Search bioRxiv⌕ Search

Biology subjects

Zeng, B.

Publications and source records attributed to Zeng, B..

At least 19 recordsLinked to original sources

In situ Discovery of Immune Repertoire Reveals Antitumor Immunity and Therapeutic Antibodies

Spatial transcriptomics offers a glimpse into the immunology of tissues. However, limitations in spatial transcriptomics preclude the detection of highly diverse, low-abundance, and previously unknown sequences, including immune repertoires and microbiota. Here, we introduce Archimap, a spatial transcriptomic platform that simultaneously profiles spatial transcriptomes, immune repertoires, and microbiota from formalin-fixed paraffin-embedded (FFPE) tissues. Using Archimap, we profile the spatial localization of TCRs, BCRs, and the microbiota landscape in archived clinical tissues at single-cell resolution. Through comprehensive benchmarking, we validate Archimaps performance and fidelity. Archimap in situ assembles the immune complex and reconstructs the clonal evolution of antibodies. Together, Archimap shows the power of in situ discovery of functional immune repertoires for their antitumor immunity.

bioinformatics↗

Refinement of Nucleus Accumbens Neuronal Dynamics During Cocaine Self-Administration Training

Drug addiction is an acquired motivational-behavioral state that begins with drug taking, which is comprised of a series of phases, including initial acquisition, stabilization, habituation, and maintenance. In rodent models of cocaine self-administration, the forebrain region nucleus accumbens (NAc) has been critically implicated in the acquisition-maintenance process of drug taking and seeking behaviors. However, it remains unknown how NAc neurons shift their activity patterns in response to these phasic transitions during cocaine taking. To examine this, we used GCaMP6m-based in vivo Ca2+ imaging to monitor activities of principal medium spiny neurons (MSNs) in the NAc across eleven days of cocaine self-administration. Behaviorally, mice exhibited progressive stabilization of operant responding and locomotion across 11 days of cocaine self-administration. During the early training days, we detected a portion of NAc neurons--a potential neuronal ensemble--that exhibited increased activities temporally contingent to the lever-press for cocaine. The number of NAc neurons exhibiting contingent activity increased progressively over the first three training days and then decreased gradually during the later training days, exhibiting expansion-refinement dynamics that may correspond to the acquisition and subsequent stabilization/maintenance of cocaine self-administration. Using a neuron-tracking technique, we found that the lever-press-contingent NAc ensemble exhibited substantial compositional dynamics, with neurons dropping into and out across training days. These activity features of lever-press-contingent neurons may represent key circuit dynamics of the NAc that transition the acquisition toward the maintenance of cocaine-taking behavior.

neuroscience↗

Myeloid CD209 impairs T-cell activation by inducing ICAM-2-ERM-dependent cortical stiffening

Resistance to PD-1-based immunotherapy remains a major challenge in cancer treatment, especially in immunologically "cold" tumors characterized by T-cell exclusion and impaired effector function. Tumor-associated myeloid cells are important mediators of this resistance, but whether they directly suppress T-cell immunity through mechanical regulation remains unclear. Here, we identify DC-SIGN (CD209), a myeloid-expressed C-type lectin receptor, as a mechanosuppressive regulator of antitumor T-cell immunity. DC-SIGN is selectively enriched in tumor-infiltrating M2-like macrophages and monocytes, and its expression is associated with poor clinical response to PD-1 blockade and elevated TIDE scores across multiple cancer types. Mechanistically, DC-SIGN directly engages ICAM-2 on T cells and activates ROCK1-ERM signaling. This interaction increases T-cell cortical stiffness, destabilizes T cell-antigen-presenting cell interactions, and attenuates T-cell receptor signaling. Blocking the DC-SIGN-ICAM-2-ERM pathway restores T-cell activation and promotes CD8+ T-cell infiltration and effector function in mouse, humanized, and ex vivo human tumor systems. Importantly, DC-SIGN blockade overcomes resistance to PD-1-based immunotherapy in refractory and immunologically "cold" tumor models, and further enhances the response to PD-1 inhibition. Together, our findings define a myeloid-derived mechanical immune checkpoint and reveal T-cell mechanosuppression as a targetable mechanism of tumor immune evasion and immunotherapy resistance.

