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Sallam A, Dawood MFA, Jarquín D, Mohamed EA, Hussein MY, Börner A, Ahmed AAM. Genome-wide scanning to identify and validate single nucleotide polymorphism markers associated with drought tolerance in spring wheat seedlings. THE PLANT GENOME 2024; 17:e20444. [PMID: 38476036 DOI: 10.1002/tpg2.20444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 02/12/2024] [Accepted: 02/15/2024] [Indexed: 03/14/2024]
Abstract
Unlike other growth stages of wheat, very few studies on drought tolerance have been done at the seedling stage, and this is due to the complexity and sensitivity of this stage to drought stress resulting from climate change. As a result, the drought tolerance of wheat seedlings is poorly understood and very few genes associated with drought tolerance at this stage were identified. To address this challenge, a set of 172 spring wheat genotypes representing 20 different countries was evaluated under drought stress at the seedling stage. Drought stress was applied on all tested genotypes by water withholding for 13 days. Two types of traits, namely morphological and physiological traits were scored on the leaves of all tested genotypes. Genome-wide association study (GWAS) is one of the effective genetic analysis methods that was used to identify target single nucleotide polymorphism (SNP) markers and candidate genes for later use in marker-assisted selection. The tested plant materials were genotyped using 25k Infinium iSelect array (25K) (herein after it will be identified as 25K) (for 172 genotypes) and genotyping-by-sequencing (GBS) (for 103 genotypes), respectively. The results of genotyping revealed 21,093 25K and 11,362 GBS-SNPs, which were used to perform GWAS analysis for all scored traits. The results of GWAS revealed that 131 and 55 significant SNPs were controlling morphological and physiological traits, respectively. Moreover, a total of eight and seven SNP markers were found to be associated with more than one morphological and physiological trait under drought stress, respectively. Remarkably, 10 significant SNPs found in this study were previously reported for their association with drought tolerance in wheat. Out of the 10 validated SNP markers, four SNPs were associated with drought at the seedling stage, while the remaining six SNPs were associated with drought stress at the reproductive stage. Moreover, the results of gene enrichment revealed 18 and six pathways as highly significant biological and molecular pathways, respectively. The selection based on drought-tolerant alleles revealed 15 genotypes with the highest number of different drought-tolerant alleles. These genotypes can be used as candidate parents in future breeding programs to produce highly drought-tolerant genotypes with high genetic diversity. Our findings in this study provide novel markers and useful information on the genetic basis of drought tolerance at early growth stages.
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Affiliation(s)
- Ahmed Sallam
- Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Stadt Seeland, Germany
- Department of Genetics, Faculty of Agriculture, Assiut University, Assiut, 71526, Egypt
| | - Mona F A Dawood
- Department of Botany and Microbiology, Faculty of Science, Assiut University, Assiut, Egypt
| | - Diego Jarquín
- Department of Agronomy, University of Florida, Gainesville, Florida, USA
| | - Elsayed A Mohamed
- Department of Genetics, Faculty of Agriculture, Assiut University, Assiut, 71526, Egypt
| | - Mohamed Y Hussein
- Department of Genetics, Faculty of Agriculture, Assiut University, Assiut, 71526, Egypt
| | - Andreas Börner
- Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Stadt Seeland, Germany
| | - Asmaa A M Ahmed
- Department of Genetics, Faculty of Agriculture, Assiut University, Assiut, 71526, Egypt
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2
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Mukherjee A, Maheshwari U, Sharma V, Sharma A, Kumar S. Functional insight into multi-omics-based interventions for climatic resilience in sorghum (Sorghum bicolor): a nutritionally rich cereal crop. PLANTA 2024; 259:91. [PMID: 38480598 DOI: 10.1007/s00425-024-04365-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 02/13/2024] [Indexed: 03/25/2024]
Abstract
MAIN CONCLUSION The article highlights omics-based interventions in sorghum to combat food and nutritional scarcity in the future. Sorghum with its unique ability to thrive in adverse conditions, has become a tremendous highly nutritive, and multipurpose cereal crop. It is resistant to various types of climatic stressors which will pave its way to a future food crop. Multi-omics refers to the comprehensive study of an organism at multiple molecular levels, including genomics, transcriptomics, proteomics, and metabolomics. Genomic studies have provided insights into the genetic diversity of sorghum and led to the development of genetically improved sorghum. Transcriptomics involves analysing the gene expression patterns in sorghum under various conditions. This knowledge is vital for developing crop varieties with enhanced stress tolerance. Proteomics enables the identification and quantification of the proteins present in sorghum. This approach helps in understanding the functional roles of specific proteins in response to stress and provides insights into metabolic pathways that contribute to resilience and grain production. Metabolomics studies the small molecules, or metabolites, produced by sorghum, provides information about the metabolic pathways that are activated or modified in response to environmental stress. This knowledge can be used to engineer sorghum varieties with improved metabolic efficiency, ultimately leading to better crop yields. In this review, we have focused on various multi-omics approaches, gene expression analysis, and different pathways for the improvement of Sorghum. Applying omics approaches to sorghum research allows for a holistic understanding of its genome function. This knowledge is invaluable for addressing challenges such as climate change, resource limitations, and the need for sustainable agriculture.
