Biology subjects

Fang, L.

Publications and source records attributed to Fang, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

SpaDiff: Denoising for Sequence-based Spatial Transcriptomics via Diffusion Process

Spatial transcriptomics enables transcriptome-scale analysis with spatial resolution but suffers from spot-swapping, where RNA molecules drift from their true locations, introducing noise and reducing spatial specificity. We introduce SpaDiff, a denoising method that treats spot-swapping as a diffusion process. SpaDiff simulates the displacement of RNA molecules and reverses it to restore their original spatial distribution while preserving molecular counts. Evaluations on simulated and real data demonstrate that SpaDiff enhances spatial specificity of gene expression, improves data integrity, and supports more accurate downstream analyses such as clustering and spatial domain identification.

bioinformatics↗

bioRxiv2025

Optimal Gene Panel Selection for Targeted Spatial Transcriptomics Experiments

Spatial transcriptomics analysis is a powerful approach for dissecting the structure of tissue microenvironment and uncovering the mechanism of cell-cell communications. However, existing technologies are limited by either spatial resolution or gene coverage. Most single-cell resolution technologies target only a few hundreds of pre-selected genes, whose choice plays an important role in the overall analysis. It remains a challenge to optimally design a gene panel to maximize the utility of spatial transcriptomics profiling. To fill this gap, we introduce a novel method, named ReconST, to automatically design optimal gene panels for spatial transcriptomics profiling. ReconST leverages information from existing scRNA-seq data, and identifies the optimal subset of genes by using a gated autoencoder. By using a high-coverage mouse brain MERFISH dataset as the reference benchmark, we showed that ReconST outperforms existing methods in terms of both reconstruction accuracy and spatial pattern preservation. As such, ReconST provides a useful and generally-applicable tool for optimal gene panel design, which in turn can significantly enhance the utility of spatial transcriptomics profiling in a wide range of biomedical investigations.

bioinformatics↗

bioRxiv2025

An integrated multi-tissue atlas of epigenomic landscapes and regulatory elements in the bovine genome

Deciphering the regulatory syntax of the genome is essential to understand the genetic and molecular architecture of complex traits, as most trait-associated variants lie in non-coding regions. Yet, functional annotation of the bovine genome remains limited, hindering our ability to unravel the mechanisms underpinning complex traits of economic and ecological importance in cattle. Here, we present a comprehensive epigenetic atlas comprising 1,138 genome-wide epigenetic profiles, including chromatin accessibility, six histone modifications, CCCTC-binding factor (CTCF) transcription factor binding, DNA methylation, chromatin conformation, and transcriptomes across 53 adult tissues, five fetal tissues, and seven primary cell types. This atlas-level data enables us to annotate around 45% of the genome as putative regulatory elements exhibiting tissue- or cell-specific regulatory activity. Leveraging sequence-to-function deep learning models, we discovered 301 sequence motifs and predicted the functional impact of genetic variants through in silico mutagenesis, thereby facilitating the decoding of the regulatory syntax of the cattle genome and fine-mapping of GWAS loci for 22 complex traits. Cross-species analysis further revealed evolutionarily conserved features of regulatory architecture and provided evolutionary insights into complex traits and diseases in humans. Together, this atlas offers a foundational resource for advancing cattle functional genomics, sustainable breeding, and studies of regulatory evolution.

genomics↗

bioRxiv2025

The Impact of New Urbanization on Quantity Increase and Quality Improvement of Green Innovation: Based on Multivariate Moderating Effect Models

New urbanization is a major national strategy that China has proposed and implemented. Whether new urbanization (NEU) can promote quantity increase and quality improvement of green innovation (GI) is a common concern of the government and scholars. This paper empirically analyzes quantity increase and quality improvement effects of new urbanization on urban GI by adopting the panel data of each city from 2011 to 2022. The study finds that new urbanization not only has a positive contribution to the quantity increase of GI in cities but also plays a positive role in the quality improvement of GI. Digital inclusive finance will further amplify the dividends of new urbanization and exert the GI effect. The interaction of digital inclusive finance and government support, informatization, regional economic development, and energy consumption also amplify the dividends of NEU and exert strong "quantity increase" and "quality improvement" effects on GI. The stronger the governments green support, the more conducive it is to new urbanization to further exert quantity increase and quality improvement effects on GI. The conclusions of this paper have important policy implications for further promoting the construction of new urbanization and GI.

