Biology subjects

Sun, W.

Publications and source records attributed to Sun, W..

At least 127 records · Page 7Linked to original sources

bioRxiv2024

G3BP1 Maintains Vascular Endothelial Barrier Integrity by Negatively Regulating the MYD88-ARNO-ARF6 Signaling Pathway

Endothelial permeability is essential for vascular function. This process is regulated by intercellular junctions, including adherens junctions (AJs) and tight junctions (TJs), which form the endothelial barrier and dynamically connect adjacent cells. However, the mechanisms that control endothelial permeability are not fully understood. We investigated the role of the RNA-binding protein G3BP1 in regulating endothelial permeability. We examined the effects of Loss of g3bp1 in conditional knockout mice and primary human HUVEC cells. We analyzed endothelial barrier integrity and permeability, focusing on AJ and TJ expression, under both normal and LPS-induced inflammatory conditions. Loss of g3bp1 in vascular endothelial cells decreased AJ and TJ expression, compromised barrier integrity, and increased permeability. These effects were exacerbated under LPS-induced inflammatory conditions. Loss of g3bp1 also increased the expression of MYD88, ARNO, and ARF6, and enhanced ARF6 activity. Mechanistically, G3BP1 bound to and stabilized MYD88 mRNA, negatively regulating the MYD88-ARNO-ARF6 signaling pathway. Inhibiting this pathway by reducing MYD88 or ARF6 expression, or inhibiting ARNO activity, restored AJ/TJ expression and barrier function in G3BP1-deficient models. Our findings identify G3BP1 as a novel regulator of vascular endothelial permeability. G3BP1 acts by negatively regulating the MYD88-ARNO-ARF6 signaling pathway. Targeting G3BP1 may be a potential therapeutic strategy for diseases associated with endothelial barrier dysfunction.

physiology↗

bioRxiv2024

SARS-CoV-2 Nsp15 antagonizes the cGAS-STING-mediated antiviral innate immune responses

Coronavirus (CoV) Nsp15 is a viral endoribonuclease (EndoU) with a preference for uridine residues. CoV Nsp15 is an innate immune antagonist which prevents dsRNA sensor recognition and stress granule formation by targeting viral and host RNAs. SARS-CoV-2 restricts and delays the host antiviral innate immune responses through multiple viral proteins, but the role of SARS-CoV-2 Nsp15 in innate immune evasion is not completely understood. Here, we generate an EndoU activity knockout rSARS-CoV-2Nsp15-H234A to elucidate the biological functions of Nsp15. Relative to wild-type rSARS-CoV-2, replication of rSARS-CoV-2Nsp15-H234A was significantly decreased in IFN-responsive A549-ACE2 cells but not in its STAT1 knockout counterpart. Transcriptomic analysis revealed upregulation of innate immune response genes in cells infected with rSARS-CoV-2Nsp15-H234A relative to wild-type virus, including cGAS-STING, cytosolic DNA sensors activated by both DNA and RNA viruses. Treatment with STING inhibitors H-151 and SN-011 rescued the attenuated phenotype of rSARS-CoV-2Nsp15-H234A. SARS-CoV-2 Nsp15 inhibited cGAS-STING-mediated IFN-{beta} promoter and NF-{kappa}B reporter activity, as well as facilitated the replication of EV-D68 and NDV by diminishing cGAS and STING expression and downstream innate immune responses. Notably, the decline in cGAS and STING was also apparent during SARS-CoV-2 infection. The EndoU activity was essential for SARS-CoV-2 Nsp15-mediated cGAS and STING downregulation, but not all HCoV Nsp15 share the consistent substrate selectivity. In the hamster model, rSARS-CoV-2Nsp15-H234A replicated to lower titers in the nasal turbinates and lungs and induced higher innate immune responses. Collectively, our findings exhibit that SARS-CoV-2 Nsp15 serves as a host innate immune antagonist by targeting host cGAS and STING. Significance statementHost innate immune system serves as the primary defense against pathogens, including SARS-CoV-2. Co-evolving with the hosts, viruses develop multiple approaches to escape the host surveillance. SARS-CoV-2 silences and dysregulates innate immune responses, and the chaos of antiviral IFN responses highly correlates to COVID-19 disease severity. Nsp15 is a conventional innate immune antagonist across coronaviruses, but the biological impact about SARS-CoV-2 Nsp15 is still unclear. Here, we provide a novel insight that SARS-CoV-2 Nsp15 hampers the expression of innate immune regulator - cGAS and STING via its endoribonuclease activity, then further ameliorates virus replication.

