Biology subjects

Zhang, Q. C.

Publications and source records attributed to Zhang, Q. C..

14 recordsLinked to original sources

bioRxiv2026

Programmable design of functional RNAs through multimodal generative learning

RNA engineering is bottlenecked by the tight coupling among sequence, structure, and function, leaving the field reliant on heuristics or screening. We introduce RNAverse, a multimodal generative model that learns a conditionable design grammar from RNA sequences, experimental structural probing profiles, and functional annotations. Beyond setting a new state of the art across 16 predictive modeling tasks, RNAverse inverts into generative design across four distinct RNA classes through three regimes, requiring experimental testing of no more than 20 candidates per-task. Zero-shot in-painting generates snoRNAs that promote premature termination codon (PTC) readthrough, and chimeric aptazymes for ligand-controlled gene regulation, exceeding rational design or large-scale screens. In both settings, RNAverse outperforms family-adapted sequence-only baselines. Fine-tuned in-painting extends to an unseen functional class, yielding IGFBP3-binding aptamers with picomolar affinity that outperform SELEX winners. Iterative optimization engineers 5' UTRs that outperform clinical benchmarks, enhancing protein production in cell-based assays for both the Zolgensma gene therapy and the BNT162b2 COVID-19 vaccine, and boosting antibody responses to BNT162b2 in mice. Together, these results establish multimodal generative learning as a route from predictive RNA modeling to programmable specification of functional RNAs.

bioinformatics↗

bioRxiv2025

CryoSeek identification of glycofibrils with diverse compositions and structural assemblies

Last year, we reported CryoSeek, a research strategy that employs cryo-electron microscopy (cryo-EM) to discover novel bio-entities from any accessible source, supplemented with AI-facilitated data processing and bioinformatic analyses. Here we report CryoSeek characterization of five additional glycofibrils isolated from the Tsinghua Lotus Pond (TLP), named TLP-IPT, TLP-12, TLP-3, TLP-2, and TLP-0, with overall resolutions ranging from 3.0-3.5 [A]. These five glycofibrils, all covered with dense glycoshells, have decreasing ratios of the central protein components, with TLP-0 with no protein at all. IPT (immunoglobulin-like, plexins, transcription factors) refers to the tandem domain that constitutes the central filament of this type of glycofibrils. In TLP-12, the central cylindrical stem is made of a trimer of dodecapeptide repeats that weave to {beta}-sheet ribbons. The central stem of TLP-3 is also a trimer, but of linear tripeptide repeats. TLP-2, similar to our previously reported TLP-4, only has a linear chain of dipeptide repeats, and glycosylation occurs to a phosphoserine in each repeat. Glycan-mediated interactions are essential for the assembly of all five glycofibrils. Our previous and present studies demonstrate the diversity in the high-order structure and folding of glycans.

biophysics↗

bioRxiv2022

rG4-seq 2.0: enhanced transcriptome-wide RNA G-quadruplex structure sequencing for low RNA input samples

RNA G-quadruplexes (rG4s) are non-canonical structural motifs that have diverse functional and regulatory roles such as transcription termination, alternative splicing, mRNA localization and stabilization and translational process. We recently developed RNA G-quadruplex structure sequencing (rG4-seq) technique and discovered many rG4s in both eukaryotic and prokaryotic transcriptomes. However, rG4-seq suffers from complicated gel purification step and limited PCR product yield and thus requires a high RNA input amount, limiting its applications for physiologically or clinically relevant studies. In this study, we have developed rG4-seq 2.0 by introducing a new ssDNA adapter containing deoxyuridine in the library preparation to enhance the library quality with no gel purification step, less PCR amplification cycles and higher yield of PCR products. We demonstrate that rG4-seq 2.0 produced high quality cDNA libraries that supported reliable and reproducible rG4 identification at varying RNA inputs (as low as 10 ng amount of RNA). rG4-seq 2.0 also improved the rG4-seq calling outcome and nucleotide bias in rG4 detection persistent in rG4-seq 1.0. Our new method can improve the identification and study of rG4s in low abundance transcripts, and our findings can provide insights to optimize cDNA library preparation in other related methods.

