Abstract
The increase in world population is stressing the need for increased production of food supplies from plants. At the same time, plant pathogens are also developing resistance to several anti-pathogen compounds. The present situation may become worse, in the near future, if not controlled. One of the solutions to the present situation is to develop disease-resistant varieties of plants. The disease resistance in plants is controlled by the products of disease-resistance genes. The plant genomes contain many disease-resistance candidate genes, activation of which can confer the natural resistance against various diseases in plants. The major step in the development of disease-resistant plant varieties is to search for the disease-resistance candidate genes in the plant genome and prioritize them. The experiments pertaining to identify disease-resistance candidate genes can be accomplished using wet lab studies but are usually time-consuming. The present chapter is a survey of the available in silico approaches to identify the candidate genes conferring disease resistance in plants. After providing a brief overview of the multilayered defense mechanism, the present article discusses different approaches for the stepwise identification of disease-resistant candidate genes in plants.
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Lakhani, J., Khuteta, A., Choudhary, A., Harwani, D. (2018). In Silico Methods to Predict Disease-Resistance Candidate Genes in Plants. In: Choudhary, D., Kumar, M., Prasad, R., Kumar, V. (eds) In Silico Approach for Sustainable Agriculture. Springer, Singapore. https://doi.org/10.1007/978-981-13-0347-0_5
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