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Article Open Access http://dx.doi.org/10.26855/abr.2024.12.003

Single-omics Approaches to Improve Abiotic Stress Tolerance in Faba Bean: A Review

Buzuayehu Mamo Mekuria1,*, Tiruwork Zewdie2, Deshu Mamo3, Adugna Abdi4

1Department of Biotechnology, College of Natural and Computational Science, Debre Markos University, Debre Markos 269, Ethiopia.

2Department of Biotechnology, College of Natural and Computational Science, Debre Birhan University, Debre Birhan 445, Ethiopia.

3Department of Environmental Protection, College of Natural and Computational Science, Assosa University, Assosa 18, Ethiopia.

4Department of Biotechnology, College of Natural and Applied Science, Addis Ababa Science and Technology University, Addis Ababa 16417, Ethiopia.

*Corresponding author: Buzuayehu Mamo Mekuria

Published: March 3,2025

Abstract

Faba bean (Vicia faba L.) is the fourth most extensively planted cool-season legume, following pea, chickpea, and lentil. It contains more protein than other common dietary beans used for food and feeds around the world. Faba beans are highly susceptible to abiotic stresses such as drought, frost, heat, and salt, which significantly reduce both crop growth and yield. For instance, drought alone can reduce faba bean yields by up to 50%, during early pod-setting, highlighting the urgent need for strategies to enhance. The absence of a fully annotated reference genome for faba beans complicates the use of CRISPR/Cas gene editing techniques, which rely on detailed genetic maps to precisely target genes involved in stress tolerance. Developing such a genome could significantly enhance the effectiveness of gene-editing strategies. Proteomic approaches were utilised to identify a variety of abiotic stressors, including heat, drought, salt and frost. Proteomic analysis reveals that a significant portion of the differentially expressed proteins in faba beans are involved in essential processes such as photosynthesis, glucose metabolism, and stress defense pathways. These proteins play crucial roles in mitigating the negative effects of drought and heat stress, contributing to improved stress tolerance in the plant phenotype. Metabolomics has been used success-fully in a variety of faba bean stress studies, including metabolic pathway studies, genotype-biochemical phenotype correlations, silent phenotype mutations, plant-environment interactions, and plant priming, a phenomenon that prepares plants for enhanced stress defence. Metabolites, such as proline and sugars, are directly involved in stress tolerance mechanisms and exhibit a stronger correlation with the plant’s phenotype than mRNA or proteins. For example, increased levels of proline under drought conditions help in osmoregulation, a key trait for enhanced drought tolerance. Although all mineral nutrients and trace elements are required for plant growth and development. Various OMICs approaches can be used to target the faba bean abiotic stress responses generated by genomic sequences, transcripts, protein organisation and interactions. In general, this review concentrated on the faba bean genomics, transcriptomics, proteomics, metabolomics, phenomics and ionomics under abiotic stress.

References

[1] Caracuta V, Weinstein-Evron M, Kaufman D, Yeshurun R, Silvent J, Boaretto E. 14,000-year-old seeds indicate the Levantine origin of the lost progenitor of faba bean. Sci Rep. 2016;6(1):37399.

[2] Alharbi NH, Adhikari KN. Factors of yield determination in faba bean (Vicia faba). Crop Pasture Sci. 2020;71(4):305-21.

[3] Khazaei H, O'Sullivan DM, Stoddard FL, et al. Recent advances in faba bean genetic and genomic tools for crop improvement. Legume Sci. 2021;3(3):e75.

[4] Warsame AO, O’Sullivan DM, Tosi P. Seed storage proteins of faba bean (Vicia faba L): Current status and prospects for genetic improvement. J Agric Food Chem. 2018;66(48):12617-26.

[5] Abou-Khater L, Maalouf F, Rubiales D. Status of faba bean (Vicia faba L.) in the Mediterranean and East African countries. In: Developing Climate Resilient Grain and Forage Legumes. Singapore: Springer Nature Singapore; 2022. p. 297-327.

[6] Abdelhaleim MS, Rahimi M, Okasha SA. Assessment of drought tolerance indices in faba bean genotypes under different irrigation regimes. Open Life Sci. 2022;17(1):1462-72.