immunology↗

Automating the Construction of Contextualized Biomedical Knowledge Graphs for Scientific Inference

Biomedical interactions are inherently dynamic, often shifting or even reversing under specific physiological states. However, existing extraction methods simplify these complex mechanisms into context-agnostic binary associations, resulting in semantic loss and contradictory evidence. Here, we present AutoBioKG, an end-to-end framework that constructs context-aware knowledge graphs by leveraging composite triples to encode environmental conditions and entity attributes alongside core relationships. Powered by an open information extraction model trained on BioOpenIE and further refined through self-training with pseudo-labels from unlabeled literature, the framework exhibits broad generalization. Notably, AutoBioKG achieved the highest zero-shot F1 across DDI, ChemProt, and BioRED, outperforming the best-performing baseline on each benchmark by 3.6-17.8 percentage points. Furthermore, AutoBioKG-derived graphs outperformed existing approaches on yes/no, factoid, and list questions in the BioASQ biomedical question-answering evaluation, particularly for queries requiring fine-grained contextual information. Together, these results support AutoBioKG as a scalable framework for transforming unstructured literature into structured, context-aware biomedical knowledge.

bioinformatics↗

Stimuli-Expressed Protein Qubits for Quantum Quantification of Heavy Metals in Natural Water

Environmental heavy metal pollution poses a severe threat to ecological security and human health, necessitating the development of highly sensitive, specific, and rapid detection technologies. Traditional fluorescent biosensors are often constrained by high background interference and limited sensitivity, while single-target detection systems struggle to meet the demands of complex environmental monitoring. This study constructs a novel magnetically modulated photonic quantum biosensing system based on the CadC-T7 gene circuit, replacing the traditional fluorescent reporter gene EGFP with the magnetically modulated fluorescent protein MagLOV - a quantum biomaterial. To enhance its magnetic modulation performance, the mutant with the highest lock-in amplitude during the directed evolution (R10, MagLOV 2) was selected; Simultaneously, systematic parameter optimization was conducted to determine the optimal magnetic modulation frequency (0.05 Hz), the heavy metal stimulation duration (the 2-hour group exhibited the most significant intra-group variation), and the bacterial concentration at the onset of the heavy metal stimulation (controlled at OD600 = 1 to prevent fluorescence quenching due to culture turbidity). The system demonstrates excellent multi-analyte detection capabilities for lead chloride, lead nitrate, and cadmium chloride across a concentration range of 10-8 to 10-4 M. Compared to conventional steady-state photometric methods based on EGFP and MagLOV 2, the lock-in analysis of MagLOV 2 achieves detection sensitivities enhanced by 1[~]2 orders of magnitude, with detection limits as low as 2.4 nM for cadmium chloride, 4.8 nM for lead nitrate, and 9.9 nM for lead chloride. Langmuir isotherm fitting results demonstrate high quantitative accuracy (R2 > 0.950), with particularly outstanding fitting performance for cadmium chloride (R2 = 0.999) and lead nitrate (R2 = 0.995).

synthetic biology↗

A Spatially Resolved Atlas of Alternative Polyadenylation Across 18 Human Tissues and 76 Disease States