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Affiliation(s)
- Ananya Mukherjee
- School of Biotechnology, Faculty of Applied Sciences and Biotechnology, Shoolini University, Solan, Himachal Pradesh, 173229, India
| | - Uma Maheshwari
- School of Biotechnology, Faculty of Applied Sciences and Biotechnology, Shoolini University, Solan, Himachal Pradesh, 173229, India
| | - Vishal Sharma
- School of Biotechnology, Faculty of Applied Sciences and Biotechnology, Shoolini University, Solan, Himachal Pradesh, 173229, India.
| | - Ankush Sharma
- Plant Genome Mapping Laboratory, Crop and Soil Science, University of Georgia, 111 Riverbend Road, Athens, GA, 30605, USA
| | - Satish Kumar
- Department of Food Science and Technology, Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, HP, 173230, India
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3
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Sharma D, Kumari A, Sharma P, Singh A, Sharma A, Mir ZA, Kumar U, Jan S, Parthiban M, Mir RR, Bhati P, Pradhan AK, Yadav A, Mishra DC, Budhlakoti N, Yadav MC, Gaikwad KB, Singh AK, Singh GP, Kumar S. Meta-QTL analysis in wheat: progress, challenges and opportunities. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:247. [PMID: 37975911 DOI: 10.1007/s00122-023-04490-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 10/16/2023] [Indexed: 11/19/2023]
Abstract
Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.
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Affiliation(s)
- Divya Sharma
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Anita Kumari
- Department of Botany, University of Delhi, Delhi, India
| | - Priya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Anupma Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Anshu Sharma
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Zahoor Ahmad Mir
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Uttam Kumar
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Sofora Jan
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - M Parthiban
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - Reyazul Rouf Mir
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - Pradeep Bhati
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Anjan Kumar Pradhan
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Aakash Yadav
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | | | - Neeraj Budhlakoti
- ICAR- Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mahesh C Yadav
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Kiran B Gaikwad
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
| | - Amit Kumar Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | | | - Sundeep Kumar
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
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4
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Leung HS, Chan LY, Law CH, Li MW, Lam HM. Twenty years of mining salt tolerance genes in soybean. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:45. [PMID: 37313223 PMCID: PMC10248715 DOI: 10.1007/s11032-023-01383-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 04/12/2023] [Indexed: 06/15/2023]
Abstract
Current combined challenges of rising food demand, climate change and farmland degradation exert enormous pressure on agricultural production. Worldwide soil salinization, in particular, necessitates the development of salt-tolerant crops. Soybean, being a globally important produce, has its genetic resources increasingly examined to facilitate crop improvement based on functional genomics. In response to the multifaceted physiological challenge that salt stress imposes, soybean has evolved an array of defences against salinity. These include maintaining cell homeostasis by ion transportation, osmoregulation, and restoring oxidative balance. Other adaptations include cell wall alterations, transcriptomic reprogramming, and efficient signal transduction for detecting and responding to salt stress. Here, we reviewed functionally verified genes that underly different salt tolerance mechanisms employed by soybean in the past two decades, and discussed the strategy in selecting salt tolerance genes for crop improvement. Future studies could adopt an integrated multi-omic approach in characterizing soybean salt tolerance adaptations and put our existing knowledge into practice via omic-assisted breeding and gene editing. This review serves as a guide and inspiration for crop developers in enhancing soybean tolerance against abiotic stresses, thereby fulfilling the role of science in solving real-life problems. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01383-3.
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Affiliation(s)
- Hoi-Sze Leung
- Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR People’s Republic of China
| | - Long-Yiu Chan
- Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR People’s Republic of China
| | - Cheuk-Hin Law
- Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR People’s Republic of China
| | - Man-Wah Li
- Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR People’s Republic of China
| | - Hon-Ming Lam
- Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR People’s Republic of China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518000 People’s Republic of China
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5
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Hashem M, Sandhu KS, Ismail SM, Börner A, Sallam A. Validation and marker-assisted selection of DArT-genomic regions associated with wheat yield-related traits under normal and drought conditions. Front Genet 2023; 14:1195566. [PMID: 37292145 PMCID: PMC10245129 DOI: 10.3389/fgene.2023.1195566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/10/2023] [Indexed: 06/10/2023] Open
Abstract
Quantitative trait loci (QTL) is one of the most important steps in marker-assisted selection. Few studies have validated quantitative trait loci for marker-assisted selection of yield traits under drought stress conditions in wheat. A set of 138 highly diverse wheat genotypes were tested under normal and drought stress conditions for 2 years. Plant height, heading date, spike length, grain number per spike, grain yield per spike, and 1000-kernel weight were scored. High genetic variation was found among genotypes in all traits scored under both conditions in the 2 years. The same panel was genotyped using a diversity-array technology (DArT) marker, and a genome-wide association study was performed to find alleles associated with yield traits under all conditions. A set of 191 significant DArT markers were identified in this study. The results of the genome-wide association study revealed eight common markers in wheat that were significantly associated with the same traits under both conditions in the 2 years. Out of the eight markers, seven were located on the D genome except one marker. Four validated markers were located on the 3D chromosome and found in complete linkage disequilibrium. Moreover, these four markers were significantly associated with the heading date under both conditions and the grain yield per spike under drought stress condition in the 2 years. This high-linkage disequilibrium genomic region was located within the TraesCS3D02G002400 gene model. Furthermore, of the eight validated markers, seven were previously reported to be associated with yield traits under normal and drought conditions. The results of this study provided very promising DArT markers that can be used for marker-assisted selection to genetically improve yield traits under normal and drought conditions.
