bioRxivGeneticsPreprint
The Y chromosome gene draupnir reveals constraints on engineering Y-linked sex-ratio distorters in malaria mosquitoes
Rocco D'Amato, Elad Shmuel YonahiD, Alessia CagnettiiD, Flávia KrsticeviciD, Arad SarigiD, Salvatore Di Martino, Alessandro Trusso, Roberto GaliziiD, Nikolai WindbichleriD, Alekos SimoniiD, Philippos Aris PapathanosiD
Abstract
Y chromosome sex distorters offer a powerful strategy for mosquito population suppression, but their implementation is constrained by the transcriptional silencing of Y-linked transgenes during spermatogenesis. To investigate how endogenous Y genes evade this repression, we characterized draupnir (formerly YG5), a multicopy Y-linked gene of Anopheles gambiae encoding a Zip3-like meiotic protein. Comparative genomic and phylogenetic analyses revealed that draupnir originated through duplication of the autosomal paralog skirnir, itself derived from the ancestral recombination factor vilya, followed by amplification into a tandem array on the Y chromosome. We show that draupnir is actively transcribed during meiosis, making it the only known Y-linked gene expressed during mosquito spermatogenesis. To test whether its regulatory region is sufficient to confer sperm-specific expression from the Y chromosome, we cloned the draupnir promoter to drive expression of an X-chromosome shredder. When inserted on an autosome, the construct drove meiotic expression and strong sex-ratio distortion in the progeny of transgenic males. In contrast, the same construct inserted on the Y chromosome was transcriptionally silent and produced balanced sex ratios. These results demonstrate that draupnir expression depends on its native genomic context within a multicopy Y-linked array and that its promoter alone cannot overcome transcription silencing. Our findings reveal a fundamental constraint on Y-chromosome-based genetic control strategies and point to future approaches for enabling transcription from otherwise repressed sex chromosomes.
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
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