Alternative polyadenylation (APA) is a key regulator of gene expression and cellular dynamics, yet systematic investigations of spatially resolved APA across diverse human tissues remain limited. Here, we developed SpatialAPA (https://github.com/Omicslab-Zhang/spatialAPA), a framework that benchmarks multiple APA identification methods and integrates spatial APA data with gene expression and cellular dynamics at spatial resolution. Applying SpatialAPA to 363 spatial transcriptomic data from 56 projects across 18 human tissues and 76 diseases, we constructed a spatially resolved APA atlas comprising 346,932 APA events across 52,175 genes. This atlas reveals organ-specific APA patterns and provides new insights into how APA regulates tissue homeostasis and disease progression beyond transcriptional control. To ensure cross-sample comparability, we applied batch correction, while spatial cell deconvolution uncovered cell-type-specific dynamics and interactions. In triple-negative breast cancer, integrated spatial and single-cell analyses identified TSPAN8-positive epithelial subpopulations whose distinct APA regulation and transcriptional programs drive differentiation and malignant progression. To facilitate community access, we developed an online platform (http://www.biomedical-web.com/spatialAPAdb/home) for exploring APA, gene expression, and cellular dynamics in health and disease. Together, this study establishes the first comprehensive spatial APA atlas, providing a valuable resource and analytical framework for investigating molecular mechanisms and therapeutic targets.

bioinformatics↗

H3K27M Mutation Reshapes the Antigenic Landscape in Diffuse Midline Glioma

Simple SummaryDiffuse midline gliomas (DMGs) are aggressive childhood brain tumours with no effective treatments. Over 80% of cases carry the histone H3K27M mutation, which alters chromatin structure and gene regulation and induce tumours growth. Immunotherapy, which uses the bodys immune system to fight cancer, relies on tumour- specific antigen molecules that immune cells can recognise. However, because DMGs have few mutations, finding suitable antigens for therapeutic purposes has been challenging. In this study, we investigated how the H3K27M mutation affects tumour antigen presentation in DMG. Using patient-derived DMG models, we found that H3K27M alters the landscape of antigens displayed on tumour cell surface, creating unique immune targets. We identified six immunogenic peptides, that triggered strong T cell responses. These antigens were absent when H3K27M was removed, confirming their link to the mutation. Our findings provide a blueprint for developing T cell-based immunotherapies for DMG, offering new hope for targeted treatments against this devastating disease. AbstractO_ST_ABSBackgroundC_ST_ABSDiffuse midline gliomas (DMGs) are among the most aggressive paediatric brain tumours, with the pathognomonic H3K27M mutation present in over 80% of cases. This mutation drives epigenetic dysregulation and transcriptional reprogramming, yet its impact on the tumour antigenic landscape remains poorly understood. Given the low mutational burden of DMG, an expanded search beyond neoantigens to include epigenetically dysregulated tumour-associated antigens (TAAs) is critical for advancing antigen-specific immunotherapies. MethodsTo assess how H3K27M influences antigenic landscape of DMG, we performed a comprehensive immunopeptidomic analysis using patient-derived DMG cell line models (SU-DIPG13 and BT245) that harbour the H3K27M mutation and their CRISPR-edited H3K27M-knockout (KO) counterparts. High-resolution mass spectrometry and bioinformatics were employed to define H3K27M-driven changes in the immunopeptidome. Functional T cell assays using HLA-matched healthy donor PBMCs were conducted to evaluate the immunogenicity of H3K27M-associated peptides. ResultsOur findings reveal that the H3K27M mutation reshapes the tumour antigenic landscape in a model-specific manner. While H3K27M knockout increased HLA-I expression in SU-DIPG13 but not BT245, immunopeptidomic profiling uncovered distinct shifts in the presentation of tumour-associated peptides, independent of direct effects on antigen processing machinery. Among these, we identified six immunogenic peptides, derived from SLITRK2, PRAME, XKR5, and CBX2, that elicited CD8 T cell responses in in vitro functional assays. Notably, PRAME, a well-characterised cancer-testis antigen was confirmed as an H3K27M-associated immunogenic target, reinforcing its therapeutic relevance. Peptides identified exclusively in H3K27M+ cells were absent in KO models, demonstrating a direct link between H3K27M-driven transcriptional dysregulation and tumour antigenicity. ConclusionsThis study provides the first systematic assessment of how H3K27M reshapes the antigenic landscape in DMG, uncovering novel, immunogenic tumour- associated peptides that could serve as targets for precision immunotherapy. By demonstrating that H3K27M mutation drives context-dependent antigen presentation, our findings establish a foundation for T cell-based therapies targeting H3K27M-associated antigens. These insights pave the way for next-generation personalised immunotherapies for this otherwise treatment-refractory disease. Key PointsH3K27M mutation induces expression of tumour-associated antigens in DMG H3K27M alters the DMG immunopeptidome without uniformly changing HLA-I levels PRAME- and CBX2-derived peptides are immunogenic and targetable by CD8 T cells Importance of StudyDiffuse midline gliomas (DMGs) are universally fatal paediatric brain tumours with limited treatment options and poor immune visibility. While the H3K27M mutation is a defining hallmark, its impact on tumour immunogenicity remains unclear. This study presents the first comprehensive to explore the effect of H3K27M-mution on the DMG immunopeptidome, revealing six immunogenic peptides derived from epigenetically dysregulated tumour- associated antigens, including SLITRK2, PRAME, XKR5, and CBX2. These antigens elicited CD8 T cell responses, establishing a direct link between H3K27M-driven transcriptional dysregulation and tumour antigenicity. By leveraging these altered antigens, we highlight actionable vulnerabilities for T cell-based immunotherapy.