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Affiliation(s)
- Mostafa Hashem
- Department of Genetics, Faculty of Agriculture, Assiut University, Assuit, Egypt
| | | | - Saleh M. Ismail
- Soils and Water Department, Faculty of Agriculture, Assiut University, Assiut, Egypt
| | - Andreas Börner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Ahmed Sallam
- Department of Genetics, Faculty of Agriculture, Assiut University, Assuit, Egypt
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
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6
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Effah Z, Li L, Xie J, Karikari B, Xu A, Wang L, Du C, Duku Boamah E, Adingo S, Zeng M. Widely untargeted metabolomic profiling unearths metabolites and pathways involved in leaf senescence and N remobilization in spring-cultivated wheat under different N regimes. FRONTIERS IN PLANT SCIENCE 2023; 14:1166933. [PMID: 37260937 PMCID: PMC10227437 DOI: 10.3389/fpls.2023.1166933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 03/24/2023] [Indexed: 06/02/2023]
Abstract
Progression of leaf senescence consists of both degenerative and nutrient recycling processes in crops including wheat. However, the levels of metabolites in flag leaves in spring-cultivated wheat, as well as biosynthetic pathways involved under different nitrogen fertilization regimes, are largely unknown. Therefore, the present study employed a widely untargeted metabolomic profiling strategy to identify metabolites and biosynthetic pathways that could be used in a wheat improvement program aimed at manipulating the rate and onset of senescence by handling spring wheat (Dingxi 38) flag leaves sampled from no-, low-, and high-nitrogen (N) conditions (designated Groups 1, 2, and 3, respectively) across three sampling times: anthesis, grain filling, and end grain filling stages. Through ultrahigh-performance liquid chromatography-tandem mass spectrometry, a total of 826 metabolites comprising 107 flavonoids, 51 phenol lipids, 37 fatty acyls, 37 organooxygen compounds, 31 steroids and steroid derivatives, 18 phenols, and several unknown compounds were detected. Upon the application of the stringent screening criteria for differentially accumulated metabolites (DAMs), 28 and 23 metabolites were differentially accumulated in Group 1_vs_Group 2 and Group 1_vs_Group 3, respectively. From these, 1-O-Caffeoylglucose, Rhoifolin, Eurycomalactone;Ingenol, 4-Methoxyphenyl beta-D-glucopyranoside, and Baldrinal were detected as core conserved DAMs among the three groups with all accumulated higher in Group 1 than in the other two groups. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that tropane, piperidine, and pyridine alkaloid biosynthesis; acarbose and validamycin biosynthesis; lysine degradation; and biosynthesis of alkaloids derived from ornithine, lysine, and nicotinic acid pathways were the most significantly (p < 0.05) enriched in Group 1_vs_Group 2, while flavone and flavonol as well as anthocyanins biosynthetic pathways were the most significantly (p < 0.05) enriched in Group 1_vs_Group 3. The results from this study provide a foundation for the manipulation of the onset and rate of leaf senescence and N remobilization in wheat.
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Affiliation(s)
- Zechariah Effah
- Department of Crop Science, State Key Laboratory of Arid Land Crop Science, Lanzhou, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
- Department of Plant Genetic Diversity, Council for Scientific and Industrial Research (CSIR)-Plant Genetic Resources Research Institute, Bunso, Ghana
| | - Lingling Li
- Department of Crop Science, State Key Laboratory of Arid Land Crop Science, Lanzhou, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Junhong Xie
- Department of Crop Science, State Key Laboratory of Arid Land Crop Science, Lanzhou, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Benjamin Karikari
- Department of Agricultural Biotechnology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Aixia Xu
- Department of Crop Science, State Key Laboratory of Arid Land Crop Science, Lanzhou, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Linlin Wang
- Department of Crop Science, State Key Laboratory of Arid Land Crop Science, Lanzhou, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Changliang Du
- Department of Crop Science, State Key Laboratory of Arid Land Crop Science, Lanzhou, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Emmanuel Duku Boamah
- Department of Plant Genetic Diversity, Council for Scientific and Industrial Research (CSIR)-Plant Genetic Resources Research Institute, Bunso, Ghana
| | - Samuel Adingo
- College of Forestry, Gansu Agricultural University, Lanzhou, China
| | - Min Zeng
- Department of Crop Science, State Key Laboratory of Arid Land Crop Science, Lanzhou, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
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7
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Baloch FS, Altaf MT, Liaqat W, Bedir M, Nadeem MA, Cömertpay G, Çoban N, Habyarimana E, Barutçular C, Cerit I, Ludidi N, Karaköy T, Aasim M, Chung YS, Nawaz MA, Hatipoğlu R, Kökten K, Sun HJ. Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding. Front Genet 2023; 14:1150616. [PMID: 37252661 PMCID: PMC10213934 DOI: 10.3389/fgene.2023.1150616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 04/17/2023] [Indexed: 05/31/2023] Open
Abstract
Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.
