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Jadhav Y, Thakur NR, Ingle KP, Ceasar SA. The role of phenomics and genomics in delineating the genetic basis of complex traits in millets. PHYSIOLOGIA PLANTARUM 2024; 176:e14349. [PMID: 38783512 DOI: 10.1111/ppl.14349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 04/22/2024] [Accepted: 04/26/2024] [Indexed: 05/25/2024]
Abstract
Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.
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Affiliation(s)
- Yashoda Jadhav
- International Crops Research Institutes for the Semi-Arid Tropics, Patancheru, TS, India
| | - Niranjan Ravindra Thakur
- International Crops Research Institutes for the Semi-Arid Tropics, Patancheru, TS, India
- Vasantrao Naik Marathwada Agricultural University, Parbhani, MS, India
| | | | - Stanislaus Antony Ceasar
- Division of Plant Molecular Biology and Biotechnology, Department of Biosciences, Rajagiri College of Social Sciences, Kochi, KL, India
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2
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Mahmoud A, Qi R, Chi X, Liao N, Malangisha GK, Ali A, Moustafa-Farag M, Yang J, Zhang M, Hu Z. Integrated Bulk Segregant Analysis, Fine Mapping, and Transcriptome Revealed QTLs and Candidate Genes Associated with Drought Adaptation in Wild Watermelon. Int J Mol Sci 2023; 25:65. [PMID: 38203237 PMCID: PMC10779233 DOI: 10.3390/ijms25010065] [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: 10/07/2023] [Revised: 12/07/2023] [Accepted: 12/09/2023] [Indexed: 01/12/2024] Open
Abstract
Drought stress has detrimental effects on crop productivity worldwide. A strong root system is crucial for maintaining water and nutrients uptake under drought stress. Wild watermelons possess resilient roots with excellent drought adaptability. However, the genetic factors controlling this trait remain uninvestigated. In this study, we conducted a bulk segregant analysis (BSA) on an F2 population consisting of two watermelon genotypes, wild and domesticated, which differ in their lateral root development under drought conditions. We identified two quantitative trait loci (qNLR_Dr. Chr01 and qNLR_Dr. Chr02) associated with the lateral root response to drought. Furthermore, we determined that a small region (0.93 Mb in qNLR_Dr. Chr01) is closely linked to drought adaptation through quantitative trait loci (QTL) validation and fine mapping. Transcriptome analysis of the parent roots under drought stress revealed unique effects on numerous genes in the sensitive genotype but not in the tolerant genotype. By integrating BSA, fine mapping, and the transcriptome, we identified six genes, namely L-Ascorbate Oxidase (AO), Cellulose Synthase-Interactive Protein 1 (CSI1), Late Embryogenesis Abundant Protein (LEA), Zinc-Finger Homeodomain Protein 2 (ZHD2), Pericycle Factor Type-A 5 (PFA5), and bZIP transcription factor 53-like (bZIP53-like), that might be involved in the drought adaptation. Our findings provide valuable QTLs and genes for marker-assisted selection in improving water-use efficiency and drought tolerance in watermelon. They also lay the groundwork for the genetic manipulation of drought-adapting genes in watermelon and other Cucurbitacea species.
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Affiliation(s)
- Ahmed Mahmoud
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
- Hainan Institute of Zhejiang University, Yazhou District, Sanya 572025, China
- Key Laboratory of Horticultural Plant Growth, Development & Quality Improvement, Ministry of Agriculture, Hangzhou 310058, China
- Horticulture Research Institute, Agricultural Research Center, 9 Cairo University St, Giza 12619, Egypt;
| | - Rui Qi
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
- Hainan Institute of Zhejiang University, Yazhou District, Sanya 572025, China
| | - Xiaolu Chi
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
- Hainan Institute of Zhejiang University, Yazhou District, Sanya 572025, China
| | - Nanqiao Liao
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
| | - Guy Kateta Malangisha
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
| | - Abid Ali
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
| | - Mohamed Moustafa-Farag
- Horticulture Research Institute, Agricultural Research Center, 9 Cairo University St, Giza 12619, Egypt;
| | - Jinghua Yang
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
- Hainan Institute of Zhejiang University, Yazhou District, Sanya 572025, China
- Key Laboratory of Horticultural Plant Growth, Development & Quality Improvement, Ministry of Agriculture, Hangzhou 310058, China
| | - Mingfang Zhang
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
- Hainan Institute of Zhejiang University, Yazhou District, Sanya 572025, China
- Key Laboratory of Horticultural Plant Growth, Development & Quality Improvement, Ministry of Agriculture, Hangzhou 310058, China
| | - Zhongyuan Hu
- Institute of Vegetable Science, Zhejiang University, Hangzhou 310058, China; (A.M.); (R.Q.); (X.C.); (N.L.); (G.K.M.); (A.A.); (J.Y.); (M.Z.)
- Hainan Institute of Zhejiang University, Yazhou District, Sanya 572025, China
- Key Laboratory of Horticultural Plant Growth, Development & Quality Improvement, Ministry of Agriculture, Hangzhou 310058, China
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3
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Hou M, Cao Y, Zhang X, Zhang S, Jia T, Yang J, Han S, Wang L, Li J, Wang H, Zhang L, Wu X, Duan C, Li H. Genome-wide association study of maize resistance to Pythium aristosporum stalk rot. FRONTIERS IN PLANT SCIENCE 2023; 14:1239635. [PMID: 37662167 PMCID: PMC10470045 DOI: 10.3389/fpls.2023.1239635] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 07/28/2023] [Indexed: 09/05/2023]
Abstract
Stalk rot, a severe and widespread soil-borne disease in maize, globally reduces yield and quality. Recent documentation reveals that Pythium aristosporum has emerged as one of the dominant causal agents of maize stalk rot. However, a previous study of maize stalk rot disease resistance mechanisms and breeding had mainly focused on other pathogens, neglecting P. aristosporum. To mitigate crop loss, resistance breeding is the most economical and effective strategy against this disease. This study involved characterizing resistance in 295 inbred lines using the drilling inoculation method and genotyping them via sequencing. By combining with population structure, disease resistance phenotype, and genome-wide association study (GWAS), we identified 39 significant single-nucleotide polymorphisms (SNPs) associated with P. aristosporum stalk rot resistance by utilizing six statistical methods. Bioinformatics analysis of these SNPs revealed 69 potential resistance genes, among which Zm00001d051313 was finally evaluated for its roles in host defense response to P. aristosporum infection. Through virus-induced gene silencing (VIGS) verification and physiological index determination, we found that transient silencing of Zm00001d051313 promoted P. aristosporum infection, indicating a positive regulatory role of this gene in maize's antifungal defense mechanism. Therefore, these findings will help advance our current understanding of the underlying mechanisms of maize defense to Pythium stalk rot.
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Affiliation(s)
- Mengwei Hou
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Yanyong Cao
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Xingrui Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shulin Zhang
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Tengjiao Jia
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Jiwei Yang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Shengbo Han
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Lifeng Wang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Jingjing Li
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Hao Wang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Lili Zhang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Xiaolin Wu
- College of Life Science, Henan Agricultural University, Zhengzhou, China
| | - Canxing Duan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huiyong Li
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
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Abbas M, Abid MA, Meng Z, Abbas M, Wang P, Lu C, Askari M, Akram U, Ye Y, Wei Y, Wang Y, Guo S, Liang C, Zhang R. Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway. PHYSIOLOGIA PLANTARUM 2022; 174:e13787. [PMID: 36169590 DOI: 10.1111/ppl.13787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/12/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.
