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Development of a pipeline of genomic and transcriptomic data analysis for the identification of target genes for silencing (RNAi) of the pathogen M. incognita.

Grant number: 21/09704-7
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): December 01, 2021
Effective date (End): November 30, 2022
Field of knowledge:Biological Sciences - Genetics
Principal researcher:Henrique Marques Barbosa de Souza
Grantee:Giovana Motta de Oliveira
Home Institution: Instituto de Biologia (IB). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Gene silencing through RNAi has revolutionized the study of gene function, particularly in non-model insects and as yet unsequenced species genomes, which is the case for most agricultural pests today. One of the most important steps for the development of RNAi technology for the control of agricultural pests and diseases is the choice of the target gene. In this context, a transcriptome analysis is a very interesting approach, as it allows the identification of novel genes based on their transcriptional profiles, in addition to several other approaches. The search for target genes by transcriptome analysis requires the development of bioinformatics pipelines, which, depending on the context of the data, can be initiated with a de novo (or with reference) assembly of the transcriptome, functional annotation of the transcripts, calculation of gene expression differential in the various experimental conditions of interest, analysis of clustering of gene families in the search for targets that do not have paralogs, among others. Thus, the objective of this work is to develop a pipeline of genomic and transcriptomic data analysis for the identification of target genes for silencing (RNAi). To this end, public genomic and transcriptomic data of the nematode Meloidogy incognita used in this project. Plant parasitic nematodes currently constitute the majority of agricultural pests that attack agronomically important cultivars worldwide. Among the various strategies to control its propagation, the RNA interference (RNAi) technique has been shown to be very viable and efficient. This is because it is possible, from their management, to identify vital and essential genes, given the functional annotation of proteins and differential expression analysis, in order to understand the complete development of all stages of life of these animals. silencing these gene components for possible extermination of selected target genes. Thus, the focus of this project is the endoparasite Meloidogyne Incognita (or root-knot nematode), a pest that reduces the productivity of crops worldwide by 5 to 10% per year, being mainly concentrated in the tropical and subtropical regions of the globe. Among the identified symptoms associated with infection by this nematode are chlorosis in the leaves of plants, growth retardation and worsening of nutritional deficiencies. Furthermore, it is known that the most devastating species of this nematode perform ameotic asexual reproduction, that is, parthenogenesis, and that there is no polyploid genome of these variants, there are many duplicated regions, with an average nucleotide divergence between species of approximately ~ 8 %, marked by hybridization events, and ~0.02% between variants of the same species, but with different geographic origin. Thus, the DNA transcripts of this animal were generated from the availability of a large library of public genome and transcriptome data, for further analysis of the differential expression of the different stages of the nematode's life cycle. they: egg, J2 (second stage of life), J3 (third stage of life), J4 (fourth stage of life), juvenile and adult, containing 3 replicas for each stage of life.Public database will also be used containing 10 genome samples of variant populations of the pest under study, with high coverage (> 100x), which are compatible with different cultivars and inhabit different geographic origins, in order to take these genomic variations (SNPs) among the nematode populations under consideration, while selecting target genes common to all of them. The cultivars all belong to the Brazilian territory and are: soybean (2 from Londrina-PR), tobacco (one from Mercedes-PR and the other from Sombrio-SC), coffee (1 from São Jorge do Patrocínio), cotton (1 from Umarama- PR, another from Campo Verde-MG, and another from Vargme Grande do Sul-SP), watermelon (1 from Londrina-PR) and cucumber (Piracaíba-SP).

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