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Bakala HS, Devi J, Singh G, Singh I. Drought and heat stress: insights into tolerance mechanisms and breeding strategies for pigeonpea improvement. Planta 2024; 259:123. [PMID: 38622376 DOI: 10.1007/s00425-024-04401-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 03/29/2024] [Indexed: 04/17/2024]
Abstract
MAIN CONCLUSION Pigeonpea has potential to foster sustainable agriculture and resilience in evolving climate change; understanding bio-physiological and molecular mechanisms of heat and drought stress tolerance is imperative to developing resilience cultivars. Pigeonpea is an important legume crop that has potential resilience in the face of evolving climate scenarios. However, compared to other legumes, there has been limited research on abiotic stress tolerance in pigeonpea, particularly towards drought stress (DS) and heat stress (HS). To address this gap, this review delves into the genetic, physiological, and molecular mechanisms that govern pigeonpea's response to DS and HS. It emphasizes the need to understand how this crop combats these stresses and exhibits different types of tolerance and adaptation mechanisms through component traits. The current article provides a comprehensive overview of the complex interplay of factors contributing to the resilience of pigeonpea under adverse environmental conditions. Furthermore, the review synthesizes information on major breeding techniques, encompassing both conventional methods and modern molecular omics-assisted tools and techniques. It highlights the potential of genomics and phenomics tools and their pivotal role in enhancing adaptability and resilience in pigeonpea. Despite the progress made in genomics, phenomics and big data analytics, the complexity of drought and heat tolerance in pigeonpea necessitate continuous exploration at multi-omic levels. High-throughput phenotyping (HTP) is crucial for gaining insights into perplexed interactions among genotype, environment, and management practices (GxExM). Thus, integration of advanced technologies in breeding programs is critical for developing pigeonpea varieties that can withstand the challenges posed by climate change. This review is expected to serve as a valuable resource for researchers, providing a deeper understanding of the mechanisms underlying abiotic stress tolerance in pigeonpea and offering insights into modern breeding strategies that can contribute to the development of resilient varieties suited for changing environmental conditions.
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Affiliation(s)
- Harmeet Singh Bakala
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India
| | - Jomika Devi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India
| | - Gurjeet Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India.
- Texas A&M University, AgriLife Research Center, Beaumont, TX, 77713, USA.
| | - Inderjit Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India
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Yu H, Bhat JA, Li C, Zhao B, Bu M, Zhang Z, Guo T, Feng X. Identification of superior and rare haplotypes to optimize branch number in soybean. Theor Appl Genet 2024; 137:93. [PMID: 38570354 PMCID: PMC10991007 DOI: 10.1007/s00122-024-04596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/07/2024] [Indexed: 04/05/2024]
Abstract
KEY MESSAGE Using the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean. Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.
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Affiliation(s)
- Hui Yu
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
- Zhejiang Lab, Hangzhou, 310012, China
| | | | - Candong Li
- Jiamusi Branch Academy of Heilongjiang Academy of Agricultural Sciences, Jiamusi, 154007, China
| | - Beifang Zhao
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Moran Bu
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Zhirui Zhang
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Tai Guo
- Jiamusi Branch Academy of Heilongjiang Academy of Agricultural Sciences, Jiamusi, 154007, China
| | - Xianzhong Feng
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
- Zhejiang Lab, Hangzhou, 310012, China.
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 101408, China.
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Singh P, Sundaram KT, Vinukonda VP, Venkateshwarlu C, Paul PJ, Pahi B, Gurjar A, Singh UM, Kalia S, Kumar A, Singh VK, Sinha P. Superior haplotypes of key drought-responsive genes reveal opportunities for the development of climate-resilient rice varieties. Commun Biol 2024; 7:89. [PMID: 38216712 PMCID: PMC10786901 DOI: 10.1038/s42003-024-05769-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 01/02/2024] [Indexed: 01/14/2024] Open
Abstract
Haplotype-based breeding is an emerging and innovative concept that enables the development of designer crop varieties by exploiting and exploring superior alleles/haplotypes among target genes to create new traits in breeding programs. In this regard, whole-genome re-sequencing of 399 genotypes (landraces and breeding lines) from the 3000 rice genomes panel (3K-RG) is mined to identify the superior haplotypes for 95 drought-responsive candidate genes. Candidate gene-based association analysis reveals 69 marker-trait associations (MTAs) in 16 genes for single plant yield (SPY) under drought stress. Haplo-pheno analysis of these 16 genes identifies superior haplotypes for seven genes associated with the higher SPY under drought stress. Our study reveals that the performance of lines possessing superior haplotypes is significantly higher (p ≤ 0.05) as measured by single plant yield (SPY), for the OsGSK1-H4, OsDSR2-H3, OsDIL1-H22, OsDREB1C-H3, ASR3-H88, DSM3-H4 and ZFP182-H4 genes as compared to lines without the superior haplotypes. The validation results indicate that a superior haplotype for the DREB transcription factor (OsDREB1C) is present in all the drought-tolerant rice varieties, while it was notably absent in all susceptible varieties. These lines carrying the superior haplotypes can be used as potential donors in haplotype-based breeding to develop high-yielding drought-tolerant rice varieties.
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Affiliation(s)
- Preeti Singh
- International Rice Research Institute (IRRI), South-Asia Hub, Hyderabad, India
| | - Krishna T Sundaram
- International Rice Research Institute (IRRI), South-Asia Hub, Hyderabad, India
| | | | | | - Pronob J Paul
- International Rice Research Institute (IRRI), South-Asia Hub, Hyderabad, India
| | - Bandana Pahi
- International Rice Research Institute (IRRI), South-Asia Hub, Hyderabad, India
| | - Anoop Gurjar
- International Rice Research Institute, South Asia Regional Centre (ISARC), Varanasi, India
| | - Uma Maheshwar Singh
- International Rice Research Institute, South Asia Regional Centre (ISARC), Varanasi, India
| | - Sanjay Kalia
- Department of Biotechnology, CGO Complex, Lodhi Road, New Delhi, India
| | - Arvind Kumar
- International Rice Research Institute, South Asia Regional Centre (ISARC), Varanasi, India
- International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
| | - Vikas K Singh
- International Rice Research Institute (IRRI), South-Asia Hub, Hyderabad, India.
| | - Pallavi Sinha
- International Rice Research Institute (IRRI), South-Asia Hub, Hyderabad, India.
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Liu G, Qiu D, Lu Y, Wu Y, Han X, Jiao Y, Wang T, Yang J, You A, Chen J, Zhang Z. Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice ( Oryza sativa L.). Genes (Basel) 2023; 14:2201. [PMID: 38137023 PMCID: PMC10742856 DOI: 10.3390/genes14122201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 12/06/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
The identification of superior haplotypes and haplotype combinations is essential for haplotype-based breeding (HBB), which provides selection targets for genomics-assisted breeding. In this study, genotypes of 42 functional genes in rice were analyzed by targeted capture sequencing in a panel of 180 Indica rice accessions. In total, 69 SNPs/Indels in seven genes were detected to be associated with grain length (GL), grain width (GW), ratio of grain length-width (L/W) and thousand-grain weight (TGW) using candidate gene-based association analysis, including BG1 and GS3 for GL, GW5 for GW, BG1 and GW5 for L/W, and AET1, SNAC1, qTGW3, DHD1 and GW5 for TGW. Furthermore, two haplotypes were identified for each of the seven genes according to these associated SNPs/Indels, and the amount of genetic variation explained by different haplotypes ranged from 3.24% to 27.66%. Additionally, three, three and eight haplotype combinations for GL, L/W and TGW explained 25.38%, 5.5% and 22.49% of the total genetic variation for each trait, respectively. Further analysis showed that Minghui63 had the superior haplotype combination Haplotype Combination 4 (HC4) for TGW. The most interesting finding was that some widely used restorer lines derived from Minghui63 also have the superior haplotype combination HC4, and our breeding varieties and lines using the haplotype-specific marker panel also confirmed that the TGW of the lines was much higher than that of their sister lines without HC4, suggesting that TGW-HC4 is the superior haplotype combination for TGW and can be utilized in rice breeding.