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Affiliation(s)
- Mubashir Abbas
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Muhammad Ali Abid
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhigang Meng
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Manzar Abbas
- School of Agriculture, Forestry and Food Engineering, Yibin University, Yibin, China
| | - Peilin Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chao Lu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Muhammad Askari
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Umar Akram
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yulu Ye
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunxiao Wei
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuan Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Sandui Guo
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chengzhen Liang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Rui Zhang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
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5
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Garrett KA, Bebber DP, Etherton BA, Gold KM, Plex Sulá AI, Selvaraj MG. Climate Change Effects on Pathogen Emergence: Artificial Intelligence to Translate Big Data for Mitigation. ANNUAL REVIEW OF PHYTOPATHOLOGY 2022; 60:357-378. [PMID: 35650670 DOI: 10.1146/annurev-phyto-021021-042636] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Plant pathology has developed a wide range of concepts and tools for improving plant disease management, including models for understanding and responding to new risks from climate change. Most of these tools can be improved using new advances in artificial intelligence (AI), such as machine learning to integrate massive data sets in predictive models. There is the potential to develop automated analyses of risk that alert decision-makers, from farm managers to national plant protection organizations, to the likely need for action and provide decision support for targeting responses. We review machine-learning applications in plant pathology and synthesize ideas for the next steps to make the most of these tools in digital agriculture. Global projects, such as the proposed global surveillance system for plant disease, will be strengthened by the integration of the wide range of new data, including data from tools like remote sensors, that are used to evaluate the risk ofplant disease. There is exciting potential for the use of AI to strengthen global capacity building as well, from image analysis for disease diagnostics and associated management recommendations on farmers' phones to future training methodologies for plant pathologists that are customized in real-time for management needs in response to the current risks. International cooperation in integrating data and models will help develop the most effective responses to new challenges from climate change.
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Affiliation(s)
- K A Garrett
- Plant Pathology Department, University of Florida, Gainesville, Florida, USA;
- Food Systems Institute, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - D P Bebber
- Department of Biosciences, University of Exeter, Exeter, United Kingdom
| | - B A Etherton
- Plant Pathology Department, University of Florida, Gainesville, Florida, USA;
- Food Systems Institute, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - K M Gold
- Plant Pathology and Plant Microbe Biology Section, School of Integrative Plant Sciences, Cornell AgriTech, Cornell University, Geneva, New York, USA
| | - A I Plex Sulá
- Plant Pathology Department, University of Florida, Gainesville, Florida, USA;
- Food Systems Institute, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - M G Selvaraj
- The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), Cali, Colombia
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Offornedo Q, Menkir A, Babalola D, Gedil M. Developing and deploying an efficient genotyping workflow for accelerating maize improvement in developing countries. Gates Open Res 2022. [DOI: 10.12688/gatesopenres.13338.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Molecular breeding is an essential tool for accelerating genetic gain in crop improvement towards meeting the need to feed an ever-growing world population. Establishing low-cost, flexible genotyping platforms in small, public and regional laboratories can stimulate the application of molecular breeding in developing countries. These laboratories can serve plant breeding projects requiring low- to medium-density markers for marker-assisted selection (MAS) and quality control (QC) activities. Methods: We performed two QC and MAS experiments consisting of 637 maize lines, using an optimised genotyping workflow involving an in-house competitive allele-specific PCR (KASP) genotyping system with an optimised sample collection, preparation, and DNA extraction and quantitation process. A smaller volume of leaf-disc size plant samples was collected directly in 96-well plates for DNA extraction, using a slightly modified CTAB-based DArT DNA extraction protocol. DNA quality and quantity analyses were performed using a microplate reader, and the KASP genotyping and data analysis was performed in our laboratory. Results: Applying the optimized genotyping workflow expedited the QC and MAS experiments from over five weeks (when outsourcing) to two weeks and eliminated the shipping cost. Using a set of 28 KASP single nucleotide polymorphisms (SNPs) validated for maize, the QC experiment revealed the genetic identity of four maize varieties taken from five seed sources. Another set of 10 KASP SNPs was sufficient in verifying the parentage of 390 F1 lines. The KASP-based MAS was successfully applied to a maize pro-vitamin A (PVA) breeding program and for introgressing the aflatoxin resistance gene into elite tropical maize lines. Conclusion: This improved workflow has helped accelerate maize improvement activities of IITA's Maize Improvement Program and facilitated DNA fingerprinting for tracking improved crop varieties. National Agricultural Research Systems (NARS) in developing countries can adopt this workflow to fast-track molecular marker-based genotyping for crop improvement.
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Offornedo Q, Menkir A, Babalola D, Gedil M. Developing and deploying an efficient genotyping workflow for accelerating maize improvement in developing countries. Gates Open Res 2022. [DOI: 10.12688/gatesopenres.13338.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Molecular breeding is an essential tool for accelerating genetic gain in crop improvement, towards meeting the need to feed an ever-growing world population. Establishing low-cost, flexible genotyping platforms in small, public and regional laboratories can stimulate the application of molecular breeding in developing countries. These laboratories can serve plant breeding projects requiring low- to medium-density markers for marker-assisted selection (MAS) and quality control (QC) activities. Methods: We performed two QC and MAS experiments consisting of 637 maize lines, using an optimised genotyping workflow involving an in-house competitive allele-specific PCR (KASP) genotyping system with an optimised sample collection, preparation, and DNA extraction and quantitation process. A smaller volume of leaf-disc size plant samples was collected directly in 96-well plates for DNA extraction, using a slightly modified CTAB-based DArT DNA extraction protocol. DNA quality and quantity analyses were performed using a microplate reader, and the KASP genotyping and data analysis was performed in our laboratory. Results: Applying the optimized genotyping workflow expedited the QC and MAS experiments from over five weeks (when outsourcing) to two weeks and eliminated the shipping cost. Using a set of 28 KASP single nucleotide polymorphisms (SNPs) validated for maize, the QC experiment revealed the genetic identity of four maize varieties taken from five seed sources. Another set of 10 KASP SNPs was sufficient in verifying the parentage of 390 F1 lines. The KASP-based MAS was successfully applied to a maize pro-vitamin A (PVA) breeding program and for introgressing the aflatoxin resistance gene into elite tropical maize lines. Conclusion: This improved workflow has helped accelerate maize improvement activities of IITA's Maize Improvement Program and facilitated DNA fingerprinting for tracking improved crop varieties. National Agricultural Research Systems (NARS) in developing countries can adopt this workflow to fast-track molecular marker-based genotyping for crop improvement.