ecology↗

bioRxiv2025

Myocyte Enhancer Factor 2A Orchestrates Vascular Redox Homeostasis via Direct Transcriptional Activation of SIRT1

Myocyte enhancer factor 2A (MEF2A), a transcription factor implicated in coronary artery disease, remains unexplored in vascular redox regulation. To address this gap and overcome limitations of current antioxidant therapies, we investigated MEF2As role in oxidative defense using human umbilical vein endothelial cells (HUVECs) and murine models. Adenoviral vectors encoding MEF2A-specific shRNA or mRNA were employed to silence or overexpress MEF2A in HUVECs. For in vivo validation, endothelial-targeted MEF2A knockdown was achieved via AAV1-shRNA delivery in mice fed a high-fat diet. Systemic redox status was assessed by measuring reactive oxygen species (ROS), glutathione homeostasis (GSH/GSSG ratio), NADH/NAD+ balance, mitochondrial membrane potential ({Delta}{Psi}m), and 8-hydroxy-2'-deoxyguanosine (8-OHdG). Mechanistic insights were derived from immunofluorescence, qPCR, western blotting, and dual-luciferase reporter assays. MEF2A silencing induced redox imbalance, characterized by elevated ROS, reduced GSH/GSSG ratio, and {Delta}{Psi}m collapse. Conversely, MEF2A overexpression synergized with SIRT1 to restore glutathione pools, maintain NAD+ homeostasis, and suppress ROS under oxidative stress. Chromatin immunoprecipitation confirmed direct MEF2A binding to two cis-elements in the SIRT1 promoter, driving transcriptional activation. In vivo, MEF2A-deficient mice exhibited amplified vascular oxidative damage, including elevated DNA damage marker (8-OHdG) and ROS levels. Downregulation of SIRT1/PGC-1 in MEF2A silenced cells was verified in vivo. Our findings establish MEF2A as a master regulator of endothelial redox defense via the SIRT1-PGC-1 axis, offering a mechanistic foundation for targeting oxidative cardiovascular disorders. This work suggests pharmacological MEF2A activation as a novel strategy for precision antioxidant therapy in vascular medicine.

molecular biology↗

bioRxiv2025

A chimeric Ad5-Envp-VLP vaccine platform confers broad-spectrum immunity against emerging and re-emerging pathogens

Integrating complementary vaccine modalities is essential for combating emerging infectious threats. Here, we developed Ad5-Envp-VLP, a chimeric adenoviral platform synergizing adenoviral delivery efficiency with virus-like particle (VLP) structural mimicry. This system stably produces self-assembling VLPs in suspension HEK293 cultures, exhibiting enhanced immunogenicity over soluble antigens. Following intramuscular immunization, the platform induces early B cell expansion and sustains germinal center reactions, driven by the upregulation of B cell cycle-related genes (Cdc6, Cdc45, Cdc20, Cdc25C, Aurka, Aurkb, and Ccnb1/2) and robust T follicular helper (Tfh) cell differentiation, generating durable neutralizing antibodies against both influenza virus and rabies virus. These effects are conserved across mouse, canine, and feline models. Crucially, integrated flow cytometry and scRNA-seq demonstrate that intranasal delivery recruits and functionally reprograms lung innate immune cells (notably alveolar macrophages and dendritic cells), driving mucosal sIgA secretion and CTL responses. A single nasal dose confers lasting protection against homologous and heterologous influenza A strains. The platform also elicits cross-neutralizing antibodies against SARS-CoV-2 variants. Together, Ad5-Envp-VLP thus establishes a modular vaccine platform for antigenically plastic pathogens by combining in vivo self-assembly with dual pulmonary-muscular delivery. One Sentence SummaryNovel mucosal and systemic vaccine delivers self-assembling particles, triggering strong lung immunity and broad virus protection across species.