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Affiliation(s)
- Gang Liu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Dongfeng Qiu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Yuxia Lu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Yan Wu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
- Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Xuesong Han
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Yaru Jiao
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Tingbao Wang
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Jinsong Yang
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Aiqing You
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Jianguo Chen
- School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Zaijun Zhang
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
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5
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Benitez-Alfonso Y, Soanes BK, Zimba S, Sinanaj B, German L, Sharma V, Bohra A, Kolesnikova A, Dunn JA, Martin AC, Khashi U Rahman M, Saati-Santamaría Z, García-Fraile P, Ferreira EA, Frazão LA, Cowling WA, Siddique KHM, Pandey MK, Farooq M, Varshney RK, Chapman MA, Boesch C, Daszkowska-Golec A, Foyer CH. Enhancing climate change resilience in agricultural crops. Curr Biol 2023; 33:R1246-R1261. [PMID: 38052178 DOI: 10.1016/j.cub.2023.10.028] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Climate change threatens global food and nutritional security through negative effects on crop growth and agricultural productivity. Many countries have adopted ambitious climate change mitigation and adaptation targets that will exacerbate the problem, as they require significant changes in current agri-food systems. In this review, we provide a roadmap for improved crop production that encompasses the effective transfer of current knowledge into plant breeding and crop management strategies that will underpin sustainable agriculture intensification and climate resilience. We identify the main problem areas and highlight outstanding questions and potential solutions that can be applied to mitigate the impacts of climate change on crop growth and productivity. Although translation of scientific advances into crop production lags far behind current scientific knowledge and technology, we consider that a holistic approach, combining disciplines in collaborative efforts, can drive better connections between research, policy, and the needs of society.
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Affiliation(s)
| | - Beth K Soanes
- Centre for Plant Sciences, School of Biology, University of Leeds, Leeds LS2 9JT, UK
| | - Sibongile Zimba
- Centre for Plant Sciences, School of Biology, University of Leeds, Leeds LS2 9JT, UK; Horticulture Department, Lilongwe University of Agriculture and Natural Resources, P.O. Box 219, Lilongwe, Malawi
| | - Besiana Sinanaj
- Plants, Photosynthesis and Soil, School of Biosciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Liam German
- Centre for Plant Sciences, School of Biology, University of Leeds, Leeds LS2 9JT, UK
| | - Vinay Sharma
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Abhishek Bohra
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA 6150, Australia
| | - Anastasia Kolesnikova
- Biological Sciences, University of Southampton, Life Sciences Building 85, Highfield Campus, Southampton SO17 1BJ, UK
| | - Jessica A Dunn
- Plants, Photosynthesis and Soil, School of Biosciences, University of Sheffield, Sheffield S10 2TN, UK; Institute for Sustainable Food, University of Sheffield, Sheffield S10 2TN, UK
| | - Azahara C Martin
- Institute for Sustainable Agriculture (IAS-CSIC), Córdoba 14004, Spain
| | - Muhammad Khashi U Rahman
- Microbiology and Genetics Department, Universidad de Salamanca, Salamanca 37007, Spain; Institute for Agribiotechnology Research (CIALE), University of Salamanca, Villamayor de la Armuña 37185, Spain
| | - Zaki Saati-Santamaría
- Microbiology and Genetics Department, Universidad de Salamanca, Salamanca 37007, Spain; Institute for Agribiotechnology Research (CIALE), University of Salamanca, Villamayor de la Armuña 37185, Spain; Institute of Microbiology of the Czech Academy of Sciences, Vídeňská, Prague, Czech Republic
| | - Paula García-Fraile
- Microbiology and Genetics Department, Universidad de Salamanca, Salamanca 37007, Spain; Institute for Agribiotechnology Research (CIALE), University of Salamanca, Villamayor de la Armuña 37185, Spain
| | - Evander A Ferreira
- Institute of Agrarian Sciences, Federal University of Minas Gerais, Avenida Universitária 1000, 39404547, Montes Claros, Minas Gerais, Brazil
| | - Leidivan A Frazão
- Institute of Agrarian Sciences, Federal University of Minas Gerais, Avenida Universitária 1000, 39404547, Montes Claros, Minas Gerais, Brazil
| | - Wallace A Cowling
- The UWA Institute of Agriculture, University of Western Australia, Perth, WA 6009, Australia
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, University of Western Australia, Perth, WA 6009, Australia
| | - Manish K Pandey
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Muhammad Farooq
- The UWA Institute of Agriculture, University of Western Australia, Perth, WA 6009, Australia; Department of Plant Sciences, College of Agricultural and Marine Sciences, Sultan Qaboos University, Al-Khoud 123, Oman
| | - Rajeev K Varshney
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA 6150, Australia
| | - Mark A Chapman
- Biological Sciences, University of Southampton, Life Sciences Building 85, Highfield Campus, Southampton SO17 1BJ, UK
| | - Christine Boesch
- School of Food Science and Nutrition, Faculty of Environment, University of Leeds, Leeds LS2 9JT, UK
| | - Agata Daszkowska-Golec
- Institute of Biology, Biotechnology and Environmental Protection, Faculty of Natural Sciences, University of Silesia in Katowice, Jagiellonska 28, 40-032 Katowice, Poland
| | - Christine H Foyer
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK
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Joshi G, Soe YP, Palanog A, Hore TK, Nha CT, Calayugan MI, Inabangan-Asilo MA, Amparado A, Pandey ID, Cruz PCS, Hernandez JE, Swamy BPM. Meta-QTL s and haplotypes for efficient zinc biofortification of rice. Plant Genome 2023; 16:e20315. [PMID: 36896580 DOI: 10.1002/tpg2.20315] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
Biofortification of rice with improved grain zinc (Zn) content is the most sustainable and cost-effective approach to address Zn malnutrition in Asia. Genomics-assisted breeding using precise and consistent Zn quantitative trait loci (QTLs), genes, and haplotypes can fast-track the development of Zn biofortified rice varieties. We conducted the meta-analysis of 155 Zn QTLs reported from 26 different studies. Results revealed 57 meta-QTLs with a significant reduction of 63.2% and 80% in the number and confidence interval of the Zn QTLs, respectively. Meta-quantitative trait loci (MQTLs) regions were found to be enriched with diverse metal homeostasis genes; at least 11 MQTLs were colocated with 20 known major genes involved in the production of root exudates, metal uptake, transport, partitioning, and loading into grains in rice. These genes were differentially expressed in vegetative and reproductive tissues, and a complex web of interactions were observed among them. We identified superior haplotypes and their combinations for nine candidate genes (CGs), and the frequency and allelic effects of superior haplotypes varied in different subgroups. The precise MQTLs with high phenotypic variance, CGs, and superior haplotypes identified in our study are useful for an efficient Zn biofortification of rice and to ensure Zn as an essential component of all the future rice varieties through mainstreaming of Zn breeding.
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Affiliation(s)
- Gaurav Joshi
- Rice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines
- Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | | | | | - Tapas Kumer Hore
- Rice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines
| | - Chau Thanh Nha
- Philippines Rice Research Institute, Muñoz, Nueva Ecija, Philippines
| | | | - Mary Ann Inabangan-Asilo
- Rice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines
| | - Amery Amparado
- Rice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines
| | - Indra Deo Pandey
- Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | | | | | - B P Mallikarjuna Swamy
- Rice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines
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Sharma N, Raman H, Wheeler D, Kalenahalli Y, Sharma R. Data-driven approaches to improve water-use efficiency and drought resistance in crop plants. Plant Sci 2023; 336:111852. [PMID: 37659733 DOI: 10.1016/j.plantsci.2023.111852] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 08/23/2023] [Accepted: 08/29/2023] [Indexed: 09/04/2023]
Abstract
With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.
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Affiliation(s)
- Niharika Sharma
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia.
| | - Harsh Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia
| | - David Wheeler
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia
| | - Yogendra Kalenahalli
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, Telangana 502324, India
| | - Rita Sharma
- Department of Biological Sciences, BITS Pilani, Pilani Campus, Rajasthan 333031, India
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Yamasani MR, Pandu VR, Kalluru S, Bommaka RR, Bandela R, Duddu B, Komeri S, Kumbha D, Vemireddy LR. Haplotype analysis of QTLs governing early seedling vigor-related traits under dry-direct-seeded rice (Oryza sativa L.) conditions. Mol Biol Rep 2023; 50:8177-8188. [PMID: 37555871 DOI: 10.1007/s11033-023-08714-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/26/2023] [Indexed: 08/10/2023]
Abstract
BACKGROUND The eventual shifting of cultivation method from puddle transplanted rice to direct-seeded rice (DSR) to save water prompted researchers to develop DSR-suitable varieties. To achieve this, identification of molecular markers associated with must-have traits for DSR, especially early seedling vigour related traits is crucial. METHODS AND RESULTS In the present investigation, the haplotype analysis using flanking markers of three important quantitative trait loci (QTLs) for early seedling vigour-related traits viz., qSV-6a (RM204 and RM402) for root length; qVI (RM20429 and RM3) for seedling vigour index; qGP-6 (RM528 and RM400) for germination percentage revealed that the marker alleles were found to show significant associations with qVI and qGP-6 QTLs. The majority of genotypes with high early seedling vigour are with qVIHap-1 (220 and 160 bp) and qGPHap-1 (290 and 290 bp). The rice genotypes with superior haplotypes for early seedling vigour are BMF536, BMF540, BMF525, MM129 and MDP2. CONCLUSIONS In conclusion, here we demonstrated that the markers RM20429 and RM3 are associated with seedling vigour index whereas RM528 and RM400 are associated with germination percentage. Therefore, these markers can be utilized to develop varieties suitable for DSR conditions through haplotype-based breeding. In addition, the rice genotypes with superior haplotypes can be of immense value to use as donors or can be released as varieties also under DSR conditions.