genomics↗

bioRxiv2021

Differential Analysis of RNA Structure Probing Experiments at Nucleotide Resolution: Uncovering Regulatory Functions of RNA Structure

RNAs perform their function by forming specific structures, which can change across cellular conditions. Structure probing experiments combined with next generation sequencing technology have enabled transcriptome-wide analysis of RNA secondary structure in various cellular conditions. Differential analysis of structure probing data in different conditions can reveal the RNA structurally variable regions (SVRs), which is important for understanding RNA functions. Here, we propose DiffScan, a computational framework for normalization and differential analysis of structure probing data in high resolution. DiffScan preprocesses structure probing datasets to remove systematic bias, and then scans the transcripts to identify SVRs and adaptively determines their lengths and locations. The proposed approach is compatible with most structure probing platforms (e.g., icSHAPE, DMS-seq). When evaluated with simulated and benchmark datasets, DiffScan identifies structurally variable regions at nucleotide resolution, with substantial improvement in accuracy compared with existing SVR detection methods. Moreover, the improvement is robust when tested in multiple structure probing platforms. Application of DiffScan in a dataset of multi-subcellular RNA structurome identified multiple regions that form different structures in nucleus and cytoplasm, linking RNA structural variation to regulation of mRNAs encoding mitochondria-associated proteins. This work provides an effective tool for differential analysis of RNA secondary structure, reinforcing the power of structure probing experiments in deciphering the dynamic RNA structurome.

bioinformatics↗

bioRxiv2021

Analysis of viral RNA-host protein interactomes enables rapid antiviral drug discovery

RNA viruses including SARS-CoV-2, Ebola virus (EBOV), and Zika virus (ZIKV) constitute a major threat to global public health and society. The interactions between viral genomes and host proteins are essential in the life cycle of RNA viruses and thus provide targets for drug development. However, viral RNA-host protein interactions have remained poorly characterized. Here we applied ChIRP-MS to profile the interactomes of human proteins and the RNA genomes of SARS-CoV-2, EBOV, and ZIKV in infected cells. Integrated interactome analyses revealed interaction patterns that reflect both common and virus-specific host responses, and enabled rapid drug screening to target the vulnerable host factors. We identified Enasidenib as a SARS-CoV-2 specific antiviral agent, and Trifluoperazine and Cepharanthine as broad spectrum antivirals against all three RNA viruses. One Sentence SummaryInteractome analyses of host proteins and the SARS-CoV-2, EBOV, and ZIKV RNA genomes unveil viral biology and drug targets.

microbiology↗

bioRxiv2021

Construction of continuously expandable single-cell atlases through integration of heterogeneous datasets in a generalized cell-embedding space

Computational tools for integrative analyses of diverse single-cell experiments are facing formidable new challenges including dramatic increases in data scale, sample heterogeneity, and the need to informatively cross-reference new data with foundational datasets. Here, we present SCALEX, a deep-learning method that integrates single-cell data by projecting cells into a batch-invariant, common cell-embedding space in a truly online manner (i.e., without retraining the model). SCALEX substantially outperforms online iNMF and other state-of-the-art non-online integration methods on benchmark single-cell datasets of diverse modalities, (e.g., scRNA-seq, scATAC-seq), especially for datasets with partial overlaps, accurately aligning similar cell populations while retaining true biological differences. We showcase SCALEXs advantages by constructing continuously expandable single-cell atlases for human, mouse, and COVID-19 patients, each assembled from diverse data sources and growing with every new data. The online data integration capacity and superior performance makes SCALEX particularly appropriate for large-scale single-cell applications to build-upon previously hard-won scientific insights.

