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Cited by 132Plant Stress Responses and TolerancePlant Micronutrient Interactions and EffectsHeavy metals in environment

The DOI matches its Crossref record; 260 of the 261 references it cites were found in a registry or an index.

Advances in “Omics” Approaches for Improving Toxic Metals/Metalloids Tolerance in Plants

Open access
Raza, Ali, Tabassum, Javaria, Zahid, Zainab, Charagh, Sidra, Bashir, Shanza, Barmukh, Rutwik, Khan, Rao Sohail Ahmad, Barbosa, Fernando, Zhang, Chong, Chen, Hua, Zhuang, Weijian, Varshney, Rajeev K.·2022·Frontiers in Plant Science
DOI 10.3389/fpls.2021.794373PMC PMC8764127
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Abstract

Food safety has emerged as a high-urgency matter for sustainable agricultural production. Toxic metal contamination of soil and water significantly affects agricultural productivity, which is further aggravated by extreme anthropogenic activities and modern agricultural practices, leaving food safety and human health at risk. In addition to reducing crop production, increased metals/metalloids toxicity also disturbs plants' demand and supply equilibrium. Counterbalancing toxic metals/metalloids toxicity demands a better understanding of the complex mechanisms at physiological, biochemical, molecular, cellular, and plant level that may result in increased crop productivity. Consequently, plants have established different internal defense mechanisms to cope with the adverse effects of toxic metals/metalloids. Nevertheless, these internal defense mechanisms are not adequate to overwhelm the metals/metalloids toxicity. Plants produce several secondary messengers to trigger cell signaling, activating the numerous transcriptional responses correlated with plant defense. Therefore, the recent advances in omics approaches such as genomics, transcriptomics, proteomics, metabolomics, ionomics, miRNAomics, and phenomics have enabled the characterization of molecular regulators associated with toxic metal tolerance, which can be deployed for developing toxic metal tolerant plants. This review highlights various response strategies adopted by plants to tolerate toxic metals/metalloids toxicity, including physiological, biochemical, and molecular responses. A seven-(omics)-based design is summarized with scientific clues to reveal the stress-responsive genes, proteins, metabolites, miRNAs, trace elements, stress-inducible phenotypes, and metabolic pathways that could potentially help plants to cope up with metals/metalloids toxicity in the face of fluctuating environmental conditions. Finally, some bottlenecks and future directions have also been highlighted, which could enable sustainable agricultural production.

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Crossref · 10.3389/fpls.2021.794373

Cites

260 of 260 references verified0 citation errors · 0 not checkable

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Figures

FIGURE 1 Plant responses to toxic metals/metalloids toxicity with possible direct and indirect effects on crop productivity. Plants interact with toxic metals/metalloids via above-ground and/or below-ground parts. The toxic effects of several toxic metals/metalloids decrease the physiological responses and increase the molecular and biochemical responses.
FIGURE 1 Plant responses to toxic metals/metalloids toxicity with possible direct and indirect effects on crop productivity. Plants interact with toxic metals/metalloids via above-ground and/or below-ground parts. The toxic effects of several toxic metals/metalloids decrease the physiological responses and increase the molecular and biochemical responses.CC BY · PubMed Central
FIGURE 2 Integrated omics approach for developing toxic metals/metalloids tolerant plants. The use of multi-omics approach can help to reveal stress-responsive mechanisms at the genomic level, understand what is happening at the transcript and proteome level, provide clues about the interaction of metabolites with the phenotype, understand the role of different mineral elements, and unravel phenotypic changes in plants in response to toxic metals/metalloids toxicity. Integrating state-of-the-art omics approaches with speed breeding will help to meet the challenge of feeding a burgeoning human population.
FIGURE 2 Integrated omics approach for developing toxic metals/metalloids tolerant plants. The use of multi-omics approach can help to reveal stress-responsive mechanisms at the genomic level, understand what is happening at the transcript and proteome level, provide clues about the interaction of metabolites with the phenotype, understand the role of different mineral elements, and unravel phenotypic changes in plants in response to toxic metals/metalloids toxicity. Integrating state-of-the-art omics approaches with speed breeding will help to meet the challenge of feeding a burgeoning human population.CC BY · PubMed Central
FIGURE 3 Persisting bottlenecks in the exploitation of omics approaches (Raza et al., 2021b). Although an outstanding revolution has been accomplished in the biotechnological era, many queries and bottlenecks presently limit the utilization of omics approaches for stress tolerance research in several plant species. The amendment of these bottlenecks using molecular tools will help us to exploit the innovative manifesto in developing toxic metals/metalloids tolerant plants.
FIGURE 3 Persisting bottlenecks in the exploitation of omics approaches (Raza et al., 2021b). Although an outstanding revolution has been accomplished in the biotechnological era, many queries and bottlenecks presently limit the utilization of omics approaches for stress tolerance research in several plant species. The amendment of these bottlenecks using molecular tools will help us to exploit the innovative manifesto in developing toxic metals/metalloids tolerant plants.CC BY · PubMed Central

