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Summary: Glioblastoma multiforme (GBM) is one of the most lethal brain tumors, characterized by profound heterogeneity. While single-cell transcriptomic studies have revealed extensive intra-tumor heterogeneity, shed light on intra-tumor diversity, spatial intricacies remain largely unexplored. Leveraging clinical GBM specimens, this study employs spatial transcriptomics technology to delve into gene expression heterogeneity. Our investigation unveils a significant enrichment of tissue stem cell signature in regions bordering necrosis and the peritumoral area, positively correlated with the mesenchymal subtype signature. Moreover, upregulated genes in these regions are linked with extracellular matrix (ECM)-receptor interaction, proteoglycans, as well as vascular endothelial growth factor (VEGF) and angiopoietin-Tie (ANGPT) signaling pathways. In contrast, signatures related to glycogen metabolism and oxidative phosphorylation show no relevance to pathological zoning, whereas creatine metabolism signature is notably exclusive to vascular-enriched areas. These spatial profiles not only offer valuable references but also pave the way for future in-depth functional and mechanistic investigations into GBM progression.

Abstract Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogate TL-modulated genes and their potential functions. We discover that the TL in the placenta is comparatively longer than in other adult tissues, but exhibiting an intra-tissue homogeneity. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identify 20 newly discovered genetic associations and provide increased polygenic determination of human TL. Next, we integrate the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 23 likely causal genes, among which 4 are functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improve the prediction performance of human TL. This study deepens our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.

Abstract Microbiota have an important function in shaping and priming neonatal immunity, although the cellular and molecular mechanisms underlying these effects remain obscure. Here we report that prenatal antibiotic exposure causes significant elevation of group 2 innate lymphoid cells (ILC2s) in neonatal lungs, in both cell numbers and functionality. Downregulation of type 1 interferon signaling in ILC2s due to diminished production of microbiota-derived butyrate represents the underlying mechanism. Mice lacking butyrate receptor GPR41 (Gpr41 -/- ) or type 1 interferon receptor IFNAR1 (Ifnar1 -/- ) recapitulate the phenotype of neonatal ILC2s upon maternal antibiotic exposure. Furthermore, prenatal antibiotic exposure induces epigenetic changes in ILC2s and has a long-lasting deteriorative effect on allergic airway inflammation in adult offspring. Prenatal supplementation of butyrate ameliorates airway inflammation in adult mice born to antibiotic-exposed dams. These observations demonstrate an essential role for the microbiota in the control of type 2 innate immunity at the neonatal stage, which suggests a therapeutic window for treating asthma in early life.

Abstract Background The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma. Results Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions. Conclusions Our study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.

BackgroundSarcoma is a highly heterogeneous malignancy with a poor prognosis. Although chemotherapy and targeted therapy have improved the prognosis to some extent, the efficacy remains unsatisfactory in some patients. The efficacy and safety of immunotherapy in sarcoma need further evaluation.MethodsWe conducted a two-center study of sarcoma patients receiving PD-1 immunotherapy at Tianjin Medical University Cancer Institute and Hospital and Henan Provincial Cancer Hospital. The treatment regimens included PD-1 inhibitor monotherapy and combination therapy based on PD-1 inhibitors. The observed primary endpoints were median progression-free survival (mPFS) and median overall survival (mOS). Survival curves were compared using the Kaplan−Meier method.ResultsA total of 43 patients were included from the two centers. The median follow-up time for all patients was 13 months (range, 1-48 months). In the group of 37 patients with advanced or unresectable sarcoma, the mPFS was 6 months (95%CI: 5-12 months), and the mOS was 16 months (95%CI: 10-28 months). The ORR was 10.8% (4/37), and the DCR was 18.9% (7/37). Subgroup analysis showed no significant differences in mPFS (p=0.11) and mOS (p=0.88) between patients with PD-L1 negative/positive expression. There were also no significant differences in mPFS (p=0.13) or mOS (p=0.72) between PD-1 inhibitor monotherapy and combination therapy. Additionally, there were no significant differences in mPFS (p=0.52) or mOS (p=0.49) between osteogenic sarcoma and soft tissue sarcoma. Furthermore, the results showed no significant differences in mPFS (p=0.66) or mOS (p=0.96) between PD-1 inhibitors combined with targeted therapy and PD-1 inhibitors combined with AI chemotherapy. Among the 6 patients receiving adjuvant therapy after surgery, the mPFS was 15 months (95%CI: 6-NA months), and the mOS was not reached. In terms of safety, most adverse events were mild (grade 1-2) and manageable. The most severe grade 4 adverse events were bone marrow suppression, which occurred in 4 patients but resolved after treatment. There was also one case of a grade 4 adverse event related to hypertension.ConclusionImmunotherapy is an effective treatment modality for sarcoma with manageable safety. Further inclusion of more patients or prospective clinical trials is needed to validate these findings.