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Affiliation(s)
- Faheem Shehzad Baloch
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Muhammad Tanveer Altaf
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Waqas Liaqat
- Department of Field Crops, Faculty of Agriculture, Çukurova University, Adana, Türkiye
| | - Mehmet Bedir
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Muhammad Azhar Nadeem
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Gönül Cömertpay
- Eastern Mediterranean Agricultural Research Institute, Adana, Türkiye
| | - Nergiz Çoban
- Eastern Mediterranean Agricultural Research Institute, Adana, Türkiye
| | - Ephrem Habyarimana
- International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, Telangana, India
| | - Celaleddin Barutçular
- Department of Field Crops, Faculty of Agriculture, Çukurova University, Adana, Türkiye
| | - Ibrahim Cerit
- Eastern Mediterranean Agricultural Research Institute, Adana, Türkiye
| | - Ndomelele Ludidi
- Plant Stress Tolerance Laboratory, Department of Biotechnology, University of the Western Cape, Bellville, South Africa
- DSI-NRF Centre of Excellence in Food Security, University of the Western Cape, Bellville, South Africa
| | - Tolga Karaköy
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Muhammad Aasim
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Yong Suk Chung
- Department of Plant Resources and Environment, Jeju National University, Jeju, Republic of Korea
| | | | - Rüştü Hatipoğlu
- Kırşehir Ahi Evran Universitesi Ziraat Fakultesi Tarla Bitkileri Bolumu, Kırşehir, Türkiye
| | - Kağan Kökten
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye
| | - Hyeon-Jin Sun
- Subtropical Horticulture Research Institute, Jeju National University, Jeju, Republic of Korea
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Bisht A, Saini DK, Kaur B, Batra R, Kaur S, Kaur I, Jindal S, Malik P, Sandhu PK, Kaur A, Gill BS, Wani SH, Kaur B, Mir RR, Sandhu KS, Siddique KHM. Multi-omics assisted breeding for biotic stress resistance in soybean. Mol Biol Rep 2023; 50:3787-3814. [PMID: 36692674 DOI: 10.1007/s11033-023-08260-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023]
Abstract
Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.
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Affiliation(s)
- Ashita Bisht
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
- CSK Himachal Pradesh Krishi Vishvavidyalaya, Highland Agricultural Research and Extension Centre, 175142, Kukumseri, Lahaul and Spiti, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India.
| | - Baljeet Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Ritu Batra
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, 25004, Meerut, India
| | - Sandeep Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Ishveen Kaur
- Agriculture, Environmental and Sustainability Sciences, College of sciences, University of Texas Rio Grande Valley, 78539, Edinburg, TX, USA
| | - Suruchi Jindal
- Division of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, India
| | - Palvi Malik
- , Gurdev Singh Khush Institute of Genetics, Plant Breeding and Biotechnology, Punjab Agricultural University,, 141004, Ludhiana, India
| | - Pawanjit Kaur Sandhu
- Department of Chemistry, University of British Columbia, V1V 1V7, Okanagan, Kelowna, Canada
| | - Amandeep Kaur
- Division of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, India
| | - Balwinder Singh Gill
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Shabir Hussain Wani
- MRCFC Khudwani, Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir, Shalimar, India
| | - Balwinder Kaur
- Department of Entomology, UF/IFAS Research and Education Center, 33430, Belle Glade, Florida, USA
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, 193201, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, 99163, Pullman, WA, USA.
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, 6001, Perth, WA, Australia.
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9
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Zuluaga DL, Blanco E, Mangini G, Sonnante G, Curci PL. A Survey of the Transcriptomic Resources in Durum Wheat: Stress Responses, Data Integration and Exploitation. PLANTS (BASEL, SWITZERLAND) 2023; 12:1267. [PMID: 36986956 PMCID: PMC10056183 DOI: 10.3390/plants12061267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/28/2023] [Accepted: 03/04/2023] [Indexed: 06/19/2023]
Abstract
Durum wheat (Triticum turgidum subsp. durum (Desf.) Husn.) is an allotetraploid cereal crop of worldwide importance, given its use for making pasta, couscous, and bulgur. Under climate change scenarios, abiotic (e.g., high and low temperatures, salinity, drought) and biotic (mainly exemplified by fungal pathogens) stresses represent a significant limit for durum cultivation because they can severely affect yield and grain quality. The advent of next-generation sequencing technologies has brought a huge development in transcriptomic resources with many relevant datasets now available for durum wheat, at various anatomical levels, also focusing on phenological phases and environmental conditions. In this review, we cover all the transcriptomic resources generated on durum wheat to date and focus on the corresponding scientific insights gained into abiotic and biotic stress responses. We describe relevant databases, tools and approaches, including connections with other "omics" that could assist data integration for candidate gene discovery for bio-agronomical traits. The biological knowledge summarized here will ultimately help in accelerating durum wheat breeding.
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Singh J, Chhabra B, Raza A, Yang SH, Sandhu KS. Important wheat diseases in the US and their management in the 21st century. FRONTIERS IN PLANT SCIENCE 2023; 13:1010191. [PMID: 36714765 PMCID: PMC9877539 DOI: 10.3389/fpls.2022.1010191] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/28/2022] [Indexed: 05/27/2023]
Abstract
Wheat is a crop of historical significance, as it marks the turning point of human civilization 10,000 years ago with its domestication. Due to the rapid increase in population, wheat production needs to be increased by 50% by 2050 and this growth will be mainly based on yield increases, as there is strong competition for scarce productive arable land from other sectors. This increasing demand can be further achieved using sustainable approaches including integrated disease pest management, adaption to warmer climates, less use of water resources and increased frequency of abiotic stress tolerances. Out of 200 diseases of wheat, 50 cause economic losses and are widely distributed. Each year, about 20% of wheat is lost due to diseases. Some major wheat diseases are rusts, smut, tan spot, spot blotch, fusarium head blight, common root rot, septoria blotch, powdery mildew, blast, and several viral, nematode, and bacterial diseases. These diseases badly impact the yield and cause mortality of the plants. This review focuses on important diseases of the wheat present in the United States, with comprehensive information of causal organism, economic damage, symptoms and host range, favorable conditions, and disease management strategies. Furthermore, major genetic and breeding efforts to control and manage these diseases are discussed. A detailed description of all the QTLs, genes reported and cloned for these diseases are provided in this review. This study will be of utmost importance to wheat breeding programs throughout the world to breed for resistance under changing environmental conditions.
