Biology subjects

Chen, X.

Publications and source records attributed to Chen, X..

At least 487 records · Page 27Linked to original sources

bioRxiv2025

Butyrolactol A is a phospholipid flippase inhibitor that potentiates the bioactivity of caspofungin against resistant fungi

Fungal infections cause millions of deaths annually and are challenging to treat due to limited therapeutic options and rising resistance. Cryptococci are intrinsically resistant to the latest generation of antifungals, echinocandins, while Candida auris, a notorious global threat, is also increasingly resistant. We performed a natural product extract screen to rescue caspofungin fungicidal activity against Cryptococcus neoformans H99 and identified butyrolactol A, which restores echinocandin efficacy against resistant fungal pathogens, including multidrug-resistant C. auris. Mode of action studies revealed that butyrolactol A inhibits the phospholipid flippase Apt1-Cdc50, blocking phospholipid transport. Cryo-electron microscopy analysis of the Apt1*butyrolactol A complex revealed that the flippase is trapped in a dead-end state. Apt1 inhibition disrupts membrane asymmetry, vesicular trafficking, and cytoskeletal organization, thereby enhancing echinocandin uptake and potency. This study identifies lipid flippases as promising antifungal targets and demonstrates the potential of revisiting natural products to expand the antifungal arsenal and combat resistance.

biochemistry↗

bioRxiv2025

1,3- and 1,4-linked Polysaccharides Uptake in Intestinal Cells Relies on Clathrin/Dynamin 1/Rab5-dependent Endocytosis

Natural polysaccharides are considered to be a promising feedstock for manufacturing sustainable materials. However, polysaccharides are believed by most biologists that they could not be absorbed by intestinal mucosa to enter circulation system owing to their high hydrophilicity and large molecule size. Herein, {beta}-1,3-linked glucan (GFPBW1) and -1,4-linked glucan (WGE) is used as the model polysaccharide and the transport experiments show that different linked and charged polysaccharides can permeate Caco-2 cell monolayers. The in vivo experiments demonstrate that GFPBW1 and WGE are detectable in rodent plasma and liver after oral administration the isotope (99mTc, 3H) and fluorescein labeled polysaccharides. Further study show that polysaccharide uptake requires clathrin heavy chain (CLTC) and its associated factors Rab5 and dynamin1 in intestinal cells using gene-knockdown strategies and inhibitors. Strikingly, polysaccharide absorption is attenuated in both CLTC intestine deficient mice and Rab5, dynamin1 conventional-knockout mice. Importantly, membrane receptors bone morphogenetic protein receptor type IA (BMPRIA), Dectin-1 and epidermal growth factor receptor (EGFR) are also critical for specific structural polysaccharide internalization. These findings provide novel insight to understand polysaccharide absorption mechanism and lay foundation for oral polysaccharide- based new drugs development.

pharmacology and toxicology↗

bioRxiv2025

Learning robust gene expression embeddings for disease subtyping, biomarker identification and cross-species alignment

High dimension gene expression measurements such as microarray and RNA-seq data, are often plagued by sources of unwanted variation. This variability can lead to the obscuring of meaningful biological signal by technical noise and non-interesting biological variation, thus resulting in failure to identify the same set of targets and biomarkers in independent studies. This phenomenon contributes to the so-called reproducibility crisis and makes preclinical drug development more challenging. There is an urgent need for an improved process to identify shared biological signals in large datasets from independent cohorts. In this article, we propose an innovative method called Joint-Embedding via Canonical Correlation Analysis (JECCA), which aims to capture relevant biological variation by learning of shared lower dimension embedding across multiple datasets. We demonstrate the efficacy of JECCA in analyzing multiple human cancer and inflammatory disease gene expression datasets, showcasing its ability to identify robust, biologically relevant signals. By leveraging these embeddings, our approach enables several important applications: (1) robust disease endotype identification by joint unsupervised analysis of multiple independent gene expression datasets (2) reproducible and biologically meaningful biomarker identification to enhance prediction of treatment outcome (3) cross-platform analysis, such as integration of RNA-seq and microarray data, which are accumulating exponentially in public databases (4) cross-species analysis to identify conserved molecular features between human and mouse. We provide comparative analyses that highlight the superior performance of JECCA over other approaches such as batch value-corrected methods based on joint analysis. As analysis of publicly available datasets becomes more prevalent, we foresee JECCA being employed in multiple disease contexts.

