Chowdhury, R.H.; Eti, F.S.; Ahmed, R.; Gupta, S.D.; Jhan, P.K.; Islam, T.; Bhuiyan, Md.A.R.; Rubel, M.H.; Khayer, A. Drought-Responsive Genes in Tomato: Meta-Analysis of Gene Expression Using Machine Learning. Scientific Reports 2023, 13, doi:10.1038/s41598-023-45942-2.
Chowdhury, R.H.; Eti, F.S.; Ahmed, R.; Gupta, S.D.; Jhan, P.K.; Islam, T.; Bhuiyan, Md.A.R.; Rubel, M.H.; Khayer, A. Drought-Responsive Genes in Tomato: Meta-Analysis of Gene Expression Using Machine Learning. Scientific Reports 2023, 13, doi:10.1038/s41598-023-45942-2.
Chowdhury, R.H.; Eti, F.S.; Ahmed, R.; Gupta, S.D.; Jhan, P.K.; Islam, T.; Bhuiyan, Md.A.R.; Rubel, M.H.; Khayer, A. Drought-Responsive Genes in Tomato: Meta-Analysis of Gene Expression Using Machine Learning. Scientific Reports 2023, 13, doi:10.1038/s41598-023-45942-2.
Chowdhury, R.H.; Eti, F.S.; Ahmed, R.; Gupta, S.D.; Jhan, P.K.; Islam, T.; Bhuiyan, Md.A.R.; Rubel, M.H.; Khayer, A. Drought-Responsive Genes in Tomato: Meta-Analysis of Gene Expression Using Machine Learning. Scientific Reports 2023, 13, doi:10.1038/s41598-023-45942-2.
Abstract
Plants have a natural protective process of altering their genetic molecules in response to changing environments. To uncover the genetic potential of plants, it is crucial to understand how they adapt to adverse conditions by analyzing their genetic molecules. In the study, we focused on understanding the responsive genes of tomatoes under drought conditions. We analyzed RNASeq data from different Tomato genotypes, tissue types, and different drought durations. We used a time series scale to identify early and late drought-responsive gene modules and applied a machine learning method to identify the best responsive genes. We found six candidate genes of Tomato (ASCT, FLA2, BAG5, DCL2b, NFP7.3, and ADC1) that were responsive to drought. We further constructed their protein-protein interaction network to identify their potential interactors and found them drought responsive proteins. The candidate genes can help to explore the adaptation of tomato plants under drought conditions. The identification of these candidate genes and modules can have far-reaching implications for molecular breeding and genome editing in Tomato, providing insights into the molecular mechanisms that underlie drought adaptation. This research underscores the importance of the genetic basis of plant adaptation, particularly in changing climates and growing populations.
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