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Affiliation(s)
- Jagdeep Singh
- Department of Crop, Soil & Environmental Sciences, Auburn University, Auburn, AL, United States
| | - Bhavit Chhabra
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, United States
| | - Ali Raza
- College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Seung Hwan Yang
- Department of Integrative Biotechnology, Chonnam National University, Yeosu, Republic of Korea
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11
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Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops. Int J Mol Sci 2022; 23:ijms231912053. [PMID: 36233352 PMCID: PMC9570234 DOI: 10.3390/ijms231912053] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/02/2022] [Accepted: 10/06/2022] [Indexed: 11/16/2022] Open
Abstract
The major challenges that agriculture is facing in the twenty-first century are increasing droughts, water scarcity, flooding, poorer soils, and extreme temperatures due to climate change. However, most crops are not tolerant to extreme climatic environments. The aim in the near future, in a world with hunger and an increasing population, is to breed and/or engineer crops to tolerate abiotic stress with a higher yield. Some crop varieties display a certain degree of tolerance, which has been exploited by plant breeders to develop varieties that thrive under stress conditions. Moreover, a long list of genes involved in abiotic stress tolerance have been identified and characterized by molecular techniques and overexpressed individually in plant transformation experiments. Nevertheless, stress tolerance phenotypes are polygenetic traits, which current genomic tools are dissecting to exploit their use by accelerating genetic introgression using molecular markers or site-directed mutagenesis such as CRISPR-Cas9. In this review, we describe plant mechanisms to sense and tolerate adverse climate conditions and examine and discuss classic and new molecular tools to select and improve abiotic stress tolerance in major crops.
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Farooqi MQU, Nawaz G, Wani SH, Choudhary JR, Rana M, Sah RP, Afzal M, Zahra Z, Ganie SA, Razzaq A, Reyes VP, Mahmoud EA, Elansary HO, El-Abedin TKZ, Siddique KHM. Recent developments in multi-omics and breeding strategies for abiotic stress tolerance in maize ( Zea mays L.). FRONTIERS IN PLANT SCIENCE 2022; 13:965878. [PMID: 36212378 PMCID: PMC9538355 DOI: 10.3389/fpls.2022.965878] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 08/23/2022] [Indexed: 06/12/2023]
Abstract
High-throughput sequencing technologies (HSTs) have revolutionized crop breeding. The advent of these technologies has enabled the identification of beneficial quantitative trait loci (QTL), genes, and alleles for crop improvement. Climate change have made a significant effect on the global maize yield. To date, the well-known omic approaches such as genomics, transcriptomics, proteomics, and metabolomics are being incorporated in maize breeding studies. These approaches have identified novel biological markers that are being utilized for maize improvement against various abiotic stresses. This review discusses the current information on the morpho-physiological and molecular mechanism of abiotic stress tolerance in maize. The utilization of omics approaches to improve abiotic stress tolerance in maize is highlighted. As compared to single approach, the integration of multi-omics offers a great potential in addressing the challenges of abiotic stresses of maize productivity.
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Affiliation(s)
| | - Ghazala Nawaz
- Department of Botanical and Environmental Sciences, Kohat University of Science and Technology, Kohat, Pakistan
| | - Shabir Hussain Wani
- Mountain Research Centre for Field Crops, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Jeet Ram Choudhary
- Division of Genetics, Indian Agricultural Research Institute, New Delhi, India
| | - Maneet Rana
- Division of Crop Improvement, ICAR-Indian Grassland and Fodder Research Institute, Jhansi, India
| | - Rameswar Prasad Sah
- Division of Crop Improvement, ICAR-National Rice Research Institute, Cuttack, India
| | - Muhammad Afzal
- College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Zahra Zahra
- Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA, United States
| | | | - Ali Razzaq
- Agronomy Department, University of Florida, Gainesville, FL, United States
| | | | - Eman A. Mahmoud
- Department of Food Industries, Faculty of Agriculture, Damietta University, Damietta, Egypt
| | - Hosam O. Elansary
- Plant Production Department, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia
- Floriculture, Ornamental Horticulture, and Garden Design Department, Faculty of Agriculture (El-Shatby), Alexandria University, Alexandria, Egypt
- Department of Geography, Environmental Management, and Energy Studies, University of Johannesburg, Johannesburg, South Africa
| | - Tarek K. Zin El-Abedin
- Department of Agriculture & Biosystems Engineering, Faculty of Agriculture (El-Shatby), Alexandria University, Alexandria, Egypt
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13
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 PMCID: PMC9372038 DOI: 10.1038/s41598-022-18149-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 12/03/2022] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 DOI: 10.1101/2022.06.24.497482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 05/20/2023] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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15
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Sohi HS, Gill MIS, Chhuneja P, Arora NK, Maan SS, Singh J. Construction of Genetic Linkage Map and Mapping QTL Specific to Leaf Anthocyanin Colouration in Mapping Population 'Allahabad Safeda' × 'Purple Guava (Local)' of Guava ( Psidium guajava L.). PLANTS (BASEL, SWITZERLAND) 2022; 11:2014. [PMID: 35956491 PMCID: PMC9370526 DOI: 10.3390/plants11152014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 07/28/2022] [Accepted: 07/29/2022] [Indexed: 06/15/2023]
Abstract
In the present investigation, F1 hybrids were developed in guava (Psidium guajava L.) by crossing high leaf-anthocyanin reflective-index (ARI1) content cultivars purple guava (local) 'PG', 'CISH G-1' and low leaf-ARI1 content cultivar Seedless 'SL' with Allahabad Safeda 'AS'. On the basis of phenotypic observations, high ARI1 content was observed in the cross 'AS' × 'PG' (0.214). Further, an SSR-markers-based genetic linkage map was developed from a mapping population of 238 F1 individuals derived from cross 'AS' × 'PG'. The linkage map comprised 11 linkage groups (LGs), spanning 1601.7 cM with an average marker interval distance of 29.61 cM between adjacent markers. Five anthocyanin-content related gene-specific markers from apple were tested for parental polymorphism in the genotypes 'AS' and 'PG'. Subsequently, a marker, viz., 'MdMYB10F1', revealed a strong association with leaf anthocyanin content in the guava mapping population. QTL (qARI-6-1) on LG6 explains much of the variation (PVE = 11.51% with LOD = 4.67) in levels of leaf anthocyanin colouration. This is the first report of amplification/utilization of apple anthocyanin-related genes in guava. The genotypic data generated from the genetic map can be further exploited in future for the enrichment of linkage maps and for identification of complex quantitative trait loci (QTLs) governing economically important fruit quality traits in guava.
