bioRxiv : the preprint server for biology最新文献

{"title":"Expanding the HP1a-binding consensus and molecular grammar for heterochromatin assembly.","authors":"Serafin U Colmenares, Shingo Tsukamoto, Collin Hickmann, Lucy D Brennan, Mohammad Khavani, Mohammad Mofrad, Gary Karpen","doi":"10.1101/2024.12.03.626544","DOIUrl":"10.1101/2024.12.03.626544","url":null,"abstract":"<p><p>The recruitment of Heterochromatin Protein 1 (HP1) partners is essential for heterochromatin assembly and function, yet our knowledge regarding their organization in heterochromatin remains limited. Here we show that interactors engage the Drosophila HP1 (HP1a) dimer through a degenerate and expanded form of the previously identified PxVxL motif, which we now term HP1a Access Codes (HACs). These HACs reside in disordered regions, possess high conservation among Drosophila homologs, and contain alternating hydrophobic residues nested in a cluster of positively charged amino acids. These findings and molecular dynamics simulations identify key electrostatic interactions that modulate HP1a-binding strength and provide a dramatically improved HP1a-binding consensus motif that can reveal protein partners and the molecular grammar involved in heterochromatin assembly. We propose HP1a acts as a scaffold for other heterochromatin components containing HAC motifs, which in turn may regulate the function and higher order structure of the heterochromatin compartment.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11642857/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142831800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cervicovaginal microbial features predict Chlamydia trachomatis spread to the upper genital tract of infected women.","authors":"Sangmi Jeong, Tammy S Tollison, Hayden Brochu, Ian Huntress, Kacy S Yount, Xiaojing Zheng, Toni Darville, Catherine M O'Connell, Xinxia Peng","doi":"10.1101/2024.11.26.625070","DOIUrl":"10.1101/2024.11.26.625070","url":null,"abstract":"<p><strong>Introduction: </strong>Chlamydia trachomatis (CT) infection can lead to pelvic inflammatory disease, infertility and other reproductive sequelae when it ascends to the upper genital tract. Factors including chlamydial burden, co-infection with other sexually-transmitted bacterial pathogens and oral contraceptive use influence risk for upper genital tract spread. Cervicovaginal microbiome composition influences CT susceptibility and we investigated if it contributes to spread by analyzing amplicon sequence variants (ASVs) derived from the V4 region of 16S rRNA genes in vaginal samples collected from women at high risk for CT infection and for whom endometrial infection had been determined.</p><p><strong>Results: </strong>Participants were classified as CT negative (CT-, n=77), CT positive at the cervix (Endo-, n=77), or CT positive at both cervix and endometrium (Endo+, n=66). Although we were unable to identify many significant differences between CT infected and uninfected women, differences in abundance of ASVs representing Lactobacillus iners and L. crispatus subspecies but not dominant lactobacilli were detected. Twelve informative ASVs predicted endometrial chlamydial infection (AUC=0.74), with CT ASV abundance emerging as a key predictor. We also observed a positive correlation between levels of cervically secreted cytokines previously associated with CT ascension and abundance of the informative ASVs.</p><p><strong>Conclusion: </strong>Our findings suggest that vaginal microbial community members may influence chlamydial spread directly by nutrient limitation and/or disrupting endocervical epithelial integrity and indirectly by modulating pro-inflammatory signaling and/or homeostasis of adaptive immunity. Further investigation of these predictive microbial factors may lead to cervicovaginal microbiome biomarkers useful for identifying women at increased risk for disease.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11623589/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142804167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Caspase-Activated DNase localizes to cancer causing translocation breakpoints during cell differentiation.","authors":"Dalal Alsowaida, Brian D Larsen, Sarah Hachmer, Mehri Azimi, Eric Arezza, Steve Brunette, Steven Tur, Carmen G Palii, Bassam Albraidy, Claus S Sorensen, Marjorie Brand, F Jeffrey Dilworth, Lynn A Megeney","doi":"10.1101/2024.09.24.614809","DOIUrl":"10.1101/2024.09.24.614809","url":null,"abstract":"<p><p>Caspase activated DNase (CAD) induced DNA breaks promote cell differentiation and therapy-induced cancer cell resistance. CAD targeting activity is assumed to be unique to each condition, as differentiation and cancer genesis are divergent cell fates. Here, we made the surprising discovery that a subset of CAD-bound targets in differentiating muscle cells are the same genes involved in the genesis of cancer-causing translocations. In muscle cells, a prominent CAD-bound gene pair is <i>Pax7</i> and <i>Foxo1a</i>, the mismatched reciprocal loci that give rise to alveolar rhabdomyosarcoma. We show that CAD-targeted breaks in the <i>Pax7</i> gene are physiologic to reduce <i>Pax7</i> expression, a prerequisite for muscle cell differentiation. A cohort of these CAD gene targets are also conserved in early differentiating T cells and include genes that spur leukemia/lymphoma translocations. Our results suggest the CAD targeting of translocation prone oncogenic genes is non-pathologic biology and aligns with initiation of cell fate transitions.