bioinformatics↗

bioRxiv2020

A novel cell culture system modeling the SARS-CoV-2 life cycle

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the global pandemic of COVID-19, and no effective antiviral agents and vaccines are available. SARS-CoV-2 is classified as a biosafety level-3 (BLS-3) agent, impeding the basic research into its biology and the development of effective antivirals. Here, we developed a biosafety level-2 (BSL-2) cell culture system for production of transcription and replication-competent SARS-CoV-2 virus-like-particles (trVLP). This trVLP expresses a reporter gene (GFP) replacing viral nucleocapsid gene (N), which is required for viral genome packaging and virion assembly (SARS-CoV-2-GFP/{Delta}N trVLP). The complete viral life cycle can be achieved and exclusively confined in the cells ectopically expressing SARS-CoV or SARS-CoV-2 N proteins, but not MERS-CoV N. Genetic recombination of N supplied in trans into viral genome was not detected, as evidenced by sequence analysis after one-month serial passages in the N-expressing cells. Moreover, intein-mediated protein trans-splicing approach was utilized to split the viral N gene into two independent vectors, and the ligated viral N protein could function in trans to recapitulate entire viral life cycle, further securing the biosafety of this cell culture model. Based on this BSL-2 SARS-CoV-2 cell culture model, we developed a 96-well format high throughput screening for antivirals discovery. We identified salinomycin, tubeimoside I, monensin sodium, lycorine chloride and nigericin sodium as potent antivirals against SARS-CoV-2 infection. Collectively, we developed a convenient and efficient SARS-CoV-2 reverse genetics tool to dissect the virus life cycle under a BSL-2 condition. This powerful tool should accelerate our understanding of SARS-CoV-2 biology and its antiviral development.

microbiology↗

bioRxiv2020

CD127 imprints functional heterogeneity to diversify monocyte responses in human inflammatory diseases

Studies on human monocytes historically focused on characterization of bulk responses, whereas functional heterogeneity is largely unknown. Here, we identified an inducible population of CD127-expressing human monocytes under inflammatory conditions and named the subset M127. M127 is nearly absent in healthy individuals yet abundantly present in patients with infectious and inflammatory conditions such as COVID-19 and rheumatoid arthritis. Multiple genomic and functional approaches revealed unique gene signatures of M127 and unified anti-inflammatory properties imposed by the CD127-STAT5 axis. M127 expansion correlated with mild COVID-19 disease outcomes. Thereby, we phenotypically and molecularly characterized a human monocyte subset marked by CD127 that retained anti-inflammatory properties within the pro-inflammatory environments, uncovering remarkable functional diversity among monocytes and signifying M127 as a potential therapeutic target for human inflammatory disorders.

immunology↗

bioRxiv2020

Predicting dynamic cellular protein-RNA interactions using deep learning and in vivo RNA structure

Interactions with RNA-binding proteins (RBPs) are crucial for RNA regulation and function. While both RNA sequence and structure are critical determinants, RNA structure is dependent on cellular environment and especially important in regulating dynamic RBP bindings across various conditions. However, how distinct it contributes to RBP binding in vivo remains poorly understood. To address this issue, we obtained transcriptome-wide RNA secondary structure profiles in multiple cell-types, and established a deep neural network, PrismNet, that uses in vivo RNA structures to accurately predict cellular protein-RNA interactions. With a deep learning "attention" strategy, PrismNet discovers the exact binding nucleotides and their mutational effect. The predicted binding sites are highly conserved and enriched for rare, deleterious genetic variants. Remarkably, dynamic RBP binding sites are enriched for structure-changing variants (riboSNitches), which are often associated with disease, reflecting dysregulated RBP bindings. Our resource enables the analysis of cell-type-specific RNA regulation, with applications in human disease. Highlights1, A big data resource of transcriptome-wide RNA secondary structure profiles in multiple cell types 2, PrismNet, a deep neural network, accurately models the sequence and structural combined patterns of protein-RNA interactions in vivo 3, RNA structural information in vivo is critical for the accurate prediction of dynamic RBP binding in various cellular conditions 4, PrismNet can dissect and predict how mutations affect RBP binding via RNA sequence or structure changes 5, RNA structure-changing RiboSNitches are enriched in dynamic RBP binding sites and often associated with disease, likely disrupting RBP-based regulation

cell biology↗

bioRxiv2019

The identification of mecciRNAs and their roles in mitochondrial entry of proteins

