Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.11.20.689590

INS-17, an insulin-receptor ligand, confers specificity in adult IIS-regulated phenotypes in C. elegans

Abstract

Insulin/IGF growth factor (IGF) signaling (IIS) is a pleiotropic signaling pathway that functions across tissues to coordinate phenotypic changes in response to nutrient status. Thus, the ubiquity of the IIS pathway hinders efforts to elucidate the mechanisms driving specific IIS-related phenotypes, Previous research in the nematode worm C. elegans has demonstrated that loss of function of the IGF transmembrane receptor (IR) ortholog, DAF-2, results in a doubled lifespan and enhanced learning and memory behaviors in young and aged animals. However, these findings are the result of reducing DAF-2 receptor function rather than modulating ligand-receptor interactions. In the current study, we aimed to dissect ligand-receptor interactions that may regulate associative behaviors apart from canonical IIS lifespan phenotypes in C. elegans. To this end, we performed targeted genetic screening of Insulin-like Peptides (ILPs) previously identified as DAF-2 antagonists to test their role in learning and memory phenotypes. We discovered that only a single uncharacterized ILP, INS-17, is required for learning and memory. We also demonstrate that INS-17 is sufficient to confer extended memory ability and can promote the maintenance of learning and memory with age. Additionally, we observe that ins-17 regulates learning and memory ability independent of lifespan, uncoupling IIS-mutant phenotypes. We find that regulation of the ins-17 genetic locus explains its unique requirement among ILP for learning and memory behaviors. Finally, we found that INS-17 may act to signal a state of nutrient deprivation that is required to properly process stimulus valence to promote advantageous behaviors. Our findings deepen the understanding of how IIS can regulate specific phenotypic outputs in response to changes in internal metabolic states.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Leptich, E. J., Vijayakumar, P., Pietryk, E. W., Williams, M. I., Arey, R. N.. 2025-11-21. INS-17, an insulin-receptor ligand, confers specificity in adult IIS-regulated phenotypes in C. elegans. https://doi.org/10.1101/2025.11.20.689590

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↗