immunology↗

bioRxiv2025

An atlas of cell type specific regulatory effects in cattle

Understanding the genetic and molecular architecture of complex traits and artificial selection is crucial for advancing sustainable precision breeding in cattle and other livestock. Yet, how genetic variation affects cellular gene expression remains elusive in cattle. Here, by integrating 8,866 bulk RNA-seq samples and 999,192 single cells of 81 cell types in 22 bovine tissues, we presented a comprehensive atlas of regulatory variants at the cell type resolution in cattle. By colocalizing with bulk-tissue expression quantitative trait loci (beQTL), we detected 57,043 novel cell-type stratified eQTL and cell-type/state interaction eQTL in 18,153 genes, which also exhibited a stronger tissue/cell-type specificity than beQTL. By examining genome-wide associations (GWAS) of 44 complex traits, these cell-resolved eQTL were colocalized with 505 (24%) additional GWAS loci compared to beQTL. Through integrating this resource with selection signatures between dairy and beef cattle, we provided tissue/cell-specific regulatory insights into cattle breeding. Overall, the current atlas of cell-type-specific regulatory variants will serve as an invaluable resource for cattle genomics and selective breeding.

genetics↗

bioRxiv2025

PB-scope: Contrastive learning of dynamic processing body formation reveals undefined mechanisms of approved compounds

Membraneless organelles (MLOs) formed by liquid-liquid phase separation contribute to intracellular compartmentalization of specific biological functions. The dynamic regulation of MLOs is critical for RNA metabolism, stress response, and signal transduction. While the number and size of MLOs serve as valuable indicators of cellular states, leveraging their spatial distribution and diverse quantitative characteristics to infer cellular conditions has posed significant challenges. Here, we present processing body (PB)-scope: an unsupervised deep learning-based framework designed for imaging-based phenotypic screening of PB, one representative MLO. The model was trained on a substantial dataset comprising over 400,000 single-cell confocal microscopy images from a colon cancer cell line treated with 280 compounds. PB-scope enabled precise drug classification based on their effects on PB characteristics, including number and size. This artificial intelligence framework offers insights previously obscured by the dynamic and subtle nature of PBs. Notably, PB-scope identified drugs with a shared function in the JAK signaling pathway, a previously unrecognized regulator of PB dynamics. PB-scope holds the potential for adapting to the study of other MLOs, offering broad applicability in this emerging field of cell biology.

cell biology↗

bioRxiv2025

Scavenger Receptor class F member 2 is an intracellular receptor for Hepatitis B virus

Hepatitis B virus (HBV) infects hepatocytes by specific binding to the cell-surface receptor --sodium taurocholate cotransporting polypeptide (NTCP)--through the preS1 region of its large envelop protein, followed by a less well understood transport process across the cytoplasm to the nucleus. Here, we report that scavenger receptor class F member 2 (SCARF2), a single-pass transmembrane protein, functions as an intracellular receptor for HBV. SCARF2 binds to a preS1 region downstream of the NTCP binding site through its N-terminal EGF-like domains 4-6, and its proline-rich C-terminal domain also plays an indispensable role in the infection. The internalized HBV virions are transported to the cytoplasmic side of nuclear pore complexes (NPCs) within the SCARF2-containing endosomes. HBV capsid release from the endosomal vesicles is significantly impaired by knockdown of SCARF2. These results suggest a model that SCARF2 conveys HBV to the periphery of NPCs and ultimately leads to viral capsid release for nuclear entry.

microbiology↗

bioRxiv2025

Controlling the taxonomic composition of biological information storage in 16S ribosomal RNA

