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Espina MJC, Lovell JT, Jenkins J, Shu S, Sreedasyam A, Jordan BD, Webber J, Boston L, Brůna T, Talag J, Goodstein D, Grimwood J, Stacey G, Cannon SB, Lorenz AJ, Schmutz J, Stupar RM. Assembly, comparative analysis, and utilization of a single haplotype reference genome for soybean. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024. [PMID: 39276372 DOI: 10.1111/tpj.17026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 08/14/2024] [Accepted: 08/27/2024] [Indexed: 09/17/2024]
Abstract
Cultivar Williams 82 has served as the reference genome for the soybean research community since 2008, but is known to have areas of genomic heterogeneity among different sub-lines. This work provides an updated assembly (version Wm82.a6) derived from a specific sub-line known as Wm82-ISU-01 (seeds available under USDA accession PI 704477). The genome was assembled using Pacific BioSciences HiFi reads and integrated into chromosomes using HiC. The 20 soybean chromosomes assembled into a genome of 1.01Gb, consisting of 36 contigs. The genome annotation identified 48 387 gene models, named in accordance with previous assembly versions Wm82.a2 and Wm82.a4. Comparisons of Wm82.a6 with other near-gapless assemblies of Williams 82 reveal large regions of genomic heterogeneity, including regions of differential introgression from the cultivar Kingwa within approximately 30 Mb and 25 Mb segments on chromosomes 03 and 07, respectively. Additionally, our analysis revealed a previously unknown large (>20 Mb) heterogeneous region in the pericentromeric region of chromosome 12, where Wm82.a6 matches the 'Williams' haplotype while the other two near-gapless assemblies do not match the haplotype of either parent of Williams 82. In addition to the Wm82.a6 assembly, we also assembled the genome of 'Fiskeby III,' a rich resource for abiotic stress resistance genes. A genome comparison of Wm82.a6 with Fiskeby III revealed the nucleotide and structural polymorphisms between the two genomes within a QTL region for iron deficiency chlorosis resistance. The Wm82.a6 and Fiskeby III genomes described here will enhance comparative and functional genomics capacities and applications in the soybean community.
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Affiliation(s)
- Mary Jane C Espina
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, 55108, USA
| | - John T Lovell
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, 35806, USA
- Lawrence Berkeley National Laboratory, Department of Energy Joint Genome Institute, Berkeley, California, 94720, USA
| | - Jerry Jenkins
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, 35806, USA
| | - Shengqiang Shu
- Lawrence Berkeley National Laboratory, Department of Energy Joint Genome Institute, Berkeley, California, 94720, USA
| | - Avinash Sreedasyam
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, 35806, USA
- Lawrence Berkeley National Laboratory, Department of Energy Joint Genome Institute, Berkeley, California, 94720, USA
| | - Brandon D Jordan
- Corn Insects and Crop Genetics Research Unit, US Department of Agriculture - Agricultural Research Service, Ames, Iowa, 50011, USA
| | - Jenell Webber
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, 35806, USA
| | - LoriBeth Boston
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, 35806, USA
| | - Tomáš Brůna
- Lawrence Berkeley National Laboratory, Department of Energy Joint Genome Institute, Berkeley, California, 94720, USA
| | - Jayson Talag
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, Arizona, 85721, USA
| | - David Goodstein
- Lawrence Berkeley National Laboratory, Department of Energy Joint Genome Institute, Berkeley, California, 94720, USA
| | - Jane Grimwood
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, 35806, USA
| | - Gary Stacey
- Division of Plant Science & Technology, C.S. Bond Life Sciences Center, University of Missouri, Columbia, Missouri, 65211, USA
| | - Steven B Cannon
- Corn Insects and Crop Genetics Research Unit, US Department of Agriculture - Agricultural Research Service, Ames, Iowa, 50011, USA
| | - Aaron J Lorenz
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, 55108, USA
| | - Jeremy Schmutz
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, 35806, USA
- Lawrence Berkeley National Laboratory, Department of Energy Joint Genome Institute, Berkeley, California, 94720, USA
| | - Robert M Stupar
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, 55108, USA
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Mane RS, Prasad BD, Sahni S, Quaiyum Z, Sharma VK. Biotechnological studies towards improvement of finger millet using multi-omics approaches. Funct Integr Genomics 2024; 24:148. [PMID: 39218842 DOI: 10.1007/s10142-024-01438-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 08/22/2024] [Accepted: 08/27/2024] [Indexed: 09/04/2024]
Abstract
A plethora of studies have uncovered numerous important genes with agricultural significance in staple crops. However, when it comes to orphan crops like minor millet, genomic research lags significantly behind that of major crops. This situation has promoted a focus on exploring research opportunities in minor millets, particularly in finger millet, using cutting-edge methods. Finger millet, a coarse cereal known for its exceptional nutritional content and ability to withstand environmental stresses represents a promising climate-smart and nutritional crop in the battle against escalating environmental challenges. The existing traditional improvement programs for finger millet are insufficient to address global hunger effectively. The lack of utilization of high-throughput platforms, genome editing, haplotype breeding, and advanced breeding approaches hinders the systematic multi-omics studies on finger millet, which are essential for pinpointing crucial genes related to agronomically important and various stress responses. The growing environmental uncertainties have widened the gap between the anticipated and real progress in crop improvement. To overcome these challenges a combination of cutting-edge multi-omics techniques such as high-throughput sequencing, speed breeding, mutational breeding, haplotype-based breeding, genomic selection, high-throughput phenotyping, pangenomics, genome editing, and more along with integration of deep learning and artificial intelligence technologies are essential to accelerate research efforts in finger millet. The scarcity of multi-omics approaches in finger millet leaves breeders with limited modern tools for crop enhancement. Therefore, leveraging datasets from previous studies could prove effective in implementing the necessary multi-omics interventions to enrich the genetic resource in finger millet.
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Affiliation(s)
- Rushikesh Sanjay Mane
- Department of AB and MB, CBS&H, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, 848125, India
| | - Bishun Deo Prasad
- Department of AB and MB, CBS&H, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, 848125, India.
| | - Sangita Sahni
- Department of Plant Pathology, TCA Dholi, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, 848125, India
| | - Zeba Quaiyum
- Department of AB and MB, CBS&H, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, 848125, India
| | - V K Sharma
- Department of AB and MB, CBS&H, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, 848125, India
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Garg V, Bohra A, Mascher M, Spannagl M, Xu X, Bevan MW, Bennetzen JL, Varshney RK. Unlocking plant genetics with telomere-to-telomere genome assemblies. Nat Genet 2024; 56:1788-1799. [PMID: 39048791 DOI: 10.1038/s41588-024-01830-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 06/12/2024] [Indexed: 07/27/2024]
Abstract
Contiguous genome sequence assemblies will help us to realize the full potential of crop translational genomics. Recent advances in sequencing technologies, especially long-read sequencing strategies, have made it possible to construct gapless telomere-to-telomere (T2T) assemblies, thus offering novel insights into genome organization and function. Plant genomes pose unique challenges, such as a continuum of ancient to recent polyploidy and abundant highly similar and long repetitive elements. Owing to progress in sequencing approaches, for most crop plants, chromosome-scale reference genome assemblies are available, but T2T assembly construction remains challenging. Here we describe methods for haplotype-resolved, gapless T2T assembly construction in plants, including various crop species. We outline the impact of T2T assemblies in elucidating the roles of repetitive elements in gene regulation, as well as in pangenomics, functional genomics, genome-assisted breeding and targeted genome manipulation. In conjunction with sequence-enriched germplasm repositories, T2T assemblies thus hold great promise for basic and applied plant sciences.
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Affiliation(s)
- Vanika Garg
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Abhishek Bohra
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
- ICAR-Indian Institute of Pulses Research, Kanpur, India
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Seeland, Germany
| | - Manuel Spannagl
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
- Plant Genome and Systems Biology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany
| | - Xun Xu
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
- BGI-Shenzhen, Shenzhen, China
| | | | | | - Rajeev K Varshney
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
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Chen J, Wang Y. Understanding the salinity resilience and productivity of halophytes in saline environments. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2024; 346:112171. [PMID: 38969140 DOI: 10.1016/j.plantsci.2024.112171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 06/15/2024] [Accepted: 06/21/2024] [Indexed: 07/07/2024]
Abstract
The escalating salinity levels in cultivable soil pose a significant threat to agricultural productivity and, consequently, human sustenance. This problem is being exacerbated by natural processes and human activities, coinciding with a period of rapid population growth. Developing halophytic crops is needed to ensure food security is not impaired and land resources can be used sustainably. Evolution has created many close halophyte relatives of our major glycophytic crops, such as Puccinellia tenuiflora (relative of barley and wheat), Oryza coarctata (relative of rice) and Glycine soja (relative of soybean). There are also some halophytes have been subjected to semi-domestication and are considered as minor crops, such as Chenopodium quinoa. In this paper, we examine the prevailing comprehension of robust salinity resilience in halophytes. We summarize the existing strategies and technologies that equip researchers with the means to enhance the salt tolerance capabilities of primary crops and investigate the genetic makeup of halophytes.
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Affiliation(s)
- Jiahong Chen
- State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 201602, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuan Wang
- State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 201602, China; Dalian Practical Biotechnology Co. LTD., Dalian, Liaoning 116200, China.
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Mangal V, Verma LK, Singh SK, Saxena K, Roy A, Karn A, Rohit R, Kashyap S, Bhatt A, Sood S. Triumphs of genomic-assisted breeding in crop improvement. Heliyon 2024; 10:e35513. [PMID: 39170454 PMCID: PMC11336775 DOI: 10.1016/j.heliyon.2024.e35513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 07/23/2024] [Accepted: 07/30/2024] [Indexed: 08/23/2024] Open
Abstract
Conventional breeding approaches have played a significant role in meeting the food demand remarkably well until now. However, the increasing population, yield plateaus in certain crops, and limited recombination necessitate using genomic resources for genomics-assisted crop improvement programs. As a result of advancements in the next-generation sequence technology, GABs have developed dramatically to characterize allelic variants and facilitate their rapid and efficient incorporation in crop improvement programs. Genomics-assisted breeding (GAB) has played an important role in harnessing the potential of modern genomic tools, exploiting allelic variation from genetic resources and developing cultivars over the past decade. The availability of pangenomes for major crops has been a significant development, albeit with varying degrees of completeness. Even though adopting these technologies is essentially determined on economic grounds and cost-effective assays, which create a wealth of information that can be successfully used to exploit the latent potential of crops. GAB has been instrumental in harnessing the potential of modern genomic resources and exploiting allelic variation for genetic enhancement and cultivar development. GAB strategies will be indispensable for designing future crops and are expected to play a crucial role in breeding climate-smart crop cultivars with higher nutritional value.
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Affiliation(s)
- Vikas Mangal
- ICAR-Central Potato Research Institute (CPRI), Shimla, Himachal Pradesh, 171001, India
| | | | - Sandeep Kumar Singh
- Department of Genetics and Plant Breeding, Faculty of Agricultural Sciences, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, 751030, India
| | - Kanak Saxena
- Department of Genetics and Plant Breeding, Rabindranath Tagore University, Raisen, Madhya Pradesh, India
| | - Anirban Roy
- Division of Genetics and Plant Breeding, Ramakrishna Mission Vivekananda Educational and Research Institute (RKMVERI), Narendrapur, Kolkata, 700103, India
| | - Anandi Karn
- Plant Breeding & Graduate Program, IFAS - University of Florida, Gainesville, USA
| | - Rohit Rohit
- Department of Genetics and Plant Breeding, GBPUA&T, Pantnagar, Uttarakhand, 263145, India
| | - Shruti Kashyap
- Department of Genetics and Plant Breeding, GBPUA&T, Pantnagar, Uttarakhand, 263145, India
| | - Ashish Bhatt
- Department of Genetics and Plant Breeding, GBPUA&T, Pantnagar, Uttarakhand, 263145, India
| | - Salej Sood
- ICAR-Central Potato Research Institute (CPRI), Shimla, Himachal Pradesh, 171001, India
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Kim EG, Jang YH, Park JR, Wang XH, Jan R, Farooq M, Asaf S, Asif S, Kim KM. OsCKq1 Regulates Heading Date and Grain Weight in Rice in Response to Day Length. RICE (NEW YORK, N.Y.) 2024; 17:48. [PMID: 39115620 PMCID: PMC11310376 DOI: 10.1186/s12284-024-00726-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 07/28/2024] [Indexed: 08/11/2024]
Abstract
BACKGROUND Photoperiod sensitivity is among the most important agronomic traits of rice, as it determines local and seasonal adaptability and plays pivotal roles in determining yield and other key agronomic characteristics. By controlling the photoperiod, early-maturing rice can be cultivated to shorten the breeding cycle, thereby reducing the risk of yield losses due to unpredictable climate change. Furthermore, early-maturing and high-yielding rice needs to be developed to ensure food security for a rapidly growing population. Early-maturing and high-yielding rice should be developed to fulfill these requirements. OsCKq1 encodes the casein kinase1 protein in rice. OsCKq1 is a gene that is activated by photophosphorylation when Ghd7, which suppresses flowering under long-day conditions, is activated. RESULTS This study investigates how OsCKq1 affects heading in rice. OsCKq1-GE rice was analyzed the function of OsCKq1 was investigated by comparing the expression levels of genes related to flowering regulation. The heading date of OsCKq1-GE lines was earlier (by about 3 to 5 days) than that of Ilmi (a rice cultivar, Oryza sativa spp. japonica), and the grain length, grain width, 1,000-grain weight, and yield increased compared to Ilmi. Furthermore, the culm and panicle lengths of OsCKq1-GE lines were either equal to or longer than those of Ilmi. CONCLUSIONS Our research demonstrates that OsCKq1 plays a pivotal role in regulating rice yield and photoperiod sensitivity. Specifically, under long-day conditions, OsCKq1-GE rice exhibited reduced OsCKq1 mRNA levels alongside increased mRNA levels of Hd3a, Ehd1, and RFT1, genes known for promoting flowering, leading to earlier heading compared to Ilmi. Moreover, we observed an increase in seed size. These findings underscore OsCKq1 as a promising target for developing early-maturing and high-yielding rice cultivars, highlighting the potential of CRISPR/Cas9 technology in enhancing crop traits.