[7] Shah WH, Rasool A, Saleem S, et al. Understanding the integrated pathways and mechanisms of transporters, protein kinases, and tran-scription factors in plants under salt stress. Int J Genomics. 2021;2021.

[8] Kosová K, Vítámvás P, Urban MO, Prášil IT, Renaut J. Plant abiotic stress proteomics: the major factors determining alterations in cellular proteome. Front Plant Sci. 2018;9:122.

[9] Maalouf F. Developing improved varieties of faba bean. Burleigh Dodds Sci. 2018.

[10] Mansour E, Desoky ESM, Ali MM, et al. Identifying drought-tolerant genotypes of faba bean and their agro-physiological responses to different water regimes in an arid Mediterranean environment. Agric Water Manag. 2021;247:106754.

[11] Muktadir MA, Adhikari KN, Merchant A, et al. Physiological and biochemical basis of faba bean breeding for drought adaptation—A review. Agronomy. 2020;10(9):1345.

[12] Maalouf F, Hu J, O'Sullivan DM, et al. Breeding and genomics status in faba bean (Vicia faba). Plant Breed. 2019;138(4):465-73.

[13] Gutiérrez N, Pégard M, Balko C, Torres AM. Genome-wide association analysis for drought tolerance and associated traits in faba bean (Vicia faba L.). Front Plant Sci. 2023;14.

[14] Awaad HA, Awaad HA. Approaches in faba bean to mitigate impact of climate change. In: Sustainable Agriculture in Egypt: Climate Change Mitigation. 2022. p. 185-217.

[15] Jan N, Rather AMUD, John R, et al. Proteomics for abiotic stresses in legumes: present status and future directions. Crit Rev Biotechnol. 2023;43(2):171-90.

[16] Chen CJ, Rutkoski J, Schnable JC, et al. Role of the genomics–phenomics–agronomy paradigm in plant breeding. Plant Breed Rev. 2022;46:627-73.

[17] Afzal M, Alghamdi SS, Migdadi HH, et al. Legume genomics and transcriptomics: From classic breeding to modern technologies. Saudi J Biol Sci. 2020;27(1):543-55.

[18] Ali A, Altaf MT, Nadeem MA, et al. Recent advancement in OMICS approaches to enhance abiotic stress tolerance in legumes. Front Plant Sci. 2022;13.

[19] Jha UC, Bohra A, Nayyar H. Advances in “omics” approaches to tackle drought stress in grain legumes. Plant Breed. 2020;139(1):1-27.

[20] Ziegler G, Nelson R, Granada S, et al. Genomewide association study of ionomic traits on diverse soybean populations from germplasm collections. Plant Direct. 2018;2(1):e00033.

[21] Mathivanan S. Abiotic Stress-Induced Molecular and Physiological Changes and Adaptive Mechanisms in Plants. In: Abiotic Stress in Plants. 2021. p. 315.

[22] Naik B, Kumar V, Rizwanuddin S, et al. Genomics, Proteomics, and Metabolomics Approaches to Improve Abiotic Stress Tolerance in Tomato Plant. Int J Mol Sci. 2023;24(3):3025.

[23] Kumar P, Choudhary M, Halder T, et al. Salinity stress tolerance and omics approaches: Revisiting the progress and achievements in major cereal crops. Heredity. 2022;128(6):497-518.

[24] Muthamilarasan M, Singh NK, Prasad M. Multi-omics approaches for strategic improvement of stress tolerance in underutilized crop species: a climate change perspective. Adv Genet. 2019;103:1-38.

[25] Sharma V, Gupta P, Kagolla P, et al. Metabolomics intervention towards better understanding of plant traits. Cells. 2021;10(2):346.

[26] Parida AK, Panda A, Rangani J. Metabolomics-guided elucidation of abiotic stress tolerance mechanisms in plants. In: Plant Metabolites and Regulation under Environmental Stress. Academic Press; 2018. p. 89-131.

[27] Varshney RK, Thudi M, Pandey MK, et al. Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy. J Exp Bot. 2018;69(13):3293-3312.

[28] Carrillo-Perdomo E, Vidal A, Kreplak J, et al. Development of new genetic resources for faba bean (Vicia faba L.) breeding through the discovery of gene-based SNP markers and the construction of a high-density consensus map. Sci Rep. 2020;10(1):6790.