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Citations

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Research works printed but not linked: 6

  1. Bahmani, 2012, Effect of cadmium chloride on growth parameters of different bean genotypes (Phaseolus vulgaris L.)., ARPN J. Agric. Biol. Sci., 7, 35
  2. Kakeshpour, 2020, Tomato Class II Glutaredoxin Mutants Generated Via Multiplex CRISPR/Cas9 Genome Editing Technology are Susceptible to Multiple Abiotic Stresses.
  3. Lin, 2011, The detoxification effect of nitrogen on cadmium stress in Populus yunnanensis., Bot. Res. J., 4, 13
  4. Muntean, 2019, Heavy metals’ uptake from soil in potato tubers: an ionomic approach., ProEnvironment, 12, 159
  5. Parmar, 2013, Physiological, biochemical and molecular response of plants against heavy metals stress., Int. J. Curr. Res., 5, 80
  6. Shenton, 2019, Plant omics data center and CATchUP: web databases for effective gene mining utilizing public RNA-Seq-based transcriptome data, The Model Legume Medicago Truncatula, 1137

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Metadata

Authors
Raza, A., Tabassum, J., Zahid, Z., Charagh, S., Bashir, S., Barmukh, R., Khan, R. S. A., Barbosa, F., Zhang, C., Chen, H., Zhuang, W., & Varshney, R. K.
Affiliations
  • Fujian Agriculture and Forestry University (CN)
  • Chinese Academy of Agricultural Sciences (CN)
  • National University of Sciences and Technology (PK)
  • International Crops Research Institute for the Semi-Arid Tropics (IN)
  • University of Agriculture Faisalabad (PK)
  • Universidade de São Paulo (BR)
  • Murdoch University (AU)
Corresponding author
  • Zhuang, Weijian
  • Varshney, Rajeev K.
ORCID
Venue
Frontiers in Plant Science
Publisher
Frontiers Media SA
Published
2022-01-04
Volume
12
Pages
794373-794373
ISSN
1664-462X (ISSN-L)
DOI
10.3389/fpls.2021.794373
PMC
PMC8764127
OpenAlex
W4206241292
Cited by
132
References
261
Citations by year
2026: 32 · 2025: 24 · 2024: 31 · 2023: 23 · 2022: 22
FWCI
2.29
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Plant Science (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics) (acceptedVersion)
  • Murdoch University Research Portal (submittedVersion, cc-by)
  • Murdoch University Research Portal (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Bill and Melinda Gates Foundation (OPP1114827)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Stress Responses and Tolerance
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Micronutrient Interactions and Effects
  • Physical Sciences › Environmental Science › Pollution › Heavy metals in environment
Keywords
metalloids, heavy metal toxicity, plant stress response, omics approaches, transcriptomics, proteomics, metabolomics, ionomics, phenomics, plant defense, stress-inducible genes, food safety, soil and water contamination

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