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Affiliation(s)
- Eun-Gyeong Kim
- National Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju, 54874, Republic of Korea
| | - Yoon-Hee Jang
- Gene Engineering Division, National Institute of Agricultural Sciences, RDA, Jeonju, 54874, Republic of Korea
- Coastal Agriculture Research Institute, Kyungpook National University, Daegu, 41566, Korea
| | - Jae-Ryoung Park
- Coastal Agriculture Research Institute, Kyungpook National University, Daegu, 41566, Korea
- Crop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, 55365, Republic of Korea
| | - Xiao-Han Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Rahmatullah Jan
- Coastal Agriculture Research Institute, Kyungpook National University, Daegu, 41566, Korea
| | - Muhammad Farooq
- Department of Agriculture Biology, College of Agriculture & Life Sciences, Jeonbuk National University, Jeonju, Korea
| | - Sajjad Asaf
- Natural and Medical Science Research Center, University of Nizwa, Nizwa, 616, Oman
| | - Saleem Asif
- Department of Applied Biosciences, Kyungpook National University, Daegu, 41566, Korea
| | - Kyung-Min Kim
- Coastal Agriculture Research Institute, Kyungpook National University, Daegu, 41566, Korea.
- Department of Applied Biosciences, Kyungpook National University, Daegu, 41566, Korea.
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Jamil S, Ahmad S, Shahzad R, Umer N, Kanwal S, Rehman HM, Rana IA, Atif RM. Leveraging Multiomics Insights and Exploiting Wild Relatives' Potential for Drought and Heat Tolerance in Maize. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:16048-16075. [PMID: 38980762 DOI: 10.1021/acs.jafc.4c01375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
Climate change, particularly drought and heat stress, may slash agricultural productivity by 25.7% by 2080, with maize being the hardest hit. Therefore, unraveling the molecular nature of plant responses to these stressors is vital for the development of climate-smart maize. This manuscript's primary objective was to examine how maize plants respond to these stresses, both individually and in combination. Additionally, the paper delved into harnessing the potential of maize wild relatives as a valuable genetic resource and leveraging AI-based technologies to boost maize resilience. The role of multiomics approaches particularly genomics and transcriptomics in dissecting the genetic basis of stress tolerance was also highlighted. The way forward was proposed to utilize a bunch of information obtained through omics technologies by an interdisciplinary state-of-the-art forward-looking big-data, cyberagriculture system, and AI-based approach to orchestrate the development of climate resilient maize genotypes.
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Affiliation(s)
- Shakra Jamil
- Agricultural Biotechnology Research Institute, Ayub Agricultural Research Institute, Faisalabad 38000, Pakistan
| | - Shakeel Ahmad
- Seed Centre and Plant Genetic Resources Bank Ministry of Environment, Water and Agriculture, Riyadh 14712, Saudi Arabia
| | - Rahil Shahzad
- Agricultural Biotechnology Research Institute, Ayub Agricultural Research Institute, Faisalabad 38000, Pakistan
| | - Noroza Umer
- Dr. Ikram ul Haq - Institute of Industrial Biotechnology, Government College University, Lahore 54590, Pakistan
| | - Shamsa Kanwal
- Agricultural Biotechnology Research Institute, Ayub Agricultural Research Institute, Faisalabad 38000, Pakistan
| | - Hafiz Mamoon Rehman
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad 38000, Pakistan
| | - Iqrar Ahmad Rana
- Centre for Advanced Studies in Agriculture and Food Security, University of Agriculture, Faisalabad 38000, Pakistan
| | - Rana Muhammad Atif
- Department of Plant Sciences, University of California Davis, California 95616, United States
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad 38000, Pakistan
- Precision Agriculture and Analytics Lab, Centre for Advanced Studies in Agriculture and Food Security, National Centre in Big Data and Cloud Computing, University of Agriculture, Faisalabad 38000, Pakistan
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Dong X, Han B, Chen J, Luo D, Zhou Q, Liu Z. Multiomics Analyses Reveal MsC3H29 Positively Regulates Flavonoid Biosynthesis to Improve Drought Resistance of Autotetraploid Cultivated Alfalfa ( Medicago sativa L.). JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:14448-14465. [PMID: 38864675 DOI: 10.1021/acs.jafc.4c02472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2024]
Abstract
Alfalfa (Medicago sativa subsp. sativa), the "queen of forage," is the most important perennial legume, with high productivity and an excellent nutritional profile. Medicago sativa subsp. falcata is a subspecies of the alfalfa complex and exhibits better drought tolerance. However, drought stress significantly hampers their development and yield. The molecular mechanisms underlying the aboveground and underground tissues of sativa and falcata responding to drought stress remain obscure. Here, we performed a comprehensive comparative analysis of the physiological and transcriptomic responses of sativa and falcata under drought stress. The results showed that photosynthesis was inhibited, and antioxidant enzymes were activated under drought stress. MsC3H29, a CCCH-type zinc finger protein, was identified as a hub gene through weighted gene coexpression network analysis (WGCNA) and was significantly induced by drought in underground tissue. The MsC3H29 protein was localized in the nucleus. Overexpression (OE) of MsC3H29 can increase the primary root length and fresh weight of transgenic alfalfa hairy roots, while RNA interference (RNAi) decreases them under drought stress. The 2',7'-dichlorodihydrofluorescein diacetate (H2DCFDA) staining revealed that MsC3H29 promoted drought tolerance of alfalfa hairy roots through decreasing ROS accumulation. The targeted metabolome analysis showed that the overexpression of MsC3H29 resulted in higher levels of accumulation for flavonoid monomers, including vicenin, daidzein, apigenin, isorhamnetin, quercetin, and tricin, in transgenic alfalfa hairy roots before and after drought stress, while RNAi led to a reduction. Our study provided a key candidate gene for molecular breeding to improve drought resistance in alfalfa.
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Affiliation(s)
- Xueming Dong
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Bingcheng Han
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Jiwei Chen
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Dong Luo
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Qiang Zhou
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Zhipeng Liu
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, People's Republic of China
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Yong S, Chen Q, Xu F, Fu H, Liang G, Guo Q. Exploring the interplay between angiosperm chlorophyll metabolism and environmental factors. PLANTA 2024; 260:25. [PMID: 38861219 PMCID: PMC11166782 DOI: 10.1007/s00425-024-04437-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 05/09/2024] [Indexed: 06/12/2024]
Abstract
MAIN CONCLUSION In this review, we summarize how chlorophyll metabolism in angiosperm is affected by the environmental factors: light, temperature, metal ions, water, oxygen, and altitude. The significance of chlorophyll (Chl) in plant leaf morphogenesis and photosynthesis cannot be overstated. Over time, researchers have made significant advancements in comprehending the biosynthetic pathway of Chl in angiosperms, along with the pivotal enzymes and genes involved in this process, particularly those related to heme synthesis and light-responsive mechanisms. Various environmental factors influence the stability of Chl content in angiosperms by modulating Chl metabolic pathways. Understanding the interplay between plants Chl metabolism and environmental factors has been a prominent research topic. This review mainly focuses on angiosperms, provides an overview of the regulatory mechanisms governing Chl metabolism, and the impact of environmental factors such as light, temperature, metal ions (iron and magnesium), water, oxygen, and altitude on Chl metabolism. Understanding these effects is crucial for comprehending and preserving the homeostasis of Chl metabolism.
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Affiliation(s)
- Shunyuan Yong
- Key Laboratory of Agricultural Biosafety and Green Production of Upper Yangtze River (Ministry of Education), College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, People's Republic of China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Academy of Agricultural Sciences of Southwest University, Chongqing, 400715, People's Republic of China
| | - Qian Chen
- Key Laboratory of Agricultural Biosafety and Green Production of Upper Yangtze River (Ministry of Education), College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, People's Republic of China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Academy of Agricultural Sciences of Southwest University, Chongqing, 400715, People's Republic of China
| | - Fan Xu
- College of Agronomy and Biotechnology, Southwest University, Chongqing, 400715, People's Republic of China
| | - Hao Fu
- Key Laboratory of Agricultural Biosafety and Green Production of Upper Yangtze River (Ministry of Education), College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, People's Republic of China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Academy of Agricultural Sciences of Southwest University, Chongqing, 400715, People's Republic of China
| | - Guolu Liang
- Key Laboratory of Agricultural Biosafety and Green Production of Upper Yangtze River (Ministry of Education), College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, People's Republic of China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Academy of Agricultural Sciences of Southwest University, Chongqing, 400715, People's Republic of China
| | - Qigao Guo
- Key Laboratory of Agricultural Biosafety and Green Production of Upper Yangtze River (Ministry of Education), College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, People's Republic of China.
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Academy of Agricultural Sciences of Southwest University, Chongqing, 400715, People's Republic of China.
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Garg V, Barmukh R, Chitikineni A, Roorkiwal M, Ojiewo C, Bohra A, Thudi M, Singh VK, Kudapa H, Saxena RK, Fountain J, Mir RR, Bharadwaj C, Chen X, Xin L, Pandey MK. Celebrating Professor Rajeev K. Varshney's transformative research odyssey from genomics to the field on his induction as Fellow of the Royal Society. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:1504-1515. [PMID: 38206288 PMCID: PMC11123405 DOI: 10.1111/pbi.14282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/17/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024]
Abstract
Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground-breaking work, especially his effort to list orphan tropical crops to genomic resource-rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape.
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Affiliation(s)
- Vanika Garg
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures InstituteMurdoch UniversityMurdochWestern AustraliaAustralia
| | - Rutwik Barmukh
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures InstituteMurdoch UniversityMurdochWestern AustraliaAustralia
| | - Annapurna Chitikineni
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures InstituteMurdoch UniversityMurdochWestern AustraliaAustralia
| | - Manish Roorkiwal
- Khalifa Center for Genetic Engineering and BiotechnologyUnited Arab Emirates UniversityAl AinUAE
| | - Chris Ojiewo
- International Maize and Wheat Improvement Center (CIMMYT)NairobiKenya
| | - Abhishek Bohra
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures InstituteMurdoch UniversityMurdochWestern AustraliaAustralia
| | | | - Vikas K. Singh
- International Rice Research Institute (IRRI)‐South‐Asia HubInternational Crops Research Institute for the Semi‐Arid TropicsHyderabadIndia
| | - Himabindu Kudapa
- Center of Excellence in Genomics & Systems BiologyInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
| | | | - Jake Fountain
- Department of Plant PathologyUniversity of GeorgiaGriffinGeorgiaUSA
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of AgricultureSKUAST‐KashmirWaduraIndia
| | | | - Xiaoping Chen
- Crops Research InstituteGuangdong Academy of Agricultural Sciences (GDAAS)GuangzhouChina
| | | | - Manish K. Pandey
- Center of Excellence in Genomics & Systems BiologyInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadIndia
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11
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Cha JK, Park H, Kwon Y, Lee SM, Jang SG, Kwon SW, Lee JH. Synergizing breeding strategies via combining speed breeding, phenotypic selection, and marker-assisted backcrossing for the introgression of Glu-B1i in wheat. FRONTIERS IN PLANT SCIENCE 2024; 15:1402709. [PMID: 38863547 PMCID: PMC11165042 DOI: 10.3389/fpls.2024.1402709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/16/2024] [Indexed: 06/13/2024]
Abstract
Wheat is a major food crop that plays a crucial role in the human diet. Various breeding technologies have been developed and refined to meet the increasing global wheat demand. Several studies have suggested breeding strategies that combine generation acceleration systems and molecular breeding methods to maximize breeding efficiency. However, real-world examples demonstrating the effective utilization of these strategies in breeding programs are lacking. In this study, we designed and demonstrated a synergized breeding strategy (SBS) that combines rapid and efficient breeding techniques, including speed breeding, speed vernalization, phenotypic selection, backcrossing, and marker-assisted selection. These breeding techniques were tailored to the specific characteristics of the breeding materials and objectives. Using the SBS approach, from artificial crossing to the initial observed yield trial under field conditions only took 3.5 years, resulting in a 53% reduction in the time required to develop a BC2 near-isogenic line (NIL) and achieving a higher recurrent genome recovery of 91.5% compared to traditional field conditions. We developed a new wheat NIL derived from cv. Jokyoung, a leading cultivar in Korea. Milyang56 exhibited improved protein content, sodium dodecyl sulfate-sedimentation value, and loaf volume compared to Jokyoung, which were attributed to introgression of the Glu-B1i allele from the donor parent, cv. Garnet. SBS represents a flexible breeding model that can be applied by breeders for developing breeding materials and mapping populations, as well as analyzing the environmental effects of specific genes or loci and for trait stacking.
