Physical Mapping of Two Nested Fixed Inversions in the X Chromosome of the Malaria Mosquito Anopheles messeae

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Abstract

Chromosomal inversions play an important role in genome evolution, speciation and adaptation of organisms to diverse environments. Mapping and characterization of inversion breakpoints can be useful for describing mechanisms of rearrangements and identification of genes involved in diversification of species. Mosquito species of the Maculipennis Subgroup include dominant malaria vectors and nonvectors in Eurasia, but breakpoint regions of inversions fixed between species have not been mapped to the genomes. Here, we use the physical genome mapping approach to identify breakpoint regions of the X chromosome inversions fixed between Anopheles atroparvus and the most widely spread sibling species An. messeae. We mapped breakpoint regions of two large nested fixed inversions (~13 Mb and ~ 10 Mb in size) using fluorescence in situ hybridization of 53 gene markers with polytene chromosomes of An. messeae. The DNA probes were designed based on gene sequences of the annotated An. atroparvus genome. The two inversions resulted in five syntenic blocks, of which only two syntenic blocks (encompassing at least 179 annotated genes in the An. atroparvus genome) changed their position and orientation in the X chromosome. Analysis of the An. atroparvus genome revealed enrichment of DNA transposons in sequences homologous to three of four breakpoint regions suggesting the presence of “hot spots” for rearrangements in mosquito genomes. Our study demonstrated that the physical genome mapping approach can be successfully applied to identification of inversion breakpoint regions in insect species with polytene chromosomes.

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Soboleva, E. S., Kirilenko, K. M., Fedorova, V. S., Kokhanenko, A. A., Artemov, G. N., & Sharakhov, I. V. (2023). Physical Mapping of Two Nested Fixed Inversions in the X Chromosome of the Malaria Mosquito Anopheles messeae. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13883 LNBI, pp. 84–99). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-36911-7_6

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