microbiology↗

bioRxiv2024

Genome-wide CRISPRi-seq identified ferredoxin-NADP reductase FprB as a synergistic target for gallium therapy in Pseudomonas aeruginosa

With the rise of antibiotic-resistant bacteria, non-antibiotic therapies like gallium are increasingly gaining attention. Gallium ions exhibit potent activity against multidrug-resistant bacteria and intravenous gallium nitrite is under phase 2 clinical trials to treat chronic Pseudomonas aeruginosa infections in cystic fibrosis patients. However, its clinical efficacy is constrained by the achievable peak concentration in human tissue. To address this limitation, we applied a genome-wide CRISPR interference approach (CRISPRi-seq), to identify potential synergistic targets with gallium. Through the systemic screening, we classified the essential genes by response time and growth reduction, pinpointing the most vulnerable therapeutic targets in this species. In addition, we identified a highly conserved gene fprB, encoding a ferredoxin-NADP+ reductase, the downregulation of which dramatically sensitized the cells to gallium. Using a null mutant, we confirmed the loss of fprB lowers the minimum inhibitory concentration of gallium from 320 {micro}M to 10 {micro}M and shifted galliums mode of action from bacteriostatic to bactericidal. Further investigation revealed that FprB plays a critical role in modulating oxidative stress induced by gallium, via control of the iron homeostasis and reactive oxygen species accumulation. Deleting fprB also enhanced galliums efficacy against biofilms formation and improved outcomes in murine lung infection model of P. aeruginosa, suggesting FprB as a promising drug target in combination with gallium. Overall, our data showed CRISPRi-seq as a powerful tool for systematic genetic analysis of P. aeruginosa, advancing identification of novel therapeutic targets.

microbiology↗

bioRxiv2024

Transmembrane channel-like 4 and 5 proteins at microvillar tips are potential ion channels and lipid scramblases

Microvilli--membrane bound actin protrusions on the surface of epithelial cells--are sites of critical processes including absorption, secretion, and adhesion. Increasing evidence suggests microvilli are mechanosensitive, but underlying molecules and mechanisms remain unknown. Here, we localize transmembrane channel-like proteins 4 and 5 (TMC4 and 5) and calcium and integrin binding protein 3 (CIB3) to microvillar tips in intestinal epithelial cells, near glycocalyx insertion sites. We find that TMC5 colocalizes with CIB3 in cultured cells and that a TMC5 fragment forms a complex with CIB3 in vitro. Homology and AlphaFold2 models reveal a putative ion permeation pathway in TMC4 and 5, and molecular dynamics simulations predict both proteins can conduct ions and perform lipid scrambling. These findings raise the possibility that TMC4 and 5 interact with CIB3 at microvillar tips to form a mechanosensitive complex, akin to TMC1 and 2, and CIB2 and 3, within the mechanotransduction channel complex at the tips of inner ear stereocilia.

cell biology↗

bioRxiv2024

Population dynamics in spatial suppression gene drive models and the effect of resistance, density dependence, and life history

Due to their super-Mendelian inheritance, gene drive systems have the potential to provide revolutionary solutions to critical public health and environmental problems. For suppression drives, however, spatial structure can cause "chasing" population dynamics that may postpone target population elimination or even cause the drive to fail. In chasing, wild-type individuals elude the drive and recolonize previously suppressed areas. The drive can re-enter these recolonized areas, but often is not able to catch up to wild-type and finally eliminate it. Previous methods for chasing detection are only suitable to limited parameter ranges. In this study with expanded parameter ranges, we found that the shift from chasing dynamics to static equilibrium outcomes is continuous as drive performance is reduced. To quantify this, we defined a Weighted Average Nearest Neighbor statistic to assess the clustering degree during chasing, while also characterizing chasing by the per-generation chance of population elimination and drive loss. To detect chasing dynamics in local areas and to detect the start of chasing, we implemented Density-Based Spatial Clustering of Applications with Noise. Using these techniques, we determined the effect of arena size, resistance allele formation rate in both the germline and in the early embryo from maternally deposited Cas9, life history and reproduction strategies, and density-dependent growth curve shape on chasing outcomes. We found that larger real-world areas will be much more vulnerable to chasing and that species with overlapping generations, fecundity-based density dependence, and concave density-dependent growth curves have smaller and more clustered local chasing with a greater chance of eventual population elimination. We also found that embryo resistance and germline resistance hinder drive performance in different ways. These considerations will be important for determining the necessary drive performance parameters needed for success in different species, and whether future drives could potentially be considered as release candidates.

