis and were projected into a high-density SNP consensus map. A total of 60 MQTLs, with significantly reduced number of initial QTLs and confidence intervals (CI), were identified across the rice genome. Candidate gene (CG) mining was carried out for the 38 MQTLs supported by multiple QTLs from at least two independent studies. Genes related to amino and organic acid transport and auxin response were found to be abundant in the MQTLs linked to PUE. CGs were cross validated using a root transcriptome database (RiceXPro) and haplotype analysis. This led to the identification of the eight CGs (OsARF8, OsSPX-MFS3, OsRING141, OsMIOX, HsfC2b, OsFER2, OsWRKY64, and OsYUCCA11) modulating PUE. Potential donors for superior PUE CG haplotypes were identified through haplotype analysis. The distribution of superior haplotypes varied among subspecies being mostly found in indica but were largely scarce in japonica. Our study offers an insight on the complex genetic networks that modulate PUE in rice. The MQTLs, CGs, and superior CG haplotypes identified in our study are useful in the combination of beneficial alleles for PUE in rice.
Collapse
Affiliation(s)
- Ian Paul Navea
- Food Crops Molecular Breeding Laboratory, Department of Integrative Biological Sciences and Industry, Sejong University, Seoul, Republic of Korea
- Convergence Research Center for Natural Products, Sejong University, Seoul, Republic of Korea
| | - Phyu Phyu Maung
- Food Crops Molecular Breeding Laboratory, Department of Integrative Biological Sciences and Industry, Sejong University, Seoul, Republic of Korea
- Convergence Research Center for Natural Products, Sejong University, Seoul, Republic of Korea
| | - Shiyi Yang
- College of Life Sciences, National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, China
| | - Jae-Hyuk Han
- Food Crops Molecular Breeding Laboratory, Department of Integrative Biological Sciences and Industry, Sejong University, Seoul, Republic of Korea
- The International Rice Research Institute-Korea Office, National Institute of Crop Science, Rural Development Administration, Iseo-myeon, Republic of Korea
| | - Wen Jing
- College of Life Sciences, National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, China
| | - Na-Hyun Shin
- Food Crops Molecular Breeding Laboratory, Department of Integrative Biological Sciences and Industry, Sejong University, Seoul, Republic of Korea
- Convergence Research Center for Natural Products, Sejong University, Seoul, Republic of Korea
| | - Wenhua Zhang
- College of Life Sciences, National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, China
| | - Joong Hyoun Chin
- Food Crops Molecular Breeding Laboratory, Department of Integrative Biological Sciences and Industry, Sejong University, Seoul, Republic of Korea
- Convergence Research Center for Natural Products, Sejong University, Seoul, Republic of Korea
| |
Collapse
|
5
|
Sethi M, Saini DK, Devi V, Kaur C, Singh MP, Singh J, Pruthi G, Kaur A, Singh A, Chaudhary DP. Unravelling the genetic framework associated with grain quality and yield-related traits in maize ( Zea mays L.). Front Genet 2023; 14:1248697. [PMID: 37609038 PMCID: PMC10440565 DOI: 10.3389/fgene.2023.1248697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 07/26/2023] [Indexed: 08/24/2023] Open
Abstract
Maize serves as a crucial nutrient reservoir for a significant portion of the global population. However, to effectively address the growing world population's hidden hunger, it is essential to focus on two key aspects: biofortification of maize and improving its yield potential through advanced breeding techniques. Moreover, the coordination of multiple targets within a single breeding program poses a complex challenge. This study compiled mapping studies conducted over the past decade, identifying quantitative trait loci associated with grain quality and yield related traits in maize. Meta-QTL analysis of 2,974 QTLs for 169 component traits (associated with quality and yield related traits) revealed 68 MQTLs across different genetic backgrounds and environments. Most of these MQTLs were further validated using the data from genome-wide association studies (GWAS). Further, ten MQTLs, referred to as breeding-friendly MQTLs (BF-MQTLs), with a significant phenotypic variation explained over 10% and confidence interval less than 2 Mb, were shortlisted. BF-MQTLs were further used to identify potential candidate genes, including 59 genes encoding important proteins/products involved in essential metabolic pathways. Five BF-MQTLs associated with both quality and yield traits were also recommended to be utilized in future breeding programs. Synteny analysis with wheat and rice genomes revealed conserved regions across the genomes, indicating these hotspot regions as validated targets for developing biofortified, high-yielding maize varieties in future breeding programs. After validation, the identified candidate genes can also be utilized to effectively model the plant architecture and enhance desirable quality traits through various approaches such as marker-assisted breeding, genetic engineering, and genome editing.
Collapse
Affiliation(s)
- Mehak Sethi
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Veena Devi
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Charanjeet Kaur
- Department of Basic Sciences and Humanities, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Mohini Prabha Singh
- Department of Floriculture and Landscaping, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jasneet Singh
- Agricultural and Environmental Sciences, Macdonald Campus, McGill University, Montreal, QC, Canada
| | - Gomsie Pruthi
- Department of Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Amanpreet Kaur
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Alla Singh
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Dharam Paul Chaudhary
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| |
Collapse
|
6
|
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.
