bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2023.07.17.549342

Population suppression by release of insects carrying a dominant sterile homing gene drive targeting doublesex in Drosophila

Chen, W.·Guo, J.·Liu, Y.·Champer, J.
View original source ↗Export metadata ↓

Abstract

Gene drive alleles, which bias their own inheritance and increase in frequency, show great promise for blocking disease transmission or directly suppressing pest populations. The most common engineered drive system is the CRISPR homing drive, which converts wild-type alleles to drive alleles in the germline of drive heterozygotes by homology-directed repair after CRISPR cleavage. One successful homing drive example targets a female-specific exon in doublesex in Anopheles mosquitos, suppressing the population by inducing recessive sterility in female drive homozygotes. We found that in Drosophila melanogaster, a 3-gRNA drive disrupting the doublesex female exon resulted in a masculine phenotype and dominant female sterility. Resistance alleles formed by end-joining repair were also dominant sterile. This was likely caused by expression of male-specific transcripts in females with drive and resistance alleles, disrupting sex development. Based on this construct, we proposed a new pest suppression system called "Release of Insects carrying a Dominant-sterile Drive" (RIDD). This entails continuously releasing drive heterozygous males, with drive and resistance alleles causing sterility in females. The drive remains at high frequency longer than currently used dominant female-lethal alleles (RIDL) due to drive conversion in males, and drive alleles also cause sterility based on resistance, both substantial advantages. With weekly releases of drive males into a cage population with overlapping generations, our RIDD system targeting dsx reached 100% prevalence within 27 weeks, progressively reducing egg production and eventually causing total population collapse. RIDD combines the merits of homing gene drive and RIDL. It is powerful but self-limiting, unlike unconfined standard homing drives, allowing for targeted population suppression.

Explore related subjects

geneticsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Chen, W., Guo, J., Liu, Y., Champer, J.. 2023-07-17. Population suppression by release of insects carrying a dominant sterile homing gene drive targeting doublesex in Drosophila. https://doi.org/10.1101/2023.07.17.549342

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Generation of a transgenic cephalopod

Coleoid cephalopods (cuttlefish, octopus, and squid) are marine mollusks with elaborate nervous systems that support a diverse repertoire of complex behaviors. These include the neural control of the color, pattern, and texture of the skin, facilitating both adaptive camouflage and innate patterning that may reflect internal state. The development of transgenic cephalopods expressing fluorescent proteins, optogenetic actuators, and reporters of neural activity would contribute a new and important technology to cephalopod biology. The generation of transgenic cephalopods, however, has remained a major challenge. Here, we report the development of stable transgenic dwarf cuttlefish (Ascarosepion bandense) expressing ubiquitous nuclear-localized mScarlet, a red fluorescent protein. We evaluated multiple strategies for transgenesis, and established cuttlefish lines using both CRISPR and the transposons Sleeping Beauty and Minos. The stable expression of transgenes enabled live imaging of cell dynamics during embryonic development. The Minos transposon emerged as the most efficient transgenesis strategy and is adaptable to promoters and transgenes of choice. These strategies now enable the generation of diverse genetic tools for mechanistic studies of cephalopod biology.

genetics↗
bioRxiv2026

Large language model-based bibliometric evaluation of population descriptors in human genetics

As the use of population descriptors such as race, ethnicity, and ancestry have become increasingly common in modern genetics research, there have been growing calls to critically examine their use. Most notably, in 2023, the National Academies of Science, Engineering, and Medicine (NASEM) published a report titled Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field, which included eight specific and actionable recommendations for researchers to implement the ethical and accurate use of population descriptors in genetic research. Here, we use the 2023 NASEM report as a benchmark to analyze the use of population descriptors in genome-wide association studies (GWAS). We develop a general toolkit for large language model-based bibliometrics, operationalize the report's recommendations into an evaluation framework, and apply this framework to evaluate all 4,007 papers from the GWAS Catalog published between 2007 and 2025 with full text available on PubMedCentral. We find significant improvements in adherence to NASEM report recommendations over time. However, most improvements predate the publication of the NASEM report itself, suggesting the report functioned primarily as a synthesis of existing best practices rather than a catalyst for change. We conclude by highlighting opportunities for growth in the field of human genetics.

genetics↗
bioRxiv2026

Mitigating biases of rescaling in forward-in-time population genetic simulations

Forward-in-time population genetic simulations are widely used in evolutionary analyses, but simulating large populations and long genomic regions remains computationally demanding. To reduce this cost, parameter rescaling is widely employed, in which the original evolutionary process is approximated by one with a smaller population size and fewer generations. Recently, several studies using the SLiM simulator have raised concerns about the accuracy of this rescaling approach. In this study, we show that many of the biases reported in these studies can be mitigated by using a different simulation algorithm. These results reveal that the accuracy of parameter rescaling depends on how well the simulation algorithm preserves diffusion-limit properties under rescaling.

genetics↗