bioinformatics↗

bioRxiv2025

Neural circuits between nodose ganglion and pulmonary neuroendocrine cells regulate lung inflammatory responses

The lungs are organs exposed to the external environment, and the air we inhale contains various pathogens, such as endotoxins. The vagus nerve, which innervates the lungs, may play a role in detecting pathogens that invade the lungs. Through transcriptome analysis, tissue clearance imaging, electrical excitability recording, and gene- and cell-specific knockout experiments, we found that vagus nerve endings innervate pulmonary neuroendocrine cells (PNECs). These nerve endings sense bacterial endotoxins via pain receptors (TRPA1) rather than toll-like receptors (TLR4), eliciting electrical excitation and enhancing the production of neuropeptides (CGRP) in the nodose ganglia. In turn, CGRP released by sensory neurons from the nodose ganglia promotes both neuropeptide production and the proliferation of PNECs, thereby amplifying endotoxin-induced lung inflammatory responses. This reveals that the neural circuits between the nodose ganglion and PNECs play a critical role in regulating lung inflammatory responses.

neuroscience↗

bioRxiv2025

ZapA employs a two-pronged mechanism to facilitate Z ring formation in Escherichia coli

The tubulin-like protein FtsZ assembles into the Z ring which leads to the assembly and activation of the division machinery in most bacteria. ZapA, a widely conserved protein that interacts with FtsZ, plays a pivotal role in organizing FtsZ filaments into a coherent Z ring. Previous studies revealed that ZapA forms a dumbbell-like tetramer that binds cooperatively to FtsZ filaments and aligns them in parallel, leading to the straightening and organization of FtsZ filament bundles. However, how ZapA interacts with FtsZ remains obscure. In this study, we uncover how ZapA interacts with FtsZ to facilitate Z ring formation in Escherichia coli. We find that mutations affecting surface exposed residues at the junction between adjacent FtsZ subunits in a filament as well as in an N-terminal motif of FtsZ weaken its interaction with ZapA in vivo and in vitro, indicating that ZapA binds to these regions of FtsZ. Consistent with this, ZapA prefers FtsZ polymers over monomeric FtsZ molecules and site-specific crosslinking confirmed that the dimer head domain of ZapA is in contact with the junction of FtsZ subunits. As a result, disruption of the putative interaction interfaces between FtsZ and ZapA abolishes the midcell localization of ZapA. Taken together, our results suggest that ZapA tetramers grab the N-terminal tails of FtsZ and then bind to the junctions between FtsZ subunits in the filament to straighten and crosslink parallel FtsZ filaments into the Z ring. SignificanceZapA is a widely conserved FtsZ-associated protein that promotes the organization of the Z ring, the key cytoskeletal element in the bacterial divisome. Although ZapA is known to crosslink FtsZ filaments, how it interacts with FtsZ remains enigmatic. In this study, we find that E. coli ZapA utilizes a dual binding mode in which it binds the junction between FtsZ subunits in a filament and to an N-terminal motif in FtsZ so that it can straighten and crosslink parallel FtsZ filaments simultaneously. Since the junction is formed when FtsZ polymerizes and falls apart when FtsZ depolymerizes, this interaction mode indicates that ZapA employs the polymerization dynamics of FtsZ to organize the filaments into the Z ring.

microbiology↗

bioRxiv2025

Flaviviruses Hijack HuR to Suppress CNPY3: A Novel Pathway for Immune Evasion and Therapeutic Intervention