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Affiliation(s)
- Jin-Kyung Cha
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang, Republic of Korea
| | - Hyeonjin Park
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang, Republic of Korea
| | - Youngho Kwon
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang, Republic of Korea
| | - So-Myeong Lee
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang, Republic of Korea
| | - Seong-Gyu Jang
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang, Republic of Korea
| | - Soon-Wook Kwon
- Department of Plant Bioscience, Pusan National University, Miryang, Republic of Korea
| | - Jong-Hee Lee
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang, Republic of Korea
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12
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Vimal SR, Singh JS, Kumar A, Prasad SM. The plant endomicrobiome: Structure and strategies to produce stress resilient future crop. CURRENT RESEARCH IN MICROBIAL SCIENCES 2024; 6:100236. [PMID: 38756233 PMCID: PMC11097330 DOI: 10.1016/j.crmicr.2024.100236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024] Open
Abstract
Plants have a microbiome, a diverse community of microorganisms, including bacteria, fungi, and viruses, living inside and on their tissues. Versatile endophytic microorganisms inhabited in every plant part without causing disease and develop endophytic microbiome or endo-microbiome. Plant endo-microbiome are drawn by the nutrient rich micro-environment, and in turn some microbes mutualistically endorse and protect plant from adverse environmental stresses. Plant endo-microbiome interact within well-designed host equilibrium containing xylem, phloem, nutrients, phytohormones, metabolites and shift according to environmental and nutritional change. Plant endo-microbiome regulate and respond to environmental variations, pathogens, herbivores by producing stress regulators, organic acids, secondary metabolites, stress hormones as well as unknown substances and signalling molecules. Endomicrobiome efficiently synthesizes multiple bioactive compounds, stress phytohormones with high competence. The technological innovation as next generation genomics biology and high-throughput multiomics techniques stepping stones on the illumination of critical endo-microbiome communities and functional characterization that aid in improving plant physiology, biochemistry and immunity interplay for best crop productivity. This review article contains deeper insight in endomicrobiome related research work in last years, recruitment, niche development, nutrient dynamics, stress removal mechanisms, bioactive services in plant health development, community architecture and communication, and immunity interplay in producing stress resilient future crop.
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Affiliation(s)
- Shobhit Raj Vimal
- Ranjan Plant Physiology & Biochemistry Laboratory, Department of Botany, University of Allahabad, Prayagraj 211002, Uttar Pradesh, India
| | - Jay Shankar Singh
- Department of Environmental Microbiology, School for Earth and Environmental Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, Uttar Pradesh, India
| | - Ashwani Kumar
- Metagenomics and Secretomics Research Laboratory, Department of Botany, University of Allahabad (A Central University), Prayagraj 211002, Uttar Pradesh, India
| | - Sheo Mohan Prasad
- Ranjan Plant Physiology & Biochemistry Laboratory, Department of Botany, University of Allahabad, Prayagraj 211002, Uttar Pradesh, India
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13
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Ding H, Wang C, Cai Y, Yu K, Zhao H, Wang F, Shi X, Cheng J, Sun H, Wu Y, Qin R, Liu C, Zhao C, Sun X, Cui F. Characterization of a wheat stable QTL for spike length and its genetic effects on yield-related traits. BMC PLANT BIOLOGY 2024; 24:292. [PMID: 38632554 PMCID: PMC11022484 DOI: 10.1186/s12870-024-04963-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 03/29/2024] [Indexed: 04/19/2024]
Abstract
Spike length (SL) is one of the most important agronomic traits affecting yield potential and stability in wheat. In this study, a major stable quantitative trait locus (QTL) for SL, i.e., qSl-2B, was detected in multiple environments in a recombinant inbred line (RIL) mapping population, KJ-RILs, derived from a cross between Kenong 9204 (KN9204) and Jing 411 (J411). The qSl-2B QTL was mapped to the 60.06-73.06 Mb region on chromosome 2B and could be identified in multiple mapping populations. An InDel molecular marker in the target region was developed based on a sequence analysis of the two parents. To further clarify the breeding use potential of qSl-2B, we analyzed its genetic effects and breeding selection effect using both the KJ-RIL population and a natural mapping population, which consisted of 316 breeding varieties/advanced lines. The results showed that the qSl-2B alleles from KN9204 showed inconsistent genetic effects on SL in the two mapping populations. Moreover, in the KJ-RILs population, the additive effects analysis of qSl-2B showed that additive effect was higher when both qSl-2D and qSl-5A harbor negative alleles under LN and HN. In China, a moderate selection utilization rate for qSl-2B was found in the Huanghuai winter wheat area and the selective utilization rate for qSl-2B continues to increase. The above findings provided a foundation for the genetic improvement of wheat SL in the future via molecular breeding strategies.
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Affiliation(s)
- Hongke Ding
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Chenyang Wang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yibiao Cai
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Kai Yu
- Yantai Agricultural Technology Extension Center, Yantai, 264001, China
| | - Haibo Zhao
- Yantai Agricultural Technology Extension Center, Yantai, 264001, China
| | - Faxiang Wang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Xinyao Shi
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Jiajia Cheng
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Han Sun
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yongzhen Wu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Ran Qin
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Cheng Liu
- Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Chunhua Zhao
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
| | - Xiaohui Sun
- Yantai Academy of Agricultural Sciences, Yantai, Shandong, 265500, China.
| | - Fa Cui
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
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14
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Wang L, Chang C. Stomatal improvement for crop stress resistance. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:1823-1833. [PMID: 38006251 DOI: 10.1093/jxb/erad477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 11/23/2023] [Indexed: 11/26/2023]
Abstract
The growth and yield of crop plants are threatened by environmental challenges such as water deficit, soil flooding, high salinity, and extreme temperatures, which are becoming increasingly severe under climate change. Stomata contribute greatly to plant adaptation to stressful environments by governing transpirational water loss and photosynthetic gas exchange. Increasing evidence has revealed that stomata formation is shaped by transcription factors, signaling peptides, and protein kinases, which could be exploited to improve crop stress resistance. The past decades have seen unprecedented progress in our understanding of stomata formation, but most of these advances have come from research on model plants. This review highlights recent research in stomata formation in crops and its multifaceted functions in abiotic stress tolerance. Current strategies, limitations, and future directions for harnessing stomatal development to improve crop stress resistance are discussed.
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Affiliation(s)
- Lu Wang
- College of Life Sciences, Qingdao University, Qingdao, Shandong, China
| | - Cheng Chang
- College of Life Sciences, Qingdao University, Qingdao, Shandong, China
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15
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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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16
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Tian D, Xu T, Kang H, Luo H, Wang Y, Chen M, Li R, Ma L, Wang Z, Hao L, Tang B, Zou D, Xiao J, Zhao W, Bao Y, Zhang Z, Song S. Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications. ABIOTECH 2024; 5:94-106. [PMID: 38576435 PMCID: PMC10987443 DOI: 10.1007/s42994-023-00134-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/18/2023] [Indexed: 04/06/2024]
Abstract
Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study. Supplementary Information The online version contains supplementary material available at 10.1007/s42994-023-00134-4.
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Affiliation(s)
- Dongmei Tian
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Tianyi Xu
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Hailong Kang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Hong Luo
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Yanqing Wang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Meili Chen
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Rujiao Li
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Lina Ma
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Zhonghuang Wang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Lili Hao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Bixia Tang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Dong Zou
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
| | - Jingfa Xiao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Wenming Zhao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Yiming Bao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Zhang Zhang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Shuhui Song
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences & China National Center for Bioinformation, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
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17
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Singh G, Kaur N, Khanna R, Kaur R, Gudi S, Kaur R, Sidhu N, Vikal Y, Mangat GS. 2Gs and plant architecture: breaking grain yield ceiling through breeding approaches for next wave of revolution in rice ( Oryza sativa L.). Crit Rev Biotechnol 2024; 44:139-162. [PMID: 36176065 DOI: 10.1080/07388551.2022.2112648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 07/10/2022] [Accepted: 07/27/2022] [Indexed: 11/03/2022]
Abstract
Rice is a principal food crop for more than half of the global population. Grain number and grain weight (2Gs) are the two complex traits controlled by several quantitative trait loci (QTLs) and are considered the most critical components for yield enhancement in rice. Novel molecular biology and QTL mapping strategies can be utilized in dissecting the complex genetic architecture of these traits. Discovering the valuable genes/QTLs associated with 2Gs traits hidden in the rice genome and utilizing them in breeding programs may bring a revolution in rice production. Furthermore, the positional cloning and functional characterization of identified genes and QTLs may aid in understanding the molecular mechanisms underlying the 2Gs traits. In addition, knowledge of modern genomic tools aids the understanding of the nature of plant and panicle architecture, which enhances their photosynthetic activity. Rice researchers continue to combine important yield component traits (including 2Gs for the yield ceiling) by utilizing modern breeding tools, such as marker-assisted selection (MAS), haplotype-based breeding, and allele mining. Physical co-localization of GW7 (for grain weight) and DEP2 (for grain number) genes present on chromosome 7 revealed the possibility of simultaneous introgression of these two genes, if desirable allelic variants were found in the single donor parent. This review article will reveal the genetic nature of 2Gs traits and use this knowledge to break the yield ceiling by using different breeding and biotechnological tools, which will sustain the world's food requirements.
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Affiliation(s)
- Gurjeet Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Navdeep Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Renu Khanna
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Rupinder Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Rajvir Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Navjot Sidhu
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Yogesh Vikal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | - G S Mangat
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
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18
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Kang H, Huang T, Duan G, Meng Y, Chen X, He S, Xia Z, Zhou X, Chao J, Tang B, Wang Z, Zhu J, Du Z, Sun Y, Zhang S, Xiao J, Tian W, Wang W, Zhao W. TCOD: an integrated resource for tropical crops. Nucleic Acids Res 2024; 52:D1651-D1660. [PMID: 37843152 PMCID: PMC10767838 DOI: 10.1093/nar/gkad870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/25/2023] [Accepted: 09/29/2023] [Indexed: 10/17/2023] Open
Abstract
Tropical crops are vital for tropical agriculture, with resource scarcity, functional diversity and extensive market demand, providing considerable economic benefits for the world's tropical agriculture-producing countries. The rapid development of sequencing technology has promoted a milestone in tropical crop research, resulting in the generation of massive amount of data, which urgently needs an effective platform for data integration and sharing. However, the existing databases cannot fully satisfy researchers' requirements due to the relatively limited integration level and untimely update. Here, we present the Tropical Crop Omics Database (TCOD, https://ngdc.cncb.ac.cn/tcod), a comprehensive multi-omics data platform for tropical crops. TCOD integrates diverse omics data from 15 species, encompassing 34 chromosome-level de novo assemblies, 1 255 004 genes with functional annotations, 282 436 992 unique variants from 2048 WGS samples, 88 transcriptomic profiles from 1997 RNA-Seq samples and 13 381 germplasm items. Additionally, TCOD not only employs genes as a bridge to interconnect multi-omics data, enabling cross-species comparisons based on homology relationships, but also offers user-friendly online tools for efficient data mining and visualization. In short, TCOD integrates multi-species, multi-omics data and online tools, which will facilitate the research on genomic selective breeding and trait biology of tropical crops.
