Gene Tags Assessment by Comparative Genomics (GTACG): A User-Friendly Framework for Bacterial Comparative Genomics

Abstract

Genomics research has produced an exponential amount of data. However, the genetic knowledge pertaining to certain phenotypic characteristics is lacking. Also, a considerable part of these genomes have coding sequences (CDSs) with unknown functions, posing additional challenges to researchers. Phylogenetically close microorganisms share much of their CDSs, and certain phenotypes unique to a set of microorganisms may be the result of the genes found exclusively in those microorganisms. This study presents the GTACG framework, an easy-to-use tool for identifying in the subgroups of bacterial genomes whose microorganisms have common phenotypic characteristics, to find data that differentiates them from other associated genomes in a simple and fast way. The GTACG analysis is based on the formation of homologous CDS clusters from local alignments. The front-end is easy to use, and the installation packages have been developed to enable users lacking knowledge of programming languages or bioinformatics analyze high-throughput data using the tool. The validation of the GTACG framework has been carried out based on a case report involving a set of 161 genomes from the Xanthomonadaceae family, in which 19 families of orthologous proteins were found in 90% of the plant-associated genomes, allowing the identification of the proteins potentially associated with adaptation and virulence in plant tissue. The results show the potential use of GTACG in the search for new targets for molecular studies, and GTACG can be used as a research tool by biologists who lack advanced knowledge in the use of computational tools for bacterial comparative genomics.

GTACG: Um arcabouço computacional focado em genômica comparativa de bactérias de um mesmo ramo evolutivo

“…Por outro lado, o frontendé destinadoà visualização dos resultados e não exige conhecimentos específicos em computação. Os resultados são exportados na forma de um website, não sendo necessária a configuração de um servidor e facilitando a publicação e compartilhamento dos resultados por parte do pesquisador [Santiago et al 2019].…”

“…Entre os principais resultados produzidos pelo presente trabalho estão: (i) o arcabouço em si, disponibilizado no GitHub (endereço apresentado na seção 3) e que já está sendo utilizado por diferentes grupos de pesquisa; (ii) um artigo publicado no periódico Journal of Computational Biology [Santiago et al 2018] que apresenta o algoritmo proposto e desenvolvido para o agrupamento de genes em famílias e (iii) um artigo publicado no periódico Frontiers in Genetics [Santiago et al 2019] que apresenta o arcabouço produzido. A tese pode ser encontrada a partir do seguinte link: https://www.teses.usp.br/teses/disponiveis/95/95131/ tde-02032020-102628/…”

Comparative genomics and phylogenomics of Xylella fastidiosa

“…The amino acid and nucleotide coding sequences (CDSs) of each annotated genome were retrieved. To perform the comparative genomics was used the GTACG framework 3 (Santiago et al, 2019) which is based in an algorithm recently published (Santiago et al, 2018). Firstly, a local alignment was performed using BLAST (Altschul et al, 1990) with an e-value of 1e-10.…”

“…Over the past 19 years, genome sequences of several X. fastidiosa strains/isolates have been released which are being constantly analyzed with different approaches and purposes (Bhattacharyya et al, 2002a;Bhattacharyya et al, 2002b;Van Sluys et al, 2002;Van Sluys et al, 2003;Koide et al, 2004;Monteiro-Vitorello et al, 2005;da Silva et al, 2007;Varani et al, 2008 In this study, we performed a comparative analysis of 46 X. fastidiosa genomes which were re-annotated with PROKKA software (Seemann, 2014) and manually curated. For this analysis, we chose the new tool GTACG framework (Santiago et al, 2019) which uses an algorithm developed to deal with phylogenetically close genomes (Santiago et al, 2018). General statistics and analysis of pan, accessory, core and singleton genome will be presented aiming to highlight relevant traits found in these genomes.…”

“…The higher the value of this coefficient, the denser the components of the graph and, therefore, its maximization produces graphs according to the expected characteristics of a homology (for instance, it is expected that the graph formed by the homology relationships is more homogeneous and denser)(Santiago et al, 2018). The recent released tool GTACG framework uses this algorithm(Santiago et al, 2019).…”