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8
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Vallejos CE, Jones JW, Bhakta MS, Gezan SA, Correll MJ. Dynamic QTL-based ecophysiological models to predict phenotype from genotype and environment data. BMC PLANT BIOLOGY 2022; 22:275. [PMID: 35658831 PMCID: PMC9169398 DOI: 10.1186/s12870-022-03624-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/04/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Predicting the phenotype from the genotype is one of the major contemporary challenges in biology. This challenge is greater in plants because their development occurs mostly post-embryonically under diurnal and seasonal environmental fluctuations. Most current crop simulation models are physiology-based models capable of capturing environmental fluctuations but cannot adequately capture genotypic effects because they were not constructed within a genetics framework. RESULTS We describe the construction of a mixed-effects dynamic model to predict time-to-flowering in the common bean (Phaseolus vulgaris L.). This prediction model applies the developmental approach used by traditional crop simulation models, uses direct observational data, and captures the Genotype, Environment, and Genotype-by-Environment effects to predict progress towards time-to-flowering in real time. Comparisons to a traditional crop simulation model and to a previously developed static model shows the advantages of the new dynamic model. CONCLUSIONS The dynamic model can be applied to other species and to different plant processes. These types of models can, in modular form, gradually replace plant processes in existing crop models as has been implemented in BeanGro, a crop simulation model within the DSSAT Cropping Systems Model. Gene-based dynamic models can accelerate precision breeding of diverse crop species, particularly with the prospects of climate change. Finally, a gene-based simulation model can assist policy decision makers in matters pertaining to prediction of food supplies.
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Affiliation(s)
- C Eduardo Vallejos
- Horticultural Sciences Department, University of Florida, Gainesville, FL, 32611, USA.
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, FL, 32611, USA.
| | - James W Jones
- Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, 32611, USA
| | - Mehul S Bhakta
- Horticultural Sciences Department, University of Florida, Gainesville, FL, 32611, USA
- Present Address: Bayer Crop Science, 700 Chesterfield Parkway, West Chesterfield, MO, 63017, USA
| | - Salvador A Gezan
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL, 32611, USA
- Present Address: VSN International, Hemel Hempstead, UK
| | - Melanie J Correll
- Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, 32611, USA
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9
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Omics: a tool for resilient rice genetic improvement strategies. Mol Biol Rep 2022; 49:5075-5088. [PMID: 35298758 DOI: 10.1007/s11033-022-07189-4] [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: 07/24/2021] [Accepted: 01/24/2022] [Indexed: 10/18/2022]
Abstract
Rice is pivotal pyramid of about half of the world population. Bearing small genome size and worldwide utmost food crop rice has been known as ideal cereal crop for genome research. Currently, decreasing water table and soil fatigue are big challenges and intense consequences in changing climate. Whole sequenced genome of rice sized 389 Mb of which 95% is covered with excellent mapping order. Sequenced rice genome helps in molecular biology and transcriptomics of cereals as it provides whole genome sequence of indica and japonica sub species. Through rice genome sequencing and functional genomics, QTLs or genes, genetic variability and halophyte blocks for agronomic characters were identified which have proved much more useful in molecular breeding and direct selection. There are different numbers of genes or QTLs identified for yield related traits i.e., 6 QTLs/genes for plant architecture, 6 for panicle characteristics, 4 for grain number, 1 gene/QTL for tiller, HGW, grain filling and shattering. QTLS/genes for grain quality, biotic stresses and for abiotic stresses are 7, 23 and 13 respectively. Low yield, inferior quality and susceptibility to biotic and abiotic stresses of a crop is due to narrow genetic background of new evolving rice verities. Wild rice provides genetic resources for improvement of these characters, molecular and genomics tool at different stages can overcome these stresses and improve yield and quality of rice crop.
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10
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Han S, Jiang S, Xiong R, Shafique K, Zahid KR, Wang Y. Response and tolerance mechanism of food crops under high temperature stress: a review. BRAZ J BIOL 2022; 82:e253898. [PMID: 35107484 DOI: 10.1590/1519-6984.253898] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 11/23/2021] [Indexed: 01/15/2023] Open
Abstract
High temperature stress events are critical factors inhibiting crop yield. Meanwhile, world population is growing very rapidly and will be reached up to 9 billion by 2050. To feed increasing world population, it is challenging task to increase about 70% global food productions. Food crops have significant contribution toward global food demand and food security. However, consequences from increasing heat stress events are demolishing their abilities to survive and sustain yield when subjected to extreme high temperature stress. Therefore, there is dire need to better understand response and tolerance mechanism of food crops following exposure to heat stress. Here, we aimed to provide recent update on impact of high temperature stress on crop yield of food crops, pollination, pollinators, and novel strategies for improving tolerance of food crop under high temperature stress. Importantly, development of heat-resistant transgenic food crops can grant food security through transformation of superior genes into current germplasm, which are associated with various signaling pathways as well as epigenetic regulation in response to extreme high temperature stress.
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Affiliation(s)
- S Han
- Liupanshui Normal University, School of Biological Sciences and Technology, Liupanshui, China
| | - S Jiang
- Zhengzhou Normal University, Bioengineering Research Center, Zhengzhou, Henan, P.R. China
| | - R Xiong
- Liupanshui Normal University, School of Biological Sciences and Technology, Liupanshui, China
| | - K Shafique
- Government Sadiq College Women University, Department of Botany, Bahawalpur, Pakistan
| | - K R Zahid
- Shenzhen University, Carson International Cancer Center, College of Life Sciences and Oceanography, Shenzhen Key Laboratory of Microbial Genetic Engineering, Shenzhen, Guangdong, China
| | - Y Wang
- Liupanshui Normal University, School of Biological Sciences and Technology, Liupanshui, China
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11
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Offornedo Q, Menkir A, Babalola D, Gedil M. Developing and deploying an efficient genotyping workflow for accelerating maize improvement in developing countries. Gates Open Res 2022. [DOI: 10.12688/gatesopenres.13338.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Molecular breeding is an essential tool for accelerating genetic gain in crop improvement, towards meeting the need to feed an ever-growing world population. Establishing low-cost, flexible genotyping platforms in small, public and regional laboratories can stimulate the application of molecular breeding in developing countries. These laboratories can serve plant breeding projects requiring low- to medium-density markers for marker-assisted selection (MAS) and quality control (QC) activities. Methods: We performed two QC and MAS experiments consisting of 637 maize lines, using an optimised genotyping workflow involving an in-house competitive allele-specific PCR (KASP) genotyping system with an optimised sample collection, preparation, and DNA extraction and quantitation process. A smaller volume of leaf-disc size plant samples was collected directly in 96-well plates for DNA extraction, using a slightly modified CTAB-based DArT DNA extraction protocol. DNA quality and quantity analyses were performed using a microplate reader, and the KASP genotyping and data analysis was performed in our laboratory. Results: Applying the optimized genotyping workflow expedited the QC and MAS experiments from over five weeks (when outsourcing) to two weeks and eliminated the shipping cost. Using a set of 28 KASP single nucleotide polymorphisms (SNPs) validated for maize, the QC experiment revealed the genetic identity of four maize varieties taken from five seed sources. Another set of 10 KASP SNPs was sufficient in verifying the parentage of 390 F1 lines. The KASP-based MAS was successfully applied to a maize pro-vitamin A (PVA) breeding program and for introgressing the aflatoxin resistance gene into elite tropical maize lines. Conclusion: This improved workflow has helped accelerate maize improvement activities of IITA's Maize Improvement Program and facilitated DNA fingerprinting for tracking improved crop varieties. National Agricultural Research Systems (NARS) in developing countries can adopt this workflow to fast-track molecular marker-based genotyping for crop improvement.