cancer biology↗

Temporal Dynamics of Nucleus Accumbens Neurons in Male Mice During Reward Seeking

The nucleus accumbens (NAc) regulates reward-motivated behavior, but the temporal dynamics of NAc neurons that enable "free-willed" animals to obtain rewards remain elusive. Here, we recorded Ca2+ activity from individual NAc neurons when mice performed self-paced lever-presses for sucrose. NAc neurons exhibited three temporally-sequenced clusters, defined by times at which they exhibited increased Ca2+ activity: approximately 0, -2.5 or -5 sec relative to the lever-pressing. Dopamine D1 receptor (D1)-expressing neurons and D2-neurons formed the majority of the -5-sec versus -2.5-sec clusters, respectively, while both neuronal subtypes were represented in the 0-sec cluster. We found that pre-press activity patterns of D1- or D2-neurons could predict subsequent lever-presses. Inhibiting D1-neurons at -5 sec or D2-neurons at -2.5 sec, but not at other timepoints, reduced sucrose-motivated lever-pressing. We propose that the time-specific activity of D1- and D2-neurons mediate key temporal features of the NAc through which reward motivation initiates reward-seeking behavior.

neuroscience↗

Precise cell recovery by cell nucleus united transcript (CellCUT) for enhanced spatial transcriptomics

Cell segmentation is the first step in parsing spatial transcriptomic data, often a challenging task. Existing cell segmentation methods do not fully leverage spatial cues between nuclear images and transcripts, tending to produce undesirable cell profiles for densely packed cells. Here, we propose CellCUT to perform cell segmentation and transcript assignment without additional manual annotations. CellCUT provides a flexible computational framework that maintains high segmentation accuracy across diverse tissues and spatial transcriptomics protocols, showing superior capabilities compared to state-of-the-art methods. CellCUT is a robust model to deal with undesirable data such as low contrast intensity, localized absence of transcripts, and blurred images. CellCUT supports a human-in-the-loop workflow to enhance its generalizability to customized datasets. CellCUT identifies subcellular structures, enabling insights at both the single-cell and subcellular levels.

bioinformatics↗

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology. One sentence summaryCell-type specific chromatin accessibility QTL reveals regulatory mechanisms underlying brain diseases.

genomics↗

The bHLH-PAS transcriptional complex Sim:Tgo plays active roles in late oogenesis to promote follicle maturation and ovulation