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Affiliation(s)
- Hailong Kang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tianhao Huang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guangya Duan
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuyan Meng
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoning Chen
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuang He
- Sanya Nanfan Research Institute, Hainan University, Sanya 572025, China
| | - Zhiqiang Xia
- Sanya Nanfan Research Institute, Hainan University, Sanya 572025, China
| | - Xincheng Zhou
- Institute of Tropical Biosciences and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Jinquan Chao
- Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Bixia Tang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Zhonghuang Wang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Junwei Zhu
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Zhenglin Du
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Yanlin Sun
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Sisi Zhang
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Jingfa Xiao
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weimin Tian
- Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Wenquan Wang
- Sanya Nanfan Research Institute, Hainan University, Sanya 572025, China
| | - Wenming Zhao
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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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] [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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20
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Garg V, Khan AW, Fengler K, Llaca V, Yuan Y, Vuong TD, Harris C, Chan TF, Lam HM, Varshney RK, Nguyen HT. Near-gapless genome assemblies of Williams 82 and Lee cultivars for accelerating global soybean research. THE PLANT GENOME 2023; 16:e20382. [PMID: 37749941 DOI: 10.1002/tpg2.20382] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 08/01/2023] [Accepted: 08/03/2023] [Indexed: 09/27/2023]
Abstract
Complete, gapless telomere-to-telomere chromosome assemblies are a prerequisite for comprehensively investigating the architecture of complex regions, like centromeres or telomeres and removing uncertainties in the order, spacing, and orientation of genes. Using complementary genomics technologies and assembly algorithms, we developed highly contiguous, nearly gapless, genome assemblies for two economically important soybean [Glycine max (L.) Merr] cultivars (Williams 82 and Lee). The centromeres were distinctly annotated on all the chromosomes of both assemblies. We further found that the canonical telomeric repeats were present at the telomeres of all chromosomes of both Williams 82 and Lee genomes. A total of 10 chromosomes in Williams 82 and eight in Lee were entirely reconstructed in single contigs without any gap. Using the combination of ab initio prediction, protein homology, and transcriptome evidence, we identified 58,287 and 56,725 protein-coding genes in Williams 82 and Lee, respectively. The genome assemblies and annotations will serve as a valuable resource for studying soybean genomics and genetics and accelerating soybean improvement.
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Affiliation(s)
- Vanika Garg
- Murdoch's Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Aamir W Khan
- Division of Plant Sciences and Technology, University of Missouri, Columbia, Missouri, USA
| | - Kevin Fengler
- Research and Development, Corteva Agriscience, Johnston, Iowa, USA
| | - Victor Llaca
- Research and Development, Corteva Agriscience, Johnston, Iowa, USA
| | - Yuxuan Yuan
- School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Tri D Vuong
- Division of Plant Sciences and Technology, University of Missouri, Columbia, Missouri, USA
| | - Charlotte Harris
- Research and Development, Corteva Agriscience, Johnston, Iowa, USA
| | - Ting-Fung Chan
- School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Hon Ming Lam
- School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Rajeev K Varshney
- Murdoch's Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Henry T Nguyen
- Division of Plant Sciences and Technology, University of Missouri, Columbia, Missouri, USA
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21
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Raza A, Tabassum J, Fakhar AZ, Sharif R, Chen H, Zhang C, Ju L, Fotopoulos V, Siddique KHM, Singh RK, Zhuang W, Varshney RK. Smart reprograming of plants against salinity stress using modern biotechnological tools. Crit Rev Biotechnol 2023; 43:1035-1062. [PMID: 35968922 DOI: 10.1080/07388551.2022.2093695] [Citation(s) in RCA: 41] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 05/08/2022] [Indexed: 01/19/2023]
Abstract
Climate change gives rise to numerous environmental stresses, including soil salinity. Salinity/salt stress is the second biggest abiotic factor affecting agricultural productivity worldwide by damaging numerous physiological, biochemical, and molecular processes. In particular, salinity affects plant growth, development, and productivity. Salinity responses include modulation of ion homeostasis, antioxidant defense system induction, and biosynthesis of numerous phytohormones and osmoprotectants to protect plants from osmotic stress by decreasing ion toxicity and augmented reactive oxygen species scavenging. As most crop plants are sensitive to salinity, improving salt tolerance is crucial in sustaining global agricultural productivity. In response to salinity, plants trigger stress-related genes, proteins, and the accumulation of metabolites to cope with the adverse consequence of salinity. Therefore, this review presents an overview of salinity stress in crop plants. We highlight advances in modern biotechnological tools, such as omics (genomics, transcriptomics, proteomics, and metabolomics) approaches and different genome editing tools (ZFN, TALEN, and CRISPR/Cas system) for improving salinity tolerance in plants and accomplish the goal of "zero hunger," a worldwide sustainable development goal proposed by the FAO.
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Affiliation(s)
- Ali Raza
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Javaria Tabassum
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Science (CAAS), Zhejiang, China
| | - Ali Zeeshan Fakhar
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan
| | - Rahat Sharif
- Department of Horticulture, College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Hua Chen
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Chong Zhang
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Luo Ju
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Science (CAAS), Zhejiang, China
| | - Vasileios Fotopoulos
- Department of Agricultural Sciences, Biotechnology & Food Science, Cyprus University of Technology, Lemesos, Cyprus
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, Perth, Australia
| | - Rakesh K Singh
- Crop Diversification and Genetics, International Center for Biosaline Agriculture, Dubai, United Arab Emirates
| | - Weijian Zhuang
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Rajeev K Varshney
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Murdoch's Centre for Crop and Food Innovation, State Agricultural Biotechnology Centre, Murdoch University, Murdoch, Australia
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Ma K, Yuan Y, Fang C. Mainstreaming production and nutrient resilience of vegetable crops in megacities: pre-breeding for terrace cultivation. FRONTIERS IN PLANT SCIENCE 2023; 14:1237099. [PMID: 38053771 PMCID: PMC10694833 DOI: 10.3389/fpls.2023.1237099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 10/30/2023] [Indexed: 12/07/2023]
Abstract
Modern megacities offer convenient lifestyles to their citizens. However, agriculture is becoming increasingly vulnerable, especially during unexpected public health emergencies such as pandemics. Fortunately, the adaptability of terrace vegetables cultivation presents an opportunity to grow horticultural crops in residential spaces, bringing numerous benefits to citizens, including enhanced nutrition and recreational engagement in the cultivation process. Although certain planting skills and equipment have been developed, the citizens tend to sow some seeds with unknown pedigree, it is rare to find new plant varieties specifically bred for cultivation as terrace vegetables. To expand the genetic basis of new breeding materials, elite parents, and varieties (pre-breeding) for terrace cultivation, this review not only discusses the molecular breeding strategy for the identification, creation, and application of rational alleles for improving horticultural characteristics including plant architecture, flavor quality, and ornamental character, but also assesses the potential for terrace cultivation of some representative vegetable crops. We conclude that the process of pre-breeding specifically for terrace cultivation environments is vital for generating a genetic basis for urban terrace vegetable crops.
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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 SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 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] [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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de Oliveira KKP, de Oliveira RR, Chalfun-Junior A. Small RNAs: Promising Molecules to Tackle Climate Change Impacts in Coffee Production. PLANTS (BASEL, SWITZERLAND) 2023; 12:3531. [PMID: 37895993 PMCID: PMC10610182 DOI: 10.3390/plants12203531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 09/28/2023] [Accepted: 09/30/2023] [Indexed: 10/29/2023]
Abstract
Over the centuries, human society has evolved based on the ability to select and use more adapted species for food supply, which means making plant species tastier and more productive in particular environmental conditions. However, nowadays, this scenario is highly threatened by climate change, especially by the changes in temperature and greenhouse gasses that directly affect photosynthesis, which highlights the need for strategic studies aiming at crop breeding and guaranteeing food security. This is especially worrying for crops with complex phenology, genomes with low variability, and the ones that support a large production chain, such as Coffea sp. L. In this context, recent advances shed some light on the genome function and transcriptional control, revealing small RNAs (sRNAs) that are responsible for environmental cues and could provide variability through gene expression regulation. Basically, sRNAs are responsive to environmental changes and act on the transcriptional and post-transcriptional gene silencing pathways that regulate gene expression and, consequently, biological processes. Here, we first discuss the predicted impact of climate changes on coffee plants and coffee chain production and then the role of sRNAs in response to environmental changes, especially temperature, in different species, together with their potential as tools for genetic improvement. Very few studies in coffee explored the relationship between sRNAs and environmental cues; thus, this review contributes to understanding coffee development in the face of climate change and towards new strategies of crop breeding.
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Affiliation(s)
| | | | - Antonio Chalfun-Junior
- Laboratory of Plant Molecular Physiology, Plant Physiology Sector, Institute of Biology, Federal University of Lavras, Lavras 3037, Brazil; (K.K.P.d.O.); (R.R.d.O.)
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25
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Qin R, Ma T, Cai Y, Shi X, Cheng J, Dong J, Wang C, Li S, Pan G, Guan Y, Zhang L, Yang S, Xu H, Zhao C, Sun H, Li X, Wu Y, Li J, Cui F. Characterization and fine mapping analysis of a major stable QTL qKnps-4A for kernel number per spike in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:211. [PMID: 37737910 DOI: 10.1007/s00122-023-04456-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 08/28/2023] [Indexed: 09/23/2023]
Abstract
KEY MESSAGE A major stable QTL for kernel number per spike was narrowed down to a 2.19-Mb region containing two potential candidate genes, and its effects on yield-related traits were characterized. Kernel number per spike (KNPS) in wheat is a key yield component. Dissection and characterization of major stable quantitative trait loci (QTLs) for KNPS would be of considerable value for the genetic improvement of yield potential using molecular breeding technology. We had previously reported a major stable QTL controlling KNPS, qKnps-4A. In the current study, primary fine-mapping analysis, based on the primary mapping population, located qKnps-4A to an interval of approximately 6.8-Mb from 649.0 to 655.8 Mb on chromosome 4A refering to 'Kenong 9204' genome. Further fine-mapping analysis based on a secondary mapping population narrowed qKnps-4A to an approximately 2.19-Mb interval from 653.72 to 655.91 Mb. Transcriptome sequencing, gene function annotation analysis and homologous gene related reports showed that TraesKN4A01HG38570 and TraesKN4A01HG38590 were most likely to be candidate genes of qKnps-4A. Phenotypic analysis based on paired near-isogenic lines in the target region showed that qKnps-4A increased KNPS mainly by increasing the number of central florets per spike. We also evaluated the effects of qKnps-4A on other yield-related traits. Moreover, we dissected the QTL cluster of qKnps-4A and qTkw-4A and proved that the phenotypic effects were probably due to close linkage of two or more genes rather than pleiotropic effects of a single gene. This study provides molecular marker resource for wheat molecular breeding designed to improve yield potential, and lay the foundation for gene functional analysis of qKnps-4A.
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Affiliation(s)
- Ran Qin
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Tianhang Ma
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yibiao Cai
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Xinyao Shi
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Jiajia Cheng
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Jizi Dong
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Chenyang Wang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Shihui Li
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Guoqing Pan
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yuxiang Guan
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Lei Zhang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Shuang Yang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Huiyuan Xu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Chunhua Zhao
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Han Sun
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Ximei Li
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
- Shandong Key Laboratory of Dryland Farming Technology, Shandong Engineering Research Center of Germplasm Innovation and Utilization of Salt-Tolerant Crops, College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, China
| | - Yongzhen Wu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
| | - Junming Li
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Hebei Collaboration Innovation Center for Cell Signaling, Shijiazhuang, 050024, China.
| | - Fa Cui
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
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Li C, Wan Y, Shang X, Fang S. Integration of transcriptomic and metabolomic analysis unveils the response mechanism of sugar metabolism in Cyclocarya paliurus seedlings subjected to PEG-induced drought stress. PLANT PHYSIOLOGY AND BIOCHEMISTRY : PPB 2023; 201:107856. [PMID: 37354727 DOI: 10.1016/j.plaphy.2023.107856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/16/2023] [Accepted: 06/19/2023] [Indexed: 06/26/2023]
Abstract
Cyclocarya paliurus (Batal.) Iljinskaja is a multiple function tree species used for functional food and valued timber production. Carbohydrates, especially water-soluble carbohydrates, play an important role in osmotic protection, signal transduction and carbon storage. Under the circumstance of global climate change the abiotic stress would restrict the development of C. paliurus plantation, whereas there is few knowledge on the regulatory mechanisms of sugar metabolism under drought stress in C. paliurus. To investigate the drought response of C. paliurus at molecular level, we conducted an integrated analysis of transcriptomic and metabolomic of C. paliurus at three PEG-induced drought stress levels (0%: control; 15%: moderate drought; 25%: severe drought) in short term. Both moderate and severe drought treatments activated the chemical defense with lowering relative water content, and enhancing the contents of soluble protein, proline and malondialdehyde in the leaves. Meanwhile, alterations in the expression of differentially expressed genes and carbohydrate metabolism profiles were observed among the treatments. Weighted gene co-expression network analysis (WGCNA) showed 3 key modules, 8 structural genes (such as genes encoding beta-fructofuranosidase (INV), sucrose synthase (SUS), raffinose synthase (RS)) and 14 regulatory transcription factors were closely linked to sugar metabolism. Our results provided the foundation to understand the response mechanism of sugar metabolism in C. paliurus under drought stress, and would drive progress in breeding of drought-tolerant varieties and plantation development of the species.