ecology↗

bioRxiv2024

A Self-Assembling Immune-Featured Osteosarcoma Patient/PDX Derived Organoid Model and Biobank for Personalized Immune Therapy

Osteosarcoma (OS) exhibit intra- and inter-heterogeneity, complicating the exploration of effective therapeutic strategies. Traditional in vitro and in vivo models are limited in inheriting biological and genomic heterogeneities of OS patients, even in inheriting the features on tumor microenvironment. The prolonged generation time of current models makes the drug development of OS slow and is not suitable to clinically rapid timing. Here, we introduce methods for generating and biobanking patient/PDX-derived osteosarcoma organoids (OS PD(X)Os) that recapitulate the histological, biological and genomic features of their paired OS patients. OS PD(X)Os can be generated quickly with high reliability in vitro or transplanted to immunodeficient mice. We further demonstrate an immune-featured OS PD(X)O (named iOS) model and its method for testing personalized chemotherapy response, personalized immune therapeutic strategy and target drug development, such as a novel PRMT5MTA inhibitor ARPN2169 on MTAP-deleted OS. Our studies show that iOS models maintain many typical features of OS and could be rapidly employed to investigate patient-specific therapeutic strategies. Additionally, our biobank establishes a rich resource for basic, translational and even clinical OS researches.

cancer biology↗

bioRxiv2024

Exploit Spatially Resolved Transcriptomic Data to Infer Cellular Features from Pathology Imaging Data}

Digital pathology is a rapidly advancing field where deep learning methods can be employed to extract meaningful imaging features. However, the efficacy of training deep learning models is often hindered by the scarcity of annotated pathology images, particularly images with detailed annotations for small image patches or tiles. To overcome this challenge, we propose an innovative approach that leverages paired spatially resolved transcriptomic data to annotate pathology images. We demonstrate the feasibility of this approach and introduce a novel transfer-learning neural network model, STpath (Spatial Transcriptomics and pathology images), designed to predict cell type proportions or classify tumor microenvironments. Our findings reveal that the features from pre-trained deep learning models are associated with cell type identities in pathology image patches. Evaluating STpath using three distinct breast cancer datasets, we observe its promising performance despite the limited training data. STpath excels in samples with variable cell type proportions and high-resolution pathology images. As the influx of spatially resolved transcriptomic data continues, we anticipate ongoing updates to STpath, evolving it into an invaluable AI tool for assisting pathologists in various diagnostic tasks.

cancer biology↗

bioRxiv2024

Non-destructive in situ monitoring of structural changes of 3D tumor spheroids during the formation, migration, and fusion process

For traditional laboratory microscopy observation, the multi-dimensional, real-time, in situ observation of three-dimensional (3D) tumor spheroids has always been the pain point in cell spheroid observation. In this study, we designed a side-view observation petri dish/device that reflects light, enabling in situ observation of the 3D morphology of cell spheroids using conventional inverted laboratory microscopes. We used a 3D-printed handle and frame to support a first surface mirror, positioning the device within a cell culture petri dish to image cell spheroid samples. The imaging conditions, such as the distance between the mirror and the 3D spheroids, the light source, and the impact of the culture medium, were systematically studied to validate the in-situ side-view observation. The results proved that placing the surface mirror adjacent to the spheroids enables non-destructive in situ real-time tracking of tumor spheroid formation, migration, and fusion dynamics. The correlation between spheroid thickness and dark core appearance under light microscopy and the therapeutic effects of chemotherapy doxorubicin and Natural Killer cells on spheroidss 3D structure was investigated.

cancer biology↗

bioRxiv2024

The m6A Reader ECT1 Mediates Seed Germination via the DAG2-ECT1-PHYB Regulatory Cascade in Arabidopsis

