Biology subjects

Wang, P. L.

Publications and source records attributed to Wang, P. L..

9 recordsLinked to original sources

bioRxiv2026

FunctionaL Assigning Sequence Homing (FLASH) maps phenotype to sequence with deep and machine learning

Genome-wide association studies (GWAS) map genetic variation to a reference genome and correlate variants to phenotypes. Yet, GWAS and similar procedures have limitations, including an inability to predict phenotype on variants never seen during the discovery phase and difficulty integrating structural variants. Deep and machine learning alternatives have not been successful at consistent prediction of resistance phenotypes (Hu et al. 2024). Here, we introduce FLASH: a new interpretable, statistically-based deep learning framework that operates directly on raw sequencing reads. In over 35,000 isolates of bacteria, fungi and viruses, FLASH achieves uniformly high accuracy on independent test data, including on variation never seen in training, meeting or exceeding bespoke state of the art methods. FLASH identifies canonical drug targets ab initio and new pan-species predictors of virulence, including those lacking annotation and those only partially aligned to NCBI reference databases. Further, FLASH can predict phenotypes beyond the possibility of GWAS, such as bacterial host range of phage, a task that to our knowledge is impossible today. FLASH is simple to run, highly efficient and constitutes a new approach for predicting gene function and phenotype across the tree of life. It is especially valuable when bioethical concerns and the vast genetic complexity of pathogenic microbes limit the feasibility of experimental validation.

bioinformatics↗

bioRxiv2024

sc-SPLASH provides ultra-efficient reference-free discovery in barcoded single-cell sequencing

Typical high-throughput single-cell RNA-sequencing (scRNA-seq) analyses are primarily conducted by (pseudo)alignment, through the lens of annotated gene models, and aimed at detecting differential gene expression. This misses diversity generated by other mechanisms that diversify the transcriptome such as splicing and V(D)J recombination, and is blind to sequences missing from imperfect reference genomes. Here, we present sc-SPLASH, a highly efficient pipeline that extends our SPLASH framework for statistics-first, reference-free discovery to barcoded scRNA-seq (10x Chromium) and spatial transcriptomics (10x Visium); we also provide its optimized module for preprocessing and k-mer counting in barcoded data, BKC, as a standalone tool. sc-SPLASH rediscovers known biology including V(D)J recombination and cell-type-specific alternative splicing in human and trans-splicing in tunicate (Ciona) and when applied to spatial datasets, detects sequence variation including tumor-specific somatic mutation. In sponge (Spongilla) and tunicate (Ciona), we uncover secreted repeat proteins expressed in immune-type cells and regulated during development; the sponge genes were absent from the reference assembly. sc-SPLASH provides a powerful alternative tool for exploring transcriptomes that is applicable to the breadth of lifes diversity.

bioinformatics↗

bioRxiv2024

Ultra-efficient, unified discovery from microbial sequencing with SPLASH and precise statistical assembly

Bacteria comprise > 12% of Earths biomass and profoundly impact human and planetary health.1 Many key biological functions of microbes, and functions differentiating strains, are conferred or modified by genome plasticity including mobilization of genetic elements, phage integration, and CRISPR arrays. Characterizing each of these processes is time-consuming and requires custom bioinformatic workflows ill-suited to enable discovery of new sources of genetic diversity or to uncover which elements are active. Further, strain typing of bacterial species and approaches to discriminate sub-populations remain time-consuming and resource intensive. Here, we show that SPLASH, our published approach for reference-free discovery and analysis directly from raw reads, and an improved statistical assembly algorithm, compactors, unify diverse tasks in microbial sequence analysis: discovering new mobile elements and CRISPR arrays missing from any reference, and generating rapid, metadata-free strain typing of diverse bacteria. SPLASH and compactors together constitute a new general discovery tool for biological discovery in the microbial world.

bioinformatics↗

bioRxiv2023

Therapy-associated remodeling of pancreatic cancer revealed by single-cell spatial transcriptomics and optimal transport analysis

In combination with cell intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged high-plex single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with specific malignant subtypes and neoadjuvant chemotherapy/radiotherapy. We developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid co-culture system. Overall, this study demonstrates that characterization of the tumor microenvironment using high-plex single-cell spatial transcriptomics allows for identification of molecular interactions that may play a role in the emergence of chemoresistance and establishes a translational spatial biology paradigm that can be broadly applied to other malignancies, diseases, and treatments.

cancer biology↗

bioRxiv2022

Unsupervised reference-free inference reveals unrecognized regulated transcriptomic complexity in human single cells