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Affiliation(s)
- Harjot Singh Sohi
- Department of Fruit Science, College of Horticulture and Forestry Punjab Agricultural University, Ludhiana 141004, India; (M.I.S.G.); (N.K.A.); (S.S.M.)
| | - Manav Indra Singh Gill
- Department of Fruit Science, College of Horticulture and Forestry Punjab Agricultural University, Ludhiana 141004, India; (M.I.S.G.); (N.K.A.); (S.S.M.)
| | - Parveen Chhuneja
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141004, India;
| | - Naresh Kumar Arora
- Department of Fruit Science, College of Horticulture and Forestry Punjab Agricultural University, Ludhiana 141004, India; (M.I.S.G.); (N.K.A.); (S.S.M.)
| | - Sukhjinder Singh Maan
- Department of Fruit Science, College of Horticulture and Forestry Punjab Agricultural University, Ludhiana 141004, India; (M.I.S.G.); (N.K.A.); (S.S.M.)
| | - Jagmohan Singh
- Division of Plant Pathology, ICAR-Indian Agricultural Research Institute, New Delhi 110012, India;
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Comparison of Presowing Wheat Treatments by Low-Temperature Plasma, Electric Field, Cold Hardening, and Action of Tebuconazole-Based Disinfectant. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12136447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
This work compares the presowing treatment of winter wheat seeds with a low-temperature plasma, a constant high-voltage electric field, a plant protection disinfectant, and cold hardening on the resistance of seedlings to freezing and their morphophysiological characteristics at the initial stage of germination. Various treatment combinations were considered, including the effect of the disinfectant jointly with low-temperature plasma treatment. The greatest stimulating effect from the point of view of seedlings’ morphophysiological characteristics was achieved when seeds were cold-hardened. The action of low-temperature plasma is noticeable up to the third day of germination. The treatment with the low-temperature plasma of seeds pretreated and not-pretreated with the disinfectant had a similar effect on the morphophysiological characteristics of seedlings. The plasma treatment and the electric field were combined with each other, i.e., the plasma treatment effects were added to the electric field effects. Resistance to low temperatures was increased with the hardening of seeds treated with the electric field and the disinfectant. Resistance to low temperatures was reduced when treated with the electric field and/or low-temperature plasma after being treated with the disinfectant.
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Gill T, Gill SK, Saini DK, Chopra Y, de Koff JP, Sandhu KS. A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping. PHENOMICS (CHAM, SWITZERLAND) 2022; 2:156-183. [PMID: 36939773 PMCID: PMC9590503 DOI: 10.1007/s43657-022-00048-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 01/29/2022] [Accepted: 02/11/2022] [Indexed: 02/04/2023]
Abstract
During the last decade, there has been rapid adoption of ground and aerial platforms with multiple sensors for phenotyping various biotic and abiotic stresses throughout the developmental stages of the crop plant. High throughput phenotyping (HTP) involves the application of these tools to phenotype the plants and can vary from ground-based imaging to aerial phenotyping to remote sensing. Adoption of these HTP tools has tried to reduce the phenotyping bottleneck in breeding programs and help to increase the pace of genetic gain. More specifically, several root phenotyping tools are discussed to study the plant's hidden half and an area long neglected. However, the use of these HTP technologies produces big data sets that impede the inference from those datasets. Machine learning and deep learning provide an alternative opportunity for the extraction of useful information for making conclusions. These are interdisciplinary approaches for data analysis using probability, statistics, classification, regression, decision theory, data visualization, and neural networks to relate information extracted with the phenotypes obtained. These techniques use feature extraction, identification, classification, and prediction criteria to identify pertinent data for use in plant breeding and pathology activities. This review focuses on the recent findings where machine learning and deep learning approaches have been used for plant stress phenotyping with data being collected using various HTP platforms. We have provided a comprehensive overview of different machine learning and deep learning tools available with their potential advantages and pitfalls. Overall, this review provides an avenue for studying various HTP platforms with particular emphasis on using the machine learning and deep learning tools for drawing legitimate conclusions. Finally, we propose the conceptual challenges being faced and provide insights on future perspectives for managing those issues.