Collapse
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.
| |
Collapse
|
7
|
Zhao M, Du C, Zeng J, Gao Z, Zhu Y, Wang J, Zhang Y, Zhu Z, Wang Y, Chen M, Wang Y, Chang J, Yang G, He G, Li Y, Chen X. Integrated omic analysis provides insights into the molecular regulation of stress tolerance by partial root-zone drying in rice. FRONTIERS IN PLANT SCIENCE 2023; 14:1156514. [PMID: 37360728 PMCID: PMC10288491 DOI: 10.3389/fpls.2023.1156514] [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: 02/01/2023] [Accepted: 04/26/2023] [Indexed: 06/28/2023]
Abstract
Partial root-zone drying (PRD) is an effective water-saving irrigation strategy that improves stress tolerance and facilitates efficient water use in several crops. It has long been considered that abscisic acid (ABA)-dependent drought resistance may be involved during partial root-zone drying. However, the molecular mechanisms underlying PRD-mediated stress tolerance remain unclear. It's hypothesized that other mechanisms might contribute to PRD-mediated drought tolerance. Here, rice seedlings were used as a research model and the complex transcriptomic and metabolic reprogramming processes were revealed during PRD, with several key genes involved in osmotic stress tolerance identified by using a combination of physiological, transcriptome, and metabolome analyses. Our results demonstrated that PRD induces transcriptomic alteration mainly in the roots but not in the leaves and adjusts several amino-acid and phytohormone metabolic pathways to maintain the balance between growth and stress response compared to the polyethylene glycol (PEG)-treated roots. Integrated analysis of the transcriptome and metabolome associated the co-expression modules with PRD-induced metabolic reprogramming. Several genes encoding the key transcription factors (TFs) were identified in these co-expression modules, highlighting several key TFs, including TCP19, WRI1a, ABF1, ABF2, DERF1, and TZF7, involved in nitrogen metabolism, lipid metabolism, ABA signaling, ethylene signaling, and stress regulation. Thus, our work presents the first evidence that molecular mechanisms other than ABA-mediated drought resistance are involved in PRD-mediated stress tolerance. Overall, our results provide new insights into PRD-mediated osmotic stress tolerance, clarify the molecular regulation induced by PRD, and identify genes useful for further improving water-use efficiency and/or stress tolerance in rice.
Collapse
Affiliation(s)
- Minhua Zhao
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| | - Canghao Du
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jian Zeng
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| | - Zhihong Gao
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| | - Yongyong Zhu
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| | - Jinfei Wang
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| | - Yupeng Zhang
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| | - Zetao Zhu
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| | - Yaqiong Wang
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Mingjie Chen
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yuesheng Wang
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Junli Chang
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Guangxiao Yang
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Guangyuan He
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yin Li
- The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoyuan Chen
- Henry Fok School of Biology and Agriculture, Guangdong Engineering Technology Research Center for Efficient Utilization of Water and Soil Resources in North Region, Shaoguan University, Shaoguan, Guangdong, China
| |
Collapse
|
8
|
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.
Collapse
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
| |
Collapse
|
9
|
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.
Collapse
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
| |
Collapse
|
10
|
Kumari A, Sharma D, Sharma P, Wang C, Verma V, Patil A, Imran M, Singh MP, Kumar K, Paritosh K, Caragea D, Kapoor S, Chandel G, Grover A, Jagadish SVK, Katiyar-Agarwal S, Agarwal M. Meta-QTL and haplo-pheno analysis reveal superior haplotype combinations associated with low grain chalkiness under high temperature in rice. FRONTIERS IN PLANT SCIENCE 2023; 14:1133115. [PMID: 36968399 PMCID: PMC10031497 DOI: 10.3389/fpls.2023.1133115] [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: 12/28/2022] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Chalk, an undesirable grain quality trait in rice, is primarily formed due to high temperatures during the grain-filling process. Owing to the disordered starch granule structure, air spaces and low amylose content, chalky grains are easily breakable during milling thereby lowering head rice recovery and its market price. Availability of multiple QTLs associated with grain chalkiness and associated attributes, provided us an opportunity to perform a meta-analysis and identify candidate genes and their alleles contributing to enhanced grain quality. From the 403 previously reported QTLs, 64 Meta-QTLs encompassing 5262 non-redundant genes were identified. MQTL analysis reduced the genetic and physical intervals and nearly 73% meta-QTLs were narrower than 5cM and 2Mb, revealing the hotspot genomic regions. By investigating expression profiles of 5262 genes in previously published datasets, 49 candidate genes were shortlisted on the basis of their differential regulation in at least two of the datasets. We identified non-synonymous allelic variations and haplotypes in 39 candidate genes across the 3K rice genome panel. Further, we phenotyped a subset panel of 60 rice accessions by exposing them to high temperature stress under natural field conditions over two Rabi cropping seasons. Haplo-pheno analysis uncovered haplotype combinations of two starch synthesis genes, GBSSI and SSIIa, significantly contributing towards the formation of grain chalk in rice. We, therefore, report not only markers and pre-breeding material, but also propose superior haplotype combinations which can be introduced using either marker-assisted breeding or CRISPR-Cas based prime editing to generate elite rice varieties with low grain chalkiness and high HRY traits.
Collapse
Affiliation(s)
- Anita Kumari
- Department of Botany, University of Delhi, Delhi, India
| | - Divya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Priya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Sahil
- Department of Botany, University of Delhi, Delhi, India
| | - Chaoxin Wang
- Department of Computer Science, Kansas State University, Manhattan, KS, United States
| | - Vibha Verma
- Department of Plant Molecular Biology, University of Delhi, New Delhi, India
| | - Arun Patil
- Department of Plant Molecular Biology and Biotechnology, Indira Gandhi Krishi Vishwavidyalaya, Chattisgarh, India
| | - Md Imran
- Department of Botany, University of Delhi, Delhi, India
| | - Madan Pal Singh
- Division of Plant Physiology, Indian Council of Agricultural Research (ICAR), New Delhi, India
| | - Kuldeep Kumar
- National Institute for Plant Biotechnology, Indian Council of Agricultural Research (ICAR), New Delhi, India
| | - Kumar Paritosh
- Centre for Genetic Manipulation of Crop Plants, New Delhi, India
| | - Doina Caragea
- Department of Computer Science, Kansas State University, Manhattan, KS, United States
| | - Sanjay Kapoor
- Department of Plant Molecular Biology, University of Delhi, New Delhi, India
| | - Girish Chandel
- Department of Plant Molecular Biology and Biotechnology, Indira Gandhi Krishi Vishwavidyalaya, Chattisgarh, India
| | - Anil Grover
- Department of Plant Molecular Biology, University of Delhi, New Delhi, India
| | | | | | - Manu Agarwal
- Department of Botany, University of Delhi, Delhi, India
| |
Collapse
|
11
|
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.