Flaviviruses represent a serious global health threat, infecting millions annually with high rates of cross-infection among different flaviviruses, yet no broad-spectrum antiviral therapy currently targets these pathogens. Through biological big data analysis, we observed a significant downregulation of Canopy FGF Signaling Regulator 3 (CNPY3), a positive regulator of defense responses, in flavivirus-infected patients, with the level of downregulation correlating with infection severity. This observation was validated in cellular and animal models. Mechanistically, we demonstrate that flaviviruses hijack the RNA-binding protein Human antigen R (HuR) to destabilize CNPY3 mRNA via adenine-uridine-rich elements (AREs), thus downregulating CNPY3 expression and promoting viral replication. Our findings identify CNPY3 as a novel antiviral mediator essential for the TLR-mediated type I interferon (IFN-I) pathway in defense against flaviviruses. In vitro, CNPY3 overexpression reduced DENV and ZIKV replication, confirming its antiviral role. To explore therapeutic potential, we developed lipid nanoparticles (LNPs) encapsulating CNPY3 mRNA (LNP-CNPY3), and early administration in flavivirus-infected mice improved survival, reduced viral loads, and attenuated neuroinflammation by enhancing antiviral and interferon responses. Together, these findings establish CNPY3 as a critical antiviral target and support LNP-CNPY3 as a promising therapeutic approach against flavivirus infections.

microbiology↗

bioRxiv2024

Molecular mechanisms of dynamics-mediated effects of pathogenic missense mutations on Menin protein function

Understanding how disease-causing missense mutations (DCMMs) affect protein function is fundamental. The traditional structure-function paradigm for proteins has evolved into a structure-dynamics-function model, as dynamics is increasingly recognized as a key regulator of protein function. Consequently, it is essential to incorporate dynamics into the once heavily emphasized structure-function framework to explain the effects of DCMMs. Although research in this area is emerging, evidence supporting a definitive role of dynamics in mediating DCMM effects on protein function remains limited. In this study, we used Menin--a mutation-prone scaffold protein involved in various pathologies--as a model system to explore how DCMMs affect Menins function. By performing molecular dynamics (MD) simulations on 24 clinically confirmed DCMMs, we showed that DCMMs do not necessarily destabilize protein stability. Instead, they induce similar dynamic changes in the protein. The consequences of DCMMs on Menins function were further assessed through umbrella sampling of the Menin-JunD protein protein interaction (PPI). We found that DCMMs attenuate this interaction and disrupt a highly conserved JunD dissociation pathway in wild-type (WT) Menin. The underlying mechanism was revealed through allosteric analysis, which showed that, despite being located far from the JunD binding site, DCMMs uniformly disturbed the coupling between residue E179 and the binding pocket. Additionally, forced maintenance of E197-pocket coupling restored the impaired Menin-JunD PPI in DCMMs. Together, these data demonstrate that DCMMs alter Menins function through dynamics, with allostery playing a crucial role. This study further supports the incorporation of dynamics into the traditional "structure-function" diagram to better explain the effects of DCMMs.

biophysics↗

bioRxiv2024

Histone H4 limits transcription of the histone locus in Drosophila

In all eukaryotes DNA replication is coupled to histone synthesis to coordinate chromatin packaging of the genome. Canonical histone genes coalesce in the nucleus into the Histone Locus Body (HLB), where gene transcription and 3 mRNA processing occurs. Both histone gene transcription and mRNA stability are reduced when DNA replication is inhibited, implying that the Histone Locus Body senses the rate of DNA synthesis. In Drosophila melanogaster, the S-phase-induced histone genes are tandemly repeated in an [~]100 copy array, whereas in humans, these histone genes are scattered. In both organisms these genes coalesce into Histone Locus Bodies. We used a transgenic histone gene reporter and RNAi in Drosophila to identify canonical H4 histone as a unique repressor of histone synthesis during the G2 phase in germline cells. Using cytology and CUT&Tag chromatin profiling, we find that histone H4 uniquely occupies histone gene promoters in both Drosophila and human cells. Our results suggest that repression of histone genes by soluble histone H4 is a conserved mechanism that coordinates DNA replication with histone synthesis in proliferating cells.

genomics↗

bioRxiv2024

Phosphotyrosine Signal Profiling of Clinical CAR-T Reveals Tonic Signaling Associated with Therapeutic Efficacy