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Affiliation(s)
- Taqdeer Gill
- grid.280741.80000 0001 2284 9820Department of Agricultural and Environmental Sciences, Tennessee State University, Nashville, TN 37209 USA
| | - Simranveer K. Gill
- grid.412577.20000 0001 2176 2352College of Agriculture, Punjab Agricultural University, Ludhiana, Punjab 141004 India
| | - Dinesh K. Saini
- grid.412577.20000 0001 2176 2352Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab 141004 India
| | - Yuvraj Chopra
- grid.412577.20000 0001 2176 2352College of Agriculture, Punjab Agricultural University, Ludhiana, Punjab 141004 India
| | - Jason P. de Koff
- grid.280741.80000 0001 2284 9820Department of Agricultural and Environmental Sciences, Tennessee State University, Nashville, TN 37209 USA
| | - Karansher S. Sandhu
- grid.30064.310000 0001 2157 6568Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99163 USA
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18
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Wheat Proteomics for Abiotic Stress Tolerance and Root System Architecture: Current Status and Future Prospects. Proteomes 2022; 10:proteomes10020017. [PMID: 35645375 PMCID: PMC9150004 DOI: 10.3390/proteomes10020017] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/03/2022] [Accepted: 05/11/2022] [Indexed: 02/06/2023] Open
Abstract
Wheat is an important staple cereal for global food security. However, climate change is hampering wheat production due to abiotic stresses, such as heat, salinity, and drought. Besides shoot architectural traits, improving root system architecture (RSA) traits have the potential to improve yields under normal and stressed environments. RSA growth and development and other stress responses involve the expression of proteins encoded by the trait controlling gene/genes. Hence, mining the key proteins associated with abiotic stress responses and RSA is important for improving sustainable yields in wheat. Proteomic studies in wheat started in the early 21st century using the two-dimensional (2-DE) gel technique and have extensively improved over time with advancements in mass spectrometry. The availability of the wheat reference genome has allowed the exploration of proteomics to identify differentially expressed or abundant proteins (DEPs or DAPs) for abiotic stress tolerance and RSA improvement. Proteomics contributed significantly to identifying key proteins imparting abiotic stress tolerance, primarily related to photosynthesis, protein synthesis, carbon metabolism, redox homeostasis, defense response, energy metabolism and signal transduction. However, the use of proteomics to improve RSA traits in wheat is in its infancy. Proteins related to cell wall biogenesis, carbohydrate metabolism, brassinosteroid biosynthesis, and transportation are involved in the growth and development of several RSA traits. This review covers advances in quantification techniques of proteomics, progress in identifying DEPs and/or DAPs for heat, salinity, and drought stresses, and RSA traits, and the limitations and future directions for harnessing proteomics in wheat improvement.
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Adverse Effects of Arsenic Uptake in Rice Metabolome and Lipidome Revealed by Untargeted Liquid Chromatography Coupled to Mass Spectrometry (LC-MS) and Regions of Interest Multivariate Curve Resolution. SEPARATIONS 2022. [DOI: 10.3390/separations9030079] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Rice crops are especially vulnerable to arsenic exposure compared to other cereal crops because flooding growing conditions facilitates its uptake. Besides, there are still many unknown questions about arsenic’s mode of action in rice. Here, we apply two untargeted approaches using liquid chromatography coupled to mass spectrometry (LC-MS) to unravel the effects on rice lipidome and metabolome in the early stages of growth. The exposure is evaluated through two different treatments, watering with arsenic-contaminated water and soil containing arsenic. The combination of regions of interest (ROI) and multivariate curve resolution (MCR) strategies in the ROIMCR data analyses workflow is proposed and complemented with other multivariate analyses such as partial least square discriminant analysis (PLS-DA) for the identification of potential markers of arsenic exposure and toxicity effects. The results of this study showed that rice metabolome (and lipidome) in root tissues seemed to be more affected by the watering and soil treatment. In contrast, aerial tissues alterations were accentuated by the arsenic dose, rather than with the watering and soil treatment itself. Up to a hundred lipids and 40 metabolites were significantly altered due to arsenic exposure. Major metabolic alterations were found in glycerophospholipids, glycerolipids, and amino acid-related pathways.
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Saini DK, Chahal A, Pal N, Srivastava P, Gupta PK. Meta-analysis reveals consensus genomic regions associated with multiple disease resistance in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:11. [PMID: 37309411 PMCID: PMC10248701 DOI: 10.1007/s11032-022-01282-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 02/07/2022] [Indexed: 06/14/2023]
Abstract
In wheat, meta-QTLs (MQTLs) and candidate genes (CGs) were identified for multiple disease resistance (MDR). For this purpose, information was collected from 58 studies for mapping QTLs for resistance to one or more of the five diseases. As many as 493 QTLs were available from these studies, which were distributed in five diseases as follows: septoria tritici blotch (STB) 126 QTLs; septoria nodorum blotch (SNB), 103 QTLs; fusarium head blight (FHB), 184 QTLs; karnal bunt (KB), 66 QTLs; and loose smut (LS), 14 QTLs. Of these 493 QTLs, only 291 QTLs could be projected onto a consensus genetic map, giving 63 MQTLs. The CI of the MQTLs ranged from 0.04 to 15.31 cM with an average of 3.09 cM per MQTL. This is a ~ 4.39 fold reduction from the CI of QTLs, which ranged from 0 to 197.6 cM, with a mean of 13.57 cM. Of 63 MQTLs, 60 were anchored to the reference physical map of wheat (the physical interval of these MQTLs ranged from 0.30 to 726.01 Mb with an average of 74.09 Mb). Thirty-eight (38) of these MQTLs were verified using marker-trait associations (MTAs) derived from genome-wide association studies. As many as 874 CGs were also identified which were further investigated for differential expression using data from five transcriptome studies, resulting in 194 differentially expressed candidate genes (DECGs). Among the DECGs, 85 genes had functions previously reported to be associated with disease resistance. These results should prove useful for fine mapping and cloning of MDR genes and marker-assisted breeding. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01282-z.