Microbes can be programmed to record participation in gene transfer by coding biological-recording devices into mobile DNA. Upon DNA uptake, these devices transcribe a catalytic RNA (cat-RNA) that binds to conserved sequences within ribosomal RNA (rRNA) and perform a trans-splicing reaction that adds a barcode to the rRNA. Existing cat-RNA designs were manually generated to be broad-host range, providing no control over the organisms that were barcoded. To achieve control over the organisms barcoded by cat-RNA, we created a program called Ribodesigner that uses input sets of rRNA sequences to create designs with varying specificities. We show how this algorithm can be used to identify designs that enable kingdom-wide barcoding, or selective barcoding of specific taxonomic groups within a kingdom. We use Ribodesigner to create cat-RNA designs that target Pseudomonadales while avoiding Enterobacterales, and we compare the performance of one design to a cat-RNA that was previously found to be broad host range. When conjugated into a mixture of Escherichia coli and Pseudomonas putida, the new design presents increased selectivity compared to a broad host range cat-RNA. Ribodesigner is expected to aid in developing cat-RNA that store information within user-defined sets of microbes in environmental communities for gene transfer studies. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/651329v2_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@bcc65borg.highwire.dtl.DTLVardef@18288f2org.highwire.dtl.DTLVardef@ecf5c7org.highwire.dtl.DTLVardef@fbe064_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

An integrated landscape of mRNA and protein isoforms

Alternative splicing and proteolytic processing expand the functional diversity of the human proteome by generating distinct protein isoforms from a single gene. However, the extent to which transcript isoforms give rise to distinct protein products remains unclear, in part due to technical limitations in proteomic workflows. Here, we combine full-length mRNA sequencing with SDS-PAGE-based protein fractionation and quantitative mass spectrometry to construct an integrated landscape of mRNA and protein isoforms in human RPE-1 cells. To overcome the inherent ambiguity of bottom-up proteomics in isoform detection, we developed IsoFrac, a computational pipeline that resolves protein isoforms based on their migration profiles across gel fractions. This approach enabled the identification of [~]45,000 full-length transcripts, [~]32,000 ORFs, and [~]16,000 distinct protein isoforms. Comparative analyses revealed widespread translation of alternative transcripts and uncovered proteolytic processing as a major, underappreciated source of proteome complexity. Our results establish a scalable framework for isoform-resolved proteogenomics and provide a reference resource for studying the molecular diversity encoded by the human genome.

systems biology↗

bioRxiv2025

Genetic control of the transcriptional response to active tuberculosis disease and treatment

Understanding the functional impact of genomic sequence variants is critical for evaluating the role of genetic variation in the host response during tuberculosis (TB) disease and anti-TB treatment (ATT). Hitherto, there have been no genome-wide in vivo response expression quantitative trait loci (reQTL) studies conducted for active TB and ATT. Here, using longitudinal peripheral blood RNA-seq data from n = 48 patients with active TB who underwent ATT, we call sequence variants directly from these transcriptomes and impute them with a multi-ancestry reference panel. Associating our variants with the expression of nearby genes, we characterise thousands of cis-eQTL and hundreds of reQTL. We further show significant changes in cell type proportions during ATT through deconvolution of the bulk RNA-seq data and identify the putative cell type specific nature of cis-eQTL. Our work sheds light on the immunogenetics of TB disease and treatment, while providing a framework for studies using only RNA-seq data.

genetics↗

bioRxiv2025

Proteomic Analysis of PTEN-Deficient Cells Reveals Src-Mediated Upregulation of EphA2 and Therapeutic Potential of Dual Inhibition