Across species, ovulation is a process induced by a myriad of signaling cascades that ultimately results in activation of proteolytic enzymes and degradation of the follicle wall to release encapsulated oocytes. Follicles need to first mature and gain ovulatory competency before ovulation. However, the signaling pathways regulating follicle maturation are incompletely understood in Drosophila and other species. Our previous work showed that bHLH-PAS transcription factor Single-minded (Sim) likely plays important roles for follicle maturation downstream of the NR5A-family nuclear receptor Ftz-f1 in Drosophila. Here, we explore the mechanism of Sim-regulated follicle maturation. We demonstrate that Tango (Tgo), another bHLH-PAS protein acts as a cofactor of Sim to promote follicle cell differentiation from stages 10 to 12. In addition, we discovered that re-upregulation of Sim in stage-14 follicle cells is also essential to promote ovulatory competency by upregulating octopamine receptor in mushroom body (OAMB), matrix metalloproteinase 2 (Mmp2), and NADPH oxidase (NOX), either independent of or in conjunction with the zinc-finger protein Hindsight (Hnt). All of these factors are critical for successful ovulation. Together, our work indicates that the transcriptional complex Sim:Tgo plays multiple roles in late-stage follicle cells to promote follicle maturation and ovulation.

developmental biology↗

A novel cuproptosis-related long non-coding RNAs model that effectively predicts prognosis in hepatocellular carcinoma

BackgroundCuproptosis has recently been considered a novel form of programmed cell death. To date, factors crucial to the regulation of this process remain unelucidated. Here, we aimed to identify long-chain non-coding RNAs (lncRNAs) associated with cuproptosis in order to predict the prognosis of patients with hepatocellular carcinoma (HCC). MethodsUsing RNA sequence data from The Cancer Genome Atlas Live Hepatocellular Carcinoma (TCGA-LIHC), a co-expression network of cuproptosis-related mRNAs and lncRNAs was constructed. For HCC prognosis, we developed a cuproptosis-related lncRNA signature (CupRLSig) using univariate Cox, lasso, and multivariate Cox regression analyses. Kaplan-Meier analysis was used to compare overall survival among high- and low-risk groups stratified by median CupRLSig score. Furthermore, comparisons of functional annotation, immune infiltration, somatic mutation, TMB (tumor mutation burden), and pharmacologic options were made between high- and low-risk groups. ResultsOur prognostic risk model was constructed using the cuproptosis-related PICSAR, FOXD2-AS1, and AP001065.1 lncRNAs. The CupRLSig high-risk group was associated with poor overall survival (hazard ratio = 1.162, 95% CI = 1.063- 1.270; p < 0.001). Model accuracy was further supported by receiver operating characteristic and principal component analysis as well as internal validation cohorts. A prognostic nomogram developed considering CupRLSig data and a number of clinical characteristics were found to exhibit adequate performance in survival risk stratification. Mutation analysis revealed that high-risk combinations with high TMB carried worse prognoses. Finally, differences in immune checkpoint expression and responses to chemotherapy as well as in targeted therapy among CupRLSig stratified high- and low-risk groups were explored. ConclusionsThe lncRNA signature constructed in this study is valuable in prognostic estimation in the setting of HCC.

bioinformatics↗

Identification of Six Thiolases and their Effects on Fatty Acid and Ergosterol Biosynthesis in Aspergillus oryzae