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Affiliation(s)
- Mounika Reddy Yamasani
- Department of Genetics and Plant Breeding, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Vasanthi Raguru Pandu
- Department of Genetics and Plant Breeding, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Sudhamani Kalluru
- Department of Genetics and Plant Breeding, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Rupeshkumar Reddy Bommaka
- Department of Genetics and Plant Breeding, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Ramanamurthy Bandela
- Department of Statistics and Computer Applications, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Bharathi Duddu
- Department of Genetics and Plant Breeding, Regional Agricultural Research Station, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Srikanth Komeri
- Department of Molecular Biology and Biotechnology, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Dineshkumar Kumbha
- Department of Genetics and Plant Breeding, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India
| | - Lakshminarayana R Vemireddy
- Department of Molecular Biology and Biotechnology, S.V. Agricultural College, Acharya NG Ranga Agricultural University (ANGRAU), Tirupati, 517502, Andhra Pradesh, India.
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9
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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.). Front Plant Sci 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] [What about the content of this article? (0)] [Affiliation(s)] [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.
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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
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10
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Karikari B, Lemay MA, Belzile F. k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives. Genes (Basel) 2023; 14:1439. [PMID: 37510343 PMCID: PMC10379394 DOI: 10.3390/genes14071439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/04/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.
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Affiliation(s)
- Benjamin Karikari
- Département de Phytologie, Université Laval, Quebec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada
- Department of Agricultural Biotechnology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale P.O. Box TL 1882, Ghana
| | - Marc-André Lemay
- Département de Phytologie, Université Laval, Quebec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada
| | - François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada
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11
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Wang Y, Liu H, Meng Y, Liu J, Ye G. Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes. Front Plant Sci 2023; 14:1194119. [PMID: 37324692 PMCID: PMC10267709 DOI: 10.3389/fpls.2023.1194119] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 05/02/2023] [Indexed: 06/17/2023]
Abstract
Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.
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Affiliation(s)
- Yamei Wang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- School of Agriculture, Sun Yat-sen University, Shenzhen, China
| | - Hongyan Liu
- Sanya Nanfan Research Institute of Hainan University, Hainan University, Sanya, China
| | - Yun Meng
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Sanya Nanfan Research Institute of Hainan University, Hainan University, Sanya, China
| | - Jindong Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Guoyou Ye
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Strategic Innovation Platform, International Rice Research Institute, Manila, Philippines
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12
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Zhang R, Jia G, Diao X. geneHapR: an R package for gene haplotypic statistics and visualization. BMC Bioinformatics 2023; 24:199. [PMID: 37189023 DOI: 10.1186/s12859-023-05318-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/04/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND Together with application of next-generation sequencing technologies and increased accumulation of genomic variation data in different organism species, an opportunity for effectively identification of superior alleles of functional genes to facilitate marker-assisted selection is emerging, and the clarification of haplotypes of functional genes is becoming an essential target in recent study works. RESULTS In this paper, we describe an R package 'geneHapR' developed for haplotypes identification, statistics and visualization analysis of candidate genes. This package could integrate genotype data, genomic annotating information and phenotypic variation data to clarify genotype variations, evolutionary-ship, and morphological effects among haplotypes through variants visualization, network construction and phenotypic comparison. 'geneHapR' also provides functions for Linkage Disequilibrium block analysis and visualizing of haplotypes geo-distribution. CONCLUSIONS The R package 'geneHapR' provided an easy-to-use tool for haplotype identification, statistic and visualization for candidate gene and will provide useful clues for gene functional dissection and molecular-assistant pyramiding of beneficial alleles of functional locus in future breeding programs.
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Affiliation(s)
- Renliang Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guanqing Jia
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
| | - Xianmin Diao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
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Yu H, Bhat JA, Li C, Zhao B, Guo T, Feng X. Genome-wide survey identified superior and rare haplotypes for plant height in the north-eastern soybean germplasm of China. Mol Breed 2023; 43:22. [PMID: 37309452 PMCID: PMC10248691 DOI: 10.1007/s11032-023-01363-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 02/18/2023] [Indexed: 06/14/2023]
Abstract
The proper and efficient utilization of natural genetic diversity can significantly impact crop improvements. Plant height is a quantitative trait governing the plant type as well as the yield and quality of soybean. Here, we used a combined approach including a genome-wide association study (GWAS) and haplotype and candidate gene analyses to explore the genetic basis of plant height in diverse natural soybean populations. For the GWAS analysis, we used the whole-genome resequencing data of 196 diverse soybean cultivars collected from different accumulated temperature zones of north-eastern China to detect the significant single-nucleotide polymorphisms (SNPs) associated with plant height across three environments (E1, E2, and E3). A total of 33 SNPs distributed on four chromosomes, viz., Chr.02, Chr.04, Chr.06, and Chr.19, were identified to be significantly associated with plant height across the three environments. Among them, 23 were consistently detected in two or more environments and the remaining 10 were identified in only one environment. Interestingly, all the significant SNPs detected on the respective chromosomes fell within the physical interval of linkage disequilibrium (LD) decay (± 38.9 kb). Hence, these genomic regions were considered to be four quantitative trait loci (QTLs), viz., qPH2, qPH4, qPH6, and qPH19, regulating plant height. Moreover, the genomic region flanking all significant SNPs on four chromosomes exhibited strong LD. These significant SNPs thus formed four haplotype blocks, viz., Hap-2, Hap-4, Hap-6, and Hap-19. The number of haplotype alleles underlying each block varied from four to six, and these alleles regulate the different phenotypes of plant height ranging from dwarf to extra-tall heights. Nine candidate genes were identified within the four haplotype blocks, and these genes were considered putative candidates regulating soybean plant height. Hence, these stable QTLs, superior haplotypes, and candidate genes (after proper validation) can be deployed for the development of soybean cultivars with desirable plant heights. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01363-7.
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Affiliation(s)
- Hui Yu
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102 China
- Zhejiang Lab, Hangzhou, 310012 China
| | | | - Candong Li
- Jiamusi Branch Academy of Heilongjiang Academy of Agricultural Sciences, Jiamusi, 154007 China
| | - Beifang Zhao
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102 China
| | - Tai Guo
- Jiamusi Branch Academy of Heilongjiang Academy of Agricultural Sciences, Jiamusi, 154007 China
| | - Xianzhong Feng
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102 China
- Zhejiang Lab, Hangzhou, 310012 China
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14
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Bisht A, Saini DK, Kaur B, Batra R, Kaur S, Kaur I, Jindal S, Malik P, Sandhu PK, Kaur A, Gill BS, Wani SH, Kaur B, Mir RR, Sandhu KS, Siddique KHM. Multi-omics assisted breeding for biotic stress resistance in soybean. Mol Biol Rep 2023; 50:3787-3814. [PMID: 36692674 DOI: 10.1007/s11033-023-08260-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023]
Abstract
Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.
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Affiliation(s)
- Ashita Bisht
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
- CSK Himachal Pradesh Krishi Vishvavidyalaya, Highland Agricultural Research and Extension Centre, 175142, Kukumseri, Lahaul and Spiti, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India.
| | - Baljeet Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Ritu Batra
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, 25004, Meerut, India
| | - Sandeep Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Ishveen Kaur
- Agriculture, Environmental and Sustainability Sciences, College of sciences, University of Texas Rio Grande Valley, 78539, Edinburg, TX, USA
| | - Suruchi Jindal
- Division of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, India
| | - Palvi Malik
- , Gurdev Singh Khush Institute of Genetics, Plant Breeding and Biotechnology, Punjab Agricultural University,, 141004, Ludhiana, India
| | - Pawanjit Kaur Sandhu
- Department of Chemistry, University of British Columbia, V1V 1V7, Okanagan, Kelowna, Canada
| | - Amandeep Kaur
- Division of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, India
| | - Balwinder Singh Gill
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Shabir Hussain Wani
- MRCFC Khudwani, Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir, Shalimar, India
| | - Balwinder Kaur
- Department of Entomology, UF/IFAS Research and Education Center, 33430, Belle Glade, Florida, USA
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, 193201, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, 99163, Pullman, WA, USA.