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Affiliation(s)
- Chenhui Li
- College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Yifeng Wan
- College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Xulan Shang
- College of Forestry, Nanjing Forestry University, Nanjing, China; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
| | - Shengzuo Fang
- College of Forestry, Nanjing Forestry University, Nanjing, China; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China.
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Raza A, Charagh S, Karikari B, Sharif R, Yadav V, Mubarik MS, Habib M, Zhuang Y, Zhang C, Chen H, Varshney RK, Zhuang W. miRNAs for crop improvement. PLANT PHYSIOLOGY AND BIOCHEMISTRY : PPB 2023; 201:107857. [PMID: 37437345 DOI: 10.1016/j.plaphy.2023.107857] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/16/2023] [Accepted: 06/19/2023] [Indexed: 07/14/2023]
Abstract
Climate change significantly impacts crop production by inducing several abiotic and biotic stresses. The increasing world population, and their food and industrial demands require focused efforts to improve crop plants to ensure sustainable food production. Among various modern biotechnological tools, microRNAs (miRNAs) are one of the fascinating tools available for crop improvement. miRNAs belong to a class of small non-coding RNAs playing crucial roles in numerous biological processes. miRNAs regulate gene expression by post-transcriptional target mRNA degradation or by translation repression. Plant miRNAs have essential roles in plant development and various biotic and abiotic stress tolerance. In this review, we provide propelling evidence from previous studies conducted around miRNAs and provide a one-stop review of progress made for breeding stress-smart future crop plants. Specifically, we provide a summary of reported miRNAs and their target genes for improvement of plant growth and development, and abiotic and biotic stress tolerance. We also highlight miRNA-mediated engineering for crop improvement and sequence-based technologies available for the identification of miRNAs associated with stress tolerance and plant developmental events.
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Affiliation(s)
- Ali Raza
- Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 35002, China
| | - Sidra Charagh
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Hangzhou, China
| | - Benjamin Karikari
- Department of Agricultural Biotechnology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Rahat Sharif
- Department of Horticulture, College of Horticulture and Landscape Architecture, Yangzhou University, 48 Wenhui East Road, Yangzhou, Jiangsu 225009, China
| | - Vivek Yadav
- College of Horticulture, Northwest Agriculture and Forestry University, Yangling, Shanxi, 712100, China
| | | | - Madiha Habib
- National Institute for Genomics and Advanced Biotechnology (NIGAB), National Agricultural Research Centre (NARC), Park Rd., Islamabad 45500, Pakistan
| | - Yuhui Zhuang
- College of Life Science, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Chong Zhang
- Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 35002, China
| | - Hua Chen
- Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 35002, China
| | - Rajeev K Varshney
- Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 35002, China; WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia.
| | - Weijian Zhuang
- Center of Legume Crop Genetics and Systems Biology, Oil Crops Research Institute, College of Agriculture, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 35002, China.
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Ruperao P, Rangan P, Shah T, Thakur V, Kalia S, Mayes S, Rathore A. The Progression in Developing Genomic Resources for Crop Improvement. Life (Basel) 2023; 13:1668. [PMID: 37629524 PMCID: PMC10455509 DOI: 10.3390/life13081668] [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: 06/15/2023] [Revised: 07/21/2023] [Accepted: 07/25/2023] [Indexed: 08/27/2023] Open
Abstract
Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques.
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Affiliation(s)
- Pradeep Ruperao
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Parimalan Rangan
- ICAR-National Bureau of Plant Genetic Resources, PUSA Campus, New Delhi 110012, India;
| | - Trushar Shah
- International Institute of Tropical Agriculture (IITA), Nairobi 30709-00100, Kenya;
| | - Vivek Thakur
- Department of Systems & Computational Biology, School of Life Sciences, University of Hyderabad, Hyderabad 500046, India;
| | - Sanjay Kalia
- Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi 110003, India;
| | - Sean Mayes
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Abhishek Rathore
- Excellence in Breeding, International Maize and Wheat Improvement Center (CIMMYT), Hyderabad 502324, India
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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] [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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Krishna TPA, Veeramuthu D, Maharajan T, Soosaimanickam M. The Era of Plant Breeding: Conventional Breeding to Genomics-assisted Breeding for Crop Improvement. Curr Genomics 2023; 24:24-35. [PMID: 37920729 PMCID: PMC10334699 DOI: 10.2174/1389202924666230517115912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/31/2023] [Accepted: 04/14/2023] [Indexed: 11/04/2023] Open
Abstract
Plant breeding has made a significant contribution to increasing agricultural production. Conventional breeding based on phenotypic selection is not effective for crop improvement. Because phenotype is considerably influenced by environmental factors, which will affect the selection of breeding materials for crop improvement. The past two decades have seen tremendous progress in plant breeding research. Especially the availability of high-throughput molecular markers followed by genomic-assisted approaches significantly contributed to advancing plant breeding. Integration of speed breeding with genomic and phenomic facilities allowed rapid quantitative trait loci (QTL)/gene identifications and ultimately accelerated crop improvement programs. The advances in sequencing technology helps to understand the genome organization of many crops and helped with genomic selection in crop breeding. Plant breeding has gradually changed from phenotype-to-genotype-based to genotype-to-phenotype-based selection. High-throughput phenomic platforms have played a significant role in the modern breeding program and are considered an essential part of precision breeding. In this review, we discuss the rapid advance in plant breeding technology for efficient crop improvements and provide details on various approaches/platforms that are helpful for crop improvement. This review will help researchers understand the recent developments in crop breeding and improvements.
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Affiliation(s)
| | - Duraipandiyan Veeramuthu
- Division of Plant Biotechnology, Entomology Research Institute, Loyola College, Chennai, Tamil Nadu, India
| | - Theivanayagam Maharajan
- Division of Plant Biotechnology, Entomology Research Institute, Loyola College, Chennai, Tamil Nadu, India
| | - Mariapackiam Soosaimanickam
- Division of Plant Biotechnology, Entomology Research Institute, Loyola College, Chennai, Tamil Nadu, India
- Department of Advanced Zoology & Biotechnology, Loyola College, Nungambakkam, Chennai, 600034, India
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Raza A, Mubarik MS, Sharif R, Habib M, Jabeen W, Zhang C, Chen H, Chen ZH, Siddique KHM, Zhuang W, Varshney RK. Developing drought-smart, ready-to-grow future crops. THE PLANT GENOME 2023; 16:e20279. [PMID: 36366733 DOI: 10.1002/tpg2.20279] [Citation(s) in RCA: 39] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 08/02/2022] [Indexed: 05/10/2023]
Abstract
Breeding crop plants with increased yield potential and improved tolerance to stressful environments is critical for global food security. Drought stress (DS) adversely affects agricultural productivity worldwide and is expected to rise in the coming years. Therefore, it is vital to understand the physiological, biochemical, molecular, and ecological mechanisms associated with DS. This review examines recent advances in plant responses to DS to expand our understanding of DS-associated mechanisms. Suboptimal water sources adversely affect crop growth and yields through physical impairments, physiological disturbances, biochemical modifications, and molecular adjustments. To control the devastating effect of DS in crop plants, it is important to understand its consequences, mechanisms, and the agronomic and genetic basis of DS for sustainable production. In addition to plant responses, we highlight several mitigation options such as omics approaches, transgenics breeding, genome editing, and biochemical to mechanical methods (foliar treatments, seed priming, and conventional agronomic practices). Further, we have also presented the scope of conventional and speed breeding platforms in helping to develop the drought-smart future crops. In short, we recommend incorporating several approaches, such as multi-omics, genome editing, speed breeding, and traditional mechanical strategies, to develop drought-smart cultivars to achieve the 'zero hunger' goal.
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Affiliation(s)
- Ali Raza
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry Univ., Fuzhou, 350002, China
| | | | - Rahat Sharif
- Dep. of Horticulture, College of Horticulture and Plant Protection, Yangzhou Univ., Yangzhou, Jiangsu, 225009, China
| | - Madiha Habib
- National Institute for Genomics and Advanced Biotechnology, National Agricultural Research Centre, Park Rd., Islamabad, 45500, Pakistan
| | - Warda Jabeen
- Institute of Environmental Sciences and Engineering, School of Civil and Environmental Engineering, National Univ. of Sciences and Technology, Islamabad, 44000, Pakistan
| | - Chong Zhang
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry Univ., Fuzhou, 350002, China
| | - Hua Chen
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry Univ., Fuzhou, 350002, China
| | - Zhong-Hua Chen
- School of Science, Hawkesbury Institute for the Environment, Western Sydney Univ., Penrith, NSW, 2751, Australia
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The Univ. of Western Australia, Crawley, Perth, 6009, Australia
| | - Weijian Zhuang
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry Univ., Fuzhou, 350002, China
| | - Rajeev K Varshney
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Oil Crops Research Institute, Center of Legume Crop Genetics and Systems Biology/College of Agriculture, Fujian Agriculture and Forestry Univ., Fuzhou, 350002, China
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Murdoch Univ., Murdoch, WA, 6150, Australia
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Zhao S, Zhang C, Wang L, Luo M, Zhang P, Wang Y, Malik WA, Wang Y, Chen P, Qiu X, Wang C, Lu H, Xiang Y, Liu Y, Ruan J, Qian Q, Zhi H, Chang Y. A prolific and robust whole-genome genotyping method using PCR amplification via primer-template mismatched annealing. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2023; 65:633-645. [PMID: 36269601 DOI: 10.1111/jipb.13395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
Whole-genome genotyping methods are important for breeding. However, it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes and species. In our study, we accidently discovered that in adapter ligation-mediated PCR, the amplification by primer-template mismatched annealing (PTMA) along the genome could generate thousands of stable PCR products. Based on this observation, we consequently developed a novel method for simultaneous foreground and background integrated genotyping by sequencing (FBI-seq) using one specific primer, in which foreground genotyping is performed by primer-template perfect annealing (PTPA), while background genotyping employs PTMA. Unlike DNA arrays, multiple PCR, or genome target enrichments, FBI-seq requires little preliminary work for primer design and synthesis, and it is easily adaptable to different foreground genes and species. FBI-seq therefore provides a prolific, robust, and accurate method for simultaneous foreground and background genotyping to facilitate breeding in the post-genomics era.
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Affiliation(s)
- Sheng Zhao
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China
- 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, 518120, China
| | - Cuicui Zhang
- 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, 518120, China
| | - Liqun Wang
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Minxuan Luo
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China
- 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, 518120, China
| | - Peng Zhang
- 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, 518120, China
| | - Yue Wang
- 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, 518120, China
| | - Waqar Afzal Malik
- 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, 518120, China
| | - Yue Wang
- 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, 518120, China
| | - Peng 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, 518120, China
| | - Xianjin Qiu
- College of Agriculture, Yangtze University, Jingzhou, 434023, China
| | - Chongrong Wang
- Guangdong Provincial Key Laboratory of New Technology in Rice Breeding, Rice Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Hong 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, 518120, China
| | - Yong Xiang
- 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, 518120, China
| | - Yuwen 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, 518120, China
| | - Jue Ruan
- 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, 518120, China
| | - Qian Qian
- 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, 518120, China
| | - Haijian Zhi
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yuxiao Chang
- 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, 518120, China
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Yan J, Wang X. Machine learning bridges omics sciences and plant breeding. TRENDS IN PLANT SCIENCE 2023; 28:199-210. [PMID: 36153276 DOI: 10.1016/j.tplants.2022.08.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 08/15/2022] [Accepted: 08/23/2022] [Indexed: 06/16/2023]
Abstract
Some of the biological knowledge obtained from fundamental research will be implemented in applied plant breeding. To bridge basic research and breeding practice, machine learning (ML) holds great promise to translate biological knowledge and omics data into precision-designed plant breeding. Here, we review ML for multi-omics analysis in plants, including data dimensionality reduction, inference of gene-regulation networks, and gene discovery and prioritization. These applications will facilitate understanding trait regulation mechanisms and identifying target genes potentially applicable to knowledge-driven molecular design breeding. We also highlight applications of deep learning in plant phenomics and ML in genomic selection-assisted breeding, such as various ML algorithms that model the correlations among genotypes (genes), phenotypes (traits), and environments, to ultimately achieve data-driven genomic design breeding.
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Affiliation(s)
- Jun Yan
- National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100094, China; Frontiers Science Center for Molecular Design Breeding, China Agricultural University, Beijing 100094, China
| | - Xiangfeng Wang
- National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100094, China; Frontiers Science Center for Molecular Design Breeding, China Agricultural University, Beijing 100094, China.
