Homology Inference Based on a Reconciliation Approach for the Comparative Genomics of Protozoa. (7th July 2018)

• Record Type: Journal Article
• Authors: Campos, Darueck A; Pereira, Elisa C; Jardim, Rodrigo; Cuadrat, Rafael RC; Bernardes, Juliana S; Dávila, Alberto MR
• Is Part Of: Evolutionary bioinformatics online. Volume 14(2018)
• Publication Date: 2018-07-07
• Subjects: protozoa -- homology -- conserved domains -- reconciliation -- distant homology; Bioinformatics -- Periodicals; Evolutionary computation -- Periodicals; Genetic programming (Computer science) -- Periodicals; Computational Biology; Evolution, Molecular; Bioinformatics; Electronic journals; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 576.8
• DOI: 10.1177/1176934318785138
• Languages: English
• ISSNs: 1176-9343

Abstract

Protozoa parasites are responsible for several diseases in tropical countries, such as malaria, sleeping sickness, Chagas disease, leishmaniasis, amebiasis, and giardiasis, which together threaten millions of people around the world. In addition, most of the classic parasitic diseases due to protozoa are zoonotic. Understanding the biology of these organisms plays a relevant role in combating these diseases. Using homology inference and comparative genomics, this study targeted 3 protozoan species from different Phyla: Cryptosporidium muris (Apicomplexa), Entamoeba invadens (Amoebozoa), and Trypanosoma grayi (Euglenozoa). In this study, we propose a new approach for the identification of homologs, based on the reconciliation of the results of 2 different homology inference software programs. Our results showed that 46.1% (59/128) of the groups inferred by our reconciliation approach could be validated using this methodology. These validated groups are here called homologous Supergroups and were compared with SUPERFAMILY and Pfam Clans.