Thiolase plays important roles in lipid metabolism. It can be divided into degradative thiolases (Thioase I) and biosynthetic thiolases (thiolases II), which are involved in fatty acid {beta}-oxidation and acetoacetyl-CoA biosynthesis, respectively. The Saccharomyces cerevisiae (S. cerevisiae) genome harbors only one gene each for thioase I and thiolase II, namely, Pot1 and Erg10, respectively. In this study, six thiolases (named AoErg10A-AoErg10F) were identified in Aspergillus oryzae (A. oryzae) genome using bioinformatics analysis. Quantitative reverse transcription-PCR (qRT-PCR) indicated that the expression of these six thiolases varied at different growth stages and under different forms of abiotic stress. Subcellular localization analysis showed that AoErg10A was located in the cytoplasm, AoErg10B and AoErg10C in the mitochondria, and AoErg10D-AoErg10F in the peroxisome. Yeast heterologous complementation assays revealed that AoErg10A, AoErg10D, AoErg10E, AoErg10F and cytoplasmic AoErg10B (AoErg10B{Delta}MTS) recovered the phenotypes of S. cerevisiae erg10 weak and lethal mutants, and that only AoErg10D-F recovered the phenotype of the pot1 mutant that cannot use oleic acid as the carbon source. Overexpression of AoErg10s either affected the growth speed or sporulation of the transgenic strains. In addition, the fatty acid and ergosterol content changed in all the AoErg10-overexpressing strains. This study revealed the function of six thiolases in A. oryzae and their effect on growth, and fatty acid and ergosterol biosynthesis, which may lay the foundation for genetic engineering for lipid metabolism in A. oryzae or other fungi. ImportanceThiolase including thioase I and thiolase II, plays important roles in lipid metabolism. A. oryzae, one of the most industrially important filamentous fungi, has been widely used for manufacturing oriental fermented food such as sauce, miso, and sake for a long time. Besides, A. oryzae has a high capability in production of high lipid content and has been used for lipid production. Thus, it is very important to investiagte the function of thiolases in A. oryzae. In this study, six thiolase (named AoErg10A-AoErg10F) were identified by bioinformatics analysis. Unlike other reported thiolases in fungi, three of the six thiolases showed dual function of thioase I and thiolase II in S. cerevisiae, indicating the lipid metabolism is more complex in A. oryzae. The reveal of founction of these thiolases in A. oryzae can lay the foundation for genetic engineering for lipid metabolism in A. oryzae or other fungi.

microbiology↗

Transcribed enhancers in the human brain identify novel disease risk mechanisms

Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding the population-level variation of enhancers in the human brain. Besides regulating tissue- and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. We expanded the catalog of known human brain transcribed enhancers by an order of magnitude by generating and jointly analyzing large-scale cell-type-specific transcriptome and regulome data. Examination of the transcriptome in 1,382 brain samples in two independent cohorts identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified significant expression quantitative trait loci (eQTL) for 25,958 enhancers which mediate 6.8% of schizophrenia heritability, mostly independent from standard gene eQTL. Inclusion of enhancer eQTL in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the enhancer-gene regulome and genetic mechanisms in the human cortex in both healthy and disease states.

neuroscience↗

A multiplex microchamber diffusion assay for the antibody-based detection of microRNAs on randomly ordered microbeads

BackgroundMicroRNAs (miRNAs) are small, conserved, noncoding RNAs regulating gene expression that functions in RNA silencing and post-transcriptional regulation of gene expression. Altered miRNA profiles have been implicated in many human diseases, and due to their circulating abilities, they have excited great interest in their use as clinical biomarkers. The development of innovative methods for miRNA detection has become of high scientific and clinical interest. MethodsWe developed a diffusion-driven microbead assay and combined it with an antibody-based miRNA detection. The diffusion process was carried out in two different approaches a) co-diffusion of miRNA and antibodies (termed diffusion approach I, DAI) and b) diffusion of miRNA in an antibody-saturated environment (DAII). In both approaches, neutravidin-coated microbeads were loaded with specific biotinylated DNA capture probes, which targets either miR-21-5p, miR-30a-3p or miR-93-5p. The miRNAs were time- and dose-dependently detected in a diffusion microchamber by primary anti-DNA:RNA hybrid and fluorescence-labeled secondary antibodies using our in-house developed inverse fluorescence microscope imaging platform VideoScan. ResultsOur assay offers the advantage that several target molecules can be detected simultaneously and in real-time in one reaction environment (multiplex), without any amplification steps. We recorded the diffusion process over a period of 24 h and found that the reaction was almost completed after 2 h. The specificity of the assay was 96.7 % for DAI and 92.3 % for DAII. The detection limits were in a concentration range of 0.03-0.43 nM for DAI and 0.14-1.09 nM for DAII, depending on the miRNA. ConclusionThe miRNAs are successively exposed to the capture probe-loaded randomly ordered microbeads (p value of CSR 0.23-0.96), which leads to microbeads that become saturated with the target molecules first in front rows. Non-bonded miRNAs continue to diffuse further and can therefore subsequently bind to the microbeads with free binding sites. Our detection principle differs from other microbead assays, in which all microbeads are simultaneously mixed with the sample solution, so that all target molecules bind equally distributed to the microbeads, resulting in an averaged signal intensity.