Mammalian mitochondria have small genomes encoding very limited numbers of proteins. Over one thousand proteins and noncoding RNAs encoded by nuclear genome have to be imported from the cytosol into the mitochondria. Here we report the identification of hundreds of circular RNAs (mecciRNAs) encoded by mitochondrial genome. We provide both in vitro and in vivo evidence to show that mecciRNAs facilitate mitochondrial entry of nuclear-encoded proteins by serving as molecular chaperones in the folding of imported proteins. Known components of mitochondrial protein and RNA importation such as TOM40 and PNPASE interact with mecciRNAs and regulate protein entry. Expression of mecciRNAs is regulated, and these transcripts are critical for mitochondria in adapting to physiological conditions and diseases such as stresses and cancers by modulating mitochondrial protein importation. mecciRNAs and their associated physiological roles add categories and functions to eukaryotic circular RNAs, and shed novel lights on communication between mitochondria and nucleus.

molecular biology↗

bioRxiv2019

VRmol: an Integrative Cloud-Based Virtual Reality System to Explore Macromolecular Structure

Past decades have seen much effort devoted to the tool development for biomacromolecule structural visualization and analysis. In recent years, we have witnessed tremendous advancement in computational technologies, especially in graphics and internet. Here we present an integrative cloud-based, virtual reality (VR) system -- VRmol that exploits these technology advances to visualize and study macromolecule structures in various forms. The immersive environment can improve user experiences in visualization, calculation, and editing of complex structures with more intuitive perception. VRmol is also a system with cloud-based capability to directly access disease-related databases, and couples the structure with genomic variation as well corresponding drugs information in a visual interface, thus serving as an integrative platform to aid structure-based translational research and drug design. VRmol is freely available at https://VRmol.net.

bioinformatics↗

bioRxiv2018

Integrative analysis of Zika virus genome RNA structure reveals critical determinants of viral infectivity

Since its outbreak in 2007, Zika virus (ZIKV) has become a global health threat that causes severe neurological conditions. Here we perform a comparative in vivo structural analysis of the RNA genomes of two ZIKV strains to decipher the regulation of their infection at the RNA level. Our analysis identified both known and novel functional RNA structural elements. We discovered a functional long-range intramolecular interaction specific for the Asian epidemic strains, which contributes to their infectivity. Our findings illuminate the structural basis of ZIKV regulation and provide a rich resource for the discovery of RNA structural elements that are important for ZIKV infection.

molecular biology↗

bioRxiv2018

Dynamic Regulation of RNA Structure in Mammalian Cells

RNA structure is intimately connected to each step of gene expression. Recent advances have enabled transcriptome-wide maps of RNA secondary structure, termed RNA structuromes. However, previous whole-cell analyses lacked the resolution to unravel the dynamic regulation of RNA structure across subcellular states. Here we reveal the RNA structuromes in three compartments -- chromatin, nucleoplasm and cytoplasm. The cytotopic structuromes substantially expand RNA structural information, and enable detailed investigation of the central role of RNA structure in linking transcription, translation, and RNA decay. Through comparative structure analysis, we develop a resource to visualize the interplay of RNA-protein interactions, RNA chemical modifications, and RNA structure, and predict both direct and indirect reader proteins of RNA modifications. We validate the novel role of the RNA binding protein LIN28A as an N6-methyladenosine (m6A) modification \"anti-reader\". Our results highlight the dynamic nature of RNA structures and its functional significance in gene regulation.

molecular biology↗

bioRxiv2018

U1 snRNP regulates chromatin retention of noncoding RNAs

Thousands of noncoding transcripts exist in mammalian genomes, and they preferentially localize to chromatin. Here, to identify cis-regulatory elements that control RNA-chromatin association, we developed a high-throughput method named RNA element for subcellular localization by sequencing (REL-seq). Coupling REL-seq with random mutagenesis (mutREL-seq), we discovered a key 7-nt U1 recognition motif in chromatin-enriched RNA elements. Reporter assays indicated a direct role for U1 snRNP recognition in regulating RNA-chromatin localization. Globally, U1 motifs and U1 binding are strongly enriched in long noncoding RNA (lncRNA) transcripts. Inhibition of U1 snRNA, and of U2 to a lesser degree, led to global reduction in chromatin association of hundreds of lncRNAs. For promoter- and enhancer-associated noncoding RNAs, U1 binds to their genomic neighborhoods, and their chromatin association depends on both U1 and U2 snRNAs. These findings reveal that U1 snRNP, perhaps together with the splicing machinery, acts widely to promote the chromatin association of noncoding transcripts.

molecular biology↗