Collapse
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
| |
Collapse
|
12
|
Arriagada O, Arévalo B, Cabeza RA, Carrasco B, Schwember AR. Meta-QTL Analysis for Yield Components in Common Bean ( Phaseolus vulgaris L.). PLANTS (BASEL, SWITZERLAND) 2022; 12:117. [PMID: 36616246 PMCID: PMC9824219 DOI: 10.3390/plants12010117] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/15/2022] [Accepted: 12/17/2022] [Indexed: 06/17/2023]
Abstract
Common bean is one of the most important legumes produced and consumed worldwide because it is a highly valuable food for the human diet. However, its production is mainly carried out by small farmers, who obtain average grain yields below the potential yield of the species. In this sense, numerous mapping studies have been conducted to identify quantitative trait loci (QTL) associated with yield components in common bean. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies. Consequently, the objective of this study was to perform a MQTL analysis to identify the most reliable and stable genomic regions associated with yield-related traits of common bean. A total of 667 QTL associated with yield-related traits reported in 21 different studies were collected. A total of 42 MQTL associated with yield-related traits were identified, in which the average confidence interval (CI) of the MQTL was 3.41 times lower than the CIs of the original QTL. Most of the MQTL (28) identified in this study contain QTL associated with yield and phenological traits; therefore, these MQTL can be useful in common bean breeding programs. Finally, a total of 18 candidate genes were identified and associated with grain yield within these MQTL, with functions related to ubiquitin ligase complex, response to auxin, and translation elongation factor activity.
Collapse
Affiliation(s)
- Osvin Arriagada
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
| | - Bárbara Arévalo
- Centro de Estudios en Alimentos Procesados, Talca 3460000, Chile
| | - Ricardo A. Cabeza
- Departamento de Producción Agrícola, Facultad de Ciencias Agrarias, Universidad de Talca, Talca 3460000, Chile
| | - Basilio Carrasco
- Centro de Estudios en Alimentos Procesados, Talca 3460000, Chile
| | - Andrés R. Schwember
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
| |
Collapse
|
13
|
Genetic structure and molecular mechanism underlying the stalk lodging traits in maize ( Zea mays L.). Comput Struct Biotechnol J 2022; 21:485-494. [PMID: 36618981 PMCID: PMC9803694 DOI: 10.1016/j.csbj.2022.12.037] [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: 08/30/2022] [Revised: 12/03/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
Stalk lodging seriously affects yield and quality of crops, and it can be caused by several factors, such as environments, developmental stages, and internal chemical components of plant stalks. Breeding of stalk lodging-resistant varieties is thus an important task for maize breeders. To better understand the genetic basis underlying stalk lodging resistance, several methods such as quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) have been used to mine potential gene resources. Based on different types of genetic populations and mapping methods, many significant loci associated with stalk lodging resistance have been identified so far. However, few work has been performed to compare and integrate these reported genetic loci. In this study, we first collected hundreds of QTLs and quantitative trait nucleotides (QTNs) related to stalk lodging traits in maize. Then we mapped and integrated the QTLs and QTNs in maize genome to identify overlapped hotspot regions. Based on the genomic confidence intervals harboring these overlapped hotspot regions, we predicted candidate genes related to stalk lodging traits. Meanwhile, we mapped reported genes to these hotspot regions. Finally, we constructed molecular regulatory networks underlying stalk lodging resistance in maize. Collectively, this study provides not only useful genetic loci for deeply exploring molecular mechanisms of stalk lodging resistance traits, but also potential candidate genes and targeted strategies for improving stalk lodging resistance to increase crop yields in future.
Collapse
|
14
|
Bashir S, Rehman N, Fakhar Zaman F, Naeem MK, Jamal A, Tellier A, Ilyas M, Silva Arias GA, Khan MR. Genome-wide characterization of the NLR gene family in tomato ( Solanum lycopersicum) and their relatedness to disease resistance. Front Genet 2022; 13:931580. [PMID: 36544493 PMCID: PMC9760929 DOI: 10.3389/fgene.2022.931580] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 11/08/2022] [Indexed: 12/12/2022] Open
Abstract
Nucleotide-binding leucine-rich-repeat receptors (NLR), the largest group of genes associated with plant disease resistance (R), have attracted attention due to their crucial role in protecting plants from pathogens. Genome-wide studies of NLRs have revealed conserved domains in the annotated tomato genome. The 321 NLR genes identified in the tomato genome have been randomly mapped to 12 chromosomes. Phylogenetic analysis and classification of NLRs have revealed that 211 genes share full-length domains categorized into three major clades (CNL, TNL, and RNL); the remaining 110 NLRs share partial domains and are classified in CN, TN, and N according to their motifs and gene structures. The cis-regulatory elements of NLRs exhibit the maximum number of these elements and are involved in response to biotic and abiotic stresses, pathogen recognition, and resistance. Analysis of the phylogenetic relationship between tomato NLRs and orthologs in other species has shown conservation among Solanaceae members and variation with A. thaliana. Synteny and Ka/Ks analyses of Solanum lycopersicum and Solanum tuberosum orthologs have underscored the importance of NLR conservation and diversification from ancestral species millions of years ago. RNA-seq data and qPCR analysis of early and late blight diseases in tomatoes revealed consistent NLR expression patterns, including upregulation in infected compared to control plants (with some exceptions), suggesting the role of NLRs as key regulators in early blight resistance. Moreover, the expression levels of NLRs associated with late blight resistance (Solyc04g007060 [NRC4] and Solyc10g008240 [RIB12]) suggested that they regulate S. lycopersicum resistance to P. infestans. These findings provide important fundamental knowledge for understanding NLR evolution and diversity and will empower the broader characterization of disease resistance genes for pyramiding through speed cloning to develop disease-tolerant varieties.