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Hirayama T, Mochida K. Plant Hormonomics: A Key Tool for Deep Physiological Phenotyping to Improve Crop Productivity. PLANT & CELL PHYSIOLOGY 2023; 63:1826-1839. [PMID: 35583356 PMCID: PMC9885943 DOI: 10.1093/pcp/pcac067] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 04/07/2022] [Accepted: 05/18/2022] [Indexed: 06/15/2023]
Abstract
Agriculture is particularly vulnerable to climate change. To cope with the risks posed by climate-related stressors to agricultural production, global population growth, and changes in food preferences, it is imperative to develop new climate-smart crop varieties with increased yield and environmental resilience. Molecular genetics and genomic analyses have revealed that allelic variations in genes involved in phytohormone-mediated growth regulation have greatly improved productivity in major crops. Plant science has remarkably advanced our understanding of the molecular basis of various phytohormone-mediated events in plant life. These findings provide essential information for improving the productivity of crops growing in changing climates. In this review, we highlight the recent advances in plant hormonomics (multiple phytohormone profiling) and discuss its application to crop improvement. We present plant hormonomics as a key tool for deep physiological phenotyping, focusing on representative plant growth regulators associated with the improvement of crop productivity. Specifically, we review advanced methodologies in plant hormonomics, highlighting mass spectrometry- and nanosensor-based plant hormone profiling techniques. We also discuss the applications of plant hormonomics in crop improvement through breeding and agricultural management practices.
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Affiliation(s)
- Takashi Hirayama
- Institute of Plant Science and Resources, Okayama University, 2-20-1 Chuo, Kurashiki, Okayama, 710-0046 Japan
| | - Keiichi Mochida
- RIKEN Center for Sustainable Resource Science, 1-7-22 Suehirocho, Tsurumiku, Yokohama, Kanagawa, 230-0045 Japan
- Kihara Institute for Biological Research, Yokohama City University, 641-12 Maiokacho, Totsukaku, Yokohama, Kanagawa, 244-0813 Japan
- School of Information and Data Sciences, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki, 852-8521 Japan
- RIKEN Baton Zone Program, RIKEN Cluster for Science, Technology and Innovation Hub, 1-7-22 Suehirocho, Tsurumiku, Yokohama, Kanagawa 230-0045 Japan
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Saeed F, Chaudhry UK, Raza A, Charagh S, Bakhsh A, Bohra A, Ali S, Chitikineni A, Saeed Y, Visser RGF, Siddique KHM, Varshney RK. Developing future heat-resilient vegetable crops. Funct Integr Genomics 2023; 23:47. [PMID: 36692535 PMCID: PMC9873721 DOI: 10.1007/s10142-023-00967-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 01/06/2023] [Accepted: 01/06/2023] [Indexed: 01/25/2023]
Abstract
Climate change seriously impacts global agriculture, with rising temperatures directly affecting the yield. Vegetables are an essential part of daily human consumption and thus have importance among all agricultural crops. The human population is increasing daily, so there is a need for alternative ways which can be helpful in maximizing the harvestable yield of vegetables. The increase in temperature directly affects the plants' biochemical and molecular processes; having a significant impact on quality and yield. Breeding for climate-resilient crops with good yields takes a long time and lots of breeding efforts. However, with the advent of new omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, the efficiency and efficacy of unearthing information on pathways associated with high-temperature stress resilience has improved in many of the vegetable crops. Besides omics, the use of genomics-assisted breeding and new breeding approaches such as gene editing and speed breeding allow creation of modern vegetable cultivars that are more resilient to high temperatures. Collectively, these approaches will shorten the time to create and release novel vegetable varieties to meet growing demands for productivity and quality. This review discusses the effects of heat stress on vegetables and highlights recent research with a focus on how omics and genome editing can produce temperature-resilient vegetables more efficiently and faster.
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Affiliation(s)
- Faisal Saeed
- Department of Agricultural Genetic Engineering, Faculty of Agricultural Sciences and Technologies, Nigde Omer Halisdemir University, 51240, Nigde, Turkey
| | - Usman Khalid Chaudhry
- Department of Agricultural Genetic Engineering, Faculty of Agricultural Sciences and Technologies, Nigde Omer Halisdemir University, 51240, Nigde, Turkey
| | - Ali Raza
- College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, 350002, China
| | - Sidra Charagh
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Hangzhou, China
| | - Allah Bakhsh
- Centre of Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan
| | - Abhishek Bohra
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Murdoch University, Murdoch, 6150, Australia
| | - Sumbul Ali
- Akhuwat Faisalabad Institute of Research Science and Technology, Faisalabad, Pakistan
| | - Annapurna Chitikineni
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Murdoch University, Murdoch, 6150, Australia
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Yasir Saeed
- Department of Plant Pathology, Faculty of Agriculture, University of Agriculture, Faisalabad, 38040, Pakistan
| | - Richard G F Visser
- Plant Breeding, Wageningen University & Research, Droevendaalsesteeg 1, 6708 PB, 15, Wageningen, The Netherlands
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Perth, 6001, Australia
| | - Rajeev K Varshney
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Murdoch University, Murdoch, 6150, Australia.
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
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Crop germplasm: Current challenges, physiological-molecular perspective, and advance strategies towards development of climate-resilient crops. Heliyon 2023; 9:e12973. [PMID: 36711267 PMCID: PMC9880400 DOI: 10.1016/j.heliyon.2023.e12973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 01/01/2023] [Accepted: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
Germplasm is a long-term resource management mission and investment for civilization. An estimated ∼7.4 million accessions are held in 1750 plant germplasm centres around the world; yet, only 2% of these assets have been utilized as plant genetic resources (PGRs). According to recent studies, the current food yield trajectory will be insufficient to feed the world's population in 2050. Additionally, possible negative effects in terms of crop failure because of climate change are already being experienced across the world. Therefore, it is necessary to reconciliation of research advancement and innovation of practices for further exploration of the potential of crop germplasm especially for the complex traits associated with yield such as water- and nitrogen use efficiency. In this review, we tried to address current challenges, research gaps, physiological and molecular aspects of two broad spectrum complex traits such as water- and nitrogen-use efficiency, and advanced integrated strategies that could provide a platform for combined stress management for climate-smart crop development. Additionally, recent development in technologies that are directly related to germplasm characterization was highlighted for further molecular utilization towards the development of elite varieties.
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Guo Z, Li B, Du J, Shen F, Zhao Y, Deng Y, Kuang Z, Tao Y, Wan M, Lu X, Wang D, Wang Y, Han Y, Wei J, Li L, Guo X, Zhao C, Yang X. LettuceGDB: The community database for lettuce genetics and omics. PLANT COMMUNICATIONS 2023; 4:100425. [PMID: 35964156 PMCID: PMC9860171 DOI: 10.1016/j.xplc.2022.100425] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 07/29/2022] [Accepted: 08/10/2022] [Indexed: 05/17/2023]
Abstract
As a globally popular leafy vegetable and a representative plant of the Asteraceae family, lettuce has great economic and academic significance. In the last decade, high-throughput sequencing, phenotyping, and other multi-omics data in lettuce have accumulated on a large scale, thus increasing the demand for an integrative lettuce database. Here, we report the establishment of a comprehensive lettuce database, LettuceGDB (https://www.lettucegdb.com/). As an omics data hub, the current LettuceGDB includes two reference genomes with detailed annotations; re-sequencing data from over 1000 lettuce varieties; a collection of more than 1300 worldwide germplasms and millions of accompanying phenotypic records obtained with manual and cutting-edge phenomics technologies; re-analyses of 256 RNA sequencing datasets; a complete miRNAome; extensive metabolite information for representative varieties and wild relatives; epigenetic data on the genome-wide chromatin accessibility landscape; and various lettuce research papers published in the last decade. Five hierarchically accessible functions (Genome, Genotype, Germplasm, Phenotype, and O-Omics) have been developed with a user-friendly interface to enable convenient data access. Eight built-in tools (Assembly Converter, Search Gene, BLAST, JBrowse, Primer Design, Gene Annotation, Tissue Expression, Literature, and Data) are available for data downloading and browsing, functional gene exploration, and experimental practice. A community forum is also available for information sharing, and a summary of current research progress on different aspects of lettuce is included. We believe that LettuceGDB can be a comprehensive functional database amenable to data mining and database-driven exploration, useful for both scientific research and lettuce breeding.
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Affiliation(s)
- Zhonglong Guo
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences and School of Advanced Agricultural Sciences, Peking University, Beijing 100871, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China; College of Biology and the Environment, Nanjing Forestry University, Nanjing 510275, P.R. China
| | - Bo Li
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China
| | - Jianjun Du
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, P.R. China
| | - Fei Shen
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China
| | - Yongxin Zhao
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China
| | - Yang Deng
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China
| | - Zheng Kuang
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China
| | - Yihan Tao
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences and School of Advanced Agricultural Sciences, Peking University, Beijing 100871, P.R. China
| | - Miaomiao Wan
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences and School of Advanced Agricultural Sciences, Peking University, Beijing 100871, P.R. China
| | - Xianju Lu
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, P.R. China
| | - Dong Wang
- WeiRan Biotech, Beijing 100085, P.R. China
| | - Ying Wang
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences and School of Advanced Agricultural Sciences, Peking University, Beijing 100871, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China
| | - Yingyan Han
- Beijing Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing 102206, P.R. China
| | - Jianhua Wei
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China
| | - Lei Li
- State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences and School of Advanced Agricultural Sciences, Peking University, Beijing 100871, P.R. China
| | - Xinyu Guo
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, P.R. China.
| | - Chunjiang Zhao
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, P.R. China.
| | - Xiaozeng Yang
- Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, P.R. China; Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Agro-biotechnology Research Center, Beijing 100097, P.R. China.
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Wang X, Han J, Li R, Qiu L, Zhang C, Lu M, Huang R, Wang X, Zhang J, Xie H, Li S, Huang X, Ouyang X. Gradual daylength sensing coupled with optimum cropping modes enhances multi-latitude adaptation of rice and maize. PLANT COMMUNICATIONS 2023; 4:100433. [PMID: 36071669 PMCID: PMC9860186 DOI: 10.1016/j.xplc.2022.100433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 08/18/2022] [Accepted: 09/05/2022] [Indexed: 06/15/2023]
Abstract
To expand crop planting areas, reestablishment of crop latitude adaptation based on genetic variation in photoperiodic genes can be performed, but it is quite time consuming. By contrast, a crop variety that already exhibits multi-latitude adaptation has the potential to increase its planting areas to be more widely and quickly available. However, the importance and potential of multi-latitude adaptation of crop varieties have not been systematically described. Here, combining daylength-sensing data with the cropping system of elite rice and maize varieties, we found that varieties with gradual daylength sensing coupled with optimum cropping modes have an enhanced capacity for multi-latitude adaptation in China. Furthermore, this multi-latitude adaptation expanded their planting areas and indirectly improved China's nationwide rice and maize unit yield. Thus, coupling the daylength-sensing process with optimum cropping modes to enhance latitude adaptability of excellent varieties represents an exciting approach for deploying crop varieties with the potential to expand their planting areas and quickly improve nationwide crop unit yield in developing countries.
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Affiliation(s)
- Xiaoying Wang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China
| | - Jiupan Han
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China
| | - Rui Li
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China
| | - Leilei Qiu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China
| | - Cheng Zhang
- Liaoning Rice Research Institute, Shenyang 110101, China
| | - Ming Lu
- Jilin Academy of Agricultural Sciences, Changchun 130033, China
| | - Rongyu Huang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China
| | - Xiangfeng Wang
- Department of Crop Genomics and Bioinformatics, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100083, China
| | - Jianfu Zhang
- Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou 350002, China
| | - Huaan Xie
- Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou 350002, China
| | - Shigui Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Rice Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Xi Huang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China
| | - Xinhao Ouyang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China.
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Oteng-Frimpong R, Karikari B, Sie EK, Kassim YB, Puozaa DK, Rasheed MA, Fonceka D, Okello DK, Balota M, Burow M, Ozias-Akins P. Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut ( Arachis hypogaea L.) germplasm. FRONTIERS IN PLANT SCIENCE 2023; 13:1076744. [PMID: 36684745 PMCID: PMC9849250 DOI: 10.3389/fpls.2022.1076744] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 11/24/2022] [Indexed: 06/17/2023]
Abstract
Early leaf spot (ELS) and late leaf spot (LLS) diseases are the two most destructive groundnut diseases in Ghana resulting in ≤ 70% yield losses which is controlled largely by chemical method. To develop leaf spot resistant varieties, the present study was undertaken to identify single nucleotide polymorphism (SNP) markers and putative candidate genes underlying both ELS and LLS. In this study, six multi-locus models of genome-wide association study were conducted with the best linear unbiased predictor obtained from 294 African groundnut germplasm screened for ELS and LLS as well as image-based indices of leaf spot diseases severity in 2020 and 2021 and 8,772 high-quality SNPs from a 48 K SNP array Axiom platform. Ninety-seven SNPs associated with ELS, LLS and five image-based indices across the chromosomes in the 2 two sub-genomes. From these, twenty-nine unique SNPs were detected by at least two models for one or more traits across 16 chromosomes with explained phenotypic variation ranging from 0.01 - 62.76%, with exception of chromosome (Chr) 08 (Chr08), Chr10, Chr11, and Chr19. Seventeen potential candidate genes were predicted at ± 300 kbp of the stable/prominent SNP positions (12 and 5, down- and upstream, respectively). The results from this study provide a basis for understanding the genetic architecture of ELS and LLS diseases in African groundnut germplasm, and the associated SNPs and predicted candidate genes would be valuable for breeding leaf spot diseases resistant varieties upon further validation.