[29] O’Sullivan DM, Angra D, Harvie T, Tagkouli V, Warsame A. A genetic toolbox for Vicia faba improvement. In: International Conference on Legume Genetics and Genomics. 2019.

[30] Mandour H, Khazaei H, Stoddard FL, Dodd IC. Identifying physiological and genetic determinants of faba bean transpiration response to evaporative demand. Ann Bot. 2023.

[31] Mokhtar MM, Hussein EH, El-Assal SEDS, Atia MA. Vf ODB: a comprehensive database of ESTs, EST-SSRs, mtSSRs, microRNA-target markers and genetic maps in Vicia faba. AoB Plants. 2020;12(6):plaa064.

[32] Webb A, Cottage A, Wood T, et al. A SNP‐based consensus genetic map for synteny‐based trait targeting in faba bean (Vicia faba L.). Plant Biotechnol J. 2016;14(1):177-85.

[33] Khan MA, Alghamdi SS, Ammar MH, et al. Transcriptome profiling of faba bean (Vicia faba L.) drought-tolerant variety hassawi-2 under drought stress using RNA sequencing. Electron J Biotechnol. 2019;39:15-29.

[34] Sallam A, Arbaoui M, El-Esawi M, Abshire N, Martsch R. Identification and verification of QTL associated with frost tolerance using linkage mapping and GWAS in winter faba bean. Front Plant Sci. 2016;7:1098.

[35] Siddiqui MH, Al-Khaishany MY, Al-Qutami MA, et al. Response of different genotypes of faba bean plant to drought stress. Int J Mol Sci. 2015;16(5):10214-27.

[36] Ewas M, Omar SA, El-Sarag E, Mubarak MH. Genome-Wide Characterization of Drought-Responsive Genes Accelerates Faba Bean Breeding Program. Egypt J Desert Res. 2021;69(2):47-67.

[37] Lyu JI, Ramekar R, Kim JM, et al. Unraveling the complexity of faba bean (Vicia faba L.) transcriptome to reveal cold-stress-responsive genes using long-read isoform sequencing technology. Sci Rep. 2021;11(1):21094.

[38] Biswas D, Saha SC, Dey A. CRISPR-Cas genome-editing tool in plant abiotic stress-tolerance. Plant Gene. 2021;26:100286.

[39] Kaur B, Sandhu KS, Kamal R, et al. Omics for the improvement of abiotic, biotic, and agronomic traits in major cereal crops: Applications, challenges, and prospects. Plants. 2021;10(10):1989.

[40] Yang Y, Saand MA, Huang L, et al. Applications of multi-omics technologies for crop improvement. Front Plant Sci. 2021;12:563953.

[41] Alghamdi SS, Khan MA, Ammar MH, et al. Characterization of drought stress-responsive root transcriptome of faba bean (Vicia faba L.) using RNA sequencing. 3 Biotech. 2018;8:1-19.

[42] Wu X, Fan Y, Li L, Liu Y. The influence of soil drought stress on the leaf transcriptome of faba bean (Vicia faba L.) in the Qinghai–Tibet Plateau. 3 Biotech. 2020;10:1-16.

[43] Braich S, Sudheesh S, Forster JW, Kaur S. Characterisation of faba bean (Vicia faba L.) transcriptome using RNA-seq: sequencing, de novo assembly, annotation, and expression analysis. Agronomy. 2017;7(3):53.

[44] Javed T, Shabbir R, Ali A, et al. Transcription factors in plant stress responses: Challenges and potential for sugarcane improvement. Plants. 2020;9(4):491.

[45] Yin X, Zhang Y, Zhang L, et al. Regulation of MYB transcription factors of anthocyanin synthesis in lily flowers. Front Plant Sci. 2021;12:2677.

[46] Singh RK, Sood P, Prasad A, Prasad M. Advances in omics technology for improving crop yield and stress resilience. Plant Breed. 2021;140(5):719-31.

[47] Yang W, Feng H, Zhang X, et al. Crop phenomics and high-throughput phenotyping: past decades, current challenges, and future perspectives. Mol Plant. 2020;13(2):187-214.

