Análise comparativa de redes gênicas de Anticarsia gemmatalis Hübner, 1818 (Lepidoptera: Erebidae) inferidas de transcriptomas de linhagens resistente e susceptível à proteína Cry de Bacillus thuringiensis

Abstract

The project is based on the database of the work by Pezenti et al., 2021; which reports in- formation about the transcriptomes of populations of A. gemmatalis resistant and susceptible to Cry toxin. The project aimed to analyze the gene networks of resistant and sensitive co- lonies to the Cry toxin of Bacillus thuringiensis. Each population had a control (+) and (-), resistance (labeled CRXTR) and susceptibility (labeled CSXTS), respectively. The experiments were performed in triplicate for each biological condition, resulting in 12 experimental units (12 RNAseq libraries obtained from the IlluminaR Hiseq 2500 system). The differentially expres- sed transcripts were those that had an adjusted p (padj) > 0.05 and a log2 fold change (LFC) > 2.0. Differential expression analysis resulted in 1500 transcripts for the CRXTR, and 975 transcripts for the CSXTS. Data were run in DimReduction software to infer the co-expression gene networks, complete networks were found, indicating a possible metabolic hardening of the network. Subsequently, KEGG pathway maps were searched to generate bipartite and multipar- tite networks using the VisANT tool, finding for the bipartite networks of the immune system unique transcripts for the CRXTR and CSXTS strains, but also intersecting transcripts such as Aminopeptidase N present in the membrane cell phone. In the case of multipartite networks, it was found that the CRXTR network had a greater number of inhibited genes than the CSXTS networks. Some multilevel network genes were also found in co-expression networks, such as the following genes: UDP-glycosyltransferase 42C2 and cactus-like NF-kappa-B inhibitor. The work concludes that caterpillars adapted to high concentrations of the Cry toxin (adapted treatments (TR)) have a smaller number of genes involved in their conformation, and that the transcripts of high connectivity in the bipartite and multilevel network correspond to proteins related to the sequential join action mechanism.