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Raza A, Chen H, Zhang C, Zhuang Y, Sharif Y, Cai T, Yang Q, Soni P, Pandey MK, Varshney RK, Zhuang W. Designing future peanut: the power of genomics-assisted breeding. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:66. [PMID: 38438591 DOI: 10.1007/s00122-024-04575-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 02/03/2024] [Indexed: 03/06/2024]
Abstract
KEY MESSAGE Integrating GAB methods with high-throughput phenotyping, genome editing, and speed breeding hold great potential in designing future smart peanut cultivars to meet market and food supply demands. Cultivated peanut (Arachis hypogaea L.), a legume crop greatly valued for its nourishing food, cooking oil, and fodder, is extensively grown worldwide. Despite decades of classical breeding efforts, the actual on-farm yield of peanut remains below its potential productivity due to the complicated interplay of genotype, environment, and management factors, as well as their intricate interactions. Integrating modern genomics tools into crop breeding is necessary to fast-track breeding efficiency and rapid progress. When combined with speed breeding methods, this integration can substantially accelerate the breeding process, leading to faster access of improved varieties to farmers. Availability of high-quality reference genomes for wild diploid progenitors and cultivated peanuts has accelerated the process of gene/quantitative locus discovery, developing markers and genotyping assays as well as a few molecular breeding products with improved resistance and oil quality. The use of new breeding tools, e.g., genomic selection, haplotype-based breeding, speed breeding, high-throughput phenotyping, and genome editing, is probable to boost genetic gains in peanut. Moreover, renewed attention to efficient selection and exploitation of targeted genetic resources is also needed to design high-quality and high-yielding peanut cultivars with main adaptation attributes. In this context, the combination of genomics-assisted breeding (GAB), genome editing, and speed breeding hold great potential in designing future improved peanut cultivars to meet market and food supply demands.
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Affiliation(s)
- Ali Raza
- Key Laboratory of Ministry of Education for Genetics, Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Hua Chen
- Key Laboratory of Ministry of Education for Genetics, Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Chong Zhang
- Key Laboratory of Ministry of Education for Genetics, Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Yuhui Zhuang
- College of Life Science, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Yasir Sharif
- Key Laboratory of Ministry of Education for Genetics, Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Tiecheng Cai
- Key Laboratory of Ministry of Education for Genetics, Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Qiang Yang
- Key Laboratory of Ministry of Education for Genetics, Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Pooja Soni
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, 502324, India
| | - Manish K Pandey
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, 502324, India
| | - Rajeev K Varshney
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia.
| | - Weijian Zhuang
- Key Laboratory of Ministry of Education for Genetics, Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China.
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Kassie FC, Nguepjop JR, Ngalle HB, Assaha DVM, Gessese MK, Abtew WG, Tossim HA, Sambou A, Seye M, Rami JF, Fonceka D, Bell JM. An Overview of Mapping Quantitative Trait Loci in Peanut ( Arachis hypogaea L.). Genes (Basel) 2023; 14:1176. [PMID: 37372356 DOI: 10.3390/genes14061176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 05/24/2023] [Accepted: 05/25/2023] [Indexed: 06/29/2023] Open
Abstract
Quantitative Trait Loci (QTL) mapping has been thoroughly used in peanut genetics and breeding in spite of the narrow genetic diversity and the segmental tetraploid nature of the cultivated species. QTL mapping is helpful for identifying the genomic regions that contribute to traits, for estimating the extent of variation and the genetic action (i.e., additive, dominant, or epistatic) underlying this variation, and for pinpointing genetic correlations between traits. The aim of this paper is to review the recently published studies on QTL mapping with a particular emphasis on mapping populations used as well as traits related to kernel quality. We found that several populations have been used for QTL mapping including interspecific populations developed from crosses between synthetic tetraploids and elite varieties. Those populations allowed the broadening of the genetic base of cultivated peanut and helped with the mapping of QTL and identifying beneficial wild alleles for economically important traits. Furthermore, only a few studies reported QTL related to kernel quality. The main quality traits for which QTL have been mapped include oil and protein content as well as fatty acid compositions. QTL for other agronomic traits have also been reported. Among the 1261 QTL reported in this review, and extracted from the most relevant studies on QTL mapping in peanut, 413 (~33%) were related to kernel quality showing the importance of quality in peanut genetics and breeding. Exploiting the QTL information could accelerate breeding to develop highly nutritious superior cultivars in the face of climate change.
