1
|
Yin Z, Huang W, Li K, Fernie AR, Yan S. Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024. [PMID: 38990529 DOI: 10.1111/tpj.16924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/24/2024] [Accepted: 07/01/2024] [Indexed: 07/12/2024]
Abstract
Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.
Collapse
Affiliation(s)
- Zhibin Yin
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
- Institute of Advanced Science Facilities, Shenzhen, 518107, Guangdong, China
| | - Wenjie Huang
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
| | - Kun Li
- Guangdong Key Laboratory of Crop Genetic Improvement, Crop Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
| | - Shijuan Yan
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
| |
Collapse
|
2
|
Ijaz A, Anwar Z, Ali A, Ditta A, Shani MY, Haidar S, Wang B, Fang L, Khan SMUD, Khan MKR. Unraveling the genetic and molecular basis of heat stress in cotton. Front Genet 2024; 15:1296622. [PMID: 38919956 PMCID: PMC11196824 DOI: 10.3389/fgene.2024.1296622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 04/29/2024] [Indexed: 06/27/2024] Open
Abstract
Human activities and climate change have resulted in frequent and intense weather fluctuations, leading to diverse abiotic stresses on crops which hampers greatly their metabolic activities. Heat stress, a prevalent abiotic factor, significantly influences cotton plant biological activities resulting in reducing yield and production. We must deepen our understanding of how plants respond to heat stress across various dimensions, encompassing genes, RNAs, proteins, metabolites for effective cotton breeding. Multi-omics methods, primarily genomics, transcriptomics, proteomics, metabolomics, and phenomics, proves instrumental in studying cotton's responses to abiotic stresses. Integrating genomics, transcriptomics, proteomics, and metabolomic is imperative for our better understanding regarding genetics and molecular basis of heat tolerance in cotton. The current review explores fundamental omics techniques, covering genomics, transcriptomics, proteomics, and metabolomics, to highlight the progress made in cotton omics research.
Collapse
Affiliation(s)
- Aqsa Ijaz
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Zunaira Anwar
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Ahmad Ali
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Allah Ditta
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
- Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad, Pakistan
| | - Muhammad Yousaf Shani
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Sajjad Haidar
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
- Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad, Pakistan
| | - Boahua Wang
- School of Life Sciences, Nantong University, Nantong, China
| | - Liu Fang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang, China
| | | | - Muhammad Kashif Riaz Khan
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
- Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad, Pakistan
| |
Collapse
|
3
|
Eftekhari M, Ma C, Orlov YL. Editorial: Applications of artificial intelligence, machine learning, and deep learning in plant breeding. FRONTIERS IN PLANT SCIENCE 2024; 15:1420938. [PMID: 38841285 PMCID: PMC11150839 DOI: 10.3389/fpls.2024.1420938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 04/26/2024] [Indexed: 06/07/2024]
Affiliation(s)
- Maliheh Eftekhari
- Department of Horticultural Sciences, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Chuang Ma
- State Key Laboratory of Crop Stress Resistance and High-Efficiency Production, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Xianyang, Shaanxi, China
- Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, Northwest A&F University, Xianyang, Shaanxi, China
| | - Yuriy L. Orlov
- Systems Biology Department, Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences (SB RAS), Novosibirsk, Russia
- Agrarian and Technological Institute, Patrice Lumumba Peoples’ Friendship University of Russia, Moscow, Russia
- Chair of Information and Internet Technologies, Institute of Biodesign and Complex System Modelling, Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), Moscow, Russia
| |
Collapse
|
4
|
Komatsu S, Smertenko A. Latest Review Papers in Molecular Plant Sciences 2023. Int J Mol Sci 2024; 25:5407. [PMID: 38791444 PMCID: PMC11121290 DOI: 10.3390/ijms25105407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 05/04/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
Success in sustaining food security in the face of global climate change depends on the multi-disciplinary efforts of plant science, physics, mathematics, and computer sciences, whereby each discipline contributes specific concepts, information, and tools [...].