Abstract Whole -genome sequencing projects of millions of subjects contain enormous genotypes, entailing a huge memory burden and time for computation. Here, we present GBC, a toolkit for rapidly compressing large-scale genotypes into highly addressable byte-encoding blocks under an optimized parallel framework. We demonstrate that GBC is up to 1000 times faster than state-of-the-art methods to access and manage compressed large-scale genotypes while maintaining a competitive compression ratio. We also showed that conventional analysis would be substantially sped up if built on GBC to access genotypes of a large population. GBC’s data structure and algorithms are valuable for accelerating large-scale genomic research.

Abstract Background ABO blood groups has been associated with risk of several cancers; however, the results for an association with ovarian cancer are inconsistent and little is known about the expression of histo‐blood group (ABH) antigens and ABO gene in ovarian tumor tissues. Methods To assess the impact of genotype‐derived ABO blood types on the risk of EOC, we conducted a case–control study in 1,870 EOC and 4,829 controls. Expression of A and B antigen in 70 pairs of ovarian tumor tissues and adjacent normal tissues were detected by immunohistochemistry. Gene expression and DNA methylation profiling was conducted in ovarian tumor tissues. Results We identified that blood group A was associated with increased risk for EOC compared to blood group O (OR = 1.18, 95% CI = 1.03–1.36, p = 0.019). Increased frequency of aberrant expression of histo‐blood group antigens was observed in patients with blood group A (76.5%) compared to patients with blood group O (21.1%) and B (5.0%) by immunohistochemistry (p

Here the authors used an evidence-based strategy to prioritize causal pleiotropic variants of autoimmune diseases, and revealed that rs4728142 modulates aberrant IRF5 alternative promoter usage by ZBTB3-mediated chromatin looping.

Summary: To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants remain elusive. Identification of causal variants and their targets from association signals is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes. Our fine-mapping analysis yielded 3,395 likely causal variants, and multiscale functional annotation linked them to 487 target genes. We prioritized rs10486567 as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in enhancer-KO cell lines rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long-range chromatin interaction.

Abstract CD73, a cell surface‐bound nucleotidase, facilitates extracellular adenosine formation by hydrolyzing 5′‐AMP to adenosine. Several studies have shown that CD73 plays an essential role in immune escape, cell proliferation and tumor angiogenesis, making it an attractive target for cancer therapies. However, there are limited clinical benefits associated with the mainstream enzymatic inhibitors of CD73, suggesting that the mechanism underlying the role of CD73 in tumor progression is more complex than anticipated, and further investigation is necessary. In this study, CD73 is found to overexpress in the cytoplasm of pancreatic ductal adenocarcinoma (PDAC) cells and promotes metastasis in a nucleotidase‐independent manner, which cannot be restrained by the CD73 monoclonal antibodies or small‐molecule enzymatic inhibitors. Furthermore, CD73 promotes the metastasis of PDAC by binding to the E3 ligase TRIM21, competing with the Snail for its binding site. Additionally, a CD73 transcriptional inhibitor, diclofenac, a non‐steroidal anti‐inflammatory drug, is more effective than the CD73 blocking antibody for the treatment of PDAC metastasis. Diclofenac also enhances the therapeutic efficacy of gemcitabine in the spontaneous KPC (LSL‐KrasG12D/+, LSL‐Trp53R172H/+, and Pdx‐1‐Cre) pancreatic cancer model. Therefore, diclofenac may be an effective anti‐CD73 therapy, when used alone or in combination with gemcitabine‐based chemotherapy regimen, for metastatic PDAC.

Abstract Ovarian cancer survival varies considerably among patients, to which germline variation may also contribute in addition to mutational signatures. To identify genetic markers modulating ovarian cancer outcome, we performed a genome-wide association study in 2130 Chinese ovarian cancer patients and found a hitherto unrecognized locus at 3p26.1 to be associated with the overall survival (P combined = 8.90 × 10−10). Subsequent statistical fine-mapping, functional annotation, and eQTL mapping prioritized a likely casual SNP rs9311399 in the non-coding regulatory region. Mechanistically, rs9311399 altered its enhancer activity through an allele-specific transcription factor binding and a long-range interaction with the promoter of a lncRNA BHLHE40-AS1. Deletion of the rs9311399-associated enhancer resulted in expression changes in several oncogenic signaling pathway genes and a decrease in tumor growth. Thus, we have identified a novel genetic locus that is associated with ovarian cancer survival possibly through a long-range gene regulation of oncogenic pathways.

