Resumen

ROMERO, Pedro Eduardo  y  CASTILLO-VILCAHUAMAN, Camila. Data mining of DNA sequences submitted by Peruvian institutions to public genetic databases. Rev. peru biol. [online]. 2021, vol.28, n.1, e17867. ISSN 1727-9933.  http://dx.doi.org/10.15381/rpb.v28i1.17867.

Genetic diversity is an important component of biodiversity, and it is crucial for current efforts to protect and sustainably manage several organisms and habitats. As far as we know, there is only one work describing Peruvian genetic information stored in public databases. We aimed to update this previous work searching in four public databases that stored digital sequence information: Nucleotide, BioProject, PATRIC, BOLD. With this information, we comment on the contribution of Peruvian institutions during recent years. In Nucleotide, the largest database, Bacteria are the most sequenced organisms by Peruvian institutions (70.60%), pathogenic bacteria such as Pasteurella multocida, Neisseria meningitidis, and Vibrio parahaemolyticus were the most abundant. We found no sequence records from the Archaea domain. In BioProject, the most common sequence belongs to Salmonella enterica subsp. enterica serovar Infantis. In PATRIC, a database of pathogenic agents, Mycobacterium tuberculosis and Yersinia pestis had the highest number of entries. Finally, in BOLD, an exclusively Eukaryotic database, Chordata (Aves and Actinopterygii), Angiospermae, and Arthropoda (Insecta, and Arachnida) were the most frequent records. Our results would indicate research preferences of Peruvian institutions, focusing on infectious diseases and some Eukaryotic phyla. Although there has been a significant increase of DNA information submitted by Peruvian institutions since the last report, the genetic diversity reflected in these databases remains inconsistent with the diversity in the country. More efforts must be made to obtain genetic information from more underestimated taxonomic groups and to promote more genetic research in regional Peruvian institutions.

Palabras clave : Genetic diversity; public databases; biodiversity; Peru; data mining.

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