Biology subjects

Zhang, D. Y.

Publications and source records attributed to Zhang, D. Y..

At least 19 recordsLinked to original sources

bioRxiv2026

mV2G: a multiomic atlas for tissue-specific variant-to-gene prioritization

The multiomic Variant-to-Gene (mV2G, https://mv2g.hbliulab.org) is a comprehensive atlas that integrates diverse functional genomic evidence to prioritize tissue-specific variant-to-gene (V2G) associations. While genome-wide association studies (GWAS) have identified millions of associations between genetic variants and diseases, translating these findings into biological mechanisms remains challenging because >90% of variants reside in noncoding regions. Existing V2G resources provide complementary regulatory evidence but are fragmented and often lack tissue-specific interpretation. To address this challenge, we constructed the mV2G atlas by integrating 24 types of functional genomic evidence across 50 human tissues, including molecular quantitative trait loci, enhancer-gene predictions, three-dimensional chromatin interactions, and experimental validation. The atlas contains 188,634,118 evidence-supported V2G pairs involving 13,618,039 variants and 69,521 genes. We further developed a unified tissue-specific V2G prioritization framework and prioritized 1,530,420 high-confidence functional V2G pairs involving 1,131,316 unique variants, with 87% exhibiting tissue-specificity. The mV2G atlas provides searchable variant- and gene-centered interfaces, an interactive browser for visualizing variants, target genes, cis-regulatory elements, and chromatin states, as well as downloadable datasets. By integrating complementary regulatory evidence into a unified framework, mV2G provides an accessible resource for interpreting the functional and phenotypic impact of genomic variation in relevant tissues for human diseases. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/743997v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@ac8319org.highwire.dtl.DTLVardef@1d31920org.highwire.dtl.DTLVardef@169225org.highwire.dtl.DTLVardef@1d4dc02_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Barcode-integrated reverse transcription for accurate, complete, and low-input RNA sequencing

In conventional total-RNA sequencing, unwanted RNA is removed by ribosomal-RNA depletion or messenger-RNA enrichment, and contaminating genomic DNA is cleared by DNase, both before reverse transcription. A sample index is added only later, during amplification, so each sample is carried through reverse transcription and cleanup on its own. These steps lose material that low-input samples cannot spare, and the per-sample handling limits throughput. Here we describe BIRT (Barcode-Integrated Reverse Transcription), a hairpin primer that carries a sample barcode and begins reverse transcription preferentially at RNA 3' ends, folding both barcoding and 3'-end capture into first-strand synthesis. Barcoding at reverse transcription enables early pooling, so samples are combined before any cleanup. It also authenticates RNA against DNA contamination: the primer barcodes RNA 909-fold more often than genomic DNA, and non-barcoded reads, which report DNA, are discarded. The 3'-end preference recovers terminal sequence that random priming loses: for a typical small nucleolar RNA, 66% of reads begin within two nucleotides of the mature 3' end, against a few percent for random hexamers. We pair BIRT with PERD (Probes for Excess RNA Depletion), a modular set of blocking probes that removes unwanted RNA within the same reaction without distorting expression (Pearson r = 0.98). We have applied BIRT to 8,079 samples across seven species, from cultured cells and primary tissue to FFPE and extracellular-vesicle RNA.

molecular biology↗

bioRxiv2026

Scaling Multiplex qPCR Primer Design to 1000-plex using the Degenerate Incomplete Multiplex Primer List Extension (DIMPLE) Algorithm

Massively multiplexed qPCR is primarily constrained by increasing primer dimer formation as the number of distinct primers in a single reaction increases. Previous multiplex primer design algorithms either fail to sufficiently suppress primer dimers at 100+ plex, or take exceedingly high amounts of computational resources to complete. Here, we present DIMPLE, a linear-runtime primer design algorithm that effectively generates 10,000+ primers to amplify thousands of potential amplicons in a single qPCR reaction. As one clinical demonstration of this algorithm, we designed an assay to detect 2,302 distinct KMT2A gene fusion subtypes using 204 primers in a single tube. In contrast to FISH and convention NGS approaches with 2% variant allele frequency (VAF) limit of detection, our DIMPLE qPCR assay was able to analytically detect gene fusions down to 0.05% VAF. We also constructed proof-of-concept multiplex qPCR panels for additional oncology gene fusions, multiplex pathogen detection, and DNA methylation markers. The scalability and low computational cost DIMPLE are complementary to new instrument platforms for massively multiplex qPCR readout for enabling rapid, point-of-care nucleic acid testing.