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Affiliation(s)
- Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab-141004 India
| | - Amneek Chahal
- College of Agriculture, Punjab Agricultural University, Ludhiana, Punjab-141004 India
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttrakhand-263145 India
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab-141004 India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
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21
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Sandhu KS, Patil SS, Aoun M, Carter AH. Multi-Trait Multi-Environment Genomic Prediction for End-Use Quality Traits in Winter Wheat. Front Genet 2022; 13:831020. [PMID: 35173770 PMCID: PMC8841657 DOI: 10.3389/fgene.2022.831020] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/06/2022] [Indexed: 11/13/2022] Open
Abstract
Soft white wheat is a wheat class used in foreign and domestic markets to make various end products requiring specific quality attributes. Due to associated cost, time, and amount of seed needed, phenotyping for the end-use quality trait is delayed until later generations. Previously, we explored the potential of using genomic selection (GS) for selecting superior genotypes earlier in the breeding program. Breeders typically measure multiple traits across various locations, and it opens up the avenue for exploring multi-trait-based GS models. This study's main objective was to explore the potential of using multi-trait GS models for predicting seven different end-use quality traits using cross-validation, independent prediction, and across-location predictions in a wheat breeding program. The population used consisted of 666 soft white wheat genotypes planted for 5 years at two locations in Washington, United States. We optimized and compared the performances of four uni-trait- and multi-trait-based GS models, namely, Bayes B, genomic best linear unbiased prediction (GBLUP), multilayer perceptron (MLP), and random forests. The prediction accuracies for multi-trait GS models were 5.5 and 7.9% superior to uni-trait models for the within-environment and across-location predictions. Multi-trait machine and deep learning models performed superior to GBLUP and Bayes B for across-location predictions, but their advantages diminished when the genotype by environment component was included in the model. The highest improvement in prediction accuracy, that is, 35% was obtained for flour protein content with the multi-trait MLP model. This study showed the potential of using multi-trait-based GS models to enhance prediction accuracy by using information from previously phenotyped traits. It would assist in speeding up the breeding cycle time in a cost-friendly manner.
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Affiliation(s)
- Karansher S. Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
| | - Shruti Sunil Patil
- School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, United States1
| | - Meriem Aoun
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
| | - Arron H. Carter
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
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22
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Sandhu KS, Merrick LF, Sankaran S, Zhang Z, Carter AH. Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs. Front Genet 2022. [PMCID: PMC8814369 DOI: 10.3389/fgene.2021.829131] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The last decade witnessed an unprecedented increase in the adoption of genomic selection (GS) and phenomics tools in plant breeding programs, especially in major cereal crops. GS has demonstrated the potential for selecting superior genotypes with high precision and accelerating the breeding cycle. Phenomics is a rapidly advancing domain to alleviate phenotyping bottlenecks and explores new large-scale phenotyping and data acquisition methods. In this review, we discuss the lesson learned from GS and phenomics in six self-pollinated crops, primarily focusing on rice, wheat, soybean, common bean, chickpea, and groundnut, and their implementation schemes are discussed after assessing their impact in the breeding programs. Here, the status of the adoption of genomics and phenomics is provided for those crops, with a complete GS overview. GS’s progress until 2020 is discussed in detail, and relevant information and links to the source codes are provided for implementing this technology into plant breeding programs, with most of the examples from wheat breeding programs. Detailed information about various phenotyping tools is provided to strengthen the field of phenomics for a plant breeder in the coming years. Finally, we highlight the benefits of merging genomic selection, phenomics, and machine and deep learning that have resulted in extraordinary results during recent years in wheat, rice, and soybean. Hence, there is a potential for adopting these technologies into crops like the common bean, chickpea, and groundnut. The adoption of phenomics and GS into different breeding programs will accelerate genetic gain that would create an impact on food security, realizing the need to feed an ever-growing population.
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Affiliation(s)
- Karansher S. Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
- *Correspondence: Karansher S. Sandhu,
| | - Lance F. Merrick
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
| | - Sindhuja Sankaran
- Department of Biological System Engineering, Washington State University, Pullman, WA, United States
| | - Zhiwu Zhang
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
| | - Arron H. Carter
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
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23
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Saini DK, Chopra Y, Singh J, Sandhu KS, Kumar A, Bazzer S, Srivastava P. Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:1. [PMID: 37309486 PMCID: PMC10248672 DOI: 10.1007/s11032-021-01272-7] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 12/10/2021] [Indexed: 06/14/2023]
Abstract
Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.
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Affiliation(s)
- Dinesh K. Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
| | - Yuvraj Chopra
- College of Agriculture, Punjab Agricultural University, Ludhiana, 141004 India
| | - Jagmohan Singh
- Division of Plant Pathology, Indian Agricultural Research Institute, New Delhi, 110012 India
| | - Karansher S. Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99163 USA
| | - Anand Kumar
- Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur, 202002 India
| | - Sumandeep Bazzer
- Division of Plant Sciences, University of Missouri, Columbia, MO 65211 USA
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
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