Collapse
Affiliation(s)
- Sehrish Bashir
- National Institute for Genomics and Advanced Biotechnology, National Agricultural Research Centre, Islamabad, Pakistan,PARC Institute for Advanced Studies in Agriculture, NARC, Islamabad, Pakistan
| | - Nazia Rehman
- National Institute for Genomics and Advanced Biotechnology, National Agricultural Research Centre, Islamabad, Pakistan,PARC Institute for Advanced Studies in Agriculture, NARC, Islamabad, Pakistan,*Correspondence: Nazia Rehman, ; Muhammad Ramzan Khan,
| | - Fabia Fakhar Zaman
- National Institute for Genomics and Advanced Biotechnology, National Agricultural Research Centre, Islamabad, Pakistan,PARC Institute for Advanced Studies in Agriculture, NARC, Islamabad, Pakistan
| | - Muhammad Kashif Naeem
- National Institute for Genomics and Advanced Biotechnology, National Agricultural Research Centre, Islamabad, Pakistan
| | - Atif Jamal
- Crop Disease Research Institute, National Agricultural Research Center, Islamabad, Pakistan
| | - Aurélien Tellier
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Muhammad Ilyas
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Gustavo Adolfo Silva Arias
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Muhammad Ramzan Khan
- National Institute for Genomics and Advanced Biotechnology, National Agricultural Research Centre, Islamabad, Pakistan,PARC Institute for Advanced Studies in Agriculture, NARC, Islamabad, Pakistan,*Correspondence: Nazia Rehman, ; Muhammad Ramzan Khan,
| |
Collapse
|
15
|
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.
Collapse
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
| |
Collapse
|
16
|
Akbari M, Sabouri H, Sajadi SJ, Yarahmadi S, Ahangar L, Abedi A, Katouzi M. Mega Meta-QTLs: A Strategy for the Production of Golden Barley (Hordeum vulgare L.) Tolerant to Abiotic Stresses. Genes (Basel) 2022; 13:genes13112087. [PMID: 36360327 PMCID: PMC9690463 DOI: 10.3390/genes13112087] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/06/2022] [Accepted: 11/07/2022] [Indexed: 11/12/2022] Open
Abstract
Abiotic stresses cause a significant decrease in productivity and growth in agricultural products, especially barley. Breeding has been considered to create resistance against abiotic stresses. Pyramiding genes for tolerance to abiotic stresses through selection based on molecular markers connected to Mega MQTLs of abiotic tolerance can be one of the ways to reach Golden Barley. In this study, 1162 original QTLs controlling 116 traits tolerant to abiotic stresses were gathered from previous research and mapped from various populations. A consensus genetic map was made, including AFLP, SSR, RFLP, RAPD, SAP, DArT, EST, CAPS, STS, RGA, IFLP, and SNP markers based on two genetic linkage maps and 26 individual linkage maps. Individual genetic maps were created by integrating individual QTL studies into the pre-consensus map. The consensus map covered a total length of 2124.43 cM with an average distance of 0.25 cM between markers. In this study, 585 QTLs and 191 effective genes related to tolerance to abiotic stresses were identified in MQTLs. The most overlapping QTLs related to tolerance to abiotic stresses were observed in MQTL6.3. Furthermore, three MegaMQTL were identified, which explained more than 30% of the phenotypic variation. MQTLs, candidate genes, and linked molecular markers identified are essential in barley breeding and breeding programs to develop produce cultivars resistant to abiotic stresses.
Collapse
Affiliation(s)
- Mahjoubeh Akbari
- Department of Plant Production, Collage of Agriculture Science and Natural Resource, Gonbad Kavous University, Gonbad-e Kavus 4971799151, Iran
| | - Hossein Sabouri
- Department of Plant Production, Collage of Agriculture Science and Natural Resource, Gonbad Kavous University, Gonbad-e Kavus 4971799151, Iran
- Correspondence: (H.S.); (M.K.); Tel.: +98-9111438917 (H.S.); +41-779660486 (M.K.)
| | - Sayed Javad Sajadi
- Department of Plant Production, Collage of Agriculture Science and Natural Resource, Gonbad Kavous University, Gonbad-e Kavus 4971799151, Iran
| | - Saeed Yarahmadi
- Horticulture-Crops Reseaech Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan 4969186951, Iran
| | - Leila Ahangar
- Department of Plant Production, Collage of Agriculture Science and Natural Resource, Gonbad Kavous University, Gonbad-e Kavus 4971799151, Iran
| | - Amin Abedi
- Department of Plant Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht 4199613776, Iran
| | - Mahnaz Katouzi
- Crop Génome Dynamics Group, Agroscope Changins, 1260 Nyon, Switzerland
- Correspondence: (H.S.); (M.K.); Tel.: +98-9111438917 (H.S.); +41-779660486 (M.K.)
| |
Collapse
|
17
|
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.
Collapse
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.
| |
Collapse
|
18
|
Anilkumar C, Sah RP, Muhammed Azharudheen TP, Behera S, Singh N, Prakash NR, Sunitha NC, Devanna BN, Marndi BC, Patra BC, Nair SK. Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification. Sci Rep 2022; 12:13832. [PMID: 35974066 PMCID: PMC9381546 DOI: 10.1038/s41598-022-17402-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
Quantitative trait loci (QTL) for rice grain weight identified using bi-parental populations in various environments were found inconsistent and have a modest role in marker assisted breeding and map-based cloning programs. Thus, the identification of a consistent consensus QTL region across populations is critical to deploy in marker aided breeding programs. Using the QTL meta-analysis technique, we collated rice grain weight QTL information from numerous studies done across populations and in diverse environments to find constitutive QTL for grain weight. Using information from 114 original QTL in meta-analysis, we discovered three significant Meta-QTL (MQTL) for grain weight on chromosome 3. According to gene ontology, these three MQTL have 179 genes, 25 of which have roles in developmental functions. Amino acid sequence BLAST of these genes indicated their orthologue conservation among core cereals with similar functions. MQTL3.1 includes the OsAPX1, PDIL, SAUR, and OsASN1 genes, which are involved in grain development and have been discovered to play a key role in asparagine biosynthesis and metabolism, which is crucial for source-sink regulation. Five potential candidate genes were identified and their expression analysis indicated a significant role in early grain development. The gene sequence information retrieved from the 3 K rice genome project revealed the deletion of six bases coding for serine and alanine in the last exon of OsASN1 led to an interruption in the synthesis of α-helix of the protein, which negatively affected the asparagine biosynthesis pathway in the low grain weight genotypes. Further, the MQTL3.1 was validated using linked marker RM7197 on a set of genotypes with extreme phenotypes. MQTL that have been identified and validated in our study have significant scope in MAS breeding and map-based cloning programs for improving rice grain weight.