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, 6001, Perth, WA, Australia.
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15
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Gayacharan, Parida SK, Mondal N, Yadav R, Vishwakarma H, Rana JC. Mining legume germplasm for genetic gains: An Indian perspective. Front Genet 2023; 14:996828. [PMID: 36816034 PMCID: PMC9933516 DOI: 10.3389/fgene.2023.996828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 01/05/2023] [Indexed: 01/24/2023] Open
Abstract
Legumes play a significant role in food and nutritional security and contribute to environmental sustainability. Although legumes are highly beneficial crops, it has not yet been possible to enhance their yield and production to a satisfactory level. Amid a rising population and low yield levels, per capita average legume consumption in India has fallen by 71% over the last 50 years, and this has led to protein-related malnutrition in a large segment of the Indian population, especially women and children. Several factors have hindered attempts to achieve yield enhancement in grain legumes, including biotic and abiotic pressures, a lack of good ideotypes, less amenability to mechanization, poorer responsiveness to fertilizer input, and a poor genetic base. Therefore, there is a need to mine the approximately 0.4 million ex situ collections of legumes that are being conserved in gene banks globally for identification of ideal donors for various traits. The Indian National Gene Bank conserves over 63,000 accessions of legumes belonging to 61 species. Recent initiatives have been undertaken in consortia mode with the aim of unlocking the genetic potential of ex situ collections and conducting large-scale germplasm characterization and evaluation analyses. We assume that large-scale phenotyping integrated with omics-based science will aid the identification of target traits and their use to enhance genetic gains. Additionally, in cases where the genetic base of major legumes is narrow, wild relatives have been evaluated, and these are being exploited through pre-breeding. Thus far, >200 accessions of various legumes have been registered as unique donors for various traits of interest.
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Affiliation(s)
- Gayacharan
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Swarup K. Parida
- DBT-National Institute of Plant Genome Research, New Delhi, India
| | - Nupur Mondal
- Shivaji College, University of Delhi, New Delhi, India
| | - Rashmi Yadav
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | | | - Jai C. Rana
- Alliance of Bioversity International and CIAT, India Office, National Agricultural Science Complex, New Delhi, India
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16
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Candotti J, Christie N, Ployet R, Mostert‐O'Neill MM, Reynolds SM, Neves LG, Naidoo S, Mizrachi E, Duong TA, Myburg AA. Haplotype mining panel for genetic dissection and breeding in Eucalyptus. Plant J 2023; 113:174-185. [PMID: 36394447 PMCID: PMC10107644 DOI: 10.1111/tpj.16026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/06/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
To improve our understanding of genetic mechanisms underlying complex traits in plants, a comprehensive analysis of gene variants is required. Eucalyptus is an important forest plantation genus that is highly outbred. Trait dissection and molecular breeding in eucalypts currently relies on biallelic single-nucleotide polymorphism (SNP) markers. These markers fail to capture the large amount of haplotype diversity in these species, and thus multi-allelic markers are required. We aimed to develop a gene-based haplotype mining panel for Eucalyptus species. We generated 17 999 oligonucleotide probe sets for targeted sequencing of selected regions of 6293 genes implicated in growth and wood properties, pest and disease resistance, and abiotic stress responses. We identified and phased 195 834 SNPs using a read-based phasing approach to reveal SNP-based haplotypes. A total of 8915 target regions (at 4637 gene loci) passed tests for Mendelian inheritance. We evaluated the haplotype panel in four Eucalyptus species (E. grandis, E. urophylla, E. dunnii and E. nitens) to determine its ability to capture diversity across eucalypt species. This revealed an average of 3.13-4.52 haplotypes per target region in each species, and 33.36% of the identified haplotypes were shared by at least two species. This haplotype mining panel will enable the analysis of haplotype diversity within and between species, and provide multi-allelic markers that can be used for genome-wide association studies and gene-based breeding approaches.
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Affiliation(s)
- Julia Candotti
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | - Nanette Christie
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | - Raphael Ployet
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | - Marja M. Mostert‐O'Neill
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | - S. Melissa Reynolds
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | | | - Sanushka Naidoo
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | - Eshchar Mizrachi
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | - Tuan A. Duong
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
| | - Alexander A. Myburg
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa
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Barmukh R, Roorkiwal M, Dixit GP, Bajaj P, Kholova J, Smith MR, Chitikineni A, Bharadwaj C, Sreeman SM, Rathore A, Tripathi S, Yasin M, Vijayakumar AG, Rao Sagurthi S, Siddique KHM, Varshney RK. Characterization of 'QTL-hotspot' introgression lines reveals physiological mechanisms and candidate genes associated with drought adaptation in chickpea. J Exp Bot 2022; 73:7255-7272. [PMID: 36006832 PMCID: PMC9730794 DOI: 10.1093/jxb/erac348] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 08/24/2022] [Indexed: 05/16/2023]
Abstract
'QTL-hotspot' is a genomic region on linkage group 04 (CaLG04) in chickpea (Cicer arietinum) that harbours major-effect quantitative trait loci (QTLs) for multiple drought-adaptive traits, and it therefore represents a promising target for improving drought adaptation. To investigate the mechanisms underpinning the positive effects of 'QTL-hotspot' on seed yield under drought, we introgressed this region from the ICC 4958 genotype into five elite chickpea cultivars. The resulting introgression lines (ILs) and their parents were evaluated in multi-location field trials and semi-controlled conditions. The results showed that the 'QTL-hotspot' region improved seed yield under rainfed conditions by increasing seed weight, reducing the time to flowering, regulating traits related to canopy growth and early vigour, and enhancing transpiration efficiency. Whole-genome sequencing data analysis of the ILs and parents revealed four genes underlying the 'QTL-hotspot' region associated with drought adaptation. We validated diagnostic KASP markers closely linked to these genes using the ILs and their parents for future deployment in chickpea breeding programs. The CaTIFY4b-H2 haplotype of a potential candidate gene CaTIFY4b was identified as the superior haplotype for 100-seed weight. The candidate genes and superior haplotypes identified in this study have the potential to serve as direct targets for genetic manipulation and selection for chickpea improvement.
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Affiliation(s)
- Rutwik Barmukh
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Department of Genetics, Osmania University, Hyderabad, India
| | | | - Girish P Dixit
- ICAR - Indian Institute of Pulses Research (IIPR), Kanpur, India
| | - Prasad Bajaj
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Jana Kholova
- Crops Physiology & Modeling, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Department of Information Technologies, Faculty of Economics and Management, Czech University of Life Sciences Prague, Kamýcká 129, Prague, Czech Republic
| | - Millicent R Smith
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Australia
| | - Annapurna Chitikineni
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Chellapilla Bharadwaj
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia, Australia
- ICAR - Indian Agricultural Research Institute (IARI), Delhi, India
| | - Sheshshayee M Sreeman
- Department of Crop Physiology, University of Agricultural Sciences, Bengaluru, India
| | - Abhishek Rathore
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | | | - Mohammad Yasin
- RAK College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior, India
| | | | | | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia, Australia
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Singh G, Gudi S, Amandeep, Upadhyay P, Shekhawat PK, Nayak G, Goyal L, Kumar D, Kumar P, Kamboj A, Thada A, Shekhar S, Koli GK, DP M, Halladakeri P, Kaur R, Kumar S, Saini P, Singh I, Ayoubi H. Unlocking the hidden variation from wild repository for accelerating genetic gain in legumes. Front Plant Sci 2022; 13:1035878. [PMID: 36438090 PMCID: PMC9682257 DOI: 10.3389/fpls.2022.1035878] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 10/17/2022] [Indexed: 11/02/2023]
Abstract
The fluctuating climates, rising human population, and deteriorating arable lands necessitate sustainable crops to fulfil global food requirements. In the countryside, legumes with intriguing but enigmatic nitrogen-fixing abilities and thriving in harsh climatic conditions promise future food security. However, breaking the yield plateau and achieving higher genetic gain are the unsolved problems of legume improvement. Present study gives emphasis on 15 important legume crops, i.e., chickpea, pigeonpea, soybean, groundnut, lentil, common bean, faba bean, cowpea, lupin, pea, green gram, back gram, horse gram, moth bean, rice bean, and some forage legumes. We have given an overview of the world and India's area, production, and productivity trends for all legume crops from 1961 to 2020. Our review article investigates the importance of gene pools and wild relatives in broadening the genetic base of legumes through pre-breeding and alien gene introgression. We have also discussed the importance of integrating genomics, phenomics, speed breeding, genetic engineering and genome editing tools in legume improvement programmes. Overall, legume breeding may undergo a paradigm shift once genomics and conventional breeding are integrated in the near future.