[48] Heinrich F, Wutke M, Das PP, et al. Identification of regulatory SNPs associated with vicine and convicine content of Vicia faba based on genotyping by sequencing data using deep learning. Genes. 2020;11(6):614.

[49] Gao B, Bian XC, Yang F, et al. Comprehensive transcriptome analysis of faba bean in response to vernalization. Planta. 2020;251:1-15.

[50] Björnsdotter E, Nadzieja M, Chang W, et al. VC1 catalyses a key step in the biosynthesis of vicine in faba bean. Nat Plants. 2021;7(7):923-31.

[51] Escobar-Herrera L, Kreplak J, Nadzieja M, et al. The faba bean pan-transcriptome. In: PAG XXVIII, Plant and Animal Genome. 2020.

[52] Razzaq MK, Aleem M, Mansoor S, et al. Omics and CRISPR-Cas9 approaches for molecular insight, functional gene analysis, and stress tolerance development in crops. Int J Mol Sci. 2021;22(3):1292.

[53] Li P, Zhang Y, Wu X, Liu Y. Drought stress impact on leaf proteome variations of faba bean (Vicia faba L.) in the Qinghai–Tibet Plateau of China. 3 Biotech. 2018;8:1-12.

[54] Yahoueian SH, Bihamta MR, Babaei HR, Bazargani MM. Proteomic analysis of drought stress response mechanism in soybean (Glycine max L.) leaves. Food Sci Nutr. 2021;9(4):2010-20.

[55] Long R, Li M, Zhang T, et al. Comparative proteomic analysis reveals differential root proteins in Medicago sativa and Medicago trun-catula in response to salt stress. In: The Model Legume Medicago truncatula. 2019. p. 1102-11.

[56] Ghatak A, Chaturvedi P, Bachmann G, et al. Physiological and proteomic signatures reveal mechanisms of superior drought resilience in pearl millet compared to wheat. Front Plant Sci. 2021;11:600278.

[57] Xu Y, Fu X. Reprogramming of plant central metabolism in response to abiotic stresses: a metabolomics view. Int J Mol Sci. 2022;23(10):5716.

[58] Tadele M. Impacts of soil acidity on growth performance of faba bean (Vicia faba L) and management options. Acad Res J Agric Sci Res. 2020;8(4):423-31.

[59] Labuschagne M, Masci S, Tundo S, et al. Proteomic analysis of proteins responsive to drought and low temperature stress in a hard red spring wheat cultivar. Molecules. 2020;25(6):1366.

[60] Baslam M, Mitsui T. The Future of Rice Demand: Quality Beyond Productivity. In: Proteomic for quality: Mining the proteome as a strategy to elucidate the protein complex applied for quality improvement. Springer Nature; 2020. p. 473-94.

[61] Carrera FP, Noceda C, Maridueña-Zavala MG, Cevallos-Cevallos JM. Metabolomics, a powerful tool for understanding plant abiotic stress. Agronomy. 2021;11(5):824.

[62] Alseekh S, Bermudez L, De Haro LA, Fernie AR, Carrari F. Crop metabolomics: From diagnostics to assisted breeding. Metabolomics. 2018;14:1-13.

[63] Abdelrahman M, Burritt DJ, Tran LSP. The use of metabolomic quantitative trait locus mapping and osmotic adjustment traits for the improvement of crop yields under environmental stresses. Semin Cell Dev Biol. 2018;83:86-94.

[64] Dawid C, Hille K. Functional metabolomics—a useful tool to characterize stress-induced metabolome alterations opening new avenues towards tailoring food crop quality. Agronomy. 2018;8(8):138.

[65] Migdadi HM, El-Harty EH, Salamh A, Khan MA. Yield and proline content of faba bean genotypes under water stress treatments. JAPS. 2016;26(6).

[66] Bista DR, Heckathorn SA, Jayawardena DM, Mishra S, Boldt JK. Effects of drought on nutrient uptake and the levels of nutrient-uptake proteins in roots of drought-sensitive and-tolerant grasses. Plants. 2018;7(2):28.

[67] Belachew KY, Stoddard FL. Screening of faba bean (Vicia faba L.) accessions to acidity and aluminium stresses. PeerJ. 2017;5:2963.