Loss of the tumor suppressor PTEN is frequently observed in various cancers and promotes tumorigenesis by activating the PI3K-AKT pathway. However, the effectiveness of therapies targeting this pathway is limited by complex signaling crosstalk and compensatory mechanisms. Here, we employed quantitative proteomic and phosphoproteomic analyses using MCF10A PTEN knockout models to comprehensively map the signaling alterations induced by PTEN loss. Our analyses revealed that PTEN deficiency not only activates canonical PI3K-AKT signaling but also induces widespread changes in cytoskeleton organization, cell cycle regulation, and central carbon metabolism. PTEN loss also substantially elevates the activity of a variety of tyrosine kinases, including Src kinase and EphA2, a receptor tyrosine kinase (RTK) implicated in cancer progression. Mechanistic studies demonstrated that Src activation, rather than the canonical AKT signaling pathway, drives the upregulation of the receptor tyrosine kinase EphA2. The activation of the noncanonical tyrosine kinase signaling renders AKT inhibition alone insufficient in PTEN-deficient cancers. Importantly, combined treatment with the FDA-approved AKT inhibitor capivasertib and the Src inhibitor dasatinib synergistically induced apoptosis and suppressed the tumor cell growth in various PTEN-deficient cell lines as well as in three-dimensional cultures of endometrial cancer patient-derived xenograft models. Our study reveals that PTEN loss drives oncogenic signaling via dual activation of PI3K-AKT and tyrosine kinase pathways. Specifically, Src-mediated upregulation of EphA2 in PTEN-deficient cells highlights a therapeutic vulnerability that can be exploited by combined AKT and Src inhibition. This approach addresses the resistance associated with AKT inhibition alone and enhances therapeutic efficacy in PTEN-deficient cancers, supporting its potential application in targeted combination therapies.

cancer biology↗

bioRxiv2025

Mapping the Landscape of Allele-Specific Expression In Porcine Genomes

Allele-specific expression (ASE) is the imbalanced expression of two alleles of the same locus. It is quite pervasive among mammals and is associated with healthy and economically relevant traits. ASE is often used to support the identification of variants related to gene expression (cis-eQTLs). Thus, profiling ASE represents a significant step in elucidating the mechanism underlying gene expression regulation. In this study, we developed an ASE pipeline using public available RNA-seq data and open-source software. Using this pipeline, we were able to profile pervasive allelic imbalance across 42 tissues and 34 breeds from the Farm-GTEX-pig consortium at both SNP and gene levels without the need for parental genotype or whole genome sequence data. ASE was widely, but not evenly, spread across the genome. We also observed considerable variation in ASE profiles among various tissues, in which the ASE fraction ranged from 1.3% to 54.1%. ASE tends to be highly tissue-specific, and the overlap across tissues is limited. The functional analysis of tissue-specific ASE sites indicates that they are involved in the critical maintenance of these tissues. Our ASE pipeline can be readily applied to other RNA-seq data sets for livestock, thereby significantly expanding its potential utility. The wealth of available ASE resources provides a solid foundation for identifying regulatory elements within the genome that drive complex traits in livestock, making our pipeline and results valuable resources for researchers in this field.

genomics↗

bioRxiv2025

Tensor analysis of animal behavior by matricization and feature selection

Contemporary neurobehavior research often collects multi-dimensional tensor (MDT) data, consisting of time-series measurements for multiple features from multiple animals subjected to various perturbations. Proper analysis of the MDT data can facilitate the dissection of the underlying neural circuitry driving the behavior. However, many common approaches for MDT analysis, such as tensor decomposition, often yield results that are difficult to interpret and not directly compatible with standard multivariate analysis (MVA), which is designed for simpler, lower-dimensional data structures. To address this issue, dimensionality reduction techniques, including matricization methods such as Index Construction and Feature Concatenation, are applied to transform all or a subset of the features in the MDT into a lower-dimensional tensor, commonly a 2-dimensional tensor (2DT), that is compatible with MVA. However, the matricization methods may exclude information from the MDT features or create too many 2DT features that introduce spurious noise to the downstream analyses. Their impacts on the downstream MVA performance remain elusive. In this study, we systematically evaluated different approaches for matricization and feature selection and their impacts on MVA performance using an MDT dataset of zebrafish visual- motor response collected from wild-types (WTs) and visually-impaired mutants. We matricized the MDT dataset using various Index Construction and Feature Concatenation methods, then identified informative 2DT features using the filter and embedded methods. To evaluate these feature-selection approaches, we conducted a classification task distinguishing WT and visually-impaired zebrafish by multiple classifiers. We then assessed classification performance with cross-validation and holdout validation. We found that most classifiers performed the best when using all 2DT features matricized by Feature Concatenation and selected by the embedded method. The results also revealed unique behavioral differences between the WTs and visually-impaired mutants that were not identified by standard MVA or MDT analysis. Our results demonstrate the utility of analyzing MDT behavioral data by matricization and feature selection.