bioengineering↗

bioRxiv2024

Patient-derived glioblastoma organoids as real-time avatars for assessing responses to clinical CAR-T cell therapy

Patient-derived tumor organoids have been leveraged for disease modeling and preclinical studies, but rarely applied in real-time to aid with interpretation of patient treatment responses in clinics. We recently demonstrated early efficacy signals in a first-in-human, phase 1 study of dual-targeting chimeric antigen receptor T cells (EGFR-IL13R2 CAR-T cells) in patients with recurrent glioblastoma. Here we analyzed six sets of patient-derived glioblastoma organoids (GBOs) treated concurrently with the same autologous CAR-T cell products as patients in our phase 1 study. We found that CAR-T cell treatment led to target antigen reduction and cytolysis of tumor cells in GBOs, the degree of which correlated with CAR-T cell engraftment detected in patients cerebrospinal fluid (CSF). Furthermore, cytokine release patterns in GBOs mirrored patient CSF samples over time. Our findings highlight a unique trial design and GBOs as a valuable platform for real-time assessment of CAR-T cell bioactivity and insights into immunotherapy efficacy.

cancer biology↗

bioRxiv2024

Temporal multi-modal single-cell analyses reveal dynamic interactions of CAR-T cells with glioblastoma and targeting of antigen-negative neoplastic cells

CAR-T therapy is a promising new immunotherapy for cancers, but its efficacy for solid tumors requires improvement. A detailed understanding of the interplay between solid tumors and CAR-T cells is critical. Here we report temporal, multi-modal, single-cell profiling of patient-derived glioblastoma organoids with CAR-T treatment. We found that all tumor cell types responded to CAR-T cell activation and contributed to an initially anti-tumor, but subsequently pro-tumor and immune-inhibitory microenvironment, accompanied by CAR-T cell exhaustion. Unexpectedly, CAR-T treatment attenuated glioma stem-like states of both antigen-positive and antigen-negative neoplastic cells and reduced their proliferation via diffusible factors, including IFN{gamma}. Analysis of samples from additional patients, including those in clinical trials, supported these findings. Our study reveals the dynamic interplay among different tumor cells and T cells in adaptive responses to immunotherapy and identifies previously unappreciated benefits of CAR-T therapy directly on antigen-negative neoplastic cells that may be leveraged to enhance therapeutic efficacy.

cancer biology↗

bioRxiv2024

Transfer Learning Of Gene Expression Using Reactome

AO_SCPLOWBSTRACTC_SCPLOWIn clinical research, translating findings from model organisms to human applications remains challenging due to biological differences between species as well as limitations of orthologous, and homologous, gene comparisons, which is fraugt with information loss as well as many-to-many mapping. To address these issues, we introduce a novel Universal Gene Embedding (UGE) model that leverages transformer-based few-shot learning for species-agnostic transfer learning with heterogeneous domain adaptation. The UGE model, trained on a dataset of gene expression from ten organs across rats and mice, establishes a unified biological latent space that effectively represents genes from any organ or species. By focusing on reactomes--comprehensive profiles of gene expression responses to drugs--the UGE model enables functional gene mapping across species based on the similarities of these profiles. Our contributions include a gene reactome vector prediction module, a robust framework for mapping drug-induced gene expression patterns across species, strategies for optimizing experimental design, and enhanced gene mapping precision. These advancements provide a new tool for genetic research and a new paradigm for cross-species insights, potentially revolutionizing our understanding of gene function, drug responses, and the translation of findings from model organisms to human clinical applications.

systems biology↗

bioRxiv2024

APOE regulates the transport of GM1

Apolipoprotein E (APOE) is responsible for lipid transport, including cholesterol transport and clearance. While the {varepsilon}4 allele of APOE (APOE4) is associated with a significant genetic risk factor for late-onset Alzheimers disease (AD), no mechanistic understanding of its contribution to AD etiology has been established yet. In addition to cholesterol, monosialotetrahexosylganglioside (GM1) is a crucial lipid component in cell membranes and has been implicated in promoting the aggregation of amyloid beta protein (A{beta}), a key protein associated with AD. Here, we ask whether there are direct interactions between APOE and GM1 that further impact AD pathology. We find that both APOE3 and APOE4 exhibit superior binding affinity to GM1 compared to cholesterol and have an enhanced cellular uptake to GM1 lipid structures than cholesterol lipid structures. APOE regulates the transport process of GM1 depending on the cell type, which is influenced by the expression of APOE receptors in different cell lines and alters GM1 contents in cell membranes. We also find that the presence of GM1 alters the secondary structure of APOE3 and APOE4 and enhances the binding affinity between APOE and its receptor low-density lipoprotein receptor (LDLR), consequently promoting the cellular uptake of lipid structures in the presence of APOE. To understand the enhanced cellular uptake observed in lipid structures containing 20% GM1, we determined the distribution of GM1 on the membrane and found that GM1 clustering in lipid rafts, thereby supporting the physiological interaction between APOE and GM1. Overall, we find that APOE plays a regulatory role in GM1 transport, and the presence of GM1 on the lipid structures influences this transport process. Our studies introduce a plausible direct link between APOE and AD etiology, wherein APOE regulates GM1, which, in turn, promotes A{beta} oligomerization and aggregation.