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Affiliation(s)
- Fentanesh C Kassie
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaounde I, Yaounde P.O. Box 337, Cameroon
- Department of Plant Science, College of Agriculture, Wolaita Sodo University, Sodo P.O. Box 138, Ethiopia
| | - Joël R Nguepjop
- UMR AGAP, CIRAD, F-34398 Montpellier, France
- AGAP Institute, Institut Agro, CIRAD, INRAE, University of Montpellier, F-34060 Montpellier, France
- Centre d'Etudes Régional Pour l'Amélioration de l'Adaptation à la Sécheresse (CERAAS/ISRA), Route de Khombole, Thiès BP 3320, Senegal
- Dispositif de Recherche et de Formation en Partenariat, Innovation et Amélioration Variétale en Afrique de l'Ouest (IAVAO), CERAAS, Route de Khombole, Thiès BP 3320, Senegal
| | - Hermine B Ngalle
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaounde I, Yaounde P.O. Box 337, Cameroon
| | - Dekoum V M Assaha
- Department of Agriculture, Higher Technical Teachers Training College, University of Buea, Kumba P.O. Box 249, Cameroon
| | - Mesfin K Gessese
- Department of Plant Science, College of Agriculture, Wolaita Sodo University, Sodo P.O. Box 138, Ethiopia
| | - Wosene G Abtew
- Department of Horticulture and Plant Science, College of Agriculture and Veterinary Medicine, Jimma University, Jimma P.O. Box 378, Ethiopia
| | - Hodo-Abalo Tossim
- Centre d'Etudes Régional Pour l'Amélioration de l'Adaptation à la Sécheresse (CERAAS/ISRA), Route de Khombole, Thiès BP 3320, Senegal
- Dispositif de Recherche et de Formation en Partenariat, Innovation et Amélioration Variétale en Afrique de l'Ouest (IAVAO), CERAAS, Route de Khombole, Thiès BP 3320, Senegal
| | - Aissatou Sambou
- Centre d'Etudes Régional Pour l'Amélioration de l'Adaptation à la Sécheresse (CERAAS/ISRA), Route de Khombole, Thiès BP 3320, Senegal
- Dispositif de Recherche et de Formation en Partenariat, Innovation et Amélioration Variétale en Afrique de l'Ouest (IAVAO), CERAAS, Route de Khombole, Thiès BP 3320, Senegal
| | - Maguette Seye
- Centre d'Etudes Régional Pour l'Amélioration de l'Adaptation à la Sécheresse (CERAAS/ISRA), Route de Khombole, Thiès BP 3320, Senegal
- Dispositif de Recherche et de Formation en Partenariat, Innovation et Amélioration Variétale en Afrique de l'Ouest (IAVAO), CERAAS, Route de Khombole, Thiès BP 3320, Senegal
| | - Jean-François Rami
- UMR AGAP, CIRAD, F-34398 Montpellier, France
- AGAP Institute, Institut Agro, CIRAD, INRAE, University of Montpellier, F-34060 Montpellier, France
- Dispositif de Recherche et de Formation en Partenariat, Innovation et Amélioration Variétale en Afrique de l'Ouest (IAVAO), CERAAS, Route de Khombole, Thiès BP 3320, Senegal
| | - Daniel Fonceka
- UMR AGAP, CIRAD, F-34398 Montpellier, France
- AGAP Institute, Institut Agro, CIRAD, INRAE, University of Montpellier, F-34060 Montpellier, France
- Centre d'Etudes Régional Pour l'Amélioration de l'Adaptation à la Sécheresse (CERAAS/ISRA), Route de Khombole, Thiès BP 3320, Senegal
- Dispositif de Recherche et de Formation en Partenariat, Innovation et Amélioration Variétale en Afrique de l'Ouest (IAVAO), CERAAS, Route de Khombole, Thiès BP 3320, Senegal
| | - Joseph M Bell
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaounde I, Yaounde P.O. Box 337, Cameroon
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Puppala N, Nayak SN, Sanz-Saez A, Chen C, Devi MJ, Nivedita N, Bao Y, He G, Traore SM, Wright DA, Pandey MK, Sharma V. Sustaining yield and nutritional quality of peanuts in harsh environments: Physiological and molecular basis of drought and heat stress tolerance. Front Genet 2023; 14:1121462. [PMID: 36968584 PMCID: PMC10030941 DOI: 10.3389/fgene.2023.1121462] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 02/06/2023] [Indexed: 03/29/2023] Open
Abstract
Climate change is significantly impacting agricultural production worldwide. Peanuts provide food and nutritional security to millions of people across the globe because of its high nutritive values. Drought and heat stress alone or in combination cause substantial yield losses to peanut production. The stress, in addition, adversely impact nutritional quality. Peanuts exposed to drought stress at reproductive stage are prone to aflatoxin contamination, which imposes a restriction on use of peanuts as health food and also adversely impact peanut trade. A comprehensive understanding of the impact of drought and heat stress at physiological and molecular levels may accelerate the development of stress tolerant productive peanut cultivars adapted to a given production system. Significant progress has been achieved towards the characterization of germplasm for drought and heat stress tolerance, unlocking