Collapse
Affiliation(s)
- Setsuko Komatsu
- Faculty of Environmental and Information Sciences, Fukui University of Technology, Fukui 910-0028, Japan
| | - Andrei Smertenko
- Institute of Biological Chemistry, Washington State University, Washington, WA 99164-7411, USA
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Ramírez Gonzales LY, Cannarozzi G, Jäggi L, Assefa K, Chanyalew S, Dell'Acqua M, Tadele Z. The role of omics in improving the orphan crop tef. Trends Genet 2024; 40:449-461. [PMID: 38599921 DOI: 10.1016/j.tig.2024.03.003] [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: 12/15/2023] [Revised: 03/13/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024]
Abstract
Tef or teff [Eragrostis tef (Zucc.) Trotter] is a cereal crop indigenous to the Horn of Africa, where it is a staple food for a large population. The popularity of tef arises from its resilience to environmental stresses and its nutritional value. For many years, tef has been considered an orphan crop, but recent research initiatives from across the globe are helping to unravel its undisclosed potential. Advanced omics tools and techniques have been directed toward the exploration of tef's diversity with the aim of increasing its productivity. In this review, we report on the most recent advances in tef omics that brought the crop into the spotlight of international research.
Collapse
Affiliation(s)
| | - Gina Cannarozzi
- University of Bern, Institute of Plant Sciences, Altenbergrain 21, 3013 Bern, Switzerland
| | - Lea Jäggi
- University of Bern, Institute of Plant Sciences, Altenbergrain 21, 3013 Bern, Switzerland
| | - Kebebew Assefa
- Ethiopian Institute of Agricultural Research, Debre Zeit Agricultural Research Center, PO Box 32, Debre Zeit, Ethiopia
| | - Solomon Chanyalew
- Ethiopian Institute of Agricultural Research, Debre Zeit Agricultural Research Center, PO Box 32, Debre Zeit, Ethiopia
| | | | - Zerihun Tadele
- University of Bern, Institute of Plant Sciences, Altenbergrain 21, 3013 Bern, Switzerland.
| |
Collapse
|
7
|
Cao Y, Li X, Song H, Abdullah M, Manzoor MA. Editorial: Multi-omics and computational biology in horticultural plants: from genotype to phenotype, volume II. FRONTIERS IN PLANT SCIENCE 2024; 15:1368909. [PMID: 38371409 PMCID: PMC10869615 DOI: 10.3389/fpls.2024.1368909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 01/24/2024] [Indexed: 02/20/2024]
Affiliation(s)
- Yunpeng Cao
- School of Health and Nursing, Wuchang University of Technology, Wuhan, China
| | - Xiaoxu Li
- Beijing Life Science Academy, Beijing, China
- Technology Center, China Tobacco Hunan Industrial Co., Ltd., Changsha, China
| | - Hui Song
- Key Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Muhammad Abdullah
- Queensland Alliance of Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, Australia
| | - Muhammad Aamir Manzoor
- Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| |
Collapse
|
8
|
Janni M, Maestri E, Gullì M, Marmiroli M, Marmiroli N. Plant responses to climate change, how global warming may impact on food security: a critical review. FRONTIERS IN PLANT SCIENCE 2024; 14:1297569. [PMID: 38250438 PMCID: PMC10796516 DOI: 10.3389/fpls.2023.1297569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
Global agricultural production must double by 2050 to meet the demands of an increasing world human population but this challenge is further exacerbated by climate change. Environmental stress, heat, and drought are key drivers in food security and strongly impacts on crop productivity. Moreover, global warming is threatening the survival of many species including those which we rely on for food production, forcing migration of cultivation areas with further impoverishing of the environment and of the genetic variability of crop species with fall out effects on food security. This review considers the relationship of climatic changes and their bearing on sustainability of natural and agricultural ecosystems, as well as the role of omics-technologies, genomics, proteomics, metabolomics, phenomics and ionomics. The use of resource saving technologies such as precision agriculture and new fertilization technologies are discussed with a focus on their use in breeding plants with higher tolerance and adaptability and as mitigation tools for global warming and climate changes. Nevertheless, plants are exposed to multiple stresses. This study lays the basis for the proposition of a novel research paradigm which is referred to a holistic approach and that went beyond the exclusive concept of crop yield, but that included sustainability, socio-economic impacts of production, commercialization, and agroecosystem management.
