Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.06.12.598716

Escalation of genome defense capacity enables control of an expanding meiotic driver

Abstract

SummaryFrom RNA interference to chromatin silencing, diverse genome defense pathways silence selfish genetic elements to safeguard genome integrity1,2. Despite their diversity, different defense pathways share a modular organization, where numerous specificity factors identify diverse targets and common effectors silence them. In the PIWI-interacting RNA (piRNA) pathway, which controls selfish elements in the metazoan germline, diverse target RNAs are first identified by complementary base pairing with piRNAs and then silenced by PIWI-clade nucleases via enzymatic cleavage1,3. Such a binary architecture allows the defense systems to be readily adaptable, where new targets can be captured via the innovation of new specificity factors4,5. Thus, our current understanding of genome defense against lineage-specific selfish genes has been largely limited to the evolution of specificity factors, while it remains poorly understood whether other types of innovations are required. Here, we describe a new type of innovation, which escalates the defense capacity of the piRNA pathway to control a recently expanded selfish gene in Drosophila melanogaster. Through an in vivo RNAi screen for repressors of Stellate--a recently evolved and expanded selfish meiotic driver6-8--we discovered a novel defense factor, Trailblazer. Trailblazer is a transcription factor that promotes the expression of two PIWI-clade nucleases, Aub and AGO3, to match Stellate in abundance. Recent innovation in the DNA-binding domain of Trailblazer enabled it to drastically elevate Aub and AGO3 expression in the D. melanogaster lineage, thereby escalating the silencing capacity of the piRNA pathway to control expanded Stellate and safeguard fertility. As copy-number expansion is a recurrent feature of diverse selfish genes across the tree of life9-12, we envision that augmenting the defense capacity to quantitatively match selfish genes is likely a repeatedly employed defense strategy in evolution.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Chen, P., Pan, K. C., Park, E. H., Luo, Y., Lee, G. Y. C., Aravin, A. A.. 2024-06-14. Escalation of genome defense capacity enables control of an expanding meiotic driver. https://doi.org/10.1101/2024.06.12.598716

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

KEEP EXPLORING

Related preprints

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↗

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↗

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↗