the physiological and molecular basis of stress tolerance, identifying significant marker-trait associations as well major QTLs and candidate genes associated with drought tolerance, which after validation may be deployed to initiate marker-assisted breeding for abiotic stress adaptation in peanut. The proof of concept about the use of transgenic technology to add value to peanuts has been demonstrated. Advances in phenomics and artificial intelligence to accelerate the timely and cost-effective collection of phenotyping data in large germplasm/breeding populations have also been discussed. Greater focus is needed to accelerate research on heat stress tolerance in peanut. A suits of technological innovations are now available in the breeders toolbox to enhance productivity and nutritional quality of peanuts in harsh environments. A holistic breeding approach that considers drought and heat-tolerant traits to simultaneously address both stresses could be a successful strategy to produce climate-resilient peanut genotypes with improved nutritional quality.
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Affiliation(s)
- Naveen Puppala
- Agricultural Science Center at Clovis, New Mexico State University, Las Cruces, NM, United States
- *Correspondence: Naveen Puppala,
| | - Spurthi N. Nayak
- Department of Biotechnology, University of Agricultural Sciences, Dharwad, India
| | - Alvaro Sanz-Saez
- Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, United States
| | - Charles Chen
- Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, United States
| | - Mura Jyostna Devi
- USDA-ARS Vegetable Crops Research, Madison, WI, United States
- Department of Horticulture, University of Wisconsin-Madison, Madison, WI, United States
| | - Nivedita Nivedita
- Department of Horticulture, University of Wisconsin-Madison, Madison, WI, United States
| | - Yin Bao
- Biosystems Engineering Department, Auburn University, Auburn, AL, United States
| | - Guohao He
- Department of Plant and Soil Sciences, Tuskegee University, Tuskegee, AL, United States
| | - Sy M. Traore
- Department of Plant and Soil Sciences, Tuskegee University, Tuskegee, AL, United States
| | - David A. Wright
- Department of Biotechnology, Iowa State University, Ames, IA, United States
| | - Manish K. Pandey
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India
| | - Vinay Sharma
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India
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Improved Genetic Map Identified Major QTLs for Drought Tolerance- and Iron Deficiency Tolerance-Related Traits in Groundnut. Genes (Basel) 2020; 12:genes12010037. [PMID: 33396649 PMCID: PMC7824586 DOI: 10.3390/genes12010037] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 12/21/2020] [Accepted: 12/25/2020] [Indexed: 12/01/2022] Open
Abstract
A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.
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Chavarro C, Chu Y, Holbrook C, Isleib T, Bertioli D, Hovav R, Butts C, Lamb M, Sorensen R, A Jackson S, Ozias-Akins P. Pod and Seed Trait QTL Identification To Assist Breeding for Peanut Market Preferences. G3 (BETHESDA, MD.) 2020; 10:2297-2315. [PMID: 32398236 PMCID: PMC7341151 DOI: 10.1534/g3.120.401147] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 05/01/2020] [Indexed: 12/20/2022]
Abstract
Although seed and pod traits are important for peanut breeding, little is known about the inheritance of these traits. A recombinant inbred line (RIL) population of 156 lines from a cross of Tifrunner x NC 3033 was genotyped with the Axiom_Arachis1 SNP array and SSRs to generate a genetic map composed of 1524 markers in 29 linkage groups (LG). The genetic positions of markers were compared with their physical positions on the peanut genome to confirm the validity of the linkage map and explore the distribution of recombination and potential chromosomal rearrangements. This linkage map was then used to identify Quantitative Trait Loci (QTL) for seed and pod traits that were phenotyped over three consecutive years for the purpose of developing trait-associated markers for breeding. Forty-nine QTL were identified in 14 LG for seed size index, kernel percentage, seed weight, pod weight, single-kernel, double-kernel, pod area and pod density. Twenty QTL demonstrated phenotypic variance explained (PVE) greater than 10% and eight more than 20%. Of note, seven of the eight major QTL for pod area, pod weight and seed weight (PVE >20% variance) were attributed to NC 3033 and located in a single linkage group, LG B06_1. In contrast, the most consistent QTL for kernel percentage were located on A07/B07 and derived from Tifrunner.