Chimeric Antigen Receptor T (CAR-T) therapies have revolutionized the treatment of cancers such as relapsed and refractory B cell malignancies. However, the precise therapeutic mechanism of CAR-T action remain to be elucidated. In this study, we systematically analyzed CAR signaling via phosphotyrosine (pTyr) proteomics in CAR-T cells from both clinical patients and healthy donors. We found that CAR-T products from clinical patients displayed heightened tyrosine phosphorylation, particularly in the JAK-STAT, MAPK and TCR signaling cascades. We also identified the significantly regulated pTyr sites in primary CAR-T cells under tonic signaling or upon stimulation by antigen-presenting CD19-K562 cells. Although both CD28{zeta} and 4-1BB{zeta} CAR-T cells exhibited comparable pTyr changes, CD28{zeta} CAR-T cells displayed a more pronounced activation in the TCR signaling pathway. Additionally, comparative analysis between clinical and primary CAR-T cells suggested that CAR-T products were subject to heightened tonic signaling, which may be related to therapeutic relapse. Our findings reveal the state of clinical CAR-T products and refine the CAR-T signal transduction network, providing comprehensive insights and informed guidance for CAR-T therapies.

immunology↗

bioRxiv2024

EpiAgent: Foundation model for single-cell epigenomic data

Large-scale foundation models have recently opened new avenues for artificial general intelligence. Such a research paradigm has recently shown considerable promise in the analysis of single-cell sequencing data, while to date, efforts have centered on transcriptome. In contrast to gene expression, chromatin accessibility provides more decisive insights into cell states, shaping the chromatin regulatory landscapes that control transcription in distinct cell types. Yet, challenges also persist due to the abundance of features, high data sparsity, and the quasi-binary nature of these data. Here, we introduce EpiAgent, the first foundation model for single-cell epigenomic data, pretrained on a large-scale Human-scATAC-Corpus comprising approximately 5 million cells and 35 billion tokens. EpiAgent encodes chromatin accessibility patterns of cells as concise "cell sentences," and employs bidirectional attention to capture cellular heterogeneity behind regulatory networks. With comprehensive benchmarks, we demonstrate that EpiAgent excels in typical downstream tasks, including unsupervised feature extraction, supervised cell annotation, and data imputation. By incorporating external embeddings, EpiAgent facilitates the prediction of cellular responses to both out-of-sample stimulated and unseen genetic perturbations, as well as reference data integration and query data mapping. By simulating the knockout of key cis-regulatory elements, EpiAgent enables in-silico treatment for cancer analysis. We further extended zero-shot capabilities of EpiAgent, allowing direct cell type annotation on newly sequenced datasets without additional training.

bioinformatics↗

bioRxiv2024

De novo design and structure of a peptide-centric TCR mimic binding module

T cell receptor (TCR) mimics offer a promising platform for tumor-specific targeting of peptide-MHC in cancer immunotherapy. Here, we designed a de novo -helical TCR mimic (TCRm) specific for the NY-ESO-1 peptide presented by HLA-A*02, achieving high on-target specificity with nanomolar affinity (Kd = 9.5 nM). The structure of the TCRm/pMHC complex at 2.05 [A] resolution revealed a rigid TCR-like docking mode with an unusual degree of focus on the up-facing NY-ESO-1 side chains, suggesting the potential for reduced off-target reactivity. Indeed, a structure-informed in silico screen of 14,363 HLA-A*02 peptides correctly predicted two off-target peptides, yet our TCRm maintained a wide therapeutic window as a T cell engager. These results represent a path for precision targeting of tumor antigens with peptide-focused -helical TCR mimics.

immunology↗

bioRxiv2024

A novel pan class-I glucose transporter inhibitor DRB18 exhibits synergistic effects in vitro and in vivo with paclitaxel against human non-small cell lung cancer