Summary: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of coronavirus disease 2019 (COVID-19), has infected hundreds of millions of people and caused millions of deaths. Looking for valid druggable targets with minimal side effects for the treatment of COVID-19 remains critical. After discovering host genes from multiscale omics data, we developed an end-to-end network method to investigate drug-host gene(s)-coronavirus (CoV) paths and the mechanism of action between the drug and the host factor in a directional network. We also inspected the potential side effect of the candidate drug on several common comorbidities. We established a catalog of host genes associated with three CoVs. Rule-based prioritization yielded 29 Food and Drug Administration (FDA)-approved drugs via accounting for the effects of drugs on CoVs, comorbidities, and drug-target confidence information. Seven drugs are currently undergoing clinical trials as COVID-19 treatment. This catalog of druggable host genes associated with CoVs and the prioritized repurposed drugs will provide a new sight in therapeutics discovery for severe COVID-19 patients.

Summary: Precise identification of context-specific transcriptional regulators (TRs) cooperation facilitates the understanding of complex gene regulation. However, previous methods are highly reliant on the availability of ChIPped TRs. Here, we provide a protocol for running 3DCoop, a pipeline for computational inference of cell type-specific TR cooperation in 3D chromatin by integrating TR motifs, open chromatin profiles, gene expression, and chromatin loops. 3DCoop provides a feasible solution to study the potential interplay among TRs across multiple human or mouse tissue/cell types.For complete details on the use and execution of this protocol, please refer to Yi et al. (2021).

Linkage disequilibrium and disease-associated variants in the non-coding regions make it difficult to distinguish the truly associated genes from the redundantly associated genes for complex diseases. In this study, we proposed a new conditional gene-based framework called eDESE that leveraged an improved effective chi-squared statistic to control the type I error rates and remove the redundant associations. eDESE initially performed the association analysis by mapping variants to genes according to their physical distance. We further demonstrated that the isoform-level eQTLs could be more powerful than the gene-level eQTLs in the association analysis using a simulation study. Then the eQTL-guided strategies, that is, mapping variants to genes according to their gene/isoform-level variant-gene cis-eQTLs associations, were also integrated with eDESE. We then applied eDESE to predict the potential susceptibility genes of schizophrenia and found that the potential susceptibility genes were enriched with many neuronal or synaptic signaling-related terms in the Gene Ontology knowledgebase and antipsychotics-gene interaction terms in the drug-gene interaction database (DGIdb). More importantly, seven potential susceptibility genes identified by eDESE were the target genes of multiple antipsychotics in DrugBank. Comparing the potential susceptibility genes identified by eDESE and other benchmark approaches (i.e., MAGMA and S-PrediXcan) implied that strategy based on the isoform-level eQTLs could be an important supplement for the other two strategies (physical distance and gene-level eQTLs). We have implemented eDESE in our integrative platform KGGSEE (http://pmglab.top/kggsee/#/) and hope that eDESE can facilitate the prediction of candidate susceptibility genes and isoforms for complex diseases in a multi-tissue context.

Mechanisms underlying gene regulation are key to understand how multicellular organisms with various cell types develop from the same genetic blueprint. Dynamic interactions between enhancers and genes are revealed to play central roles in controlling gene transcription, but the determinants to link functional enhancer-promoter pairs remain elusive. A major challenge is the lack of reliable approach to detect and verify functional enhancer-promoter interactions (EPIs). In this review, we summarized the current methods for detecting EPIs and described how developing techniques facilitate the identification of EPI through assessing the merits and drawbacks of these methods. We also reviewed recent state-of-art EPI prediction methods in terms of their rationale, data usage and characterization. Furthermore, we briefly discussed the evolved strategies for validating functional EPIs.