biochemistry↗

The three-dimensional landscape of chromatin accessibility in Alzheimer's disease

Much is still unknown about the neurobiology of Alzheimers disease (AD). To better understand AD, we generated 636 ATAC-seq libraries from cases and controls to construct detailed genomewide chromatin accessibility maps of neurons and non-neurons from two AD-affected brain regions, the entorhinal cortex and superior temporal gyrus. By analyzing a total of 19.6 billion read pairs, we expanded the known repertoire of regulatory sequences in the human brain. Multi-omic data integration associated global patterns of chromatin accessibility with gene expression and identified cell-specific enhancer-promoter interactions. Using inter-individual variation in chromatin accessibility, we define cis-regulatory domains capturing the 3D structure of the genome. Multifaceted analyses uncovered disease associated perturbations impacting chromatin accessibility, transcription factor regulatory networks and the 3D genome, and implicated transcriptional dysregulation in AD. Overall, we applied a systematic approach to understand the role of the 3D genome in AD and to illuminate novel disease biology that can advance diagnosis and therapy.

neuroscience↗

piRPheno: a manually curated database to prioritize and analyze human disease related piRNAs

Many studies have uncovered that piRNAs (PIWI-interacting RNA) are associated with a broad range of diseases and might be a novel type of biomarkers and targets for precision medicine. However, public resource of high-quality curated human disease-associated piRNAs remains unavailable. Therefore, we developed the piRPheno (http://www.biomedical-web.com/pirpheno) database to provide an up-to-date, interactive and extensible data reference for human piRNA-disease associations. piRPheno includes 9057 experimentally supported associations between 474 piRNAs and 204 diseases through a manual curation of publications. To prioritize the piRNA-disease associations, each association in piRPheno is assigned with a confidence score and clinical correlations based on the experimentally supported evidences. piRPheno is freely available with user-friendly interface and novel applications to enable easy exploration and analysis of the human disease related piRNAs.

bioinformatics↗

TreeMap: A Structured Approach to Fine Mapping of eQTL Variants

MotivationExpression quantitative trait loci (eQTL) harbor genetic variants modulating gene transcription. Fine mapping of regulatory variants at these loci is a daunting task due to the juxtaposition of causal and linked variants at a locus as well as the likelihood of interactions among multiple variants. This problem is exacerbated in genes with multiple cis-acting eQTL, where superimposed effects of adjacent loci further distort the association signals. ResultsWe developed a novel algorithm, TreeMap, that identifies putative causal variants in cis-eQTL accounting for multisite effects and genetic linkage at a locus. Guided by the hierarchical structure of linkage disequilibrium, TreeMap performs an organized search for individual and multiple causal variants. Via extensive simulations, we show that TreeMap detects co-regulating variants more accurately than current methods. Furthermore, its high computational efficiency enables genome-wide analysis of long-range eQTL. We applied TreeMap to GTEx data of brain hippocampus samples and transverse colon samples to search for eQTL in gene bodies and in 4 Mbps gene-flanking regions, discovering numerous distal eQTL. Furthermore, we found concordant distal eQTL that were present in both brain and colon samples, implying long-range regulation of gene expression. AvailabilityTreeMap is available as an R package enabled for parallel processing at https://github.com/liliulab/treemap.

bioinformatics↗