neuroscience↗

bioRxiv2024

Brain-wide neuronal circuit connectome of human glioblastoma

Glioblastoma (GBM), a universally fatal brain cancer, infiltrates the brain and can be synaptically innervated by neurons, which drives tumor progression1-6. Synaptic inputs onto GBM cells identified so far are largely short-range and glutamatergic7-9. The extent of integration of GBM cells into brain-wide neuronal circuitry is not well understood. Here we applied a rabies virus-mediated retrograde monosynaptic tracing approach10-12 to systematically investigate circuit integration of human GBM organoids transplanted into adult mice. We found that GBM cells from multiple patients rapidly integrated into brain-wide neuronal circuits and exhibited diverse local and long-range connectivity. Beyond glutamatergic inputs, we identified a variety of neuromodulatory inputs across the brain, including cholinergic inputs from the basal forebrain. Acute acetylcholine stimulation induced sustained calcium oscillations and long-lasting transcriptional reprogramming of GBM cells into a more invasive state via the metabotropic CHRM3 receptor. CHRM3 downregulation suppressed GBM cell invasion, proliferation, and survival in vitro and in vivo. Together, these results reveal the capacity of human GBM cells to rapidly and robustly integrate into anatomically and molecularly diverse neuronal circuitry in the adult brain and support a model wherein rapid synapse formation onto GBM cells and transient activation of upstream neurons may lead to a long-lasting increase in fitness to promote tumor infiltration and progression.

cancer biology↗

bioRxiv2023

BIOFORMERS: A SCALABLE FRAMEWORK FOR EXPLORING BIOSTATES USING TRANSFORMERS

AO_SCPLOWBSTRACTC_SCPLOWGenerative pre-trained models, such as BERT and GPT, have demonstrated remarkable success in natural language processing and computer vision. Leveraging the combination of large-scale, diverse datasets, transformers, and unsupervised learning, these models have emerged as a promising method for understanding complex systems like language. Despite the apparent differences, human language and biological systems share numerous parallels. Biology, like language, is a dynamic, interconnected network where biomolecules interact to create living entities akin to words forming coherent narratives. Inspired by this analogy, we explored the potential of using transformer-based unsupervised model development for analyzing biological systems and proposed a framework that can ingest vast amounts of biological data to create a foundational model of biology using BERT or GPT. This framework focuses on the concept of a biostate, defined as a high-dimensional vector encompassing various biological markers such as genomic, proteomic, transcriptomic, physiological, and phenotypical data. We applied this technique to a small dataset of single-cell transcriptomics to demonstrate its ability to capture meaningful biological insights into genes and cells, even without any pre-training. Furthermore, the model can be readily used for gene network inference and genetic perturbation prediction.

bioinformatics↗

bioRxiv2023

High Frequency Longitudinal RNAseq Reveals Temporally Varying Genes and Recovery Trajectories in Rats

When living organisms are exposed to potentially toxic chemicals, they respond via changes in gene expression. Traditional differentially expressed gene analysis based on before/after blood samples does not reveal the responses temporal dynamics, and often produces false positives and negatives. Here, we performed longitudinal daily RNA sequencing on rats dosed with tetracycline, isoniazid, carbon tetrachloride, or valproate. We identified 4,302 temporally variable genes (TVGs) with statistically strong change in expression following dosing. Projecting TVG expressions into a 3-dimensional principal component (PC) space reveals consistent trajectories for recovery following dosing, and enables separation of healthy from recovering states with 91% to 99% area under the receiver operator curve. Finally, we observed that Fast Recovery vs. Slow Recovery rats exhibited distinct temporal expression patterns in the TVGs, suggesting that individual variations could be potentially captured via longitudinal RNAseq analysis.

molecular biology↗

bioRxiv2022

Screening and Development of Constitutively Synergistic Combination Drug Formulations for T Cell Acute Lymphoblastic Leukemia