animal behavior and cognition↗

bioRxiv2024

OmiGA: A Toolkit for Ultra-efficient Molecular Trait Analysis in Complex Populations

Molecular quantitative trait loci (molQTL) mapping is one of the most popular approaches to systematically characterize functional impacts of genomic variants, leading to advanced understanding of the regulatory mechanisms underpinning complex traits and diseases. However, when applied to high-throughput molecular phenotypes, the existing molQTL mapping tools often implement simple linear models, overlooking complex inter-individual relatedness, leading to false positives and insufficient statistical power. Here, we introduce the Omics Genetic Analysis toolkit (OmiGA), an ultra-efficient linear mixed model (LMM) based toolkit, for molQTL mapping in populations with complex relatedness. Both computational simulations and real data analyses demonstrated that OmiGA outperformed the existing popular tools regarding molQTL discovery power, fine mapping of causal variants, colocalization of molQTL and trait associations, and computational efficiency. In summary, we recommend OmiGA for molQTL mapping in populations with complex relatedness, for example, those in the Farm animal Genotype-Tissue Expression (FarmGTEx) project and family-based molQTL studies in humans.

bioinformatics↗

bioRxiv2024

Identifying Effect Modification of Latent Population Characteristics on Risk Factors with a Sparse Varying Coefficient Regression

Leveraging observational data to understand the associations between risk factors and disease outcomes and conduct disease risk prediction is a common task in epidemiology. While traditional linear regression and other machine learning models have been extensively implemented for this task, the associations between risk factors and disease outcomes are typically deemed fixed. In many cases, however, such associations may vary by some underlying features of the individuals, which may involve certain subpopulation characteristics and environmental factors. While data for these latent features may not be available, the observed data on risk factors may have captured some proportion of the variation in these features. Thus extracting latent factors from risk factors and incorporating this effect modification into the model may better capture the underlying data structure and improve inference. We develop a novel regression model with some coefficients varying as functions of latent features extracted from the risk factors. We have demonstrated the superiority of our approach in various data settings via simulation studies. An application on a dataset for lung cancer patients from The Cancer Genome Atlas (TCGA) Program showed that our approach led to a 6% - 118% increase in (AUC-0.5) for distinguishing between different lung cancer stages compared to the classic lasso and elastic net regressions and identified interesting latent effect modifications associated with certain gene pathways.

genetics↗

bioRxiv2024

A multi-tissue developmental gene expression atlas towards understanding the biological basis of phenotypes in sheep

Sheep (Ovis aries) represents one of the most important livestock species for animal protein and wool production worldwide. However, little is known about the genetic and biological basis of ovine phenotypes, particularly for those of high economic value and environmental impact. Here, by generating and integrating 1,413 RNA-seq samples from 51 distinct tissues across 14 developmental time points, representing early prenatal, late prenatal, neonate, lamb, juvenile, adult, and elderly stages, we built a high-resolution developmental Gene Expression Atlas (dGEA) in sheep. We observed dynamic patterns of gene expression and regulatory networks across tissues and developmental stages. When harnessing this resource for interpreting genomic associations of 48 monogenetic and 12 complex traits in sheep, we found that genes upregulated at prenatal developmental stages played more important roles in shaping these phenotypes than those upregulated at postnatal stages. For instance, genetic associations of crimp number, mean staple length (MSL), and individual birth weight were significantly enriched in the prenatal rather than postnatal skin and immune tissues. By comprehensively integrating fine-mapping results and the sheep dGEA, we identified several key genes associated with complex traits in sheep, such as SOX9 (associated with MSL), GNRHR (associated with litter size at birth), and PRKDC (associated with live weight). These results provide novel insights into the gene regulatory and developmental architecture underlying ovine phenotypes. The dGEA (https://sheepdgea.njau.edu.cn/) will serve as an invaluable resource for sheep developmental biology, genetics, genomics, and selective breeding.

genetics↗