Susceptibility of field-collected nyssorhynchus darlingi to plasmodium spp. In western amazonian Brazil

• Autor(a) principal: Alonso, Diego Peres [UNESP]
• Data de Publicação: 2021
• Outros Autores: Alvarez, Marcus Vinicius Niz [UNESP], Ribolla, Paulo Eduardo Martins [UNESP], Conn, Jan E., de Oliveira, Tatiane Marques Porangaba, Sallum, Maria Anice Mureb
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.3390/genes12111693; http://hdl.handle.net/11449/233774
• topic: Chitinase; Cytochrome P450; GWAS; NextRAD; Nyssorhynchus darlingi

Mosquito susceptibility to Plasmodium spp. infection is of paramount importance for malaria occurrence and sustainable transmission. Therefore, understanding the genetic features underlying the mechanisms of susceptibility traits is pivotal to assessing malaria transmission dynamics in endemic areas. The aim of this study was to investigate the susceptibility of Nyssorhynchus darlingi—the dominant malaria vector in Brazil—to Plasmodium spp. using a reduced representation genome-sequencing protocol. The investigation was performed using a genome-wide association study (GWAS) to identify mosquito genes that are predicted to modulate the susceptibility of natural populations of the mosquito to Plasmodium infection. After applying the sequence alignment protocol, we generated the variant panel and filtered variants; leading to the detection of 202,837 SNPs in all specimens analyzed. The resulting panel was used to perform GWAS by comparing the pool of SNP variants present in Ny. darlingi infected with Plasmodium spp. with the pool obtained in field-collected mosquitoes with no evidence of infection by the parasite (all mosquitoes were tested separately using RT-PCR). The GWAS results for infection status showed two statistically significant variants adjacent to important genes that can be associated with susceptibility to Plasmodium infec-tion: Cytochrome P450 (cyp450) and chitinase. This study provides relevant knowledge on malaria transmission dynamics by using a genomic approach to identify mosquito genes associated with susceptibility to Plasmodium infection in Ny. darlingi in western Amazonian Brazil.