Myriad mechanisms diversify the sequence content of eukaryotic transcripts at both the DNA and RNA levels, leading to profound functional consequences. Examples of this diversity include RNA splicing and V(D)J recombination. Currently, these mechanisms are detected using fragmented bioinformatic tools that require predefining a form of transcript diversification and rely on alignment to an incomplete reference genome, filtering out unaligned sequences, potentially crucial for novel discoveries. Here, we present SPLASH+, significantly advancing biological discovery possible with SPLASH, our recently introduced efficient, reference-free statistical approach. Integrating a micro-assembly and biological interpretation framework, SPLASH+ enables new discoveries including broad and novel examples of transcript diversification in single cells de novo, without the need for cell type metadata, which is impossible with current algorithms. Applied to 10,326 primary human single cells across 19 tissues profiled with SmartSeq2, SPLASH+ discovers a set of splicing and histone regulators with highly conserved intronic regions that are themselves subject to complex splicing regulation. Additionally, it reveals unreported transcript diversity in the heat shock protein HSP90AA1, as well as diversification in centromeric RNA expression, V(D)J recombination, RNA editing, and repeat expansion, all missed by existing methods. SPLASH+ is highly efficient, enabling the discovery of an unprecedented breadth of RNA regulation and diversification in single cells through a new automated paradigm of unbiased transcriptomic analysis.

bioinformatics↗

bioRxiv2022

DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery

Diversity-generating and mobile genetic elements are paramount to microbial and viral evolution and result in evolutionary leaps conferring novel phenotypes, such as antimicrobial resistance. State-of-the-art algorithms to detect these elements have many limitations, including reliance on reference genomes, assemblers, and heuristics, resulting in computational bottlenecks and limiting the scope of biological discoveries. Here we introduce DIVE, a new reference-free approach to overcome these limitations using information contained in sequencing reads alone. We show that DIVE has improved detection power compared to existing reference-based methods using simulations and real data. We use DIVE to rediscover and characterize the activity of known and novel elements and generate new biological hypotheses about the mobilome. Using DIVE we rediscover CRISPR and identify novel repeats, and we discover unannotated genetic hyper-variability hotspots in Escherichia coli and Vibrio cholerae. Building on DIVE, we develop a reference-free framework capable of de novo discovery of mobile genetic elements, not currently available to our knowledge, and we use it to rediscover the known transposons in Mycobacterium tuberculosis, the causative agent of tuberculosis.

bioinformatics↗

bioRxiv2022

Macrophage depletion blocks congenital SARM1-dependent neuropathy

Axon loss contributes to many common neurodegenerative disorders. In healthy axons, the axon survival factor NMNAT2 inhibits SARM1, the central executioner of programmed axon degeneration. We identified two rare NMNAT2 missense variants in two brothers afflicted with a progressive neuropathy syndrome. The polymorphisms result in amino acid substitutions, V98M and R232Q, which reduce NMNAT2 NAD+-synthetase activity. We generated a mouse model of the human syndrome and found that Nmnat2V98M/Nmnat2R232Q compound-heterozygous CRISPR mice survive to adulthood but develop progressive motor dysfunction, peripheral axon loss, and macrophage infiltration. These disease phenotypes are all SARM1-dependent. Remarkably, macrophage depletion therapy blocks and reverses neuropathic phenotypes in Nmnat2V98M/R232Q mice, identifying a SARM1-dependent neuroimmune mechanism as a key driver of disease pathogenesis. These findings demonstrate that SARM1 induces an inflammatory neuropathy and highlight the potential of immune therapy to treat this rare syndrome and other neurodegenerative conditions associated with NMNAT2 loss and SARM1 activation.

neuroscience↗

bioRxiv2020

The pan-cancer lncRNA PLANE regulates an alternative splicing program to promote cancer pathogenesis

Genomic amplification of the distal portion of chromosome 3q, which encodes a number of oncogenic proteins, is one of the most frequent chromosomal abnormalities in malignancy. Here we functionally characterise a non-protein product of the 3q region, the long noncoding RNA (lncRNA) PLANE, which is upregulated in diverse cancer types through copy number gain as well as E2F1-mediated transcriptional activation. PLANE forms an RNA-RNA duplex with the nuclear receptor co-repressor 2 (NCOR2) pre-mRNA at intron 45, binds to heterogeneous ribonucleoprotein M (hnRNPM) and facilitates the association of hnRNPM with the intron, thus leading to repression of the alternative splicing (AS) event generating NCOR2-202, a major protein-coding NCOR2 AS variant. In consequence, PLANE promotes cancer cell proliferation and tumorigenicity and its upregulation is associated with poor patient outcomes. These results uncover the function and regulation of PLANE and suggest that PLANE may constitute a therapeutic target in the pan-cancer context.

cancer biology↗

bioRxiv2019

Peripheral nerve resident macrophages are microglia-like cells with tissue-specific programming

Whereas microglia are recognized as fundamental players in central nervous system (CNS) development and function, much less is known about macrophages of the peripheral nervous system (PNS). Here we show that self-maintaining PNS macrophages share unique features with CNS microglia. By comparing gene expression across neural and conventional tissue-resident macrophages, we identified transcripts that were shared among neural resident macrophages as well as selectively enriched in PNS macrophages. Remarkably, PNS macrophages constitutively expressed genes previously identified to be upregulated by activated microglia during aging or neurodegeneration. Several microglial activation-associated and PNS macrophage-enriched genes were also expressed in spinal cord microglia at steady state. While PNS macrophages arose from both embryonic and hematopoietic precursors, their expression of activation-associated genes did not differ by ontogeny. Collectively, these data uncover shared and unique features between neural resident macrophages and emphasize the role of nerve environment for shaping PNS macrophage identity.

immunology↗