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Guo Z, Yang Q, Huang F, Zheng H, Sang Z, Xu Y, Zhang C, Wu K, Tao J, Prasanna BM, Olsen MS, Wang Y, Zhang J, Xu Y. Development of high-resolution multiple-SNP arrays for genetic analyses and molecular breeding through genotyping by target sequencing and liquid chip. PLANT COMMUNICATIONS 2021; 2:100230. [PMID: 34778746 PMCID: PMC8577115 DOI: 10.1016/j.xplc.2021.100230] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 08/05/2021] [Accepted: 08/06/2021] [Indexed: 05/26/2023]
Abstract
Genotyping platforms, as critical supports for genomics, genetics, and molecular breeding, have been well implemented at national institutions/universities in developed countries and multinational seed companies that possess high-throughput, automatic, large-scale, and shared facilities. In this study, we integrated an improved genotyping by target sequencing (GBTS) system with capture-in-solution (liquid chip) technology to develop a multiple single-nucleotide polymorphism (mSNP) approach in which mSNPs can be captured from a single amplicon. From one 40K maize mSNP panel, we developed three types of markers (40K mSNPs, 251K SNPs, and 690K haplotypes), and generated multiple panels with various marker densities (1K-40K mSNPs) by sequencing at different depths. Comparative genetic diversity analysis was performed with genic versus intergenic markers and di-allelic SNPs versus non-typical SNPs. Compared with the one-amplicon-one-SNP system, mSNPs and within-mSNP haplotypes are more powerful for genetic diversity detection, linkage disequilibrium decay analysis, and genome-wide association studies. The technologies, protocols, and application scenarios developed for maize in this study will serve as a model for the development of mSNP arrays and highly efficient GBTS systems in animals, plants, and microorganisms.
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Affiliation(s)
- Zifeng Guo
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Quannv Yang
- School of Food Science and Engineering, Foshan University/CIMMYT-China Tropical Maize Research Center, Foshan 528225, Guangdong, China
| | - Feifei Huang
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang 050035, China
| | - Hongjian Zheng
- Crop Breeding and Cultivation Research Institute, Shanghai Academy of Agricultural Sciences/CIMMYT-China Specialty Maize Research Center, Shanghai 201403, China
| | - Zhiqin Sang
- Xinjiang Academy of Agricultural Reclamation, Shihezi 832000, Xinjiang, China
| | - Yanfen Xu
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang 050035, China
| | - Cong Zhang
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang 050035, China
| | - Kunsheng Wu
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang 050035, China
| | - Jiajun Tao
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang 050035, China
| | - Boddupalli M. Prasanna
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF Campus, United Nations Avenue, Nairobi, Kenya
| | - Michael S. Olsen
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF Campus, United Nations Avenue, Nairobi, Kenya
| | - Yunbo Wang
- School of Food Science and Engineering, Foshan University/CIMMYT-China Tropical Maize Research Center, Foshan 528225, Guangdong, China
| | - Jianan Zhang
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang 050035, China
- National Foxtail Millet Improvement Center, Minor Cereal Crops Laboratory of Hebei Province, Institute of Millet Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang 050035, China
| | - Yunbi Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- School of Food Science and Engineering, Foshan University/CIMMYT-China Tropical Maize Research Center, Foshan 528225, Guangdong, China
- Crop Breeding and Cultivation Research Institute, Shanghai Academy of Agricultural Sciences/CIMMYT-China Specialty Maize Research Center, Shanghai 201403, China
- International Maize and Wheat Improvement Center (CIMMYT), El Batan Texcoco 56130, Mexico
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Cerón-Souza I, Galeano CH, Tehelen K, Jiménez HR, González C. Opportunities and Challenges to Improve a Public Research Program in Plant Breeding and Enhance Underutilized Plant Genetic Resources in the Tropics. Genes (Basel) 2021; 12:genes12101584. [PMID: 34680981 PMCID: PMC8535561 DOI: 10.3390/genes12101584] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 01/15/2023] Open
Abstract
The American tropics are hotspots of wild and domesticated plant biodiversity, which is still underutilized by breeding programs despite being conserved at regional gene banks. The improvement of those programs depends on long-term public funds and the maintenance of specialized staff. Unfortunately, financial ups and downs complicate staff connectivity and their research impact. Between 2000 and 2010, Agrosavia (Corporación Colombiana de Investigación Agropecuaria) dramatically decreased its public financial support. In 2017, we surveyed all 52 researchers from Agrosavia involved in plant breeding and plant genetic resource programs to examine the effect of decimating funds in the last ten years. We hypothesized that the staff dedicated to plant breeding still suffer a strong fragmentation and low connectivity. As we expected, the social network among researchers is weak. The top ten central leaders are predominantly males with an M.Sc. degree but have significant experience in the area. The staff has experience in 31 tropical crops, and 17 are on the list of underutilized species. Moreover, although 26 of these crops are in the national germplasm bank, this has not been the primary source for their breeding programs. We proposed five principles to improve connectivity among teams and research impact: (1) The promotion of internal discussion about gender gaps and generation shifts to design indicators to monitor and decrease this disparity over time. (2) The construction of long-term initiatives and synergies with the Colombian government to support the local production of food security crops independent of market trends. (3) Better collaboration between the National Plant Germplasm Bank and plant breeding researchers. (4) A concerted priority list of species (especially those neglected or underutilized) and external institutions to better focus the collaborative efforts in research using public funds. (5) Better spaces for the design of projects among researchers and training programs in new technologies. These principles could also apply in other tropical countries with public plant breeding research programs facing similar challenges.
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Affiliation(s)
- Ivania Cerón-Souza
- Corporación Colombiana de Investigación Agropecuaria—Agrosavia, C.I. Tibaitatá, Mosquera 250047, Colombia; (H.R.J.); (C.G.)
- Correspondence: ; Tel.: +57-144-227-300 (ext. 1457)
| | - Carlos H. Galeano
- Corporación Colombiana de Investigación Agropecuaria—Agrosavia, C.I. Palmira, Palmira 763533, Colombia;
| | | | - Hugo R. Jiménez
- Corporación Colombiana de Investigación Agropecuaria—Agrosavia, C.I. Tibaitatá, Mosquera 250047, Colombia; (H.R.J.); (C.G.)
| | - Carolina González
- Corporación Colombiana de Investigación Agropecuaria—Agrosavia, C.I. Tibaitatá, Mosquera 250047, Colombia; (H.R.J.); (C.G.)