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Affiliation(s)
- Richard Oteng-Frimpong
- Groundnut Improvement Program, Council for Scientific and Industrial Research (CSIR)-Savanna Agricultural Research Institute, Tamale, Ghana
| | - Benjamin Karikari
- Department of Agricultural Biotechnology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Emmanuel Kofi Sie
- Groundnut Improvement Program, Council for Scientific and Industrial Research (CSIR)-Savanna Agricultural Research Institute, Tamale, Ghana
| | - Yussif Baba Kassim
- Groundnut Improvement Program, Council for Scientific and Industrial Research (CSIR)-Savanna Agricultural Research Institute, Tamale, Ghana
| | - Doris Kanvenaa Puozaa
- Groundnut Improvement Program, Council for Scientific and Industrial Research (CSIR)-Savanna Agricultural Research Institute, Tamale, Ghana
| | - Masawudu Abdul Rasheed
- Groundnut Improvement Program, Council for Scientific and Industrial Research (CSIR)-Savanna Agricultural Research Institute, Tamale, Ghana
| | - Daniel Fonceka
- Centre d’Etude Régional pour l’Amélioration de l’Adaptation àla Sécheresse (CERAAS), Institut Sénégalais de Recherches Agricoles (ISRA), Thiès, Senegal
| | - David Kallule Okello
- Oil Crops Research Program, National Semi-Arid Resources Research Institute (NaSARRI), Soroti, Uganda
| | - Maria Balota
- School of Plant and Environmental Sciences, Tidewater Agricultural Research and Extension Center (AREC), Virginia Tech, Suffolk, VA, United States
| | - Mark Burow
- Texas A&M AgriLife Research and Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, United States
| | - Peggy Ozias-Akins
- Institute of Plant Breeding Genetics and Genomics, University of Georgia, Tifton, GA, United States
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Lisker A, Maurer A, Schmutzer T, Kazman E, Cöster H, Holzapfel J, Ebmeyer E, Alqudah AM, Sannemann W, Pillen K. A Haplotype-Based GWAS Identified Trait-Improving QTL Alleles Controlling Agronomic Traits under Contrasting Nitrogen Fertilization Treatments in the MAGIC Wheat Population WM-800. PLANTS (BASEL, SWITZERLAND) 2022; 11:3508. [PMID: 36559621 PMCID: PMC9784842 DOI: 10.3390/plants11243508] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 11/27/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
The multi-parent-advanced-generation-intercross (MAGIC) population WM-800 was developed by intercrossing eight modern winter wheat cultivars to enhance the genetic diversity present in breeding populations. We cultivated WM-800 during two seasons in seven environments under two contrasting nitrogen fertilization treatments. WM-800 lines exhibited highly significant differences between treatments, as well as high heritabilities among the seven agronomic traits studied. The highest-yielding WM-line achieved an average yield increase of 4.40 dt/ha (5.2%) compared to the best founder cultivar Tobak. The subsequent genome-wide-association-study (GWAS), which was based on haplotypes, located QTL for seven agronomic traits including grain yield. In total, 40, 51, and 46 QTL were detected under low, high, and across nitrogen treatments, respectively. For example, the effect of QYLD_3A could be associated with the haplotype allele of cultivar Julius increasing yield by an average of 4.47 dt/ha (5.2%). A novel QTL on chromosome 2B exhibited pleiotropic effects, acting simultaneously on three-grain yield components (ears-per-square-meter, grains-per-ear, and thousand-grain-weight) and plant-height. These effects may be explained by a member of the nitrate-transporter-1 (NRT1)/peptide-family, TaNPF5.34, located 1.05 Mb apart. The WM-800 lines and favorable QTL haplotypes, associated with yield improvements, are currently implemented in wheat breeding programs to develop advanced nitrogen-use efficient wheat cultivars.
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Affiliation(s)
- Antonia Lisker
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Andreas Maurer
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Thomas Schmutzer
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Ebrahim Kazman
- Syngenta Seeds GmbH, Kroppenstedter Str. 4, 39387 Oschersleben, Germany
| | | | - Josef Holzapfel
- Secobra Saatzucht GmbH, Feldkirchen 3, 85368 Moosburg an der Isar, Germany
| | - Erhard Ebmeyer
- KWS Lochow GMBH, Ferdinand-Lochow-Str. 5, 29303 Bergen, Germany
| | - Ahmad M. Alqudah
- Biological Science Program, Department of Biological and Environmental Sciences, College of Art and Science, Qatar University, Doha P.O. Box 2713, Qatar
| | - Wiebke Sannemann
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Klaus Pillen
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
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Kumar B, Singh AK, Bahuguna RN, Pareek A, Singla‐Pareek SL. Orphan crops: A genetic treasure trove for hunting stress tolerance genes. Food Energy Secur 2022. [DOI: 10.1002/fes3.436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Affiliation(s)
- Brijesh Kumar
- Plant Stress Biology Group International Centre for Genetic Engineering and Biotechnology New Delhi India
| | - Anil Kumar Singh
- ICAR‐National Institute for Plant Biotechnology LBS Centre New Delhi India
| | - Rajeev Nayan Bahuguna
- Center for Advanced Studies on Climate Change Dr. Rajendra Prasad Central Agricultural University Bihar Pusa, Samastipur India
| | - Ashwani Pareek
- Stress Physiology and Molecular Biology Laboratory, School of Life Sciences Jawaharlal Nehru University New Delhi India
| | - Sneh L. Singla‐Pareek
- Plant Stress Biology Group International Centre for Genetic Engineering and Biotechnology New Delhi India
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42
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Adler L, Díaz-Ramos A, Mao Y, Pukacz KR, Fei C, McCormick AJ. New horizons for building pyrenoid-based CO2-concentrating mechanisms in plants to improve yields. PLANT PHYSIOLOGY 2022; 190:1609-1627. [PMID: 35961043 PMCID: PMC9614477 DOI: 10.1093/plphys/kiac373] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 07/06/2022] [Indexed: 05/06/2023]
Abstract
Many photosynthetic species have evolved CO2-concentrating mechanisms (CCMs) to improve the efficiency of CO2 assimilation by Rubisco and reduce the negative impacts of photorespiration. However, the majority of plants (i.e. C3 plants) lack an active CCM. Thus, engineering a functional heterologous CCM into important C3 crops, such as rice (Oryza sativa) and wheat (Triticum aestivum), has become a key strategic ambition to enhance yield potential. Here, we review recent advances in our understanding of the pyrenoid-based CCM in the model green alga Chlamydomonas reinhardtii and engineering progress in C3 plants. We also discuss recent modeling work that has provided insights into the potential advantages of Rubisco condensation within the pyrenoid and the energetic costs of the Chlamydomonas CCM, which, together, will help to better guide future engineering approaches. Key findings include the potential benefits of Rubisco condensation for carboxylation efficiency and the need for a diffusional barrier around the pyrenoid matrix. We discuss a minimal set of components for the CCM to function and that active bicarbonate import into the chloroplast stroma may not be necessary for a functional pyrenoid-based CCM in planta. Thus, the roadmap for building a pyrenoid-based CCM into plant chloroplasts to enhance the efficiency of photosynthesis now appears clearer with new challenges and opportunities.
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Affiliation(s)
- Liat Adler
- Institute of Molecular Plant Sciences, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Aranzazú Díaz-Ramos
- Institute of Molecular Plant Sciences, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Yuwei Mao
- Institute of Molecular Plant Sciences, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Krzysztof Robin Pukacz
- Institute of Molecular Plant Sciences, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Chenyi Fei
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA
| | - Alistair J McCormick
- Institute of Molecular Plant Sciences, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, UK
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Han X, Li L, Chen H, Liu L, Sun L, Wang X, Xiang Y, Wan Z, Liu C. Resequencing of 558 Chinese mungbean landraces identifies genetic loci associated with key agronomic traits. FRONTIERS IN PLANT SCIENCE 2022; 13:1043784. [PMID: 36311125 PMCID: PMC9597495 DOI: 10.3389/fpls.2022.1043784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Mungbean is a warm-season annual food legume and plays important role in supplying food and nutritional security in many tropical countries. However, the genetic basis of its agronomic traits remains poorly understood. Therefore, we resequenced 558 Chinese mungbean landraces and produced a comprehensive map of mungbean genomic variation. We phenotyped all landraces in six different environments. Genome-wide association studies (GWAS) produced 110 signals significantly associated with nine agronomic traits, for which several candidate genes were identified. Overall, this study provides new insight into the genetic architecture of mungbean agronomic traits. Moreover, the genome-wide variations identified here should be valuable resources for future breeding studies of this important food legume.
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Affiliation(s)
- Xuesong Han
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
| | - Li Li
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
| | - Hongwei Chen
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
| | - Liangjun Liu
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
| | - Longqin Sun
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
| | - Xingmin Wang
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
| | - Yantao Xiang
- College of Agronomy, Yangtze University, Jingzhou, China
| | - Zhenghuang Wan
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
| | - Changyan Liu
- Institute of Food Crops, Hubei Academy of Agricultural Sciences/Hubei Key Laboratory of Food Crop Germplasm and Genetic, Wuhan, China
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44
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Shen Q, Xie Y, Qiu X, Yu J. The era of cultivating smart rice with high light efficiency and heat tolerance has come of age. FRONTIERS IN PLANT SCIENCE 2022; 13:1021203. [PMID: 36275525 PMCID: PMC9585279 DOI: 10.3389/fpls.2022.1021203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/16/2022] [Indexed: 06/16/2023]
Abstract
How to improve the yield of crops has always been the focus of breeding research. Due to the population growth and global climate change, the demand for food has increased sharply, which has brought great challenges to agricultural production. In order to make up for the limitation of global cultivated land area, it is necessary to further improve the output of crops. Photosynthesis is the main source of plant assimilate accumulation, which has a profound impact on the formation of its yield. This review focuses on the cultivation of high light efficiency plants, introduces the main technical means and research progress in improving the photosynthetic efficiency of plants, and discusses the main problems and difficulties faced by the cultivation of high light efficiency plants. At the same time, in view of the frequent occurrence of high-temperature disasters caused by global warming, which seriously threatened plant normal production, we reviewed the response mechanism of plants to heat stress, introduced the methods and strategies of how to cultivate heat tolerant crops, especially rice, and briefly reviewed the progress of heat tolerant research at present. Given big progress in these area, the era of cultivating smart rice with high light efficiency and heat tolerance has come of age.
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Affiliation(s)
- Qiuping Shen
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, Zhejiang A & F University, Hangzhou, China
- College of Advanced Agricultural Sciences, Zhejiang A & F University, Hangzhou, China
| | - Yujun Xie
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, Zhejiang A & F University, Hangzhou, China
- College of Advanced Agricultural Sciences, Zhejiang A & F University, Hangzhou, China
| | - Xinzhe Qiu
- College of Advanced Agricultural Sciences, Zhejiang A & F University, Hangzhou, China
| | - Jinsheng Yu
- The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, Zhejiang A & F University, Hangzhou, China
- College of Advanced Agricultural Sciences, Zhejiang A & F University, Hangzhou, China
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Abdullah-Zawawi MR, Govender N, Harun S, Muhammad NAN, Zainal Z, Mohamed-Hussein ZA. Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom. PLANTS (BASEL, SWITZERLAND) 2022; 11:2614. [PMID: 36235479 PMCID: PMC9573505 DOI: 10.3390/plants11192614] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/05/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.