Collapse
Affiliation(s)
- C Anilkumar
- ICAR-National Rice Research Institute, Cuttack, India.
| | | | | | | | - Namita Singh
- Indira Gandhi Krishi Vishwavidyalaya, Raipur, India
| | - Nitish Ranjan Prakash
- ICAR-Central Soil Salinity Research Institute, Regional Research Station, Canning Town, India
| | - N C Sunitha
- University of Agricultural Sciences, Bangalore, India
| | - B N Devanna
- ICAR-National Rice Research Institute, Cuttack, India
| | - B C Marndi
- ICAR-National Rice Research Institute, Cuttack, India
| | - B C Patra
- ICAR-National Rice Research Institute, Cuttack, India
| | | |
Collapse
|
19
|
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.
Collapse
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
| |
Collapse
|
20
|
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.
Collapse
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
| |
Collapse
|
21
|
Rai KK. Integrating speed breeding with artificial intelligence for developing climate-smart crops. Mol Biol Rep 2022; 49:11385-11402. [PMID: 35941420 PMCID: PMC9360691 DOI: 10.1007/s11033-022-07769-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 07/05/2022] [Indexed: 11/25/2022]
Abstract
INTRODUCTION In climate change, breeding crop plants with improved productivity, sustainability, and adaptability has become a daunting challenge to ensure global food security for the ever-growing global population. Correspondingly, climate-smart crops are also the need to regulate biomass production, which is imperative for the maintenance of ecosystem services worldwide. Since conventional breeding technologies for crop improvement are limited, time-consuming, and involve laborious selection processes to foster new and improved crop varieties. An urgent need is to accelerate the plant breeding cycle using artificial intelligence (AI) to depict plant responses to environmental perturbations in real-time. MATERIALS AND METHODS The review is a collection of authorized information from various sources such as journals, books, book chapters, technical bulletins, conference papers, and verified online contents. CONCLUSIONS Speed breeding has emerged as an essential strategy for accelerating the breeding cycles of crop plants by growing them under artificial light and temperature conditions. Furthermore, speed breeding can also integrate marker-assisted selection and cutting-edged gene-editing tools for early selection and manipulation of essential crops with superior agronomic traits. Scientists have recently applied next-generation AI to delve deeper into the complex biological and molecular mechanisms that govern plant functions under environmental cues. In addition, AIs can integrate, assimilate, and analyze complex OMICS data sets, an essential prerequisite for successful speed breeding protocol implementation to breed crop plants with superior yield and adaptability.
Collapse
Affiliation(s)
- Krishna Kumar Rai
- Centre of Advanced Study in Botany, Department of Botany, Institute of Science, Banaras Hindu University (BHU), 221005, Varanasi, Uttar Pradesh, India.
| |
Collapse
|
22
|
Veisi S, Sabouri A, Abedi A. Meta-analysis of QTLs and candidate genes associated with seed germination in rice ( Oryza sativa L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2022; 28:1587-1605. [PMID: 36389095 PMCID: PMC9530108 DOI: 10.1007/s12298-022-01232-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 08/18/2022] [Accepted: 09/16/2022] [Indexed: 06/12/2023]
Abstract
Seed germination is one of the critical stages of plant life, and many quantitative trait loci (QTLs) control this complex trait. Meta-analysis of QTLs is a powerful computational technique for estimating the most stable QTLs regardless of the population's genetic background. Besides, this analysis effectively narrows down the confidence interval (CI) to identify candidate genes (CGs) and marker development. In the current study, a comprehensive genome-wide meta-analysis was performed on QTLs associated with germination in rice. This analysis was conducted based on the data reported over the last two decades. In this case, various analyses were performed, including seed germination rate, plumule length, radicle length, germination percentage, coleoptile length, coleorhiza length, radicle fresh weight, germination potential, and germination index. A total of 67 QTLs were projected onto a reference map for these traits and then integrated into 32 meta-QTLs (MQTLs) to provide a genetic framework for seed germination. The average CI of MQTLs was considerably reduced from 15.125 to 8.73 cM compared to the initial QTLs. This situation identified 728 well-known functionally characterized genes and novel putative CGs for investigated traits. The fold change calculation demonstrated that 155 CGs had significant changes in expression analysis. In this case, 112 and 43 CGs were up-regulated and down-regulated during germination, respectively. This study provides an overview and compares genetic loci controlling traits related to seed germination in rice. The findings can bridge the gap between QTLs and CGs for seed germination. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-022-01232-1.