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Affiliation(s)
- Carolina Chavarro
- Center for Applied Genetic Technologies, University of Georgia, Athens, GA 30602
| | - Ye Chu
- Department of Horticulture and Institute of Plant Breeding, Genetics & Genomics, University of Georgia, Tifton, GA 31793
| | - Corley Holbrook
- USDA- Agricultural Research Service, Crop Genetics and Breeding Research Unit, Tifton, GA 31793
| | - Thomas Isleib
- Department of Crop Science, North Carolina State University, P.O. Box 7629, Raleigh, NC 27695
| | - David Bertioli
- Center for Applied Genetic Technologies, University of Georgia, Athens, GA 30602
| | - Ran Hovav
- Department of Field and Vegetable Crops, Plant Sciences Institute, ARO (Volcani Center), Bet Dagan, Israel, and
| | - Christopher Butts
- USDA- Agricultural Research Service, National Peanut Research Laboratory, Dawson, GA 39842
| | - Marshall Lamb
- USDA- Agricultural Research Service, National Peanut Research Laboratory, Dawson, GA 39842
| | - Ronald Sorensen
- USDA- Agricultural Research Service, National Peanut Research Laboratory, Dawson, GA 39842
| | - Scott A Jackson
- Center for Applied Genetic Technologies, University of Georgia, Athens, GA 30602
| | - Peggy Ozias-Akins
- Department of Horticulture and Institute of Plant Breeding, Genetics & Genomics, University of Georgia, Tifton, GA 31793,
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Mondal S, Badigannavar AM. Identification of major consensus QTLs for seed size and minor QTLs for pod traits in cultivated groundnut ( Arachis hypogaea L.). 3 Biotech 2019; 9:347. [PMID: 31497465 DOI: 10.1007/s13205-019-1881-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Accepted: 08/22/2019] [Indexed: 12/16/2022] Open
Abstract
Hundred kernel weight is an important indicator for large-seeded genotype selection. A recombinant inbred line population was used to decipher the genetic architecture of seed size and three pod traits in cultivated groundnut based on the phenotypic data from six and three environments, respectively. The study revealed a consensus major QTL for HKW in B07 group that explained 10.5-23.9% phenotypic variation due to seed size. Further, two other minor QTLs were identified in B03 and B08 group for the seed size. Two minor QTLs for pod beak were positioned in B03 and A08. A minor QTL for pod reticulation was also mapped in the same map interval with the pod beak QTL in A08. Another minor QTL for pod constriction was co-mapped with the minor QTL for HKW in B08. The other minor QTL for pod constriction was placed in the neighboring map interval with the consensus QTL for seed size in B07 that suggests linkage of pod constriction with large seed trait. Analysis of the flanking markers profile in 71 cultivated groundnut genotypes revealed a strong association of pPGPseq_2E06 marker with large seed trait.
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Affiliation(s)
- Suvendu Mondal
- 1Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai, 400085 India
- 2Homi Bhabha National Institute, Training School Complex, Anushaktinagar, Mumbai 400094 India
| | - Anand M Badigannavar
- 1Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai, 400085 India
- 2Homi Bhabha National Institute, Training School Complex, Anushaktinagar, Mumbai 400094 India
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Luo H, Pandey MK, Khan AW, Guo J, Wu B, Cai Y, Huang L, Zhou X, Chen Y, Chen W, Liu N, Lei Y, Liao B, Varshney RK, Jiang H. Discovery of genomic regions and candidate genes controlling shelling percentage using QTL-seq approach in cultivated peanut (Arachis hypogaea L.). PLANT BIOTECHNOLOGY JOURNAL 2019; 17:1248-1260. [PMID: 30549165 PMCID: PMC6576108 DOI: 10.1111/pbi.13050] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 11/27/2018] [Accepted: 11/28/2018] [Indexed: 05/12/2023]
Abstract
Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing high-quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics-assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL-seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68-4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89-790.32 million reads and achieving 91.85%-93.18% genome coverage and 14.04-21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68-4/two bulks) using the QTL-seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non-synonymous effects or in UTRs were identified in these regions for SP. Cost-effective KASP (Kompetitive Allele-Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties.