The N6-methyladenosine (m6A) RNA modification, a significant epitranscriptomic mark, is integral to plant growth and development. m6A reader proteins are capable of recognizing m6A modifications to impact RNA metabolic and biological processes. Here, we discovered ECT1 as an m6A reader protein that directly binds to the m6A site and plays a role in positively regulating seed germination in the context of gibberellins (GAs). ECT1 undergoes m6A modification to ensure its own stability and engages in self-interaction to enhance its protein stability. Moreover, ECT1 establishes a regulatory circuit with DAG2, which has been reported to play a positive regulatory role in GA-mediated seed germination. We found that DAG2 directly binds to the ECT1 promoter to control its transcription. ECT1 modulates the mRNA stability of DAG2. Furthermore, we identified PHYB, which encodes a key photoreceptor controlling GA-regulated seed germination, as a common downstream target of DAG2 and ECT1. DAG2 and ECT1 regulate the expression of PHYB at the transcriptional and post-transcriptional levels, respectively. ECT1 binds directly to PHYB, thereby influencing its stability. While DAG2 binds to the PHYB promoter to regulate its transcription. Together, these results unveil that ECT1 participates in the m6A signaling pathway through complex and multifaceted molecular mechanisms, broadening the spectrum of m6A reader functions and deepening our insight into the m6A signaling network in Arabidopsis.

plant biology↗

bioRxiv2024

Supervised Deep Learning with Gene Annotation for Cell Classification

Gene-by-gene differential expression analysis is a widely used supervised approach for interpreting single-cell RNA-sequencing (scRNA-seq) data. However, modern scRNA-seq datasets often contain large numbers of cells, which can produce numerous differentially expressed genes with exceedingly small p-values but minimal effect sizes, and thus making biological interpretation difficult. To overcome this challenge, we developed Supervised Deep learning with gene ANnotation (SDAN), a method that integrates gene-annotation information with gene-expression profiles using a graph neural network. SDAN identifies functionally coherent gene sets that best classify cells, and the resulting cell-level classification scores can be aggregated to make individual-level predictions. We evaluated SDAN and two representative existing methods in three real-data applications to identify gene sets associated with severe COVID-19, dementia, and immunotherapy response in cancer. SDAN consistently outperformed alternative approaches by achieving two key objectives simultaneously: accurate classification of outcomes and unambiguous assignment of genes to gene sets of functionally related genes.

bioinformatics↗

bioRxiv2024

Single-cell transcriptomic changes in oligodendrocytes and precursors derived from Parkinson's disease patient-iPSCs with LRRK2-G2019S mutation

Despite extensive research, the contribution of the LRRK2 p.G2019S mutation to Parkinsons disease (PD) remains unclear. Recent findings indicate oligodendrocytes (ODCs) and their progenitors are vulnerable in PD pathogenesis. Notably, oligodendrocyte precursor cells (OPCs) exhibit high endogenous expression of LRRK2. We induced PD patient-iPSCs with the LRRK2 p.G2019S mutation into oligodendroglial lineages and performed single-cell RNA sequencing. Cell type composition analysis revealed an increase in OPCs, proliferating OPCs and ciliated ependymal cells in LRRK2 lines, all of which are characterized by LRRK2 expression. Differential expression analysis revealed transcriptomic changes in several pathways, including down-regulation of genes related to myelin assembly in ODCs, semaphorin-plexin pathway in OPCs, and cilium movement in proliferating OPCs. Cell-cell communication analysis identified significant alterations in several signaling pathways including a deactivation of PSAP signaling and an activation of MIF signaling in LRRK2 lines. Additionally, we observed an overall increase in SEMA6 signaling communication in LRRK2 cell lines; however, OPCs derived from these LRRK2 lines specifically lost SEMA6 signaling due to a down-regulation of SEMA6A and PLXNA2. Pseudotemporal trajectory analysis revealed that SHH had significantly altered expression along the pseudotime, accompanied by higher expression levels in LRRK2 lines. We propose that dysfunctional semaphorin-plexin signaling, along with cilia movement and SHH signaling, might represent early events in PD pathology.

neuroscience↗

bioRxiv2024

PlantRNA-FM: An Interpretable RNA Foundation Model for Exploration 1 Functional RNA Motifs in Plants