PurposeCancer cells depend on glucose for biomass synthesis, cell proliferation, and drug resistance. Glucose transporter (GLUT) transcripts as well as proteins are upregulated in human lungs and other cancers and are negatively correlated with patient survival, particularly GLUT1 and GLUT3. Thus, inhibiting GLUT function has been an attractive anticancer strategy. We previously characterized WZB117 and DRB18, first- and second-generation pan-class I GLUT inhibitors, respectively. DRB18 strongly inhibits glucose transport mediated by GLUT1-4 in non-small lung cancer (NSCLC) A549 cells in vitro and in vivo. Here, we report DRB18 as a more stable and potent anticancer compound, compared to WZB117. MethodsImmunohistochemistry analysis was performed in Lung adenocarcinoma (LUAD) tissue array to investigate GLUT1 and GLUT3 protein expression between normal, lower and higher stage LUAD patients. Bioinformatics analysis was performed to examine additive effect of GLUT3 to GLUT1 mediated prognosis in LUAD. Glucose uptake and resazurin dye-based proliferation assays were used to determine glucose uptake inhibitory and cell proliferation inhibitory against panel of human cancer cell lines A549, Panc1 and Hela. DRB18 potency was tested against the presence of extracellular nutrients glucose, glutamine and ATP. Synergism between DRB18 and clinically approved anticancer drugs was tested against cancer cells. DRB18 and advanced NSCLC drug Paclitaxel were tested for synergy in vitro and in vivo. ResultsGLUT1/3 combination exhibited higher hazard ratio than either GLUT1 and GLUT3 alone in many cancer types including LUAD. DRB18 reduced glucose uptake in NSCLC A549, pancreatic Panc1, and cervical Hela cancer cells with varied but strong anticancer potencies in the presence or absence of extracellular nutrients such as ATP and glucose. Combined with different clinical and pre-clinical anticancer compounds such as V9302, CB839, Sutent, Brigatinib, DRB18 significantly increased death of A549 and Panc1 cells. Noteworthy, DRB18 exhibited strong anticancer synergy with paclitaxel, an approved chemo drug for NSCLC, drastically reducing cancer cell proliferation in vitro and growth of A549 tumors grafted on the flank of nude mice without significant side effects, compared to single drug treatments. ConclusionsCollectively, our results demonstrate anticancer efficacy of pan class-I GLUT inhibitor DRB18 in combination with paclitaxel, providing a potentially more efficacious therapeutic strategy for treating advanced NSCLC and other cancers.

cancer biology↗

bioRxiv2024

Traveling waves enhance hippocampal-parahippocampal couplings in humanepisodic and working memory

Multiple brain regions in the human medial temporal lobe (MTL) are coordinated in memory processing. Traveling waves is a potential mechanism to coordinate information transfer through organizing the timing or spatiotemporal patterns of wave propagation. Based on direct human intracranial EEG recordings, we detected bidirectional hippocampal and parahippocampal traveling waves (4-10 Hz) along the posterior-anterior axis during a verbal memory task. Hippocampal traveling waves enhanced hippocampal-parahippocampal and intra-hippocampal couplings in both amplitude and phase as well as hippocampal theta phase-gamma amplitude coupling, suggesting a facilitatory role of TWs. Granger causality analysis showed asymmetric information flow, with greater predictability in the parahippocampal-to-hippocampal direction and dominant peak at the beta band (20-30 Hz). Hippocampal power and bidirectional hippocampal-parahippocampal information flow at the gamma band (35-50 Hz) showed reductions during successful memory encoding trials. These results support functional significance of frequency-specific parahippocampal-hippocampal and intra-hippocampal communications during memory encoding and retrieval. HighlightsO_LIBidirectional hippocampal traveling waves enhance hippocampal-parahippocampal couplings in both amplitude and phase. C_LIO_LIHippocampal-parahippocampal gamma coherence is greater in memory retrieval than memory encoding. C_LIO_LIIntra-hippocampal theta phase-gamma amplitude coupling is greater in memory encoding than recall. C_LIO_LIHippocampal power and hippocampal-parahippocampal granger causality in gamma band reduced in successful trials. C_LI

neuroscience↗

bioRxiv2024

Genomic Insights into Hybridization and Speciation of Mitten Crabs in the Eriocheir Genus

Hybridization is a prominent and influential phenomenon with significant implications for adaptive evolution, species distribution and biodiversity. However, the intricacies of how hybridization influences genomic structure and facilitates adaptive evolution still elude our full understanding. Analyzing whole genome data from seven populations within Eriocheir genus across diverse geographic regions, we have validated a complex hybridization history between Chinese and Japanese mitten crabs. This hybridization gave rise to two distinct ecological species: Hepu and Russian mitten crabs with unique genomic architectures and adaptations. Genes related to reproduction, development, and temperature adaptation exhibit divergent selection signals, potentially contributing to their phenotypic diversity and ecological niches. Meanwhile, genes associated with reproduction, namely Birc6, Bap31, and Poxn, displayed robust evidence of selective sweeps in Hepu mitten crab. Notably, the favored alleles for these genes originated from the parental lineages during the hybridization process. Furthermore, Hepu mitten crab is a homoploid hybrid species that originated from an ancient hybridization event, resolving its longstanding taxonomic controversy. Our study sheds light on the evolutionary history of mitten crabs and highlights the crucial role of hybridization in driving adaptation, range expansion, and diversification within the Eriochier genus.

