Whole Genome Sequences of Aedes aegypti (Linn.) Field Isolates from Southern India
Bernard, V.; Moudgalya, S.; Reegan, D.; Sreekanthreddy, P.; Mohan, A.; Subramanya, H. S.; Vembar, S. S.; Ghosh, S.
Show abstract
Aedes spp. mosquitoes are a major health concern as they transmit several viral pathogens resulting in millions of deaths annually around the world. This is compounded by the emergence of insecticide-resistant strains and global warming, which could expose more than half of the world's population to Aedes-borne diseases in the future. Therefore, a comprehensive understanding of vector biology and the genomic basis of phenotypes such as insecticide resistance in natural populations are of paramount importance. Here, we sequenced the genome of Aedes aegypti mosquitos sampled from dengue-endemic areas and investigated the genetic variations between the previously reported laboratory-reared strain and our field isolates. The mosquito genomic DNA was used for paired-end sequencing using the Illumina platform. The reads were used for template-based assembly and mapped to the Aedes aegypti reference genome. Stringent parameters and multiple variant calling methods were used to identify unique single nucleotide variants (SNVs) and insertions-deletions (indels) and mapped to the Aedes chromosomes to create a draft consensus genome. Gene Ontology analyses was performed on the variant-enriched genes while two gene families involved in insecticide resistance were used for comparative sequence and phylogenetic analyses. Comparative sequence variant analyses showed that the majority of the high-quality variants in our samples mapped to non-coding regions of the genome, while gene ontology analyses of genic variants revealed enrichment of terms relevant to drug binding and insecticide resistance. Importantly, one mutation implicated in pyrethroid resistance was found in one Aedes sample. This is the first report of genome sequences of A. aegypti field isolates from India which reveals variants specific to the wild population. This is a useful resource which will facilitate development of robust integrated vector control strategies for management of Aedes-borne diseases through genetic manipulation of local mosquito populations.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Polymorphism analyses and protein modelling inform on functional specialization of Piwi clade genes in the arboviral vector Aedes albopictus 97%
- The influence of roads on the fine-scale population genetic structure of the dengue vector Aedes aegypti (Linnaeus) 96%
- Sex-specific distribution and classification of Wolbachia infections and mitochondrial DNA haplogroups in Aedes albopictus from the Indo-Pacific 96%
Similar papers in this journal
- Sex-based de novo transcriptome assemblies of the parasitoid wasp Encarsia suzannae, a host of the manipulative heritable symbiont Cardinium hertigii 94%
- Aedes mosquito distribution across urban and peri-urban areas of Kinshasa city, Democratic Republic of Congo 94%
- Whole Genome Sequencing and Assembly of the House Sparrow, Passer domesticus 94%
Similar papers in this journal
- Aedes koreicus, a vector on the rise: pan-European genetic patterns, mitochondrial and draft genome sequencing 95%
- Evaluation of intron-1 of odorant-binding protein-1 of Anopheles stephensi as a marker for the identification of biological forms or putative sibling species 95%
- Genetic analysis of Aedes aegypti captured in two international airports serving the Greater Tokyo area during 2012-2015 95%
Similar papers in this journal
Similar papers in this journal
- Genetic stability of Aedes aegypti populations following invasion by wMel Wolbachia 96%
- Whole genome comparisons reveal panmixia among fall armyworm (Spodoptera frugiperda) from diverse locations 94%
- Precise annotation of tick mitochondrial genomes reveals multiple STR variation and one transposon-like element 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.