Search bioRxiv⌕ Search

bioRxiv · 10.64898/2025.12.02.691955

WormTagDB: A Systematic Survey of Endogenously Tagged Proteins in C. elegans and Roadmap Towards the Tagged Proteome

Abstract

Endogenous protein tagging in Caenorhabditis elegans enables direct visualization and manipulation of proteins in vivo, providing native readouts of expression, localization, and dynamics. No coordinated effort currently exists to comprehensively tag proteins on a large scale, resulting in patchy coverage that limits comprehensive proteome analyses. We systematically reviewed 2,500 primary research articles, identifying 778 that report novel endogenous tags, and integrated these with the Caenorhabditis Genetics Center strain records to catalog >90% of all existing tagged alleles. In total, we found that 1,554 unique genes (~8% of the proteome) have been endogenously tagged. Gene Ontology enrichment analysis revealed that cytoskeletal proteins, transcription factors, and RNA-binding proteins dominate the tagged proteome, while membrane proteins, metabolic enzymes, and mitochondrial components remain largely untagged, reflecting both technical barriers and research priorities that have shaped the last decade of tagging efforts. We created WormTagDB (https://wormtagdb.rc.duke.edu), an interactive, community-updatable resource that consolidates all known endogenously tagged alleles and provides precomputed CRISPR guide and homology-arm primer designs for N- and C-terminal knock-ins across all protein-coding genes. This will enable researchers to easily identify existing alleles to prevent redundant strain generation and rapidly initiate new knock-in experiments. A systematic effort to tag every C. elegans gene would deliver the first complete metazoan visual proteome, providing comprehensive insights into protein localization, dynamics, and regulation, revealing new protein associations and molecular processes.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Leyhr, J., Chi, Q., Zeng, L., Shen, E.-Z., Zou, W., Sherwood, D.. 2025-12-05. WormTagDB: A Systematic Survey of Endogenously Tagged Proteins in C. elegans and Roadmap Towards the Tagged Proteome. https://doi.org/10.64898/2025.12.02.691955

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

KEEP EXPLORING

Related preprints

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↗

OPA1 controls mitochondrial dysfunction-driven liver fibrosis in MASLD

Progressive hepatic fibrosis is the principal determinant of morbidity and mortality in metabolic dysfunction-associated steatotic liver disease and steatohepatitis (MASLD/MASH). Mitochondrial dysfunction is a hallmark of MASH, and the release of mitochondrial damage-associated molecular patterns (mito-DAMPs) from injured hepatocytes can promote fibrosis. However, how mitochondrial dynamics and quality control shape the fibrotic response in MASLD/MASH remains unclear. Here, through large-scale genomic analyses of mitochondrial genes governing mitophagy, fusion and fission in human MASLD, with a power-equivalent sample size of approximately 700,000 individuals, we identify a strong association between hepatic fibrosis and the mitochondrial fusion factor dynamin-like GTPase optic atrophy 1 (OPA1). OPA1 transcripts and protein abundance in the liver epithelium were progressively dysregulated with advancing fibrosis. In mice, hepatocyte-specific OPA1 loss alone was sufficient to induce hepatic stellate cell activation and fibrosis in zone 3, promoted the release of mito-DAMPs into the circulation and exacerbated fibrosis in experimental MASH. These findings identify OPA1 as a central regulator of the hepatic fibrotic response and connect defective mitochondrial homeostasis to mito-DAMP release, hepatic stellate cell activation and fibrosis in MASLD.

genetics↗