The complex language of plant RNA encodes a vast array of biological regulatory elements that orchestrate crucial aspects of plant growth, development, and adaptation to environmental stresses. Recent advancements in foundation models (FMs) have demonstrated their unprecedented potential to decipher complex language in biology. In this study, we introduced PlantRNA-FM, a novel high-performance and interpretable RNA FM specifically designed based on RNA features including both sequence and structure. PlantRNA-FM was pre-trained on an extensive dataset, integrating RNA sequences and RNA structure information from 1,124 distinct plant species. PlantRNA-FM exhibits superior performance in plant-specific downstream tasks, such as plant RNA annotation prediction and RNA translation efficiency (TE) prediction. Compared to the second-best FMs, PlantRNA-FM achieved an F1 score improvement of up to 52.45% in RNA genic region annotation prediction and up to 15.30% in translation efficiency prediction, respectively. Our PlantRNA-FM is empowered by our interpretable framework that facilitates the identification of biologically functional RNA sequence and structure motifs, including both RNA secondary and tertiary structure motifs across transcriptomes. Through experimental validations, we revealed novel translation-associated RNA motifs in plants. Our PlantRNA-FM also highlighted the importance of the position information of these functional RNA motifs in genic regions. Taken together, our PlantRNA-FM facilitates the exploration of functional RNA motifs across the complexity of transcriptomes, empowering plant scientists with novel capabilities for programming RNA codes in plants.

bioinformatics↗

bioRxiv2024

Preventing trogocytosis by cathepsin B inhibition augments CAR T cell function

Chimeric antigen receptor (CAR) T cell therapy has shown remarkable efficacy in cancer treatment. Still, most patients receiving CAR T cells relapse within 5 years of treatment. CAR-mediated trogocytosis (CMT) is a potential tumor escape mechanism in which cell surface proteins transfer from tumor cells to CAR T cells. CMT results in the emergence of antigen-negative tumor cells, which can evade future CAR detection, and antigen-positive CAR T cells, which has been suggested to cause CAR T cell fratricide and exhaustion. Whether CMT indeed causes CAR T cell dysfunction and the molecular mechanisms conferring CMT remain unknown. Using a selective degrader of trogocytosed antigen in CAR T cells, we show that the presence of trogocytosed antigen on the CAR T cell surface directly causes CAR T cell fratricide and exhaustion. By performing a small molecule screening using a custom high throughput CMT-screening assay, we found that the cysteine protease cathepsin B is essential for CMT and that inhibition of cathepsin B is sufficient to prevent CAR T cell fratricide and exhaustion, leading to improved long-term CAR T cell persistence and anti-tumor activity. Our data demonstrate that it is feasible to separate CMT from cytotoxic activity, that CAR T cell persistence, a key factor associated with clinical CAR T cell efficacy, is directly linked to cathepsin B activity in CAR T cells, and that it is possible to improve CAR T cell function through selective inhibition of CMT. One sentence summary: CAR-mediated trogocytosis is mediated by the cysteine protease cathepsin B and directly causes CAR T cell exhaustion and fratricide. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/598379v3_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@5c058dorg.highwire.dtl.DTLVardef@1707fa7org.highwire.dtl.DTLVardef@ccdff1org.highwire.dtl.DTLVardef@82800b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Inferring metabolite states from spatial transcriptomes using multiple graph neural

Metabolism serves as the pivotal interface connecting genotype and phenotype in various contexts, such as cancer reprogramming and immune metabolic reprogramming. Compared to the transcriptome, the development of the single-cell metabolome faces significant challenges. While various methods exist for predicting metabolite levels from transcriptome, their efficacy remains limited. We developed an efficient and adaptable algorithm known as Multiple Graph-based Flux Estimation Analysis (MGFEA). MGFEA enables rapid inference from million-level single-cell transcriptome datasets and achieves accuracy comparable to that of scFEA. Additionally, MGFEA can detect metabolite biomarkers in different cancer bulk RNA-seq datasets. As an attempt to integrate multi-omics dataset, MGFEA can further improve the accuracy of these inferences by leveraging additional metabolome.