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11463586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142396675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The conserved ATPase PCH-2 controls the number and distribution of crossovers by antagonizing their formation in <i>C. elegans</i>.","authors":"Bhumil Patel, Maryke Grobler, Alberto Herrera, Elias Logari, Valery Ortiz, Needhi Bhalla","doi":"10.1101/2024.08.13.607819","DOIUrl":"10.1101/2024.08.13.607819","url":null,"abstract":"<p><p>Meiotic crossover recombination is essential for both accurate chromosome segregation and the generation of new haplotypes for natural selection to act upon. This requirement is known as crossover assurance and is one example of crossover control. While the conserved role of the ATPase, PCH-2, during meiotic prophase has been enigmatic, a universal phenotype when <i>pch-2</i> or its orthologs are mutated is a change in the number and distribution of meiotic crossovers. Here, we show that PCH-2 controls the number and distribution of crossovers by antagonizing their formation. This antagonism produces different effects at different stages of meiotic prophase: early in meiotic prophase, PCH-2 prevents double strand breaks from becoming crossover-eligible intermediates, limiting crossover formation at sites of initial double strand break formation and homolog interactions. Later in meiotic prophase, PCH-2 winnows the number of crossover-eligible intermediates, contributing to the designation of crossovers and ultimately, crossover assurance. We also demonstrate that PCH-2 accomplishes this regulation through the meiotic HORMAD, HIM-3. Our data strongly support a model in which PCH-2's conserved role is to remodel meiotic HORMADs throughout meiotic prophase to destabilize crossover-eligible precursors, coordinate meiotic recombination with synapsis, and contribute to the progressive implementation of meiotic recombination, guaranteeing crossover control.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343117/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142057860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of peptide structural conformations with AlphaFold2.","authors":"Alexander M Ille, Christopher Markosian, Stephen K Burley, Renata Pasqualini, Wadih Arap","doi":"10.1101/2024.12.03.626727","DOIUrl":"10.1101/2024.12.03.626727","url":null,"abstract":"<p><p>Protein structure prediction <i>via</i> artificial intelligence/machine learning (AI/ML) approaches has sparked substantial research interest in structural biology and adjacent disciplines. More recently, AlphaFold2 (AF2) has been adapted for the prediction of multiple structural conformations in addition to single-state structures. This novel avenue of research has focused on proteins (typically 50 residues in length or greater), while multi-conformation prediction of shorter peptides has not yet been explored in this context. Here, we report AF2-based structural conformation prediction of a total of 557 peptides (ranging in length from 10 to 40 residues) for a benchmark dataset with corresponding nuclear magnetic resonance (NMR)-determined conformational ensembles. <i>De novo</i> structure predictions were accompanied by structural comparison analyses to assess prediction accuracy. We found that the prediction of conformational ensembles for peptides with AF2 varied in accuracy <i>versus</i> NMR data, with average root-mean-square deviation (RMSD) among structured regions under 2.5 Å and average root-mean-square fluctuation (RMSF) differences under 1.5 Å. Our results reveal notable capabilities of AF2-based structural conformation prediction for peptides but also underscore the necessity for interpretation discretion.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11642853/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142831827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Myeloid Protein Kinase C - Epsilon as a Novel Atheroprotective Gene.","authors":"Alexis T Wells, Michelle M Shen, Redwan H Binrouf, Anna E D'Amico, Ramon Bossardi Ramos, Michelle R Lennartz","doi":"10.1101/2024.12.09.627650","DOIUrl":"10.1101/2024.12.09.627650","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Atherosclerosis is a lipid mediated chronic inflammatory disease driven my macrophages (MØ). Protein Kinase C - epsilon (PKCɛ) is is a serine/threonine kinase involved in diverse cellular processes such as migration, growth, differentiation, and survival. PKCɛ is known to act in a context dependent manner within heart, however, its role in atherosclerosis is unknown.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Bone marrow derived MØ from global PKCɛ KO mice were examined for impact of lipid metabolism and inflammatory factor secretion. Public geneset analysis assessed raw counts of PKCɛ to determine translational relevance. To determine the function myeloid PKCɛ on atherosclerosis a novel murine model was generated using LysM Cre technology. After its characterization, human-like hypercholesterolemia was induced to assess plaque morphology in WT mice or mice lacking myeloid PKCɛ.