Collapse
Affiliation(s)
- Sheida Veisi
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P.O. Box: 41635-1314, Rasht, Iran
| | - Atefeh Sabouri
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P.O. Box: 41635-1314, Rasht, Iran
| | - Amin Abedi
- Department of Plant Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
| |
Collapse
|
23
|
Sheoran S, Gupta M, Kumari S, Kumar S, Rakshit S. Meta-QTL analysis and candidate genes identification for various abiotic stresses in maize ( Zea mays L.) and their implications in breeding programs. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:26. [PMID: 37309532 PMCID: PMC10248626 DOI: 10.1007/s11032-022-01294-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 03/26/2022] [Indexed: 06/14/2023]
Abstract
Global climate change leads to the concurrence of a number of abiotic stresses including moisture stress (drought, waterlogging), temperature stress (heat, cold), and salinity stress, which are the major factors affecting maize production. To develop abiotic stress tolerance in maize, many quantitative trait loci (QTL) have been identified, but very few of them have been utilized successfully in breeding programs. In this context, the meta-QTL analysis of the reported QTL will enable the identification of stable/real QTL which will pave a reliable way to introgress these QTL into elite cultivars through marker-assisted selection. In this study, a total of 542 QTL were summarized from 33 published studies for tolerance to different abiotic stresses in maize to conduct meta-QTL analysis using BiomercatorV4.2.3. Among those, only 244 major QTL with more than 10% phenotypic variance were preferably utilised to carry out meta-QTL analysis. In total, 32 meta-QTL possessing 1907 candidate genes were detected for different abiotic stresses over diverse genetic and environmental backgrounds. The MQTL2.1, 5.1, 5.2, 5.6, 7.1, 9.1, and 9.2 control different stress-related traits for combined abiotic stress tolerance. The candidate genes for important transcription factor families such as ERF, MYB, bZIP, bHLH, NAC, LRR, ZF, MAPK, HSP, peroxidase, and WRKY have been detected for different stress tolerances. The identified meta-QTL are valuable for future climate-resilient maize breeding programs and functional validation of candidate genes studies, which will help to deepen our understanding of the complexity of these abiotic stresses. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01294-9.
Collapse
Affiliation(s)
- Seema Sheoran
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 141004 India
- Present Address: ICAR-Indian Agricultural Research Institute, Regional Station, Karnal, 132001 India
| | - Mamta Gupta
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 141004 India
| | - Shweta Kumari
- ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012 India
| | - Sandeep Kumar
- Present Address: ICAR-Indian Agricultural Research Institute, Regional Station, Karnal, 132001 India
- ICAR-Indian Institute of Pulses Research, Regional Station, Phanda, Bhopal, 462030 India
| | - Sujay Rakshit
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 141004 India
| |
Collapse
|
24
|
Javed T, I I, Singhal RK, Shabbir R, Shah AN, Kumar P, Jinger D, Dharmappa PM, Shad MA, Saha D, Anuragi H, Adamski R, Siuta D. Recent Advances in Agronomic and Physio-Molecular Approaches for Improving Nitrogen Use Efficiency in Crop Plants. FRONTIERS IN PLANT SCIENCE 2022; 13:877544. [PMID: 35574130 PMCID: PMC9106419 DOI: 10.3389/fpls.2022.877544] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 03/11/2022] [Indexed: 05/05/2023]
Abstract
The efficiency with which plants use nutrients to create biomass and/or grain is determined by the interaction of environmental and plant intrinsic factors. The major macronutrients, especially nitrogen (N), limit plant growth and development (1.5-2% of dry biomass) and have a direct impact on global food supply, fertilizer demand, and concern with environmental health. In the present time, the global consumption of N fertilizer is nearly 120 MT (million tons), and the N efficiency ranges from 25 to 50% of applied N. The dynamic range of ideal internal N concentrations is extremely large, necessitating stringent management to ensure that its requirements are met across various categories of developmental and environmental situations. Furthermore, approximately 60 percent of arable land is mineral deficient and/or mineral toxic around the world. The use of chemical fertilizers adds to the cost of production for the farmers and also increases environmental pollution. Therefore, the present study focused on the advancement in fertilizer approaches, comprising the use of biochar, zeolite, and customized nano and bio-fertilizers which had shown to be effective in improving nitrogen use efficiency (NUE) with lower soil degradation. Consequently, adopting precision farming, crop modeling, and the use of remote sensing technologies such as chlorophyll meters, leaf color charts, etc. assist in reducing the application of N fertilizer. This study also discussed the role of crucial plant attributes such as root structure architecture in improving the uptake and transport of N efficiency. The crosstalk of N with other soil nutrients plays a crucial role in nutrient homeostasis, which is also discussed thoroughly in this analysis. At the end, this review highlights the more efficient and accurate molecular strategies and techniques such as N transporters, transgenes, and omics, which are opening up intriguing possibilities for the detailed investigation of the molecular components that contribute to nitrogen utilization efficiency, thus expanding our knowledge of plant nutrition for future global food security.
Collapse
Affiliation(s)
- Talha Javed
- College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China
- Department of Agronomy, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Indu I
- Indian Council of Agricultural Research (ICAR)-Indian Grassland and Fodder Research Institute, Jhansi, India
| | - Rajesh Kumar Singhal
- Indian Council of Agricultural Research (ICAR)-Indian Grassland and Fodder Research Institute, Jhansi, India
| | - Rubab Shabbir
- College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China
- Department of Plant Breeding and Genetics, Seed Science and Technology, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Adnan Noor Shah
- Department of Agricultural Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan
| | - Pawan Kumar
- Indian Council of Agricultural Research (ICAR)-Central Institute for Arid Horticulture, Bikaner, India
| | - Dinesh Jinger
- Research Centre, Indian Council of Agricultural Research (ICAR)-Indian Institute of Soil and Water Conservation, Anand, India
| | - Prathibha M. Dharmappa
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Horticultural Research, Bengaluru, India
| | - Munsif Ali Shad
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene, Hubei Hongshan Laboratory, Wuhan, China
| | - Debanjana Saha
- Centurion University of Technology and Management, Jatni, India
| | - Hirdayesh Anuragi
- Indian Council of Agricultural Research (ICAR)- Central Agroforestry Research Institute, Jhansi, India
| | - Robert Adamski
- Faculty of Process and Environmental Engineering, Łódź University of Technology, Łódź, Poland
| | - Dorota Siuta
- Faculty of Process and Environmental Engineering, Łódź University of Technology, Łódź, Poland
| |
Collapse
|
25
|
Sandhu N, Pruthi G, Prakash Raigar O, Singh MP, Phagna K, Kumar A, Sethi M, Singh J, Ade PA, Saini DK. Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship. Front Genet 2021; 12:807210. [PMID: 34992638 PMCID: PMC8724540 DOI: 10.3389/fgene.2021.807210] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.
