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 diseaseresistance 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.
CITATION STYLE
Lakhani, J., Khuteta, A., Choudhary, A., & Harwani, D. (2018). In silico methods to predict disease-resistance candidate genes in plants. In In Silico Approach for Sustainable Agriculture (pp. 91–106). Springer Singapore. https://doi.org/10.1007/978-981-13-0347-0_5
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