Collapse
Affiliation(s)
- Michela Janni
- Institute of Bioscience and Bioresources (IBBR), National Research Council (CNR), Bari, Italy
- Institute of Materials for Electronics and Magnetism (IMEM), National Research Council (CNR), Parma, Italy
| | - Elena Maestri
- Department of Chemistry, Life Sciences and Environmental Sustainability, Interdepartmental Centers SITEIA.PARMA and CIDEA, University of Parma, Parma, Italy
| | - Mariolina Gullì
- Department of Chemistry, Life Sciences and Environmental Sustainability, Interdepartmental Centers SITEIA.PARMA and CIDEA, University of Parma, Parma, Italy
| | - Marta Marmiroli
- Department of Chemistry, Life Sciences and Environmental Sustainability, Interdepartmental Centers SITEIA.PARMA and CIDEA, University of Parma, Parma, Italy
| | - Nelson Marmiroli
- Consorzio Interuniversitario Nazionale per le Scienze Ambientali (CINSA) Interuniversity Consortium for Environmental Sciences, Parma/Venice, Italy
| |
Collapse
|
9
|
Yang Z, Luo C, Pei X, Wang S, Huang Y, Li J, Liu B, Kong F, Yang QY, Fang C. SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding. Nucleic Acids Res 2024; 52:D1639-D1650. [PMID: 37811889 PMCID: PMC10767819 DOI: 10.1093/nar/gkad786] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/13/2023] [Accepted: 09/15/2023] [Indexed: 10/10/2023] Open
Abstract
Advanced multi-omics technologies offer much information that can uncover the regulatory mechanisms from genotype to phenotype. In soybean, numerous multi-omics databases have been published. Although they cover multiple omics, there are still limitations when it comes to the types and scales of omics datasets and analysis methods utilized. This study aims to address these limitations by collecting and integrating a comprehensive set of multi-omics datasets. This includes 38 genomes, transcriptomes from 435 tissue samples, 125 phenotypes from 6686 accessions, epigenome data involving histone modification, transcription factor binding, chromosomal accessibility and chromosomal interaction, as well as genetic variation data from 24 501 soybean accessions. Then, common analysis pipelines and statistical methods were applied to mine information from these multi-omics datasets, resulting in the successful establishment of a user-friendly multi-omics database called SoyMD (https://yanglab.hzau.edu.cn/SoyMD/#/). SoyMD provides researchers with efficient query options and analysis tools, allowing them to swiftly access relevant omics information and conduct comprehensive multi-omics data analyses. Another notable feature of SoyMD is its capability to facilitate the analysis of candidate genes, as demonstrated in the case study on seed oil content. This highlights the immense potential of SoyMD in soybean genetic breeding and functional genomics research.
Collapse
Affiliation(s)
- Zhiquan Yang
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510405, China
| | - Chengfang Luo
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Xinxin Pei
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510405, China
| | - Shengbo Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Yiming Huang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Jiawei Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Baohui Liu
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510405, China
| | - Fanjiang Kong
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510405, China
| | - Qing-Yong Yang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural Reclamation Sciences, Shihezi 832000, China
| | - Chao Fang
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510405, China
| |
Collapse
|
10
|
Bharati R, Sen MK, Severová L, Svoboda R, Fernández-Cusimamani E. Polyploidization and genomic selection integration for grapevine breeding: a perspective. FRONTIERS IN PLANT SCIENCE 2023; 14:1248978. [PMID: 38034577 PMCID: PMC10684766 DOI: 10.3389/fpls.2023.1248978] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023]
Abstract
Grapevines are economically important woody perennial crops widely cultivated for their fruits that are used for making wine, grape juice, raisins, and table grapes. However, grapevine production is constantly facing challenges due to climate change and the prevalence of pests and diseases, causing yield reduction, lower fruit quality, and financial losses. To ease the burden, continuous crop improvement to develop superior grape genotypes with desirable traits is imperative. Polyploidization has emerged as a promising tool to generate genotypes with novel genetic combinations that can confer desirable traits such as enhanced organ size, improved fruit quality, and increased resistance to both biotic and abiotic stresses. While previous studies have shown high polyploid induction rates in Vitis spp., rigorous screening of genotypes among the produced polyploids to identify those exhibiting desired traits remains a major bottleneck. In this perspective, we propose the integration of the genomic selection approach with omics data to predict genotypes with desirable traits among the vast unique individuals generated through polyploidization. This integrated approach can be a powerful tool for accelerating the breeding of grapevines to develop novel and improved grapevine varieties.