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Public geneset analysis of human atherosclerotic plaque tissue revealed that PKCɛ expression is inversely correlated with plaque size and vulnerability. Similarly, peritoneal MØ from hypercholesterolemic mice have significantly lower PKCɛ expression. As MØ play a major role in atherogenesis, we generated a mouse strain with PKCɛ selectively deleted in the myeloid lineage (mɛKO). qPCR revealed no basal differences between genotypes in the expression of lipid uptake receptors, efflux transporters, or inflammatory markers. However, upon lipid loading, mɛKO MØs retained significantly more cholesterol than WT. Human-like hypercholesterolemia was induced in WT and mɛKO mice and assessed for lesion area and plaque morphology in aortic arches and aortic roots. We found that, compared to WT, the lesion area in mɛKO mice was significantly larger, more necrotic, had larger foam cells, and thinner collagen caps.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Loss of myeloid PKCɛ promotes atherosclerosis as determined by larger lesions, more necrosis, thinner plaque caps). Together, these data identify myeloid PKCɛ as a novel atheroprotective gene, laying the foundation for mechanistic studies on the signaling networks responsible for the phenotype.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Highlights: &lt;/strong&gt;A novel murine model in which PKCɛ is floxed (PKCɛ &lt;sup&gt;fl/fl&lt;/sup&gt; ) on both alleles haas been generated, backcrossed, and deposited into Jackson Laboratories. PKCε &lt;sup&gt;fl/fl&lt;/sup&gt; mice have been crossed with those on the LysM Cre background thereby deleting PKCε from myeloid cells (mεKO). Deletion of PKCε has no basal affects on other PKC isoforms, lipid handling markers, or inflammatory markers.Upon stimulation with lopid loading in vitro or hypercholesterolemia in vivo, mεKO BMDMs retain more cholesterol and mεKO mice develop a more vulnerable plaque phenotype (i.e. larger lesions, more necrosis, thimmer plaque caps).These findings provide a rationale for the need to identify mediators in the PKCε signaling pathway responsible for protection against vulnerabl","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142879329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LM-Merger: A workflow for merging logical models with an application to gene regulation.","authors":"Luna Xingyu Li, Boris Aguilar, John H Gennari, Guangrong Qin","doi":"10.1101/2024.09.13.612961","DOIUrl":"10.1101/2024.09.13.612961","url":null,"abstract":"<p><strong>Motivation: </strong>Gene regulatory network (GRN) models provide mechanistic understanding of genetic interactions that regulate gene expression and, consequently, influence cellular behavior. Dysregulated gene expression plays a critical role in disease progression and treatment response, making GRN models a promising tool for precision medicine. While researchers have built many models to describe specific subsets of gene interactions, more comprehensive models that cover a broader range of genes are challenging to build. This necessitates the development of automated approaches for merging existing models.</p><p><strong>Results: </strong>We present LM-Merger, a workflow for semi-automatically merging logical GRN models. The workflow consists of five main steps: (a) model identification, (b) model standardization and annotation, (c) model verification, (d) model merging, and (d) model evaluation. We demonstrate the feasibility and benefit of this workflow with two pairs of published models pertaining to acute myeloid leukemia (AML). The integrated models were able to retain the predictive accuracy of the original models, while expanding coverage of the biological system. Notably, when applied to a new dataset, the integrated models outperformed the individual models in predicting patient response. This study highlights the potential of logical model merging to advance systems biology research and our understanding of complex diseases.</p><p><strong>Availability and implementation: </strong>The workflow and accompanying tools, including modules for model standardization, automated logical model merging, and evaluation, are available at https://github.com/IlyaLab/LogicModelMerger/.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11429764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142336156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Functional Connectome Mediating Circadian Synchrony in the Suprachiasmatic Nucleus.","authors":"K L Nikhil, Bharat Singhal, Daniel Granados-Fuentes, Jr-Shin Li, István Z Kiss, Erik D Herzog","doi":"10.1101/2024.12.06.627294","DOIUrl":"10.1101/2024.12.06.627294","url":null,"abstract":"<p><p>Circadian rhythms in mammals arise from the spatiotemporal synchronization of ~20,000 neuronal clocks in the Suprachiasmatic Nucleus (SCN). While anatomical, molecular, and genetic approaches have revealed diverse cell types and signaling mechanisms, the network wiring that enables SCN cells to communicate and synchronize remains unclear. To overcome the challenges of revealing functional connectivity from fixed tissue, we developed MITE (Mutual Information & Transfer Entropy), an information theory approach that infers directed cell-cell connections with high fidelity. By analyzing 