Advances in multiagent chemotherapy have led to recent improvements in overall survival for patients with acute lymphoblastic leukemia (ALL); however, a significant fraction do not respond to frontline chemotherapy or later relapse with recurrent disease, after which long-term survival rates remain low. To address the challenge of developing new, effective treatment options for these patients, we conducted a series of high-throughput combination drug screens to identify chemotherapies that synergize in a lineage-specific manner with MRX-2843, a small molecule dual MERTK and FLT3 kinase inhibitor currently in clinical testing for treatment of relapsed/refractory leukemias and solid tumors. Using experimental and computational approaches, we found that MRX-2843 synergized strongly - and in a ratio-dependent manner - with vincristine chemotherapy to inhibit T-ALL cell expansion and, based on these findings, we developed multiagent lipid nanoparticle formulations of these drugs that not only constitutively maintained ratiometric drug synergy following T-ALL cell delivery, but also improved anti-leukemic activity following drug encapsulation. To determine the clinical relevance of these combination drug formulations and the therapeutic impact of ratiometric drug synergy, we compared the efficacy of lipid nanoparticles comprising synergistic, additive, and antagonistic ratios of MRX-2843 and vincristine, and observed that trends in in vitro synergy were directly recapitulated in primary T-ALL patient samples. Together, these findings present a systematic approach to high-throughput combination drug screening and multiagent drug delivery that maximizes the therapeutic potential of combined MRX-2843 and vincristine in T-ALL. This broadly generalizable approach could lead to the development of constitutively synergistic combination products for the treatment of cancer and other diseases.

bioengineering↗

bioRxiv2022

COVID-19 Contact Tracing Analysis with Bluetooth Technology Using Raspberry Pis

Contact tracing, a method for detecting and preventing the spread of a disease, can become more efficient by becoming automated, rather than being done manually. Bluetooth based contact tracing is a potential method for creating an automated method for contact tracing. However, Bluetooth signals cannot always predict something with complete accuracy due to many subtle obstructions. Received signal strength indicator (RSSI), a value produced when Bluetooth devices send and receive signals, generated from Raspberry Pis can predict the distance between the two devices. By running many experiments with variations of obstructions, I was able to successfully create models to correlate RSSI values and distance with a potential success rate of 91.973%. For my research, a success is determined to be anything but a false negative. Despite the limitations when conducting my research, the inaccuracies of my results prove Bluetooth based contact tracing to not be a reliable method for determining people who have been in contact with an index case in the real world.

bioinformatics↗

bioRxiv2021

Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Plasma lipids are heritable modifiable causal factors for coronary artery disease, the leading cause of death globally. Despite the well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing, partly due to limited sample sizes, ancestral diversity, and interpretation of potential clinical significance. Increasingly larger whole genome sequence datasets with plasma lipids coupled with methodologic advances enable us to more fully catalog the allelic spectrum for lipids. Here, among 66,329 ancestrally diverse (56% non-European ancestry) participants, we associate 428M variants from deep-coverage whole genome sequences with plasma lipids. Approximately 400M of these variants were not studied in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with plasma lipids through analysis of common and rare coding variants. We additionally discover several significantly associated rare non-coding variants largely at Mendelian lipid genes. Notably, we detect rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for plasma lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

genetics↗

bioRxiv2021

Direct capture and sequencing reveal ultra-short single-stranded DNA in biofluids

Direct capture and sequencing revealed a new DNA population in biofluids, named ultra-short single-stranded DNA (ussDNA), which was neglected by conventional DNA extraction and sequencing approaches. Evaluation of the size distribution and abundance of ussDNA in biofluids manifested generality of its presence in human, animal, and plants. Red blood cells were found to contain abundant ussDNA with enriched functional elements, and thus possesses great potential as a novel DNA biomarker.

genomics↗

bioRxiv2021

Single Tube qPCR detection and quantitation of hotspot mutations down to 0.01% VAF

Clinically and biologically, rare DNA sequence variants are significant and informative. However, existing detection technologies are either complex in workflow, or restricted in the limit of detection (LoD), or do not allow for multiplexing. Blocker displacement amplification (BDA) method can stably and effectively detect and enrich multiple rare variants with LoD around 0.1% variant allele fraction (VAF). Nonetheless, the detailed mutation information has to be identified by additional sequencing technologies. Here, we present allele-specific BDA (As-BDA), a method combining BDA with allele-specific TaqMan (As-TaqMan) probes for effective variant enrichment and simultaneous SNV profiling. We demonstrated that As-BDA could detect mutations down to 0.01% VAF. Further, As-BDA could detect up to four mutations with low to 0.1% VAF per reaction using only 15 ng DNA input. The median error of As-BDA in VAF determination is approximately 9.1%. Comparison experiments using As-BDA and droplet digital PCR (ddPCR) on peripheral blood mononuclear cell (PBMC) clinical samples showed 100% concordance for samples with mutations at [≥] 0.1% VAF. Hence, we have shown that As-BDA can achieve simultaneous enrichment and identification of multiple targeted mutations within the same reaction with high clinical sensitivity and specificity, thus helpful for clinical diagnosis.