genomics↗

bioRxiv2024

Patient-Derived Xenografts of Triple-Negative Breast Cancer Enable Deconvolution and Prediction of Chemotherapy Responses

Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significanceIntegration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

cancer biology↗

bioRxiv2024

Enhancing RNA Delivery: Practical Insights into NeoLNP Transfection Reagent

The rapid advancement of RNA-based therapeutics, particularly in the wake of COVID-19 vaccine success, has prompted significant research into optimizing RNA delivery mechanisms. This study evaluates the NeoLNP RNA Transfection Kit developed by Scindy Pharmaceutical, which utilizes lipid nanoparticles (LNPs) for efficient RNA encapsulation and delivery. We systematically investigate various parameters affecting transfection efficiency, including RNA concentration, RNA/LNP volume ratios, mixing techniques, LNP stability, and culture media. Our results demonstrate that the optimal RNA concentration for transfection efficiency is around 40-60 ng/{micro}L, with a 1:0.75-1:1 RNA-to-LNP ratio yielding the highest protein expression. Additionally, we find that gentle mixing techniques outperform harsher methods, and the stability of LNP-RNA complexes significantly influences transfection outcomes. This research provides practical guidelines for enhancing RNA transfection efficiency, paving the way for more effective RNA therapeutics.

molecular biology↗

bioRxiv2024

SegCSR: Weakly-Supervised Cortical Surfaces Reconstruction from Brain Ribbon Segmentations

Deep learning-based cortical surface reconstruction (CSR) methods heavily rely on pseudo ground truth (pGT) generated by conventional CSR pipelines as supervision, leading to dataset-specific challenges and lengthy training data preparation. We propose a new approach for reconstructing multiple cortical surfaces using weak supervision from brain MRI ribbon segmentations. Our approach initializes a midthickness surface and then deforms it inward and outward to form the inner (white matter) and outer (pial) cortical surfaces, respectively, by jointly learning diffeomorphic flows to align the surfaces with the boundaries of the cortical ribbon segmentation maps. Specifically, a boundary surface loss drives the initialization surface to the target inner and outer boundaries, and an inter-surface normal consistency loss regularizes the pial surface in challenging deep cortical sulci. Additional regularization terms are utilized to enforce surface smoothness and topology. Evaluated on two large-scale brain MRI datasets, our weakly-supervised method achieves comparable or superior CSR accuracy and regularity to existing supervised deep learning alternatives.

neuroscience↗

bioRxiv2024

StarPhase: Comprehensive Phase-Aware Pharmacogenomic Diplotyper for Long-Read Sequencing Data

Pharmacogenomics is central to precision medicine, informing medication safety and efficacy. Phar-macogenomic diplotyping of complex genes requires full-length DNA sequences and detection of structural rearrangements. We introduce StarPhase, a tool that leverages PacBio HiFi sequence data to diplotype 21 CPIC Level A pharmacogenes and provides detailed haplotypes and supporting visualizations for HLA-A, HLA-B, and CYP2D6. StarPhase diplotypes have high concordance with benchmarks where 99.5% are either exact matches or minor discrepancies. Manual inspection of the 0.5% mismatches indicates they were correctly called by StarPhase. With StarPhase, we update or correct 26.2% of GeT-RM pharmacogenomic diplotypes. Population distributions from StarPhase mostly reflect those of the All of Us cohort, while also highlighting gaps in existing pharmacogenomic databases that long-read sequencing can fill. With a single HiFi whole genome sequencing assay, StarPhase enables robust PGx diplotyping even as additional pharmacogenes and haplotypes are discovered.

bioinformatics↗