3447 hours of continuously recorded clock gene expression from 9011 cells in 17 mice, we found that the functional connectome of SCN was highly conserved bilaterally and across mice, sparse, and organized into a dorsomedial and a ventrolateral module. While most connections were local, we discovered long-range connections from ventral cells to cells in both the ventral and dorsal SCN. Based on their functional connectivity, SCN cells can be characterized as circadian signal generators, broadcasters, sinks, or bridges. For example, a subset of VIP neurons acts as hubs that generate circadian signals critical to synchronize daily rhythms across the SCN neural network. Simulations of the experimentally inferred SCN networks recapitulated the stereotypical dorsal-to-ventral wave of daily PER2 expression and ability to spontaneously synchronize, revealing that SCN emergent dynamics are sculpted by cell-cell connectivity. We conclude that MITE provides a powerful method to infer functional connectomes, and that the conserved architecture of cell-cell connections mediates circadian synchrony across space and time in the mammalian SCN.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661124/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142879493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>iModMix</i>: Integrative Module Analysis for Multi-omics Data.","authors":"Isis Narváez-Bandera, Ashley Lui, Yonatan Ayalew Mekonnen, Vanessa Rubio, Noah Sulman, Christopher Wilson, Hayley D Ackerman, Oscar E Ospina, Guillermo Gonzalez-Calderon, Elsa Flores, Qian Li, Ann Chen, Brooke Fridley, Paul Stewart","doi":"10.1101/2024.11.12.623208","DOIUrl":"10.1101/2024.11.12.623208","url":null,"abstract":"<p><strong>Summary: </strong>The integration of metabolomics with other omics (\"multi-omics\") offers complementary insights into disease biology. However, this integration remains challenging due to the fragmented landscape of current methodologies, which often require programming experience or bioinformatics expertise. Moreover, existing approaches are limited in their ability to accommodate unidentified metabolites, resulting in the exclusion of a significant portion of data from untargeted metabolomics experiments. Here, we introduce <i>iModMix - Integrative Module Analysis for Multi-omics Data</i>, a novel approach that uses a graphical lasso to construct network modules for integration and analysis of multi-omics data. <i>iModMix</i> uses a horizontal integration strategy, allowing metabolomics data to be analyzed alongside proteomics or transcriptomics to explore complex molecular associations within biological systems. Importantly, it can incorporate both identified and unidentified metabolites, addressing a key limitation of existing methodologies. <i>iModMix</i> is available as a user-friendly R Shiny application that requires no programming experience (https://imodmix.moffitt.org), and it includes example data from several publicly available multi-omic studies for exploration. An R package is available for advanced users (https://github.com/biodatalab/iModMix).</p><p><strong>Availability and implementation: </strong>Shiny application: https://imodmix.moffitt.org. The R package and source code: https://github.com/biodatalab/iModMix.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11601443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142742079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inferring gene-pathway associations from consolidated transcriptome datasets: an interactive gene network explorer for <i>Tetrahymena thermophila</i>.","authors":"Michael A Bertagna, Lydia J Bright, Fei Ye, Yu-Yang Jiang, Debolina Sarkar, Ajay Pradhan, Santosh Kumar, Shan Gao, Aaron P Turkewitz, Lev M Z Tsypin","doi":"10.1101/2024.12.12.627356","DOIUrl":"10.1101/2024.12.12.627356","url":null,"abstract":"<p><p>Although an established model organism, <i>Tetrahymena thermophila</i> remains comparatively inaccessible to high throughput screens, and alternative bioinformatic approaches still rely on unconnected datasets and outdated algorithms. Here, we report a new approach to consolidating RNA-seq and microarray data based on a systematic exploration of parameters and computational controls, enabling us to infer functional gene associations from their co-expression patterns. To illustrate the power of this approach, we took advantage of new data regarding a previously studied pathway, the biogenesis of a secretory organelle called the mucocyst. Our untargeted clustering approach recovered over 80% of the genes that were previously verified to play a role in mucocyst biogenesis. Furthermore, we tested four new genes that we predicted to be mucocyst-associated based on their co-expression and found that knocking out each of them results in mucocyst secretion defects. We also found that our approach succeeds in clustering genes associated with several other cellular pathways that we evaluated based on prior literature. We present the <i>Tetrahymena</i> Gene Network Explorer (TGNE) as an interactive tool for genetic hypothesis generation and functional annotation in this organism and as a framework for building similar tools for other systems.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142879412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}