bioinformatics↗

bioRxiv2024

Lipid droplets restrict phagosome formation during Candida challenge

Lipid droplets (LDs) are intracellular organelles which can be induced and interact with phagosomes during the process of pathogen phagocytosis in macrophages. However, the function of LDs in the phagocytosis remains elusive. Here, we unveil the role of LDs in modulating phagosome formation using a fungal infection model. Specifically, LDs accumulation restricted the quantity of phagosome formation, and protected macrophages from death. Mechanistically, LDs formation competitively consumed intracellular endoplasmic reticulum membrane and altered RAC1 translocation and its GTPase activity, which resulted in limiting phagosomes formation in macrophages during fungi engulfed. Mice with Hilpda-deficient macrophages were more susceptible to the lethal sequelae of systemic infection with C. albicans. Notably, administration of ATGL inhibitor Atglistatin improved host outcomes in disseminated fungal infections. Taken together, our study elucidates the mechanism of LDs in controlling phagosomes formation to avoid immune cell death, and offers a potential drug target for treatment of C. albicans infections. HighlightsO_LIC. albicans infection induces triglycerides production and LD accumulation in macrophages. C_LIO_LILD restricts the quantity of phagosome formation and protects macrophages from death. C_LIO_LILD consumes intracellular ER membrane components and alters RAC1 translocation and its GTPase activity. C_LIO_LIAdministration of ATGL inhibitor Atglistatin improves host outcomes in disseminated fungal infections. C_LI

microbiology↗

bioRxiv2024

Mechanical control of the splicing factor PTBP1 regulates extracellular matrix stiffness-induced cell proliferation and mechanomemory

Cells sense and respond to mechanical cues from their environment. Mechanical cues are important for many biological processes, including embryonic development, ageing, cellular homeostasis, and diseases. Cells translate mechanical cues into cellular biochemical signals that govern cellular behaviour, like cell proliferation or migration, via a process called mechanotransduction. However, this process and the proteins involved remain incompletely understood. Here, we present an unbiased and large-scale approach to identify proteins involved in mechanotransduction. The screen revealed that the splicing factor PTBP1 is a novel mechanotransducer. We show that the nuclear localisation of PTBP1 depends on extracellular matrix stiffness, cell density, and the actomyosin-based contractility of the cell. Furthermore, we demonstrate that PTBP1 promotes the mechanosensitive splicing of the adapter protein Numb and that alternative splicing of Numb is crucial for matrix stiffness-induced cell proliferation and mechanomemory. Our results support the idea that changes in alternative splicing are an integral part of mechanotransduction and provide a mechanism by which matrix stiffness regulates cell proliferation and the formation of a mechanomemory in cells.

cell biology↗

bioRxiv2024

An empirical evaluation of simulated gastrointestinal digestion platforms for use in plant breeding, using common bean (Phaseolus vulgaris L.) as a model

There remains a disconnect in plant breeding between increasing nutrient levels in crops at time of harvest and increasing bioaccessible levels of those nutrients during digestion. This study aims to develop and compare simulated digestion models for use in plant breeding and examine bioaccessible nutrient levels in common bean samples with differing seed coat coloration and patterning. The highest trait values (starch and protein hydrolysis, total phenolics, and antioxidant power) were observed from more dynamic digestion models, but even simple dynamic models showed higher trait values than a commonly used static digestion model. The use of these models provided insight on nutrient bioaccessibility; e.g., differences were observed during digestion between common bean genotypes for protein hydrolysis and between growing environments for both total phenolics and protein hydrolysis. Together, these results inform potential future pathways for applying simulated digestion models in plant breeding to improve bioaccessible nutrient levels in crops.

plant biology↗

bioRxiv2024

SEQSIM - A novel bioinformatics tool for comparisons of upstream gene regions - a case study of calcium binding protein spermatid associated 1 (CABS1)

The regulation of gene expression is carefully overseen by upstream gene regions (UGRs) which include promoters, enhancers, and other regulatory elements. Understanding these regions is difficult using standard bioinformatic approaches due to the scale of the human genome. Here we present SEQSIM, a novel bioinformatics tool based on a modified Needleman-Wunsch algorithm that allows for fast, comprehensive, and accurate comparison of UGRs across the human genome. In this study, we detailed the applicability and validity of SEQSIM through an extensive case study of the calcium binding protein spermatid-associated 1 (CABS1). By analyzing 2000 base pairs upstream of every human gene, SEQSIM identified distinct clusters of UGRs, revealing conserved motifs and suggesting potential regulatory interactions. Our analysis identified 41 clusters, the second largest of which contains the CABS1 UGR. Studying the other members of the CABS1 cluster could offer new insights into its regulatory mechanisms and suggest broader implications for genes involved in similar pathways or functions. The development and implementation of SEQSIM represents a significant step forward for the genomics field, providing a powerful new tool to dissect the complexity of the human genome and gain a better understanding of how gene expression is regulated. The study not only shows that SEQSIM is an effective means to identify potential regulatory elements and gene clusters, but also opens up new lines of inquiry to understand overall genomic architecture.

bioinformatics↗