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Song JM, Arif M, Zi Y, Sze SH, Zhang M, Zhang HB. Molecular and genetic dissection of the USDA rice mini-core collection using high-density SNP markers. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2021; 308:110910. [PMID: 34034867 DOI: 10.1016/j.plantsci.2021.110910] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 04/05/2021] [Accepted: 04/10/2021] [Indexed: 06/12/2023]
Abstract
Molecular tools and knowledge of crop germplasm are vital for their effective utilization. In this study, we developed 40,866 high-quality and well distributed SNPs for a rice mini-core collection (RMC) developed by the United States Department of Agriculture (USDA). The high-quality SNPs clustered the USDA-RMC into five subpopulations (Ind, indica; Aus, aus; Afr, African rice; TeJ, temperate japonica; TrJ, tropical japonica) and one admixture (Adm). This classification was further confirmed by phylogenetic and principal component analyses. The rice ARO (aromatic) subpopulation of previous studies was re-assigned with Adm and the WD (wild-type) subpopulation was re-defined to the Afr subpopulation because most of its accessions are African cultivated rice. The Aus and Ind subpopulations had a substantially wider genetic variation than the TrJ and TeJ subpopulations. The genetic diversities were much larger between the Ind or Aus subpopulation and the TrJ or TeJ subpopulation than between the Afr subpopulation and the Ind, Aus, TrJ or TeJ subpopulation. Comparative agronomic trait analysis between the subpopulations also supported the genetic structure and variation of the RMC, and suggested the existence of extensive variation in the genes controlling agronomic traits among them. Furthermore, analysis of ancestral membership of the RMC accessions revealed that reproductive barrier or wide incompatibility existed between the Indica and Japonica groups, while gene flow occurred between them. These results provide high-quality SNPs and knowledge of genetic structure and diversity of the USDA-RMC necessary for enhanced rice research and breeding.
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Affiliation(s)
- Jian-Min Song
- Crop Research Institute/National Engineering Laboratory for Wheat and Maize, Shandong Academy of Agricultural Sciences (SAAS), Jinan, 250100, PR China; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, 77843-2474, USA.
| | - Muhammad Arif
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, 77843-2474, USA; Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan.
| | - Yan Zi
- Crop Research Institute/National Engineering Laboratory for Wheat and Maize, Shandong Academy of Agricultural Sciences (SAAS), Jinan, 250100, PR China
| | - Sing-Hoi Sze
- Department of Computer Science and Engineering and Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.
| | - Meiping Zhang
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, 77843-2474, USA.
| | - Hong-Bin Zhang
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, 77843-2474, USA.
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Genetic Dissection and Identification of Candidate Genes for Salinity Tolerance Using Axiom ®CicerSNP Array in Chickpea. Int J Mol Sci 2020; 21:ijms21145058. [PMID: 32709160 PMCID: PMC7404205 DOI: 10.3390/ijms21145058] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 07/10/2020] [Accepted: 07/14/2020] [Indexed: 01/22/2023] Open
Abstract
Globally, chickpea production is severely affected by salinity stress. Understanding the genetic basis for salinity tolerance is important to develop salinity tolerant chickpeas. A recombinant inbred line (RIL) population developed using parental lines ICCV 10 (salt-tolerant) and DCP 92-3 (salt-sensitive) was screened under field conditions to collect information on agronomy, yield components, and stress tolerance indices. Genotyping data generated using Axiom®CicerSNP array was used to construct a linkage map comprising 1856 SNP markers spanning a distance of 1106.3 cM across eight chickpea chromosomes. Extensive analysis of the phenotyping and genotyping data identified 28 quantitative trait loci (QTLs) explaining up to 28.40% of the phenotypic variance in the population. We identified QTL clusters on CaLG03 and CaLG06, each harboring major QTLs for yield and yield component traits under salinity stress. The main-effect QTLs identified in these two clusters were associated with key genes such as calcium-dependent protein kinases, histidine kinases, cation proton antiporter, and WRKY and MYB transcription factors, which are known to impart salinity stress tolerance in crop plants. Molecular markers/genes associated with these major QTLs, after validation, will be useful to undertake marker-assisted breeding for developing better varieties with salinity tolerance.
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17
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Peng H, Wang K, Chen Z, Cao Y, Gao Q, Li Y, Li X, Lu H, Du H, Lu M, Yang X, Liang C. MBKbase for rice: an integrated omics knowledgebase for molecular breeding in rice. Nucleic Acids Res 2020; 48:D1085-D1092. [PMID: 31624841 PMCID: PMC7145604 DOI: 10.1093/nar/gkz921] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 10/04/2019] [Accepted: 10/08/2019] [Indexed: 11/25/2022] Open
Abstract
To date, large amounts of genomic and phenotypic data have been accumulated in the fields of crop genetics and genomic research, and the data are increasing very quickly. However, the bottleneck to using big data in breeding is integrating the data and developing tools for revealing the relationship between genotypes and phenotypes. Here, we report a rice sub-database of an integrated omics knowledgebase (MBKbase-rice, www.mbkbase.org/rice), which integrates rice germplasm information, multiple reference genomes with a united set of gene loci, population sequencing data, phenotypic data, known alleles and gene expression data. In addition to basic data search functions, MBKbase provides advanced web tools for genotype searches at the population level and for visually displaying the relationship between genotypes and phenotypes. Furthermore, the database also provides online tools for comparing two samples by their genotypes and finding target germplasms by genotype or phenotype information, as well as for analyzing the user submitted SNP or sequence data to find important alleles in the germplasm. A soybean sub-database is planned for release in 3 months and wheat and maize will be added in 1–2 years. The data and tools integrated in MBKbase will facilitate research in crop functional genomics and molecular breeding.
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Affiliation(s)
- Hua Peng
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kai Wang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhuo Chen
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yinghao Cao
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Qiang Gao
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Yan Li
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiuxiu Li
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongwei Lu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huilong Du
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Lu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Yang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Chengzhi Liang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
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Varshney RK, Ojiewo C, Monyo E. A decade of Tropical Legumes projects: Development and adoption of improved varieties, creation of market-demand to benefit smallholder farmers and empowerment of national programmes in sub-Saharan Africa and South Asia. PLANT BREEDING = ZEITSCHRIFT FUR PFLANZENZUCHTUNG 2019; 138:379-388. [PMID: 31762525 PMCID: PMC6853253 DOI: 10.1111/pbr.12744] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Revised: 07/01/2019] [Accepted: 07/02/2019] [Indexed: 05/17/2023]
Abstract
This article highlights 12 years (2007-2019) of research, achievements, lessons learned, challenges and gaps in discovery-to-delivery research in legumes emanating from three projects, collectively called Tropical Legumes (TL) with a total investment of about US$ 67 million funded by the Bill & Melinda Gates Foundation. These projects were implemented by three CGIAR centres (ICRISAT, CIAT and IITA) together with 15 national agricultural research system partners in sub-Saharan Africa and South Asia. The TL projects together with some of their precursors and complementary projects from other agencies, facilitated the development of 266 improved legume varieties and the production of about 497,901 tons of certified seeds of the target legume crops in the focus countries. The certified seeds have been planted on about 5.0 million ha by more than 25 million smallholder farmers in the 15 countries and beyond, producing about 6.1 million tons of grain worth US$ 3.2 billion. Furthermore, the projects also trained 52 next generation scientists that included 10 women, by supporting 34 Masters degrees and 18 PhD degrees.