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Affiliation(s)
- Huaiyong Luo
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Manish K. Pandey
- Center of Excellence in Genomics & Systems Biology (CEGSB)International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
| | - Aamir W. Khan
- Center of Excellence in Genomics & Systems Biology (CEGSB)International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
| | - Jianbin Guo
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Bei Wu
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Yan Cai
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Li Huang
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Xiaojing Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Yuning Chen
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Weigang Chen
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Nian Liu
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Yong Lei
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Boshou Liao
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
| | - Rajeev K. Varshney
- Center of Excellence in Genomics & Systems Biology (CEGSB)International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil CropsMinistry of AgricultureOil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhanChina
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Luo H, Guo J, Ren X, Chen W, Huang L, Zhou X, Chen Y, Liu N, Xiong F, Lei Y, Liao B, Jiang H. Chromosomes A07 and A05 associated with stable and major QTLs for pod weight and size in cultivated peanut (Arachis hypogaea L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:267-282. [PMID: 29058050 DOI: 10.1007/s00122-017-3000-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 10/07/2017] [Indexed: 05/22/2023]
Abstract
Co-localized intervals and candidate genes were identified for major and stable QTLs controlling pod weight and size on chromosomes A07 and A05 in an RIL population across four environments. Cultivated peanut (Arachis hypogaea L.) is an important legume crops grown in > 100 countries. Hundred-pod weight (HPW) is an important yield trait in peanut, but its underlying genetic mechanism was not well studied. In this study, a mapping population (Xuhua 13 × Zhonghua 6) with 187 recombinant inbred lines (RILs) was developed to map quantitative trait loci (QTLs) for HPW together with pod length (PL) and pod width (PW) by both unconditional and conditional QTL analyses. A genetic map covering 1756.48 cM was constructed with 817 markers. Additive effects, epistatic interactions, and genotype-by-environment interactions were analyzed using the phenotyping data generated across four environments. Twelve additive QTLs were identified on chromosomes A05, A07, and A08 by unconditional analysis, and five of them (qPLA07, qPLA05.1, qPWA07, qHPWA07.1, and qHPWA05.2) showed major and stable expressions in all environments. Conditional QTL mapping found that PL had stronger influences on HPW than PW. Notably, qHPWA07.1, qPLA07, and qPWA07 that explained 17.93-43.63% of the phenotypic variations of the three traits were co-localized in a 5 cM interval (1.48 Mb in physical map) on chromosome A07 with 147 candidate genes related to catalytic activity and metabolic process. In addition, qHPWA05.2 and qPLA05.1 were co-localized with minor QTL qPWA05.2 to a 1.3 cM genetic interval (280 kb in physical map) on chromosome A05 with 12 candidate genes. This study provides a comprehensive characterization of the genetic components controlling pod weight and size as well as candidate QTLs and genes for improving pod yield in future peanut breeding.
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Affiliation(s)
- Huaiyong Luo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Jianbin Guo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xiaoping Ren
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Weigang Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Li Huang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xiaojing Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Yuning Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Nian Liu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Fei Xiong
- Huanggang Academy of Agricultural Sciences, Huanggang, 463000, China
| | - Yong Lei
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Boshou Liao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
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Luo H, Xu Z, Li Z, Li X, Lv J, Ren X, Huang L, Zhou X, Chen Y, Yu J, Chen W, Lei Y, Liao B, Jiang H. Development of SSR markers and identification of major quantitative trait loci controlling shelling percentage in cultivated peanut (Arachis hypogaea L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2017; 130:1635-1648. [PMID: 28508097 PMCID: PMC5511596 DOI: 10.1007/s00122-017-2915-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 04/27/2017] [Indexed: 05/04/2023]
Abstract
A total of 204,439 SSR markers were developed in diploid genomes, and 25 QTLs for shelling percentage were identified in a RIL population across 4 years including five consistent QTLs. Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing edible oil and protein for human nutrition. Genome sequences of its diploid ancestors, Arachis duranensis and A. ipaensis, were reported, but their SSRs have not been well exploited and utilized hitherto. Shelling percentage is an important economic trait and its improvement has been one of the major objectives in peanut breeding programs. In this study, the genome sequences of A. duranensis and A. ipaensis were used to develop SSR markers, and a mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 recombinant inbred lines was used to map QTLs controlling shelling percentage. The numbers of newly developed SSR markers were 84,383 and 120,056 in the A. duranensis and A. ipaensis genomes, respectively. Genotyping of the mapping population was conducted with both newly developed and previously reported markers. QTL analysis using the phenotyping data generated in Wuhan across four consecutive years and genotyping data of 830 mapped loci identified 25 QTLs with 4.46-17.01% of phenotypic variance explained in the four environments. Meta-analysis revealed five consistent QTLs that could be detected in at least two environments. Notably, the consistent QTL cqSPA09 was detected in all four environments and explained 10.47-17.01% of the phenotypic variance. The segregation in the progeny of a residual heterozygous line confirmed that the cpSPA09 locus had additive effect in increasing shelling percentage. These consistent and major QTL regions provide opportunity not only for further gene discovery, but also for the development of functional markers for breeding.