[68] Wang X, Guo R, Li M, et al. Metabolomics reveals the drought-tolerance mechanism in wild soybean (Glycine soja). Acta Physiol Plant. 2019;41:1-11.

[69] Ghatak A, Chaturvedi P, Weckwerth W. Metabolomics in plant stress physiology. In: Plant Genetics and Molecular Biology. 2018. p. 187-236.

[70] Richter JA, Behr JH, Erban A, Kopka J, Zörb C. Ion‐dependent metabolic responses of Vicia faba L. to salt stress. Plant Cell Environ. 2019;42(1):295-309.

[71] Bueno PC, Lopes NP. Metabolomics to characterize adaptive and signaling responses in legume crops under abiotic stresses. ACS Ome-ga. 2020;5(4):1752-63.

[72] Singh B, Mishra S, Bohra A, et al. Crop phenomics for abiotic stress tolerance in crop plants. In: Biochemical, Physiological and Molecular Avenues for Combating Abiotic Stress Tolerance in Plants. 2018. p. 277-96.

[73] Scossa F, Alseekh S, Fernie AR. Integrating multi-omics data for crop improvement. J Plant Physiol. 2021;257:153352.

[74] Pratap A, Gupta S, Nair RM, et al. Using plant phenomics to exploit the gains of genomics. Agronomy. 2019;9(3):126.

[75] Sandhu D, Kaundal A. Dynamics of salt tolerance: molecular perspectives. In: Biotechnologies of Crop Improvement, Volume 3: Genomic Approaches. 2018. p. 25-40.

[76] Jangra S, Chaudhary V, Yadav RC, Yadav NR. High-throughput phenotyping: a platform to accelerate crop improvement. Phenomics. 2021;1(2):31-53.

[77] Hassan MU, Chattha MU, Khan I, et al. Heat stress in cultivated plants: Nature, impact, mechanisms, and mitigation strategies—A review. Plant Biosyst. 2021;155(2):211-34.

[78] Jung J, Maeda M, Chang A, et al. The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems. Curr Opin Biotechnol. 2021;70:15-22.

[79] Javaid M, Haleem A, Khan IH, Suman R. Understanding the potential applications of Artificial Intelligence in Agriculture Sector. Adv Agrochem. 2023;2(1):15-30.

[80] Chen A, Hansen TH, Olsen LI, et al. Towards single-cell ionomics: a novel micro-scaled method for multi-element analysis of nano-gram-sized biological samples. Plant Methods. 2020;16(1):1-13.

[81] Serafin-Andrzejewska M, Jama-Rodzeńska A, Helios W, Kotecki A, Kozak M, Białkowska M, Bárta J, Bártová V. Accumulation of Minerals in Faba Bean Seeds and Straw in Relation to Sowing Density. Agriculture. 2023;13(1):147.

[82] Ali S, Tyagi A, Bae H. Ionomic approaches for discovery of novel stress-resilient genes in plants. Int J Mol Sci. 2021;22(13):7182.

[83] Banerjee A, Singh A, Sudarshan M, Roychoudhury A. Silicon nanoparticle-pulsing mitigates fluoride stress in rice by fine-tuning the ionomic and metabolomic balance and refining agronomic traits. Chemosphere. 2021;262:127826.

[84] Nazir M, Mahajan R, Mansoor S, Rasool S, Mir RA, Singh R, Zargar SM. Identification of QTLs/Candidate Genes for Seed Mineral Contents in Common Bean (Phaseolus vulgaris L.) Through Genotyping-by-Sequencing. Front Genet. 2022;13:143.

[85] Mukherjee R, Barwant M, Sinha D. Ionomics vis à vis Heavy Metals Stress and Amelioration. In: Heavy Metals in Plants Physiological to Molecular Approach. 2022:246-280.

How to cite this paper

Single-omics Approaches to Improve Abiotic Stress Tolerance in Faba Bean: A Review

How to cite this paper: Buzuayehu Mamo Mekuria, Tiruwork Zewdie, Deshu Mamo, Adugna Abdi. (2024) Single-omics Approaches to Improve Abiotic Stress Tolerance in Faba Bean: A ReviewAdvance in Biological Research5(2), 49-64.

DOI: http://dx.doi.org/10.26855/abr.2024.12.003