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Affiliation(s)
- Rajeev K. Varshney
- International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)PatancheruIndia
| | - Chris Ojiewo
- International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)NairobiKenya
| | - Emmanuel Monyo
- International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)NairobiKenya
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19
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Islam MS, Ivanov S, Robson E, Dooley-Cullinane T, Coffey L, Doolin K, Balasubramaniam S. Genetic similarity of biological samples to counter bio-hacking of DNA-sequencing functionality. Sci Rep 2019; 9:8684. [PMID: 31213619 PMCID: PMC6581904 DOI: 10.1038/s41598-019-44995-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 05/29/2019] [Indexed: 11/27/2022] Open
Abstract
We present the work towards strengthening the security of DNA-sequencing functionality of future bioinformatics systems against bio-computing attacks. Recent research has shown how using common tools, a perpetrator can synthesize biological material, which upon DNA-analysis opens a cyber-backdoor for the perpetrator to hijack control of a computational resource from the DNA-sequencing pipeline. As DNA analysis finds its way into practical everyday applications, the threat of bio-hacking increases. Our wetlab experiments establish that malicious DNA can be synthesized and inserted into E. coli, a common contaminant. Based on that, we propose a new attack, where a hacker to reach the target hides the DNA with malicious code on common surfaces (e.g., lab coat, bench, rubber glove). We demonstrated that the threat of bio-hacking can be mitigated using dedicated input control techniques similar to those used to counter conventional injection attacks. This article proposes to use genetic similarity of biological samples to identify material that has been generated for bio-hacking. We considered freely available genetic data from 506 mammary, lymphocyte and erythrocyte samples that have a bio-hacking code inserted. During the evaluation we were able to detect up to 95% of malicious DNAs confirming suitability of our method.
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Affiliation(s)
| | - Stepan Ivanov
- Telecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland.
| | - Eric Robson
- Telecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland
| | - Tríona Dooley-Cullinane
- Pharmaceutical and Molecular Biotechnology Research Centre, Waterford Institute of Technology, Waterford, Ireland
| | - Lee Coffey
- Pharmaceutical and Molecular Biotechnology Research Centre, Waterford Institute of Technology, Waterford, Ireland
| | - Kevin Doolin
- Telecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland
| | - Sasitharan Balasubramaniam
- Telecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland
- Faculty of Information and Communication Sciences, Tampere University, Tampere, Finland
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20
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QTLian breeding for climate resilience in cereals: progress and prospects. Funct Integr Genomics 2019; 19:685-701. [PMID: 31093800 DOI: 10.1007/s10142-019-00684-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 04/05/2019] [Accepted: 04/30/2019] [Indexed: 10/26/2022]
Abstract
The ever-rising population of the twenty-first century together with the prevailing challenges, such as deteriorating quality of arable land and water, has placed a big challenge for plant breeders to satisfy human needs for food under erratic weather patterns. Rice, wheat, and maize are the major staple crops consumed globally. Drought, waterlogging, heat, salinity, and mineral toxicity are the key abiotic stresses drastically affecting crop yield. Conventional plant breeding approaches towards abiotic stress tolerance have gained success to limited extent, due to the complex (multigenic) nature of these stresses. Progress in breeding climate-resilient crop plants has gained momentum in the last decade, due to improved understanding of the physiochemical and molecular basis of various stresses. A good number of genes have been characterized for adaptation to various stresses. In the era of novel molecular markers, mapping of QTLs has emerged as viable solution for breeding crops tolerant to abiotic stresses. Therefore, molecular breeding-based development and deployment of high-yielding climate-resilient crop cultivars together with climate-smart agricultural practices can pave the path to enhanced crop yields for smallholder farmers in areas vulnerable to the climate change. Advances in fine mapping and expression studies integrated with cheaper prices offer new avenues for the plant breeders engaged in climate-resilient plant breeding, and thereby, hope persists to ensure food security in the era of climate change.
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Mall T, Gupta M, Dhadialla TS, Rodrigo S. Overview of Biotechnology-Derived Herbicide Tolerance and Insect Resistance Traits in Plant Agriculture. Methods Mol Biol 2019; 1864:313-342. [PMID: 30415345 DOI: 10.1007/978-1-4939-8778-8_21] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Biotechnology has been central for the acceleration of crop improvement over the last two decades. Since 1994, when the first commercial biotechnology-derived tomato crop was commercialized, the cultivated area for genetically modified crops has reached 185.1 million hactares worldwide. Both the number of crops and the number of traits developed using biotechnology have accounted for this increase. Among the most impactful biotechnology-derived traits are insect resistance and herbicide tolerance, which have greatly contributed to the worldwide increase in agricultural productivity and stabilization of food security. In this chapter, we provide an overview of the history of the biotechnology-derived input traits, the existing genetically engineered commercial crop products carrying insect resistance and herbicide tolerance traits, as well as a perspective on how new technologies could further impact the development of new traits in crops. With the projection of the world population to increase to 9.8 billion by the year 2050 and reduction in available farmland, one of the biggest challenges will be to provide sustainable nourishment to the projected population. Biotechnology will continue to be the key enabler for development of insect resistance and herbicide tolerance traits to overcome that imminent challenge.
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Affiliation(s)
- Tejinder Mall
- Corteva Agriscience™, Agriculture Division of DowDuPont™, Indianapolis, IN, USA
| | - Manju Gupta
- Corteva Agriscience™, Agriculture Division of DowDuPont™, Indianapolis, IN, USA
| | | | - Sarria Rodrigo
- Corteva Agriscience™, Agriculture Division of DowDuPont™, Indianapolis, IN, USA.
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22
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Du Q, Lu W, Quan M, Xiao L, Song F, Li P, Zhou D, Xie J, Wang L, Zhang D. Genome-Wide Association Studies to Improve Wood Properties: Challenges and Prospects. FRONTIERS IN PLANT SCIENCE 2018; 9:1912. [PMID: 30622554 PMCID: PMC6309013 DOI: 10.3389/fpls.2018.01912] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 12/10/2018] [Indexed: 05/02/2023]
Abstract
Wood formation is an excellent model system for quantitative trait analysis due to the strong associations between the transcriptional and metabolic traits that contribute to this complex process. Investigating the genetic architecture and regulatory mechanisms underlying wood formation will enhance our understanding of the quantitative genetics and genomics of complex phenotypic variation. Genome-wide association studies (GWASs) represent an ideal statistical strategy for dissecting the genetic basis of complex quantitative traits. However, elucidating the molecular mechanisms underlying many favorable loci that contribute to wood formation and optimizing GWAS design remain challenging in this omics era. In this review, we summarize the recent progress in GWAS-based functional genomics of wood property traits in major timber species such as Eucalyptus, Populus, and various coniferous species. We discuss several appropriate experimental designs for extensive GWAS in a given undomesticated tree population, such as omics-wide association studies and high-throughput phenotyping technologies. We also explain why more attention should be paid to rare allelic and major structural variation. Finally, we explore the potential use of GWAS for the molecular breeding of trees. Such studies will help provide an integrated understanding of complex quantitative traits and should enable the molecular design of new cultivars.
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Affiliation(s)
- Qingzhang Du
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Wenjie Lu
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Mingyang Quan
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Liang Xiao
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Fangyuan Song
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Peng Li
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Daling Zhou
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Jianbo Xie
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Longxin Wang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Deqiang Zhang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
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Lavarenne J, Guyomarc'h S, Sallaud C, Gantet P, Lucas M. The Spring of Systems Biology-Driven Breeding. TRENDS IN PLANT SCIENCE 2018; 23:706-720. [PMID: 29764727 DOI: 10.1016/j.tplants.2018.04.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 04/12/2018] [Accepted: 04/16/2018] [Indexed: 05/08/2023]
Abstract
Genetics and molecular biology have contributed to the development of rationalized plant breeding programs. Recent developments in both high-throughput experimental analyses of biological systems and in silico data processing offer the possibility to address the whole gene regulatory network (GRN) controlling a given trait. GRN models can be applied to identify topological features helping to shortlist potential candidate genes for breeding purposes. Time-series data sets can be used to support dynamic modelling of the network. This will enable a deeper comprehension of network behaviour and the identification of the few elements to be genetically rewired to push the system towards a modified phenotype of interest. This paves the way to design more efficient, systems biology-based breeding strategies.
