Marker-assisted mapping enables effective forward genetic analysis in the arboviral vector Aedes aegypti, a species with vast recombination deserts
Chujia CheniD, Austin ComptoniD, Katerina NikolouliiD, Aihua WangiD, Azadeh AryaniD, Atashi SharmaiD, Yumin Qi, Camden Dellinger, Melanie HempeliD, Mark PottersiD, Antonios A. AugustinosiD, David W. SeversoniD, Kostas BourtzisiD, Zhijian Jake TuiD
Abstract
Aedes aegypti is a major vector of arboviruses that cause dengue, chikungunya, yellow fever and Zika. Although recent success in reverse genetics has facilitated rapid progress in basic and applied research, integration of forward genetics with modern technologies remains challenging in this important species, as up-to-47% of its chromosome is refractory to genetic mapping due to extremely low rate of recombination. Here we report the development of a marker-assisted-mapping (MAM) strategy to readily screen for and genotype only the rare but informative recombinants, drastically increasing both the resolution and signal-to-noise ratio. Using MAM, we mapped a transgene that was inserted in a >100 Mb recombination desert and a sex-linked spontaneous red-eye (re) mutation just outside the region. We subsequently determined, by CRISPR/Cas9-mediated knockout, that cardinal is the causal gene of re, which is the first forward genetic identification of a causal gene in Ae. aegypti. This study provides the molecular foundation for using gene-editing to develop versatile and stable genetic sexing methods by improving upon the current re-based genetic sexing strains. MAM does not require densely populated markers and can be readily applied throughout the genome to facilitate the mapping of genes responsible for insecticide- and viral-resistance. By enabling effective forward genetic analysis, MAM bridges a significant gap in establishing Ae. aegypti as a model system for research in vector biology. As large regions of suppressed recombination are also common in other plant and animal species including those of economic significance, MAM will have broad applications beyond vector biology.
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