bioengineering↗

bioRxiv2021

High-throughput variant detection using a color-mixing strategy in real-time PCR reactions

Many diseases are related to multiple genetic alterations along a single gene. Probing for highly multiple (>10) variants in a single qPCR tube is not possible due to a limited number of fluorescence channels and one variant per channel, so many more tubes are needed. Here, we experimentally validate our novel color-mixing strategy that uses fluorescence combinations as digital color codes to probe multiple variants simultaneously. The color-mixing strategy relies on a simple intra-tube assay that can probe for 15 variants as part of an inter-tube assay that can probe for an exponentially increased number of variants. The color-mixing strategy is achieved using multiplex double-stranded toehold probes modified with fluorophores and quenchers; the probes are designed to be quenched or luminous after binding to wildtype or variant templates. We used the color-mixing strategy to probe for 21 pathogenic mutations in thalassemia and to distinguish between heterozygous and homozygous variants in 6 tubes, with a specificity of 99% and a sensitivity of 94%. To support tuberculosis diagnosis, we used the same strategy to simultaneously probe in Mycobacterium tuberculosis for rifampicin-resistance mutations occurring within one 81-bp region and one 48-bp region in rpoB gene, plus five isoniazid-resistance mutations in inhA and katG genes.

genetics↗

bioRxiv2021

Experimental Confirmation of Multiple Co-Existent DNA Secondary Structures using Low-Yield Bisulfite Sequencing

Predicting DNA secondary structures is critical to a broad range of applications involving single-stranded DNA (ssDNA), yet remains an open problem. Existing prediction models are limited by insufficient experimental data, due to a lack of high-throughput methods to study DNA structures, in contrast to RNA structures. Here, we present a method for profiling DNA secondary structures using multiplexed low-yield bisulfite sequencing (MLB-seq), which examines the chemical accessibility of cytosines in thousands of different oligonucleotides. By establishing a probability-based model to evaluate the consensus probability between MLB-seq data and structures proposed using NUPACK software, we identified the secondary structures of individual ssDNA molecules and estimated the distribution of multiple secondary structures in solution. We studied the structures of 1,057 human genome subsequences and experimentally confirmed that 84% adopted two or more structures. MLB-seq thus enables high-throughput ssDNA structure profiling and will benefit the design of probes, primers, aptamers, and genetic regulators.

molecular biology↗

bioRxiv2021

High Affinity Chimeric Antigen Receptor with Cross-Reactive scFv to Clinically Relevant EGFR Oncogenic Isoforms

Tumor heterogeneity is a key reason for therapeutic failure and tumor recurrence in glioblastoma (GBM). Our chimeric antigen receptor (CAR) T cell (2173 CAR T cells) clinical trial (NCT02209376) against Epidermal growth factor receptor (EGFR) variant III (EGFRvIII) demonstrated successful trafficking of T cells across the blood brain barrier into GBM active tumor sites. However, CAR T cell infiltration was associated only with a selective loss of EGFRvIII+ tumor, demonstrating little to no effect on EGFRvIII- tumor cells. Post-CAR T treated tumor specimens showed continued presence of EGFR amplification and oncogenic EGFR extracellular domain (ECD) missense mutations, despite loss of EGFRvIII. To address tumor escape, we generated an EGFR-specific CAR by fusing monoclonal antibody (mAb) 806 to a 4-1BB co-stimulatory domain. The resulting construct was compared to 2173 CAR T cells in GBM, using in vitro and in vivo models. 806 CAR T cells specifically lysed tumor cells and secreted cytokines in response to amplified EGFR, EGFRvIII, and EGFR-ECD mutations in U87MG cells, GBM neurosphere-derived cell lines, and patient-derived GBM organoids. 806 CAR T cells did not lyse fetal brain astrocytes or primary keratinocytes to a significant degree. They also exhibited superior antitumor activity in vivo when compared to 2173 CAR T cells. The broad specificity of 806 CAR T cells to EGFR alterations gives us the potential to target multiple clones within a tumor and reduce opportunities for tumor escape via antigen loss.

cancer biology↗