Collapse
Affiliation(s)
| | | | | | | | - Kanika Phagna
- Indian Institute of Science Education and Research, Berhampur, India
| | - Aman Kumar
- Punjab Agricultural University, Ludhiana, India
| | - Mehak Sethi
- Punjab Agricultural University, Ludhiana, India
| | | | | | | |
Collapse
|
26
|
Pal N, Saini DK, Kumar S. Meta-QTLs, ortho-MQTLs and candidate genes for the traits contributing to salinity stress tolerance in common wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2021; 27:2767-2786. [PMID: 35035135 PMCID: PMC8720133 DOI: 10.1007/s12298-021-01112-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 12/04/2021] [Accepted: 12/07/2021] [Indexed: 05/20/2023]
Abstract
A meta-analysis of QTLs associated with the traits contributing to salinity tolerance was undertaken in wheat to detect consensus and robust meta-QTLs (MQTLs) using 844 known QTLs retrieved from 26 earlier studies. A consensus map with a total length of 4621.56 cM including 7710 markers was constructed using 21 individual linkage maps and three previously published integrated genetic maps. Out of 844 QTLs, 571 QTLs were projected on the consensus map which gave origin to 100 MQTLs. Interestingly, 49 MQTLs were co-located with marker-trait associations reported in wheat genome-wide association studies for the traits contributing to salinity stress tolerance. Five potential MQTLs associated with the major salinity-responsive traits were also identified to be utilized in the breeding programme. In the resulted MQTLs, the average confidence interval (CI, 3.58 cM) was reduced up to 4.16 folds compared to the mean CI of the initial QTLs. Furthermore, as many as 617 gene models including 81 most likely candidate genes (CGs) were identified in the high confidence MQTL regions. These most likely CGs encoded proteins mainly belonging to the following families: B-box-type zinc finger, cytochrome P450 protein, pentatricopeptide repeat, phospholipid/glycerol acyltransferase, F-box protein, small auxin-up RNA, UDP-glucosyltransferase, glutathione S-transferase protein, etc. In addition, ortho-MQTL analysis based on synteny among wheat, rice and barley was also performed which permitted the identification of six ortho-MQTLs among these three cereals. This meta-analysis defines a genome-wide landscape on the most stable and consistent loci associated with reliable molecular markers and candidate genes for salinity tolerance in wheat. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s12298-021-01112-0.
Collapse
Affiliation(s)
- Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttarakhand 263145 India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab 141004 India
| | - Sundip Kumar
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttarakhand 263145 India
| |
Collapse
|
27
|
Kumar S, Singh VP, Saini DK, Sharma H, Saripalli G, Kumar S, Balyan HS, Gupta PK. Meta-QTLs, ortho-MQTLs, and candidate genes for thermotolerance in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2021; 41:69. [PMID: 37309361 PMCID: PMC10236124 DOI: 10.1007/s11032-021-01264-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/04/2021] [Indexed: 06/14/2023]
Abstract
Meta-QTL analysis for thermotolerance in wheat was conducted to identify robust meta-QTLs (MQTLs). In this study, 441 QTLs related to 31 heat-responsive traits were projected on the consensus map with 50,310 markers. This exercise resulted in the identification of 85 MQTLs with confidence interval (CI) ranging from 0.11 to 34.9 cM with an average of 5.6 cM. This amounted to a 2.96-fold reduction relative to the mean CI (16.5 cM) of the QTLs used. Seventy-seven (77) of these MQTLs were also compared and verified with the results of recent genome-wide association studies (GWAS). The 85 MQTLs included seven MQTLs that are particularly useful for breeding purposes (we called them breeders' MQTLs). Seven ortho-MQTLs between wheat and rice genomes were also identified using synteny and collinearity. The MQTLs were used for the identification of 1,704 candidate genes (CGs). In silico expression analysis of these CGs permitted identification of 182 differentially expressed genes (DEGs), which included 36 high confidence CGs with known functions previously reported to be important for thermotolerance. These high confidence CGs encoded proteins belonging to the following families: protein kinase, WD40 repeat, glycosyltransferase, ribosomal protein, SNARE associated Golgi protein, GDSL lipase/esterase, SANT/Myb domain, K homology domain, etc. Thus, the present study resulted in the identification of MQTLs (including breeders' MQTLs), ortho-MQTLs, and underlying CGs, which could prove useful not only for molecular breeding for the development of thermotolerant wheat cultivars but also for future studies focused on understanding the molecular basis of thermotolerance. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-021-01264-7.