Collapse
Affiliation(s)
- Rohit Bharati
- Department of Crop Sciences and Agroforestry, The Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Suchdol, Czechia
| | - Madhab Kumar Sen
- Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Suchdol, Czechia
| | - Lucie Severová
- Department of Economic Theories, Faculty of Economics and Management, Czech University of Life Sciences Prague, Prague, Czechia
| | - Roman Svoboda
- Department of Economic Theories, Faculty of Economics and Management, Czech University of Life Sciences Prague, Prague, Czechia
| | - Eloy Fernández-Cusimamani
- Department of Crop Sciences and Agroforestry, The Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Suchdol, Czechia
| |
Collapse
|
11
|
Sestili S, Prohens J, Ficcadenti N, Beleggia R. Editorial: Sustainable horticulture: from omic sciences to new breeding techniques. FRONTIERS IN PLANT SCIENCE 2023; 14:1257469. [PMID: 37621883 PMCID: PMC10446478 DOI: 10.3389/fpls.2023.1257469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 08/01/2023] [Indexed: 08/26/2023]
Affiliation(s)
- Sara Sestili
- Council for Agricultural Research and Economics (CREA) Research Centre for Vegetable and Ornamental Crops, Monsampolo del Tronto (AP), Italy
| | - Jaime Prohens
- Instituto de Conservacion y Mejora de la Agrodiversidad Valenciana, Universitat Politècnica de València, Valencia, Spain
| | - Nadia Ficcadenti
- Council for Agricultural Research and Economics (CREA) Research Centre for Vegetable and Ornamental Crops, Monsampolo del Tronto (AP), Italy
| | - Romina Beleggia
- Council for Agricultural Research and Economics (CREA) Research Center for Cereals and Industrial Crops, Foggia (FG), Italy
| |
Collapse
|
12
|
Roychowdhury R, Das SP, Gupta A, Parihar P, Chandrasekhar K, Sarker U, Kumar A, Ramrao DP, Sudhakar C. Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses. Genes (Basel) 2023; 14:1281. [PMID: 37372461 DOI: 10.3390/genes14061281] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/03/2023] [Accepted: 06/14/2023] [Indexed: 06/29/2023] Open
Abstract
The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.
Collapse
Affiliation(s)
- Rajib Roychowdhury
- Department of Plant Pathology and Weed Research, Institute of Plant Protection, Agricultural Research Organization (ARO)-The Volcani Institute, Rishon Lezion 7505101, Israel
| | - Soumya Prakash Das
- School of Bioscience, Seacom Skills University, Bolpur 731236, West Bengal, India
| | - Amber Gupta
- Dr. Vikram Sarabhai Institute of Cell and Molecular Biology, Faculty of Science, Maharaja Sayajirao University of Baroda, Vadodara 390002, Gujarat, India
| | - Parul Parihar
- Department of Biotechnology and Bioscience, Banasthali Vidyapith, Banasthali 304022, Rajasthan, India
| | - Kottakota Chandrasekhar
- Department of Plant Biochemistry and Biotechnology, Sri Krishnadevaraya College of Agricultural Sciences (SKCAS), Affiliated to Acharya N.G. Ranga Agricultural University (ANGRAU), Guntur 522034, Andhra Pradesh, India
| | - Umakanta Sarker
- Department of Genetics and Plant Breeding, Faculty of Agriculture, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur 1706, Bangladesh
| | - Ajay Kumar
- Department of Botany, Maharshi Vishwamitra (M.V.) College, Buxar 802102, Bihar, India
| | - Devade Pandurang Ramrao
- Department of Biotechnology, Mizoram University, Pachhunga University College Campus, Aizawl 796001, Mizoram, India
| | - Chinta Sudhakar
- Plant Molecular Biology Laboratory, Department of Botany, Sri Krishnadevaraya University, Anantapur 515003, Andhra Pradesh, India
| |
Collapse
|