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Affiliation(s)
- Jérémy Lavarenne
- UMR DIADE, Université de Montpellier, IRD, 911 Avenue Agropolis, 34394 Montpellier cedex 5, France; Biogemma, Centre de Recherches de Chappes, Route d'Ennezat, 63720 Chappes, France
| | - Soazig Guyomarc'h
- UMR DIADE, Université de Montpellier, IRD, 911 Avenue Agropolis, 34394 Montpellier cedex 5, France
| | - Christophe Sallaud
- Biogemma, Centre de Recherches de Chappes, Route d'Ennezat, 63720 Chappes, France
| | - Pascal Gantet
- UMR DIADE, Université de Montpellier, IRD, 911 Avenue Agropolis, 34394 Montpellier cedex 5, France.
| | - Mikaël Lucas
- UMR DIADE, Université de Montpellier, IRD, 911 Avenue Agropolis, 34394 Montpellier cedex 5, France
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Scheben A, Batley J, Edwards D. Revolution in Genotyping Platforms for Crop Improvement. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2018; 164:37-52. [PMID: 29356847 DOI: 10.1007/10_2017_47] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.
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Affiliation(s)
- Armin Scheben
- School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Crawley, WA, Australia.,Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - David Edwards
- School of Biological Sciences, University of Western Australia, Crawley, WA, Australia. .,Institute of Agriculture, University of Western Australia, Crawley, WA, Australia.
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25
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Alves ML, Brites C, Paulo M, Carbas B, Belo M, Mendes-Moreira PMR, Brites C, Bronze MDR, Gunjača J, Šatović Z, Vaz Patto MC. Setting Up Decision-Making Tools toward a Quality-Oriented Participatory Maize Breeding Program. FRONTIERS IN PLANT SCIENCE 2017; 8:2203. [PMID: 29312428 PMCID: PMC5744637 DOI: 10.3389/fpls.2017.02203] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 12/14/2017] [Indexed: 05/30/2023]
Abstract
Previous studies have reported promising differences in the quality of kernels from farmers' maize populations collected in a Portuguese region known to produce maize-based bread. However, several limitations have been identified in the previous characterizations of those populations, such as a limited set of quality traits accessed and a missing accurate agronomic performance evaluation. The objectives of this study were to perform a more detailed quality characterization of Portuguese farmers' maize populations; to estimate their agronomic performance in a broader range of environments; and to integrate quality, agronomic, and molecular data in the setting up of decision-making tools for the establishment of a quality-oriented participatory maize breeding program. Sixteen farmers' maize populations, together with 10 other maize populations chosen for comparison purposes, were multiplied in a common-garden experiment for quality evaluation. Flour obtained from each population was used to study kernel composition (protein, fat, fiber), flour's pasting behavior, and bioactive compound levels (carotenoids, tocopherols, phenolic compounds). These maize populations were evaluated for grain yield and ear weight in nine locations across Portugal; the populations' adaptability and stability were evaluated using additive main effects and multiplication interaction (AMMI) model analysis. The phenotypic characterization of each population was complemented with a molecular characterization, in which 30 individuals per population were genotyped with 20 microsatellites. Almost all farmers' populations were clustered into the same quality-group characterized by high levels of protein and fiber, low levels of carotenoids, volatile aldehydes, α- and δ-tocopherols, and breakdown viscosity. Within this quality-group, variability on particular quality traits (color and some bioactive compounds) could still be found. Regarding the agronomic performance, farmers' maize populations had low, but considerably stable, grain yields across the tested environments. As for their genetic diversity, each farmers' population was genetically heterogeneous; nonetheless, all farmers' populations were distinct from each other's. In conclusion, and taking into consideration different quality improvement objectives, the integration of the data generated within this study allowed the outline and exploration of alternative directions for future breeding activities. As a consequence, more informed choices will optimize the use of the resources available and improve the efficiency of participatory breeding activities.
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Affiliation(s)
- Mara L. Alves
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
| | - Cláudia Brites
- Instituto Politécnico de Coimbra, Escola Superior Agrária, Coimbra, Portugal
| | - Manuel Paulo
- Instituto Politécnico de Coimbra, Escola Superior Agrária, Coimbra, Portugal
| | - Bruna Carbas
- Unidade de Tecnologia e Inovação, Instituto Nacional de Investigação Agrária e Veterinária, Oeiras, Portugal
| | - Maria Belo
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
| | | | - Carla Brites
- Unidade de Tecnologia e Inovação, Instituto Nacional de Investigação Agrária e Veterinária, Oeiras, Portugal
| | - Maria do Rosário Bronze
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
- Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal
- Food and Health Division, Instituto de Biologia Experimental e Tecnológica, Oeiras, Portugal
| | - Jerko Gunjača
- Faculty of Agriculture, University of Zagreb, Zagreb, Croatia
- Centre of Excellence for Biodiversity and Molecular Plant Breeding (CoE CroP-BioDiv), Zagreb, Croatia
| | - Zlatko Šatović
- Faculty of Agriculture, University of Zagreb, Zagreb, Croatia
- Centre of Excellence for Biodiversity and Molecular Plant Breeding (CoE CroP-BioDiv), Zagreb, Croatia
| | - Maria C. Vaz Patto
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
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26
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Classical and Molecular Approaches for Mapping of Genes and Quantitative Trait Loci in Peanut. ACTA ACUST UNITED AC 2017. [DOI: 10.1007/978-3-319-63935-2_7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
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Rasheed A, Hao Y, Xia X, Khan A, Xu Y, Varshney RK, He Z. Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives. MOLECULAR PLANT 2017; 10:1047-1064. [PMID: 28669791 DOI: 10.1016/j.molp.2017.06.008] [Citation(s) in RCA: 219] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Revised: 05/29/2017] [Accepted: 06/19/2017] [Indexed: 05/18/2023]
Abstract
There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.
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Affiliation(s)
- Awais Rasheed
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China; International Maize and Wheat Improvement Center (CIMMYT), c/o CAAS, Beijing 100081, China
| | - Yuanfeng Hao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Awais Khan
- Department of Plant Pathology and Plant-Microbe Biology, Cornell University, Geneva, NY, USA
| | - Yunbi Xu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China; International Maize and Wheat Improvement Center (CIMMYT), c/o CAAS, Beijing 100081, China
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India
| | - Zhonghu He
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China; International Maize and Wheat Improvement Center (CIMMYT), c/o CAAS, Beijing 100081, China.
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28
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Xu Y, Li P, Zou C, Lu Y, Xie C, Zhang X, Prasanna BM, Olsen MS. Enhancing genetic gain in the era of molecular breeding. JOURNAL OF EXPERIMENTAL BOTANY 2017; 68:2641-2666. [PMID: 28830098 DOI: 10.1093/jxb/erx135] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 04/03/2017] [Indexed: 05/20/2023]
Abstract
As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders' demonstration trials and the actual yield in farmers' fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary approaches, team breeding, will be required to address the challenge of maintaining a plentiful and safe food supply for future generations. New opportunities for enhancing genetic gain, a high efficiency breeding pipeline, and broad-sense genetic gain are also discussed prospectively.