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Affiliation(s)
- Gurjeet Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Amandeep
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Priyanka Upadhyay
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Pooja Kanwar Shekhawat
- Division of Crop Improvement, Plant Breeding and Genetics, Indian Council of Agricultural Research (ICAR)-Central Soil Salinity Research Institute, Karnal, Haryana, India
- Department of Plant Breeding and Genetics, Sri Karan Narendra Agriculture University, Jobner, Rajasthan, India
| | - Gyanisha Nayak
- Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India
| | - Lakshay Goyal
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Deepak Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana, India
| | - Pradeep Kumar
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Akashdeep Kamboj
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Antra Thada
- Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India
| | - Shweta Shekhar
- Department of Plant Molecular Biology and Biotechnology, Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India
| | - Ganesh Kumar Koli
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana, India
| | - Meghana DP
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Priyanka Halladakeri
- Department of Genetics and Plant Breeding, Anand Agricultural University, Anand, Gujarat, India
| | - Rajvir Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Sumit Kumar
- Department of Agronomy, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Pawan Saini
- CSB-Central Sericultural Research & Training Institute (CSR&TI), Ministry of Textiles, Govt. of India, Jammu- Kashmir, Pampore, India
| | - Inderjit Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Habiburahman Ayoubi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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Bhat JA, Adeboye KA, Ganie SA, Barmukh R, Hu D, Varshney RK, Yu D. Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.). Front Genet 2022; 13:953833. [PMID: 36419833 PMCID: PMC9677453 DOI: 10.3389/fgene.2022.953833] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 07/22/2022] [Indexed: 11/09/2022] Open
Abstract
Identifying the genetic components underlying yield-related traits in soybean is crucial for improving its production and productivity. Here, 211 soybean genotypes were evaluated across six environments for four yield-related traits, including seed yield per plant (SYP), number of pods per plant number of seeds per plant and 100-seed weight (HSW). Genome-wide association study (GWAS) and genomic prediction (GP) analyses were performed using 12,617 single nucleotide polymorphism markers from NJAU 355K SoySNP Array. A total of 57 SNPs were significantly associated with four traits across six environments and a combined environment using five Genome-wide association study models. Out of these, six significant SNPs were consistently identified in more than three environments using multiple GWAS models. The genomic regions (±670 kb) flanking these six consistent SNPs were considered stable QTL regions. Gene annotation and in silico expression analysis revealed 15 putative genes underlying the stable QTLs that might regulate soybean yield. Haplotype analysis using six significant SNPs revealed various allelic combinations regulating diverse phenotypes for the studied traits. Furthermore, the GP analysis revealed that accurate breeding values for the studied soybean traits is attainable at an earlier generation. Our study paved the way for increasing soybean yield performance within a short breeding cycle.
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Affiliation(s)
- Javaid Akhter Bhat
- Soybean Research Institution, National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
- International Genome Center, Jiangsu University, Zhenjiang, China
- *Correspondence: Javaid Akhter Bhat, ; Rajeev K. Varshney, ; Deyue Yu,
| | | | - Showkat Ahmad Ganie
- Plant Molecular Science and Centre of Systems and Synthetic Biology, Department of Biological Sciences, Royal Holloway University of London, Surrey, United Kingdom
| | - Rutwik Barmukh
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Dezhou Hu
- Soybean Research Institution, National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Rajeev K. Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Murdoch’s Centre for Crop & Food Innovation, State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Perth, WA, Australia
- *Correspondence: Javaid Akhter Bhat, ; Rajeev K. Varshney, ; Deyue Yu,
| | - Deyue Yu
- Soybean Research Institution, National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
- *Correspondence: Javaid Akhter Bhat, ; Rajeev K. Varshney, ; Deyue Yu,
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Bhat JA, Karikari B, Adeboye KA, Ganie SA, Barmukh R, Hu D, Varshney RK, Yu D. Identification of superior haplotypes in a diverse natural population for breeding desirable plant height in soybean. Theor Appl Genet 2022; 135:2407-2422. [PMID: 35639109 PMCID: PMC9271120 DOI: 10.1007/s00122-022-04120-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/28/2022] [Indexed: 06/14/2023]
Abstract
KEY MESSAGE Plant height of soybean is associated with a haplotype block on chromosome 19, which classified 211 soybean accessions into five distinct groups showing significant differences for the target trait. Genetic variation is pivotal for crop improvement. Natural populations are precious genetic resources. However, efficient strategies for the targeted utilization of these resources for quantitative traits, such as plant height (PH), are scarce. Being an important agronomic trait associated with soybean yield and quality, it is imperative to unravel the genetic mechanisms underlying PH in soybean. Here, a genome-wide association study (GWAS) was performed to identify single nucleotide polymorphisms (SNPs) significantly associated with PH in a natural population of 211 cultivated soybeans, which was genotyped with NJAU 355 K Soy SNP Array and evaluated across six environments. A total of 128 SNPs distributed across 17 chromosomes were found to be significantly associated with PH across six environments and a combined environment. Three significant SNPs were consistently identified in at least three environments on Chr.02 (AX-93958260), Chr.17 (AX-94154834), and Chr.19 (AX-93897200). Genomic regions of ~ 130 kb flanking these three consistent SNPs were considered as stable QTLs, which included 169 genes. Of these, 22 genes (including Dt1) were prioritized and defined as putative candidates controlling PH. The genomic region flanking 12 most significant SNPs was in strong linkage disequilibrium (LD). These SNPs formed a single haplotype block containing five haplotypes for PH, namely Hap-A, Hap-B, Hap-C, Hap-D, and Hap-E. Deployment of such superior haplotypes in breeding programs will enable development of improved soybean varieties with desirable plant height.
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Affiliation(s)
- Javaid Akhter Bhat
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China.
- International Genome Center, Jiangsu University, Zhenjiang, 212013, China.
| | - Benjamin Karikari
- Department of Crop Science, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Kehinde Adewole Adeboye
- Department of Agricultural Technology, Ekiti State Polytechnic, P. M. B. 1101, Isan, Nigeria
| | - Showkat Ahmad Ganie
- Department of Plant Science and Landscape Architecture, University of Connecticut, Storrs, USA
| | - Rutwik Barmukh
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Dezhou Hu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Rajeev K Varshney
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
- Murdoch's Centre for Crop and Food Innovation, State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
| | - Deyue Yu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China.
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21
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Kumar J, Kumar A, Sen Gupta D, Kumar S, DePauw RM. Reverse genetic approaches for breeding nutrient-rich and climate-resilient cereal and food legume crops. Heredity (Edinb) 2022; 128:473-496. [PMID: 35249099 PMCID: PMC9178024 DOI: 10.1038/s41437-022-00513-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 02/10/2022] [Accepted: 02/10/2022] [Indexed: 12/21/2022] Open
Abstract
In the last decade, advancements in genomics tools and techniques have led to the discovery of many genes. Most of these genes still need to be characterized for their associated function and therefore, such genes remain underutilized for breeding the next generation of improved crop varieties. The recent developments in different reverse genetic approaches have made it possible to identify the function of genes controlling nutritional, biochemical, and metabolic traits imparting drought, heat, cold, salinity tolerance as well as diseases and insect-pests. This article focuses on reviewing the current status and prospects of using reverse genetic approaches to breed nutrient-rich and climate resilient cereal and food legume crops.
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Affiliation(s)
- Jitendra Kumar
- Division of Crop Improvement, ICAR-Indian Institute of Pulses Research, Kanpur, India.
| | - Ajay Kumar
- Department of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA
| | - Debjyoti Sen Gupta
- Division of Crop Improvement, ICAR-Indian Institute of Pulses Research, Kanpur, India
| | - Sachin Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, 250 004, India
| | - Ron M DePauw
- Advancing Wheat Technologies, 118 Strathcona Rd SW, Calgary, AB, T3H 1P3, Canada
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22
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Hu G, Wu Y, Guo C, Lu D, Dong N, Chen B, Qiao Y, Zhang Y, Pan Q. Haplotype Analysis of Chloroplast Genomes for Jujube Breeding. Front Plant Sci 2022; 13:841767. [PMID: 35360311 PMCID: PMC8961131 DOI: 10.3389/fpls.2022.841767] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 02/11/2022] [Indexed: 05/31/2023]
Abstract
Jujube (family Rhamnaceae) is an important economic fruit tree in China. In this study, we reported 26 chloroplast (cp) sequences of jujube using Illumina paired-end sequencing. The sequence length of cp genome was 161, 367-161, 849 bp, which was composed of a large single-copy region (89053-89437 bp) and a small single-copy region (19356-19362 bp) separated by a pair of reverse repeat regions (26478-26533 bp). Each cp genome encodes the same 130 genes, including 112 unique genes, being quite conserved in genome structure and gene sequence. A total of 118 single base substitutions (SNPs) and 130 InDels were detected in 65 jujube accessions. Phylogenetic and haplotype network construction methods were used to analyze the origin and evolution of jujube and its sour-tasting relatives. We detected 32 effective haplotypes, consisting of 20 unique jujube haplotypes and 9 unique sour-jujube haplotypes. Compared with sour-jujube, jujube showed greater haplotype diversity at the chloroplast DNA level. To cultivate crisp and sweet fruit varieties featuring strong resistance, by combining the characteristics of sour-jujube and cultivated jujube, three hybrid combinations were suggested for reciprocal crosses: "Dongzao" × "Jingzao39," "Dongzao" × "Jingzao60," "Dongzao" × "Jingzao28." This study provides the basis for jujube species' identification and breeding, and lays the foundation for future research.