Collapse
Affiliation(s)
- Sourabh Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Vivudh Pratap Singh
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab India
| | - Hemant Sharma
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Sachin Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Harindra Singh Balyan
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| |
Collapse
|
28
|
Abdelrahman M, Selim ME, ElSayed MA, Ammar MH, Hussein FA, ElKholy NK, ElShamey EA, Khan N, Attia KA. Developing Novel Rice Genotypes Harboring Specific QTL Alleles Associated with High Grain Yield under Water Shortage Stress. PLANTS (BASEL, SWITZERLAND) 2021; 10:2219. [PMID: 34686028 PMCID: PMC8538742 DOI: 10.3390/plants10102219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/14/2021] [Accepted: 10/14/2021] [Indexed: 12/05/2022]
Abstract
Rice is considered a strategic crop for many countries around the world, being the main cash crop for farmers. Water shortage stress occurrence as a result of climate change is among the main threats challenging rice breeders in the last few decades. In the current study, 19 Fn-lines were developed from four populations by crossing a reverse thermo-responsive genic male sterile (rTGMS) line, M.J.5460S, with the three high-quality Egyptian commercial cultivars Giza177, Sakha105, Sakha106 and the promising line GZ7768 as male parents. These newly developed lines, along with their parents, and two water shortage stress-tolerant international genotypes (Azucena and IRAT170), were cultivated under water-shortage stress conditions and compared with their performance under well-watered conditions. Results indicated that the yielding ability of the 19 newly developed lines exceeded those for the two Egyptian parents (Giza177 and Sakha105) under well-watered conditions. The lines M.J5460S/GIZA177-3 and M.J5460S/GIZA177-12 were the best performing genotypes under water shortage stress conditions. The genetic and heritability in broad sense estimates indicated that direct selection for grain yield (GY) under water-shortage stress is highly effective in the current study. Molecular marker analysis revealed that M.J5460S/GIZA177-3 had accumulated the quantitative trait loci (QTL)s, on the chromosomes 2, 3, and 9, which contribute to GY under water-shortage stress from their high yielding tolerant ancestor, M.J5460S. It could be concluded that those lines are high yielding under both well-watered and water-stress conditions harboring several QTLs for yield enhancement under both conditions and that the markers RM555, RM14551, RM3199, RM257, RM242, and RM410 are among the markers that could be used in marker-assisted selection (MAS) breeding programs for such stress condition.
Collapse
Affiliation(s)
- Mohamed Abdelrahman
- Rice Research and Training Center, Field Crops Research Institute, Agricultural Research Center, Kafrelsheikh 33717, Egypt; (M.A.); (M.E.S.); (M.A.E.); (M.H.A.); (F.A.H.); (N.K.E.)
| | - Mahmoud E. Selim
- Rice Research and Training Center, Field Crops Research Institute, Agricultural Research Center, Kafrelsheikh 33717, Egypt; (M.A.); (M.E.S.); (M.A.E.); (M.H.A.); (F.A.H.); (N.K.E.)
| | - Mahmoud A. ElSayed
- Rice Research and Training Center, Field Crops Research Institute, Agricultural Research Center, Kafrelsheikh 33717, Egypt; (M.A.); (M.E.S.); (M.A.E.); (M.H.A.); (F.A.H.); (N.K.E.)
| | - Megahed H. Ammar
- Rice Research and Training Center, Field Crops Research Institute, Agricultural Research Center, Kafrelsheikh 33717, Egypt; (M.A.); (M.E.S.); (M.A.E.); (M.H.A.); (F.A.H.); (N.K.E.)
| | - Fatma A. Hussein
- Rice Research and Training Center, Field Crops Research Institute, Agricultural Research Center, Kafrelsheikh 33717, Egypt; (M.A.); (M.E.S.); (M.A.E.); (M.H.A.); (F.A.H.); (N.K.E.)
| | - Neama K. ElKholy
- Rice Research and Training Center, Field Crops Research Institute, Agricultural Research Center, Kafrelsheikh 33717, Egypt; (M.A.); (M.E.S.); (M.A.E.); (M.H.A.); (F.A.H.); (N.K.E.)
| | - Essam A. ElShamey
- Rice Research and Training Center, Field Crops Research Institute, Agricultural Research Center, Kafrelsheikh 33717, Egypt; (M.A.); (M.E.S.); (M.A.E.); (M.H.A.); (F.A.H.); (N.K.E.)
| | - Naeem Khan
- Department of Agronomy, Institute of Food and Agricultural Sciences, Florida University, Gainesville, FL 32611, USA;
| | - Kotb A. Attia
- Department of Biochemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
| |
Collapse
|
29
|
Saini DK, Chopra Y, Pal N, Chahal A, Srivastava P, Gupta PK. Meta-QTLs, ortho-MQTLs and candidate genes for nitrogen use efficiency and root system architecture in bread wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2021; 27:2245-2267. [PMID: 34744364 PMCID: PMC8526679 DOI: 10.1007/s12298-021-01085-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 05/04/2023]
Abstract
In wheat, meta-QTLs (MQTLs), ortho-MQTLs, and candidate genes (CGs) were identified for nitrogen use efficiency and root system architecture. For this purpose, 1788 QTLs were available from 24 studies published during 2006-2020. Of these, 1098 QTLs were projected onto the consensus map resulting in 118 MQTLs. The average confidence interval (CI) of MQTLs was reduced up to 8.56 folds in comparison to the average CI of QTLs. Of the 118 MQTLs, 112 were anchored to the physical map of the wheat reference genome. The physical interval of MQTLs ranged from 0.02 to 666.18 Mb with a mean of 94.36 Mb. Eighty-eight of these 112 MQTLs were verified by marker-trait associations (MTAs) identified in published genome-wide association studies (GWAS); the MQTLs that were verified using GWAS also included 9 most robust MQTLs, which are particularly useful for breeders; we call them 'Breeder's QTLs'. Some selected wheat MQTLs were further utilized for the identification of ortho-MQTLs for wheat and maize; 9 such ortho-MQTLs were available. As many as 1991 candidate genes (CGs) were also detected, which included 930 CGs with an expression level of > 2 transcripts per million in relevant organs/tissues. Among the CGs, 97 CGs with functions previously reported as important for the traits under study were selected. Based on homology analysis and expression patterns, 49 orthologues of 35 rice genes were also identified in MQTL regions. The results of the present study may prove useful for the improvement of selection strategy for yield potential, stability, and performance under N-limiting conditions. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s12298-021-01085-0.
Collapse
Affiliation(s)
- Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
| | - Yuvraj Chopra
- College of Agriculture, Punjab Agricultural University, Ludhiana, 141004 India
- Present Address: Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583 USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttarakhand 263145 India
| | - Amneek Chahal
- College of Agriculture, Punjab Agricultural University, Ludhiana, 141004 India
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| |
Collapse
|