Summary: Context-specific activities of transcription regulators (TRs) in the nucleus modulate spatiotemporal gene expression precisely. Using the largest ChIP-seq data and chromatin loops in the human K562 cell line, we initially interrogated TR cooperation in 3D chromatin via a graphical model and revealed many known and novel TRs manipulating context-specific pathways. To explore TR cooperation across broad tissue/cell types, we systematically leveraged large-scale open chromatin profiles, computational footprinting, and high-resolution chromatin interactions to investigate tissue/cell type-specific TR cooperation. We first delineated a landscape of TR cooperation across 40 human tissue/cell types. Network modularity analyses uncovered the commonality and specificity of TR cooperation in different conditions. We also demonstrated that TR cooperation information can better interpret the disease-causal variants identified by genome-wide association studies and recapitulate cell states during neural development. Our study characterizes shared and unique patterns of TR cooperation associated with the cell type specificity of gene regulation in 3D chromatin.

Genome-wide association studies (GWASs) have identified multiple susceptibility loci for Alzheimer's disease (AD), which is characterized by early and progressive damage to the hippocampus. However, the association of hippocampal gene expression with AD and the underlying neurobiological pathways remain largely unknown. Based on the genomic and transcriptomic data of 111 hippocampal samples and the summary data of two large-scale meta-analyses of GWASs, a transcriptome-wide association study (TWAS) was performed to identify genes with significant associations between hippocampal expression and AD. We identified 54 significantly associated genes using an AD-GWAS meta-analysis of 455,258 individuals; 36 of the genes were confirmed in another AD-GWAS meta-analysis of 63,926 individuals. Fine-mapping models further prioritized 24 AD-related genes whose effects on AD were mediated by hippocampal expression, including APOE and two novel genes (PTPN9 and PCDHA4). These genes are functionally related to amyloid-beta formation, phosphorylation/dephosphorylation, neuronal apoptosis, neurogenesis and telomerase-related processes. By integrating the predicted hippocampal expression and neuroimaging data, we found that the hippocampal expression of QPCTL and ERCC2 showed significant difference between AD patients and cognitively normal elderly individuals as well as correlated with hippocampal volume. Mediation analysis further demonstrated that hippocampal volume mediated the effect of hippocampal gene expression (QPCTL and ERCC2) on AD. This study identifies two novel genes associated with AD by integrating hippocampal gene expression and genome-wide association data and reveals candidate hippocampus-mediated neurobiological pathways from gene expression to AD.

High-throughput genome-wide epigenomic assays, such as ChIP-seq, DNase-seq and ATAC-seq, have profiled a huge number of functional elements across numerous human tissues/cell types, which provide an unprecedented opportunity to interpret human genome and disease in context-dependent manner. Colocalization analysis determines whether genomic features are functionally related to a given search and will facilitate identifying the underlying biological functions characterizing intricate relationships with queries for genomic regions. Existing colocalization methods leveraged diverse assumptions and background models to assess the significance of enrichment, however, they only provided limited and predefined sets of epigenomic features. Here, we comprehensively collected and integrated over 44,385 bulk or single-cell epigenomic assays across 53 human tissues/cell types, such as transcription factor binding, histone modification, open chromatin and transcriptional event. By classifying these profiles into hierarchy of tissue/cell type, we developed a web portal, epiCOLOC (http://mulinlab.org/epicoloc or http://mulinlab.tmu.edu.cn/epicoloc), for users to perform context-dependent colocalization analysis in a convenient way.

One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Polycomb group (PcG) proteins are critical chromatin regulators for cell fate control. The mono‐ubiquitylation on histone H2AK119 (H2AK119ub1) is one of the well‐recognized mechanisms for Polycomb repressive complex 1 (PRC1)‐mediated transcription repression. Unexpectedly, the specific H2AK119 deubiquitylation complex composed by additional sex comb‐like proteins and BAP1 has also been genetically characterized as Polycomb repressive deubiquitnase (PR‐DUB) for unclear reasons. However, it remains a mystery whether and how PR‐DUB deficiency affects chromatin states and cell fates through impaired PcG silencing. Here through a careful epigenomic analysis, we demonstrate that a bulk of H2AK119ub1 is diffusely distributed away from promoter regions and their enrichment is positively correlated with PRC1 occupancy. Upon deletion of Asxl2 in mouse embryonic stem cells (ESCs), a pervasive gain of H2AK119ub1 is coincident with increased PRC1 sampling at chromatin. Accordingly, PRC1 is significantly lost from a subset of highly occupied promoters, leading to impaired silencing of associated genes before and after lineage differentiation of Asxl2‐null ESCs. Therefore, our study highlights the importance of genomewide H2AK119ub1 restriction by PR‐DUB in safeguarding robust PRC1 deposition and its roles in developmental regulation. [ABSTRACT FROM AUTHOR]