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Affiliation(s)
- Huaiyong Luo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Zhijun Xu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Zhendong Li
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xinping Li
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Jianwei Lv
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xiaoping Ren
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Li Huang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xiaojing Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Yuning Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Jingyin Yu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Weigang Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Yong Lei
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Boshou Liao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
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10
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Luo H, Ren X, Li Z, Xu Z, Li X, Huang L, Zhou X, Chen Y, Chen W, Lei Y, Liao B, Pandey MK, Varshney RK, Guo B, Jiang X, Liu F, Jiang H. Co-localization of major quantitative trait loci for pod size and weight to a 3.7 cM interval on chromosome A05 in cultivated peanut (Arachis hypogaea L.). BMC Genomics 2017; 18:58. [PMID: 28068921 PMCID: PMC5223410 DOI: 10.1186/s12864-016-3456-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Accepted: 12/22/2016] [Indexed: 11/26/2022] Open
Abstract
Background Cultivated peanut (Arachis hypogaea L.), an important source of edible oil and protein, is widely grown in tropical and subtropical areas of the world. Genetic improvement of yield-related traits is essential for improving yield potential of new peanut varieties. Genomics-assisted breeding (GAB) can accelerate the process of genetic improvement but requires linked markers for the traits of interest. In this context, we developed a recombinant inbred line (RIL) mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 individuals and used to map quantitative trait loci (QTLs) associated with three important pod features, namely pod length, pod width and hundred-pod weight. Results QTL analysis using the phenotyping data generated across four environments in two locations and genotyping data on 743 mapped loci identified 15 QTLs for pod length, 11 QTLs for pod width and 16 QTLs for hundred-pod weight. The phenotypic variation explained (PVE) ranged from 3.68 to 27.84%. Thirteen QTLs were consistently detected in at least two environments and three QTLs (qPLA05.7, qPLA09.3 and qHPWA05.6) were detected in all four environments indicating their consistent and stable expression. Three major QTLs, detected in at least three environments, were found to be co-localized to a 3.7 cM interval on chromosome A05, and they were qPLA05.7 for pod length (16.89–27.84% PVE), qPWA05.5 for pod width (13.73–14.12% PVE), and qHPWA05.6 for hundred-pod weight (13.75–26.82% PVE). This 3.7 cM linkage interval corresponds to ~2.47 Mb genomic region of the pseudomolecule A05 of A. duranensis, including 114 annotated genes related to catalytic activity and metabolic process. Conclusions This study identified three major consistent and stable QTLs for pod size and weight which were co-localized in a 3.7 cM interval on chromosome A05. These QTL regions not only offer further investigation for gene discovery and development of functional markers but also provide opportunity for deployment of these QTLs in GAB for improving yield in peanut. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3456-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Huaiyong Luo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xiaoping Ren
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Zhendong Li
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Zhijun Xu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xinping Li
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Li Huang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Xiaojing Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Yuning Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Weigang Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Yong Lei
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Boshou Liao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Manish K Pandey
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Baozhu Guo
- Crop Protection and Management Research Unit, USDA-ARS, Tifton, GA, 31793, USA
| | - Xiangguo Jiang
- Xiangyang Academy of Agricultural Sciences, Xiangyang, 461057, China
| | - Fei Liu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan, 430062, China.
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