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Affiliation(s)
| | | | | | | | | | | | | | - Yuping Zhang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing Engineering Research Center for Deciduous Fruit Trees, Institute of Forestry and Pomology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Qinghua Pan
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing Engineering Research Center for Deciduous Fruit Trees, Institute of Forestry and Pomology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
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Lu L, Liu H, Wu Y, Yan G. Identification and Validation of a Chromosome 4D Quantitative Trait Locus Hotspot Conferring Heat Tolerance in Common Wheat (Triticum aestivum L.). Plants 2022; 11:729. [PMID: 35336611 PMCID: PMC8949852 DOI: 10.3390/plants11060729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 03/03/2022] [Accepted: 03/07/2022] [Indexed: 11/24/2022]
Abstract
Understanding of the genetic mechanism of heat tolerance (HT) can accelerate and improve wheat breeding in dealing with a warming climate. This study identified and validated quantitative trait loci (QTL) responsible for HT in common wheat. The International Triticeae Mapping Initiative (ITMI) population, recombinant inbreed lines (RILs) derived from a cross between Synthetic W7984 and Opata M85, was phenotyped for shoot length, root length, whole plant length under heat stress and corresponding damage indices (DIs) to compare HT performances of individuals. Wide variations among the RILs were shown for all the traits. A total of 13 QTL including 9 major QTL and 4 minor QTL were identified, distributed on 6 wheat chromosomes. The six major QTL with the highest R2 were associated with different traits under heat stress. They were all from Opata M85 background and located within a 2.2 cm interval on chromosome 4D, making up a QTL hotspot conferring HT in common wheat. The QTL hotspot was validated by genotyping-phenotyping association analysis using single-nucleotide-polymorphism (SNP) assays. The QTL, especially the 4D QTL hotspot identified and validated in this study, are valuable for the further fine mapping and identification of key genes and exploring genetic mechanism of HT in wheat.
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24
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Kumar P, Choudhary M, Halder T, Prakash NR, Singh V, V. VT, Sheoran S, T. RK, Longmei N, Rakshit S, Siddique KHM. Salinity stress tolerance and omics approaches: revisiting the progress and achievements in major cereal crops. Heredity (Edinb) 2022; 128:497-518. [DOI: 10.1038/s41437-022-00516-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 02/12/2022] [Accepted: 02/14/2022] [Indexed: 02/07/2023] Open
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Abstract
Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications. This review article highlights ways to mine haplotypes and apply them for complex trait dissection and in GAB approaches including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior haplotypes to hasten breeding progress will be key to safeguarding global food security.
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Affiliation(s)
- Javaid Akhter Bhat
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Deyue Yu
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Abhishek Bohra
- Crop Improvement Division, ICAR- Indian Institute of Pulses Research (ICAR- IIPR), Kanpur, India
| | - Showkat Ahmad Ganie
- Department of Biotechnology, Visva-Bharati, Santiniketan, 731235, WB, India.
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
- State Agricultural Biotechnology Centre, Centre for Crop & Food Research Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
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Sharmin RA, Karikari B, Chang F, Al Amin GM, Bhuiyan MR, Hina A, Lv W, Chunting Z, Begum N, Zhao T. Genome-wide association study uncovers major genetic loci associated with seed flooding tolerance in soybean. BMC Plant Biol 2021; 21:497. [PMID: 34715792 PMCID: PMC8555181 DOI: 10.1186/s12870-021-03268-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 09/29/2021] [Indexed: 06/01/2023]
Abstract
BACKGROUND Seed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage. RESULTS In the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation. CONCLUSIONS Our findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.
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Affiliation(s)
- Ripa Akter Sharmin
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
- Jagannath University, Dhaka, 1100, Bangladesh
| | - Benjamin Karikari
- Department of Crop Science, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Fangguo Chang
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - G M Al Amin
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Mashiur Rahman Bhuiyan
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Aiman Hina
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Wenhuan Lv
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Zhang Chunting
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Naheeda Begum
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Tuanjie Zhao
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China.
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27
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Razzaq A, Wani SH, Saleem F, Yu M, Zhou M, Shabala S. Rewilding crops for climate resilience: economic analysis and de novo domestication strategies. J Exp Bot 2021; 72:6123-6139. [PMID: 34114599 DOI: 10.1093/jxb/erab276] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 06/09/2021] [Indexed: 05/08/2023]
Abstract
To match predicted population growth, annual food production should be doubled by 2050. This is not achievable by current agronomical and breeding practices, due to the impact of climate changes and associated abiotic stresses on agricultural production systems. Here, we analyze the impact of global climate trends on crop productivity and show that the overall loss in crop production from climate-driven abiotic stresses may exceed US$170 billion year-1 and represents a major threat to global food security. We also show that abiotic stress tolerance had been present in wild progenitors of modern crops but was lost during their domestication. We argue for a major shift in our paradigm of crop breeding, focusing on climate resilience, and call for a broader use of wild relatives as a major tool in this process. We argue that, while molecular tools are currently in place to harness the potential of climate-resilient genes present in wild relatives, the complex polygenic nature of tolerance traits remains a major bottleneck in this process. Future research efforts should be focused not only on finding appropriate wild relatives but also on development of efficient cell-based high-throughput phenotyping platforms allowing assessment of the in planta operation of key genes.
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Affiliation(s)
- Ali Razzaq
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisald 38040,Pakistan
| | - Shabir Hussain Wani
- Mountain Research Center for Field Crops, Khudwani, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, J&K,India
| | - Fozia Saleem
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisald 38040,Pakistan
| | - Min Yu
- International Research Centre for Environmental Membrane Biology, Foshan University, Foshan 528000,China
| | - Meixue Zhou
- Tasmanian Institute of Agriculture, University of Tasmania, Hobart, Tas 7001,Australia
| | - Sergey Shabala
- International Research Centre for Environmental Membrane Biology, Foshan University, Foshan 528000,China
- Tasmanian Institute of Agriculture, University of Tasmania, Hobart, Tas 7001,Australia
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28
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Varshney RK, Barmukh R, Roorkiwal M, Qi Y, Kholova J, Tuberosa R, Reynolds MP, Tardieu F, Siddique KHM. Breeding custom-designed crops for improved drought adaptation. Adv Genet (Hoboken) 2021; 2:e202100017. [PMID: 36620433 PMCID: PMC9744523 DOI: 10.1002/ggn2.202100017] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 08/11/2021] [Indexed: 01/11/2023]
Abstract
The current pace of crop improvement is inadequate to feed the burgeoning human population by 2050. Higher, more stable, and sustainable crop production is required against a backdrop of drought stress, which causes significant losses in crop yields. Tailoring crops for drought adaptation may hold the key to address these challenges and provide resilient production systems for future harvests. Understanding the genetic and molecular landscape of the functionality of alleles associated with adaptive traits will make designer crop breeding the prospective approach for crop improvement. Here, we highlight the potential of genomics technologies combined with crop physiology for high-throughput identification of the genetic architecture of key drought-adaptive traits and explore innovative genomic breeding strategies for designing future crops.