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Affiliation(s)
- Muhammad-Redha Abdullah-Zawawi
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia
- Institute of System Biology (INBIOSIS), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
| | - Nisha Govender
- Institute of System Biology (INBIOSIS), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
| | - Sarahani Harun
- Institute of System Biology (INBIOSIS), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
| | - Nor Azlan Nor Muhammad
- Institute of System Biology (INBIOSIS), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
| | - Zamri Zainal
- Institute of System Biology (INBIOSIS), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
- Faculty of Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
| | - Zeti-Azura Mohamed-Hussein
- Institute of System Biology (INBIOSIS), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
- Faculty of Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
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Utebayev MU, Shelaeva TV, Bome NA, Chilimova IV, Kradetskaya OO, Dashkevich SM, Novokhatin VN, Weisfeld LI. Grain quality of spring wheat (<i>Triticum aestivum</i> L.) cultivars developed in Western Siberia under the conditions of Northern Kazakhstan. PROCEEDINGS ON APPLIED BOTANY, GENETICS AND BREEDING 2022. [DOI: 10.30901/2227-8834-2022-3-27-38] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Background. Environmental testing is the first stage of wheat breeding, the purpose of which is to identify wheat samples suitable for local environments and capable of forming a fairly stable yield and high-quality grain. The proposed study presents the test results for spring bread wheat cultivars of Russian breeding grown in arid environments of Northern Kazakhstan in order to preserve their yield and baking qualities.Materials and methods. The material of the study included 15 spring bread wheat cultivars. Protein and gluten content and the quality of gluten were determined using an infrared analyzer; the physical properties of the test were assessed using a Chopin alveograph and Brabender farinograph.Results. As a result of biochemical assessment, increased protein and gluten content and grain weight were observed in cvs. ‘Tyumenskaya 30’, ‘Aviada’, ‘Lutescens 585’, ‘Serebrina’, and ‘Tyumenets 2’. Dough deformation energy (W) characteristic of high-quality wheat and the balance in the P/L ratio (elasticity/elongation) were shown by cvs. ‘Tyumenskaya 33’ (290 a.u.; 1.15 P/L), ‘SKENT-3’ (307 a.u.; 0.89 P/L), and ‘Lutescens 585’ (374 a.u., 1.10 P/L). In laboratory baking, the volume of bread ranged from 620 ml (‘Tyumenskaya 27’) to 768 ml (‘Tyumenskaya 29’) with an average value of 707 ml. A baking quality analysis of the cultivars grown in the Northern Trans-Urals and Northern Kazakhstan demonstrated that the conditions in Northern Kazakhstan were more favorable for obtaining bread with an increased volume. On the basis of environmental tests and an assessment of a set of biochemical and technological indicators, cvs. ‘SKENT-3’ and ‘Tyumenskaya 29’ were selected. It makes sense to continue studying wheat cultivars that can be sources and donors of high-quality grain for the development of cultivars for the arid steppe of Northern Kazakhstan.
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Affiliation(s)
- M. U. Utebayev
- A.I. Barayev Research and Production Center of Grain Farming
| | - T. V. Shelaeva
- A.I. Barayev Research and Production Center of Grain Farming
| | | | - I. V. Chilimova
- A.I. Barayev Research and Production Center of Grain Farming
| | | | | | - V. N. Novokhatin
- Tyumen Scientific Center of the Siberian Branch of the Russian Academy of Sciences, Research Institute of Agriculture for the Northern TransUral Region
| | - L. I. Weisfeld
- Emanuel Institute of Biochemical Physics of the Russian Academy of Sciences
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Raza A, Sharif Y, Chen K, Wang L, Fu H, Zhuang Y, Chitikineni A, Chen H, Zhang C, Varshney RK, Zhuang W. Genome-Wide Characterization of Ascorbate Peroxidase Gene Family in Peanut ( Arachis hypogea L.) Revealed Their Crucial Role in Growth and Multiple Stress Tolerance. FRONTIERS IN PLANT SCIENCE 2022; 13:962182. [PMID: 36186077 PMCID: PMC9524023 DOI: 10.3389/fpls.2022.962182] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 06/23/2022] [Indexed: 06/16/2023]
Abstract
Ascorbate peroxidase (APX), an important antioxidant enzyme, plays a significant role in ROS scavenging by catalyzing the decrease of hydrogen peroxide under various environmental stresses. Nevertheless, information about the APX gene family and their evolutionary and functional attributes in peanut (Arachis hypogea L.) was not reported. Therefore, a comprehensive genome-wide study was performed to discover the APX genes in cultivated peanut genome. This study identified 166 AhAPX genes in the peanut genome, classified into 11 main groups. The gene duplication analysis showed that AhAPX genes had experienced segmental duplications and purifying selection pressure. Gene structure and motif investigation indicated that most of the AhAPX genes exhibited a comparatively well-preserved exon-intron pattern and motif configuration contained by the identical group. We discovered five phytohormones-, six abiotic stress-, and five growth and development-related cis-elements in the promoter regions of AhAPX. Fourteen putative ah-miRNAs from 12 families were identified, targeting 33 AhAPX genes. Furthermore, we identified 3,257 transcription factors from 38 families (including AP2, ARF, B3, bHLH, bZIP, ERF, MYB, NAC, WRKY, etc.) in 162 AhAPX genes. Gene ontology and KEGG enrichment analysis confirm the role of AhAPX genes in oxidoreductase activity, catalytic activity, cell junction, cellular response to stimulus and detoxification, biosynthesis of metabolites, and phenylpropanoid metabolism. Based on transcriptome datasets, some genes such as AhAPX4/7/17/77/82/86/130/133 and AhAPX160 showed significantly higher expression in diverse tissues/organs, i.e., flower, leaf, stem, roots, peg, testa, and cotyledon. Likewise, only a few genes, including AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, were significantly upregulated under abiotic (drought and cold), and phytohormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid) treatments. qRT-PCR-based expression profiling presented the parallel expression trends as generated from transcriptome datasets. Our discoveries gave new visions into the evolution of APX genes and provided a base for further functional examinations of the AhAPX genes in peanut breeding programs.
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Affiliation(s)
- Ali Raza
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Center of Legume Plant Genetics and Systems Biology, College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Yasir Sharif
- College of Plant Protection, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Kun Chen
- College of Plant Protection, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Lihui Wang
- College of Plant Protection, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Huiwen Fu
- College of Plant Protection, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Yuhui Zhuang
- College of Life Science, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Annapurna Chitikineni
- Murdoch’s Centre for Crop and Food Innovation, State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, WA, Australia
| | - Hua Chen
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Center of Legume Plant Genetics and Systems Biology, College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
- College of Plant Protection, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Chong Zhang
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Center of Legume Plant Genetics and Systems Biology, College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
- College of Plant Protection, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
| | - Rajeev K. Varshney
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Center of Legume Plant Genetics and Systems Biology, College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
- Murdoch’s Centre for Crop and Food Innovation, State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, WA, Australia
| | - Weijian Zhuang
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, Center of Legume Plant Genetics and Systems Biology, College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
- College of Plant Protection, Fujian Agriculture and Forestry University (FAFU), Fuzhou, China
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Sandhu KS, Shiv A, Kaur G, Meena MR, Raja AK, Vengavasi K, Mall AK, Kumar S, Singh PK, Singh J, Hemaprabha G, Pathak AD, Krishnappa G, Kumar S. Integrated Approach in Genomic Selection to Accelerate Genetic Gain in Sugarcane. PLANTS 2022; 11:plants11162139. [PMID: 36015442 PMCID: PMC9412483 DOI: 10.3390/plants11162139] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/08/2022] [Accepted: 08/08/2022] [Indexed: 11/30/2022]
Abstract
Marker-assisted selection (MAS) has been widely used in the last few decades in plant breeding programs for the mapping and introgression of genes for economically important traits, which has enabled the development of a number of superior cultivars in different crops. In sugarcane, which is the most important source for sugar and bioethanol, marker development work was initiated long ago; however, marker-assisted breeding in sugarcane has been lagging, mainly due to its large complex genome, high levels of polyploidy and heterozygosity, varied number of chromosomes, and use of low/medium-density markers. Genomic selection (GS) is a proven technology in animal breeding and has recently been incorporated in plant breeding programs. GS is a potential tool for the rapid selection of superior genotypes and accelerating breeding cycle. However, its full potential could be realized by an integrated approach combining high-throughput phenotyping, genotyping, machine learning, and speed breeding with genomic selection. For better understanding of GS integration, we comprehensively discuss the concept of genetic gain through the breeder’s equation, GS methodology, prediction models, current status of GS in sugarcane, challenges of prediction accuracy, challenges of GS in sugarcane, integrated GS, high-throughput phenotyping (HTP), high-throughput genotyping (HTG), machine learning, and speed breeding followed by its prospective applications in sugarcane improvement.
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Affiliation(s)
- Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99163, USA
| | - Aalok Shiv
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow 226002, India
| | - Gurleen Kaur
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA
| | - Mintu Ram Meena
- Regional Center, ICAR-Sugarcane Breeding Institute, Karnal 132001, India
| | - Arun Kumar Raja
- Division of Crop Production, ICAR-Sugarcane Breeding Institute, Coimbatore 641007, India
| | - Krishnapriya Vengavasi
- Division of Crop Production, ICAR-Sugarcane Breeding Institute, Coimbatore 641007, India
| | - Ashutosh Kumar Mall
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow 226002, India
| | - Sanjeev Kumar
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow 226002, India
| | - Praveen Kumar Singh
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow 226002, India
| | - Jyotsnendra Singh
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow 226002, India
| | - Govind Hemaprabha
- Division of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore 641007, India
| | - Ashwini Dutt Pathak
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow 226002, India
| | - Gopalareddy Krishnappa
- Division of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore 641007, India
- Correspondence: (G.K.); (S.K.)
| | - Sanjeev Kumar
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow 226002, India
- Correspondence: (G.K.); (S.K.)
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Lu W, Sui M, Zhao X, Jia H, Han D, Yan X, Han Y. Genome-Wide Identification of Candidate Genes Underlying Soluble Sugar Content in Vegetable Soybean ( Glycine max L.) via Association and Expression Analysis. FRONTIERS IN PLANT SCIENCE 2022; 13:930639. [PMID: 35991392 PMCID: PMC9387354 DOI: 10.3389/fpls.2022.930639] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 05/18/2022] [Indexed: 05/11/2023]
Abstract
Soluble sugar is a major indicator of the intrinsic quality of vegetable soybean [Glycine max (L.) Merr. ]. The improvement of soluble sugar content in soybean is very important due to its healthcare functions for humans. The genetic mechanism of soluble sugar in soybean is unclear. In this study, 278 diverse soybean accessions were utilized to identify the quantitative trait nucleotides (QTNs) for total soluble sugar content in soybean seeds based on a genome-wide association study (GWAS). A total of 25,921 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected for GWAS. Totally, thirteen QTNs associated with total soluble sugar content were identified, which were distributed on ten chromosomes. One hundred and fifteen genes near the 200-kb flanking region of these identified QTNs were considered candidate genes associated with total soluble sugar content in soybean seed. Gene-based association analysis and haplotype analysis were utilized to further identify the effect of candidate genes on total soluble sugar content. Totally, 84 SNPs from seventeen genes across four chromosomes were significantly associated with the total soluble sugar content. Among them, three SNPs from Glyma.02G292900 were identified at two locations, and other eighty-one SNPs from sixteen genes were detected at three locations. Furthermore, expression level analysis of candidate genes revealed that Glyma.02G293200 and Glyma.02G294900 were significantly positively associated with soluble sugar content and Glyma.02G294000 was significantly negatively associated with soluble sugar content. Six genes (i.e., Glyma.02G292600, Glyma.02G292700, Glyma.02G294000, Glyma.02G294300, Glyma.02G294400, and Glyma.15G264200) identified by GWAS were also detected by the analysis of differential expression genes based on soybean germplasms with higher and lower soluble sugar content. Among them, Glyma.02G294000 is the only gene that was identified by gene-based association analysis with total soluble sugar content and was considered an important candidate gene for soluble sugar content. These candidate genes and beneficial alleles would be useful for improving the soluble sugar content of soybean.
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Affiliation(s)
- Wencheng Lu
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Meinan Sui
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Xunchao Zhao
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Hongchang Jia
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Dezhi Han
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Xiaofei Yan
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Yingpeng Han
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
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Liu L, Wang X, Chang C. Toward a smart skin: Harnessing cuticle biosynthesis for crop adaptation to drought, salinity, temperature, and ultraviolet stress. FRONTIERS IN PLANT SCIENCE 2022; 13:961829. [PMID: 35958191 PMCID: PMC9358614 DOI: 10.3389/fpls.2022.961829] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 07/01/2022] [Indexed: 06/15/2023]
Abstract
Drought, salinity, extreme temperatures, and ultraviolet (UV) radiation are major environmental factors that adversely affect plant growth and crop production. As a protective shield covering the outer epidermal cell wall of plant aerial organs, the cuticle is mainly composed of cutin matrix impregnated and sealed with cuticular waxes, and greatly contributes to the plant adaption to environmental stresses. Past decades have seen considerable progress in uncovering the molecular mechanism of plant cutin and cuticular wax biosynthesis, as well as their important roles in plant stress adaptation, which provides a new direction to drive strategies for stress-resilient crop breeding. In this review, we highlighted the recent advances in cuticle biosynthesis in plant adaptation to drought, salinity, extreme temperatures, and UV radiation stress, and discussed the current status and future directions in harnessing cuticle biosynthesis for crop improvement.
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