Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity

• DOI: 10.1007/s00299-024-03153-7
• Publication Date: 2024-02-27T11:02:31Z
• Authors: Ali Raza; Hajar Salehi; Shanza Bashir; Javaria Tabassum; Monica Jamla; Sidra Charagh; Rutwik Barmukh; Rakeeb Ahmad Mir; Basharat Ahmad Bhat; Muhammad Arshad J...; Dong-Xing Guan; Reyazul Rouf Mir; Kadambot H. M. Si...; Rajeev K. Varshney
• Keywords: 0301 basic medicine; Proteomics; FOS: Computer and information sciences; Environmental Impact of Heavy Metal Contamination; Bioinformatics; Omics; Review; Gene; Analytical Chemistry; Computational biology; Soil; Context (archaeology); Artificial Intelligence; FOS: Chemical sciences; Biochemistry, Genetics and Molecular Biology; Genetics; Metabolomics; Trace Element Analysis in Medicinal Plants and Teas; Molecular Biology; Biology; Ecosystem; 0303 health sciences; Ecology; Gene Expression Profiling; Life Sciences; Paleontology; Agriculture; Food security; Pollution; Advances in Metabolomics Research; Chemistry; Metals; FOS: Biological sciences; Physical Sciences; Environmental Science; Biotechnology

AbstractThe escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.