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Affiliation(s)
- Yunbi Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, CP 56130, México
| | - Ping Li
- Nantong Xinhe Bio-Technology, Nantong 226019, PR China
| | - Cheng Zou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yanli Lu
- Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
| | - Chuanxiao Xie
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuecai Zhang
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, CP 56130, México
| | - Boddupalli M Prasanna
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF campus, United Nations Avenue, Nairobi, Kenya
| | - Michael S Olsen
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF campus, United Nations Avenue, Nairobi, Kenya
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29
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Foyer CH, Lam HM, Nguyen HT, Siddique KHM, Varshney RK, Colmer TD, Cowling W, Bramley H, Mori TA, Hodgson JM, Cooper JW, Miller AJ, Kunert K, Vorster J, Cullis C, Ozga JA, Wahlqvist ML, Liang Y, Shou H, Shi K, Yu J, Fodor N, Kaiser BN, Wong FL, Valliyodan B, Considine MJ. Neglecting legumes has compromised human health and sustainable food production. NATURE PLANTS 2016; 2:16112. [PMID: 28221372 DOI: 10.1038/nplants.2016.112] [Citation(s) in RCA: 307] [Impact Index Per Article: 38.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
The United Nations declared 2016 as the International Year of Pulses (grain legumes) under the banner 'nutritious seeds for a sustainable future'. A second green revolution is required to ensure food and nutritional security in the face of global climate change. Grain legumes provide an unparalleled solution to this problem because of their inherent capacity for symbiotic atmospheric nitrogen fixation, which provides economically sustainable advantages for farming. In addition, a legume-rich diet has health benefits for humans and livestock alike. However, grain legumes form only a minor part of most current human diets, and legume crops are greatly under-used. Food security and soil fertility could be significantly improved by greater grain legume usage and increased improvement of a range of grain legumes. The current lack of coordinated focus on grain legumes has compromised human health, nutritional security and sustainable food production.
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Affiliation(s)
- Christine H Foyer
- Centre for Plant Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
- School of Plant Biology, Faculty of Science, The University of Western Australia, Perth, Western Australia 6009, Australia
| | - Hon-Ming Lam
- School of Life Sciences and Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region
| | - Henry T Nguyen
- Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri, Columbia, Missouri 65211, USA
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia 6009, Australia
| | - Rajeev K Varshney
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia 6009, Australia
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Greater Hyderabad, India
| | - Timothy D Colmer
- School of Plant Biology, Faculty of Science, The University of Western Australia, Perth, Western Australia 6009, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia 6009, Australia
| | - Wallace Cowling
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia 6009, Australia
| | - Helen Bramley
- Plant Breeding Institute, Faculty of Agriculture and Environment, The University of Sydney, Narrabri, New South Wales 2390, Australia
| | - Trevor A Mori
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia 6009, Australia
- School of Medicine and Pharmacology, Royal Perth Hospital Unit, The University of Western Australia, Perth, Western Australia 6000, Australia
| | - Jonathan M Hodgson
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia 6009, Australia
- School of Medicine and Pharmacology, Royal Perth Hospital Unit, The University of Western Australia, Perth, Western Australia 6000, Australia
| | - James W Cooper
- Centre for Plant Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Anthony J Miller
- Department of Metabolic Biology, John Innes Centre, Norwich Research Park, NR4 7UH, UK
| | - Karl Kunert
- Department of Plant Production and Soil Science, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria 0002, South Africa
| | - Juan Vorster
- Department of Plant Production and Soil Science, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria 0002, South Africa
| | - Christopher Cullis
- Department of Biology, Case Western Reserve University, Cleveland, Ohio 44106-7080, USA
| | - Jocelyn A Ozga
- Plant BioSystems Division, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, T6G 2P5, Canada
| | - Mark L Wahlqvist
- Fuli Institute of Food Science, Zhejiang University, Hangzhou, 310058, China
- Monash Asia Institute, Monash University, Melbourne, Victoria 3800, Australia
| | - Yan Liang
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China
| | - Huixia Shou
- College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Kai Shi
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China
| | - Jingquan Yu
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China
| | - Nandor Fodor
- Centre for Plant Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Brent N Kaiser
- Centre for Carbon Water and Food, Faculty of Agriculture and Environment, The University of Sydney, Brownlow Hill, New South Wales 2570, Australia
| | - Fuk-Ling Wong
- School of Life Sciences and Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region
| | - Babu Valliyodan
- Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri, Columbia, Missouri 65211, USA
| | - Michael J Considine
- School of Plant Biology, Faculty of Science, The University of Western Australia, Perth, Western Australia 6009, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia 6009, Australia
- The Department of Agriculture and Food, Western Australia, South Perth, Western Australia 6151, Australia
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30
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Barakate A, Stephens J. An Overview of CRISPR-Based Tools and Their Improvements: New Opportunities in Understanding Plant-Pathogen Interactions for Better Crop Protection. FRONTIERS IN PLANT SCIENCE 2016; 7:765. [PMID: 27313592 PMCID: PMC4887484 DOI: 10.3389/fpls.2016.00765] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2016] [Accepted: 05/17/2016] [Indexed: 05/04/2023]
Abstract
Modern omics platforms have made the determination of susceptible/resistance genes feasible in any species generating huge numbers of potential targets for crop protection. However, the efforts to validate these targets have been hampered by the lack of a fast, precise, and efficient gene targeting system in plants. Now, the repurposing of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system has solved this problem. CRISPR/Cas9 is the latest synthetic endonuclease that has revolutionized basic research by allowing facile genome editing in prokaryotes and eukaryotes. Gene knockout is now feasible at an unprecedented efficiency with the possibility of multiplexing several targets and even genome-wide mutagenesis screening. In a short time, this powerful tool has been engineered for an array of applications beyond gene editing. Here, we briefly describe the CRISPR/Cas9 system, its recent improvements and applications in gene manipulation and single DNA/RNA molecule analysis. We summarize a few recent tests targeting plant pathogens and discuss further potential applications in pest control and plant-pathogen interactions that will inform plant breeding for crop protection.
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31
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Pandey MK, Roorkiwal M, Singh VK, Ramalingam A, Kudapa H, Thudi M, Chitikineni A, Rathore A, Varshney RK. Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects. FRONTIERS IN PLANT SCIENCE 2016; 7:455. [PMID: 27199998 PMCID: PMC4852475 DOI: 10.3389/fpls.2016.00455] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Accepted: 03/24/2016] [Indexed: 05/19/2023]
Abstract
Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries.
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Affiliation(s)
- Manish K. Pandey
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Manish Roorkiwal
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Vikas K. Singh
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Abirami Ramalingam
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Himabindu Kudapa
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Mahendar Thudi
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Anu Chitikineni
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Abhishek Rathore
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
| | - Rajeev K. Varshney
- International Crops Research Institute for the Semi-Arid TropicsHyderabad, India
- The University of Western AustraliaCrawley, WA, Australia
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