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Affiliation(s)
- Rajeev K. Varshney
- Centre of Excellence in Genomics and Systems BiologyInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia,State Agricultural Biotechnology Centre, Centre for Crop and Food InnovationMurdoch UniversityMurdochWestern AustraliaAustralia
| | - Rutwik Barmukh
- Centre of Excellence in Genomics and Systems BiologyInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
| | - Manish Roorkiwal
- Centre of Excellence in Genomics and Systems BiologyInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
| | - Yiping Qi
- Department of Plant Science and Landscape ArchitectureUniversity of MarylandCollege ParkMarylandUSA,Institute for Bioscience and Biotechnology ResearchUniversity of MarylandRockvilleMarylandUSA
| | - Jana Kholova
- Crop Physiology and ModellingInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
| | - Roberto Tuberosa
- Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
| | | | - Francois Tardieu
- Université de Montpellier, INRAE, Laboratoire d'Ecophysiologie des Plantes sous Stress, EnvironnementauxMontpellierFrance
| | - Kadambot H. M. Siddique
- The UWA Institute of AgricultureThe University of Western AustraliaPerthWestern AustraliaAustralia
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29
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Varshney RK, Bohra A, Roorkiwal M, Barmukh R, Cowling WA, Chitikineni A, Lam HM, Hickey LT, Croser JS, Bayer PE, Edwards D, Crossa J, Weckwerth W, Millar H, Kumar A, Bevan MW, Siddique KHM. Fast-forward breeding for a food-secure world. Trends Genet 2021; 37:1124-1136. [PMID: 34531040 DOI: 10.1016/j.tig.2021.08.002] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/03/2021] [Accepted: 08/04/2021] [Indexed: 10/20/2022]
Abstract
Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits. Targeted and rapid assembly of beneficial alleles using optimized breeding strategies and precise genome editing techniques could deliver ideal crops for the future. Realizing desired productivity gains in the field is imperative for securing an adequate future food supply for 10 billion people.
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Affiliation(s)
- Rajeev K Varshney
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India; State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch WA 6150, Western Australia, Australia; The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia.
| | - Abhishek Bohra
- ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India
| | - Manish Roorkiwal
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India; The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia
| | - Rutwik Barmukh
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Wallace A Cowling
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia
| | - Annapurna Chitikineni
- Centre of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Hon-Ming Lam
- School of Life Sciences and Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Lee T Hickey
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, QLD, Australia
| | - Janine S Croser
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia
| | - Philipp E Bayer
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia; School of Biological Sciences, The University of Western Australia, Crawley, WA, Australia
| | - David Edwards
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia; School of Biological Sciences, The University of Western Australia, Crawley, WA, Australia
| | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Wolfram Weckwerth
- Department of Ecogenomics and Systems Biology, Vienna Metabolomics Center (VIME), University of Vienna, Vienna, Austria
| | - Harvey Millar
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia; ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, WA, Australia
| | - Arvind Kumar
- Deputy Director General's Office, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | | | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6009, Australia
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30
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Liu J, Zhan J, Chen J, Lu X, Zhi S, Ye G. Validation of Genes Affecting Rice Grain Zinc Content Through Candidate Gene-Based Association Analysis. Front Genet 2021; 12:701658. [PMID: 34434221 PMCID: PMC8381382 DOI: 10.3389/fgene.2021.701658] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 07/02/2021] [Indexed: 11/27/2022] Open
Abstract
Several key genes governing Zn homeostasis and grain zinc content (GZC) have been functionally characterized. However, the effects of these genes in diverse breeding populations have not been evaluated; thus, their availability in breeding is unclear. In this study, the effects of 65 genes related to rice zinc responses on GZC were evaluated using two panels of breeding lines, and the superior haplotypes were identified. One panel consisted of mega varieties from the International Rice Research Institute (IRRI), South Asia, and Southeast Asia (SEA), and the other panel is breeding lines/varieties from South China (SC). In addition, a multiparent advanced generation intercross (MAGIC) population, named as DC1, was also employed. Three analytical methods, single-locus mixed linear model (SL-MLM), multilocus random-SNP-effect mixed linear model (mrMLM), and haplotype-based association analysis (Hap-AA), were applied. OsIDEF1 (which explained 12.3% of the phenotypic variance) and OsZIFL7 (8.3-9.1%), OsZIP7 (18.9%), and OsIRT1 (17.9%) were identified by SL-MLM in SEA and SC, respectively, whereas no gene was significantly associated with GZC in DC1. In total, five (OsNRAMP6, OsYSL15, OsIRT1, OsIDEF1, and OsZIFL7, 7.70-15.39%), three (OsFRDL1, OsIRT1, and OsZIP7, 11.87-17.99%), and two (OsYSL7 and OsZIP7, 9.85-10.57%) genes were detected to be significantly associated with GZC in SEA, SC, and DC1 by mrMLM, respectively. Hap-AA indicated that Hap1-OsNRAMP5, Hap5-OsZIP4, Hap1-OsIRT1, Hap3-OsNRAMP6, Hap6-OsMTP1, and Hap6-OsYSL15 had the largest effects for GZC in SEA, whereas Hap3-OsOPT7, Hap4-OsIRT2, Hap4-OsZIP7, Hap5-OsIRT1, and Hap5-OsSAMS1 were the most significant in the SC population. Besides, superior alleles were also identified for the significant genes. The genes significantly associated with GZC and their superior haplotypes identified in different panels could be used in enhancing GZC through molecular breeding, which could further address the problem of Zn malnutrition among rice consumers.
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Affiliation(s)
- Jindong Liu
- Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Junhui Zhan
- Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Jingguang Chen
- Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- School of Agriculture, Sun Yat-sen University, Guangzhou, China
| | - Xiang Lu
- Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Shuai Zhi
- Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Guoyou Ye
- Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Strategic Innovation Platform, International Rice Research Institute, Makati, Philippines
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31
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Varshney RK, Bohra A, Yu J, Graner A, Zhang Q, Sorrells ME. Designing Future Crops: Genomics-Assisted Breeding Comes of Age. Trends Plant Sci 2021; 26:631-649. [PMID: 33893045 DOI: 10.1016/j.tplants.2021.03.010] [Citation(s) in RCA: 146] [Impact Index Per Article: 48.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 03/16/2021] [Accepted: 03/17/2021] [Indexed: 05/18/2023]
Abstract
Over the past decade, genomics-assisted breeding (GAB) has been instrumental in harnessing the potential of modern genome resources and characterizing and exploiting allelic variation for germplasm enhancement and cultivar development. Sustaining GAB in the future (GAB 2.0) will rely upon a suite of new approaches that fast-track targeted manipulation of allelic variation for creating novel diversity and facilitate their rapid and efficient incorporation in crop improvement programs. Genomic breeding strategies that optimize crop genomes with accumulation of beneficial alleles and purging of deleterious alleles will be indispensable for designing future crops. In coming decades, GAB 2.0 is expected to play a crucial role in breeding more climate-smart crop cultivars with higher nutritional value in a cost-effective and timely manner.
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Affiliation(s)
- Rajeev K Varshney
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India; State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
| | - Abhishek Bohra
- Crop Improvement Division, ICAR- Indian Institute of Pulses Research (ICAR- IIPR), Kanpur, India
| | - Jianming Yu
- Department of Agronomy, Iowa State University, Ames, IA, USA
| | - Andreas Graner
- Leibniz Institute of Plant Genetics and Crops Plant Research (IPK), Gatersleben, Germany
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Mark E Sorrells
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, USA
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32
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Sinha P, Singh VK, Bohra A, Kumar A, Reif JC, Varshney RK. Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits. Theor Appl Genet 2021; 134:1829-1843. [PMID: 34014373 PMCID: PMC8205890 DOI: 10.1007/s00122-021-03847-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 04/29/2021] [Indexed: 05/03/2023]
Abstract
KEY MESSAGE Integrating genomics technologies and breeding methods to tweak core parameters of the breeder's equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers' fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder's equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder's equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits.
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Affiliation(s)
- Pallavi Sinha
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- International Rice Research Institute (IRRI), IRRI South Asia Hub, ICRISAT, Hyderabad, India
| | - Vikas K Singh
- International Rice Research Institute (IRRI), IRRI South Asia Hub, ICRISAT, Hyderabad, India
| | - Abhishek Bohra
- ICAR- Indian Institute of Pulses Research (IIPR), Kanpur, India
| | - Arvind Kumar
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
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33
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Yadav OP, Gupta SK, Govindaraj M, Sharma R, Varshney RK, Srivastava RK, Rathore A, Mahala RS. Genetic Gains in Pearl Millet in India: Insights Into Historic Breeding Strategies and Future Perspective. Front Plant Sci 2021; 12:645038. [PMID: 33859663 DOI: 10.3389/fpls.2021.64503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/19/2021] [Indexed: 05/27/2023]
Abstract
Pearl millet (Pennisetum glaucum R. Br.) is an important staple and nutritious food crop in the semiarid and arid ecologies of South Asia (SA) and Sub-Saharan Africa (SSA). In view of climate change, depleting water resources, and widespread malnutrition, there is a need to accelerate the rate of genetic gains in pearl millet productivity. This review discusses past strategies and future approaches to accelerate genetic gains to meet future demand. Pearl millet breeding in India has historically evolved very comprehensively from open-pollinated varieties development to hybrid breeding. Availability of stable cytoplasmic male sterility system with adequate restorers and strategic use of genetic resources from India and SSA laid the strong foundation of hybrid breeding. Genetic and cytoplasmic diversification of hybrid parental lines, periodic replacement of hybrids, and breeding disease-resistant and stress-tolerant cultivars have been areas of very high priority. As a result, an annual yield increase of 4% has been realized in the last three decades. There is considerable scope to further accelerate the efforts on hybrid breeding for drought-prone areas in SA and SSA. Heterotic grouping of hybrid parental lines is essential to sustain long-term genetic gains. Time is now ripe for mainstreaming of the nutritional traits improvement in pearl millet breeding programs. New opportunities are emerging to improve the efficiency and precision of breeding. Development and application of high-throughput genomic tools, speed breeding, and precision phenotyping protocols need to be intensified to exploit a huge wealth of native genetic variation available in pearl millet to accelerate the genetic gains.
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Affiliation(s)
| | - S K Gupta
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Mahalingam Govindaraj
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Rajan Sharma
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia
| | - Rakesh K Srivastava
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - A Rathore
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
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34
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Thudi M, Palakurthi R, Schnable JC, Chitikineni A, Dreisigacker S, Mace E, Srivastava RK, Satyavathi CT, Odeny D, Tiwari VK, Lam HM, Hong YB, Singh VK, Li G, Xu Y, Chen X, Kaila S, Nguyen H, Sivasankar S, Jackson SA, Close TJ, Shubo W, Varshney RK. Genomic resources in plant breeding for sustainable agriculture. J Plant Physiol 2021; 257:153351. [PMID: 33412425 PMCID: PMC7903322 DOI: 10.1016/j.jplph.2020.153351] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/14/2020] [Accepted: 12/14/2020] [Indexed: 05/19/2023]
Abstract
Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.
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Affiliation(s)
- Mahendar Thudi
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India; University of Southern Queensland, Toowoomba, Australia
| | - Ramesh Palakurthi
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | | | - Annapurna Chitikineni
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | | | - Emma Mace
- Agri-Science Queensland, Department of Agriculture & Fisheries (DAF), Warwick, Australia
| | - Rakesh K Srivastava
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - C Tara Satyavathi
- Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India
| | - Damaris Odeny
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Nairobi, Kenya
| | | | - Hon-Ming Lam
- Center for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region
| | - Yan Bin Hong
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Vikas K Singh
- South Asia Hub, International Rice Research Institute (IRRI), Hyderabad, India
| | - Guowei Li
- Shandong Academy of Agricultural Sciences, Jinan, China
| | - Yunbi Xu
- International Maize and Wheat Improvement Center (CYMMIT), Mexico DF, Mexico; Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaoping Chen
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Sanjay Kaila
- Department of Biotechnology, Ministry of Science and Technology, Government of India, India
| | - Henry Nguyen
- National Centre for Soybean Research, University of Missouri, Columbia, USA
| | - Sobhana Sivasankar
- Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, Vienna, Austria
| | | | | | - Wan Shubo
- Shandong Academy of Agricultural Sciences, Jinan, China
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
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35
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Yadav OP, Gupta SK, Govindaraj M, Sharma R, Varshney RK, Srivastava RK, Rathore A, Mahala RS. Genetic Gains in Pearl Millet in India: Insights Into Historic Breeding Strategies and Future Perspective. Front Plant Sci 2021; 12:645038. [PMID: 33859663 PMCID: PMC8042313 DOI: 10.3389/fpls.2021.645038] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/19/2021] [Indexed: 05/09/2023]
Abstract
Pearl millet (Pennisetum glaucum R. Br.) is an important staple and nutritious food crop in the semiarid and arid ecologies of South Asia (SA) and Sub-Saharan Africa (SSA). In view of climate change, depleting water resources, and widespread malnutrition, there is a need to accelerate the rate of genetic gains in pearl millet productivity. This review discusses past strategies and future approaches to accelerate genetic gains to meet future demand. Pearl millet breeding in India has historically evolved very comprehensively from open-pollinated varieties development to hybrid breeding. Availability of stable cytoplasmic male sterility system with adequate restorers and strategic use of genetic resources from India and SSA laid the strong foundation of hybrid breeding. Genetic and cytoplasmic diversification of hybrid parental lines, periodic replacement of hybrids, and breeding disease-resistant and stress-tolerant cultivars have been areas of very high priority. As a result, an annual yield increase of 4% has been realized in the last three decades. There is considerable scope to further accelerate the efforts on hybrid breeding for drought-prone areas in SA and SSA. Heterotic grouping of hybrid parental lines is essential to sustain long-term genetic gains. Time is now ripe for mainstreaming of the nutritional traits improvement in pearl millet breeding programs. New opportunities are emerging to improve the efficiency and precision of breeding. Development and application of high-throughput genomic tools, speed breeding, and precision phenotyping protocols need to be intensified to exploit a huge wealth of native genetic variation available in pearl millet to accelerate the genetic gains.
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Affiliation(s)
- Om Parkash Yadav
- ICAR-Central Arid Zone Research Institute, Jodhpur, India
- *Correspondence: Om Parkash Yadav
| | - S. K. Gupta
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Mahalingam Govindaraj
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Rajan Sharma
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Rajeev K. Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia
| | - Rakesh K. Srivastava
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - A. Rathore
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
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Varshney RK, Roorkiwal M, Sun S, Bajaj P, Chitikineni A, Thudi M, Singh NP, Du X, Upadhyaya HD, Khan AW, Wang Y, Garg V, Fan G, Cowling WA, Crossa J, Gentzbittel L, Voss-Fels KP, Valluri VK, Sinha P, Singh VK, Ben C, Rathore A, Punna R, Singh MK, Tar'an B, Bharadwaj C, Yasin M, Pithia MS, Singh S, Soren KR, Kudapa H, Jarquín D, Cubry P, Hickey LT, Dixit GP, Thuillet AC, Hamwieh A, Kumar S, Deokar AA, Chaturvedi SK, Francis A, Howard R, Chattopadhyay D, Edwards D, Lyons E, Vigouroux Y, Hayes BJ, von Wettberg E, Datta SK, Yang H, Nguyen HT, Wang J, Siddique KHM, Mohapatra T, Bennetzen JL, Xu X, Liu X. A chickpea genetic variation map based on the sequencing of 3,366 genomes. Nature 2021; 599:622-7. [PMID: 34759320 DOI: 10.1038/s41586-021-04066-1] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 09/28/2021] [Indexed: 11/17/2022]
Abstract
Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.
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Bohra A, Chand Jha U, Godwin ID, Kumar Varshney R. Genomic interventions for sustainable agriculture. Plant Biotechnol J 2020; 18:2388-2405. [PMID: 32875704 PMCID: PMC7680532 DOI: 10.1111/pbi.13472] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 07/21/2020] [Accepted: 08/16/2020] [Indexed: 05/05/2023]
Abstract
Agricultural production faces a Herculean challenge to feed the increasing global population. Food production systems need to deliver more with finite land and water resources while exerting the least negative influence on the ecosystem. The unpredictability of climate change and consequent changes in pests/pathogens dynamics aggravate the enormity of the challenge. Crop improvement has made significant contributions towards food security, and breeding climate-smart cultivars are considered the most sustainable way to accelerate food production. However, a fundamental change is needed in the conventional breeding framework in order to respond adequately to the growing food demands. Progress in genomics has provided new concepts and tools that hold promise to make plant breeding procedures more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing delineate breeding targets that could contribute to securing future food supply. In this review, we highlight key breakthroughs in plant genome sequencing and explain how the presence of these genome resources in combination with gene editing techniques has revolutionized the procedures of trait discovery and manipulation. Adoption of new approaches such as speed breeding, genomic selection and haplotype-based breeding could overcome several limitations of conventional breeding. We advocate that strengthening varietal release and seed distribution systems will play a more determining role in delivering genetic gains at farmer's field. A holistic approach outlined here would be crucial to deliver steady stream of climate-smart crop cultivars for sustainable agriculture.
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Affiliation(s)
- Abhishek Bohra
- ICAR‐Indian Institute of Pulses Research (IIPR)KanpurIndia
| | - Uday Chand Jha
- ICAR‐Indian Institute of Pulses Research (IIPR)KanpurIndia
| | - Ian D. Godwin
- Centre for Crop ScienceQueensland Alliance for Agriculture and Food Innovation (QAAFI)The University of QueenslandBrisbaneQldAustralia
| | - Rajeev Kumar Varshney
- International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
- The UWA Institute of AgricultureThe University of Western AustraliaPerthAustralia
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