Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

Recent studies have shown that disease-susceptibility variants frequently lie in cell-type-specific enhancer elements. To identify, interpret, and prioritize such risk variants, we must identify the enhancers active in disease-relevant cell types, their upstream transcription factor (TF) binding, and their downstream target genes. To address this need, we built HACER (http://bioinfo.vanderbilt.edu/AE/HACER/), an atlas of Human ACtive Enhancers to interpret Regulatory variants. The HACER atlas catalogues and annotates in-vivo transcribed cell-type-specific enhancers, as well as placing enhancers within transcriptional regulatory networks by integrating ENCODE TF ChIP-Seq and predicted/validated chromatin interaction data. We demonstrate the utility of HACER in (i) offering a mechanistic hypothesis to explain the association of SNP rs614367 with ER-positive breast cancer risk, (ii) exploring tumor-specific enhancers in selective MYC dysregulation and (iii) prioritizing/annotating non-coding regulatory regions targeting CCND1. HACER provides a valuable resource for studies of GWAS, non-coding variants, and enhancer-mediated regulation.

WebGestalt is a popular tool for the interpretation of gene lists derived from large scale -omics studies. In the 2019 update, WebGestalt supports 12 organisms, 342 gene identifiers and 155 175 functional categories, as well as user-uploaded functional databases. To address the growing and unique need for phosphoproteomics data interpretation, we have implemented phosphosite set analysis to identify important kinases from phosphoproteomics data. We have completely redesigned result visualizations and user interfaces to improve user-friendliness and to provide multiple types of interactive and publication-ready figures. To facilitate comprehension of the enrichment results, we have implemented two methods to reduce redundancy between enriched gene sets. We introduced a web API for other applications to get data programmatically from the WebGestalt server or pass data to WebGestalt for analysis. We also wrapped the core computation into an R package called WebGestaltR for users to perform analysis locally or in third party workflows. WebGestalt can be freely accessed at http://www.webgestalt.org.

Because of the requirement of oxygen (O2) to produce energy, aerobic organisms developed mechanisms to protect themselves against a shortage of oxygen in both acute status and chronic status. To date, how organisms tolerate acute hypoxia and the underlying mechanisms remain largely unknown. Here, we identify that Tet1, one member of the ten-eleven translocation (TET) family of methylcytosine dioxygenases, is required for hypoxia tolerance in zebrafish and mice. Tet1-null zebrafish and mice are more sensitive to hypoxic conditions compared with their wild-type siblings. We demonstrate that Tet1 stabilizes hypoxia-inducible factor α (HIF-α) and enhances HIF-α transcription activity independent of its enzymatic activity. In addition, we show that Tet1 modulates HIF-2α and HIF-1α through different mechanisms. Tet1 competes with prolyl hydroxylase protein 2 (PHD2) to bind to HIF-2α, resulting in a reduction of HIF-2α hydroxylation by PHD2. For HIF-1α, however, Tet1 has no effect on HIF-1α hydroxylation, but rather it appears to stabilize the C-terminus of HIF-1α by affecting lysine site modification. Furthermore, we found that Tet1 enhances rather than prevents poly-ubiquitination on HIF-α. Our results reveal a previously unrecognized function of Tet1 independent of its methylcytosine dioxygenase activity in hypoxia signaling.

Nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) are global epidemic public health problems with pathogenesis incompletely understood. Hepatocyte excessive apoptosis is a significant symbol for NAFLD/NASH patients, and therefore anti-apoptosis therapy could be used for NAFLD/NASH treatment. Up-regulation of BCL-2 has been found to be closely related with anti-apoptosis. BCL-2 gene promoter region has a C-rich sequence, which can form i-motif structure and play important role in regulating gene transcription. In this study, after extensive screening and evaluation, we found that acridone derivative A22 could up-regulate BCL-2 transcription and translation in vitro and in cells through selective binding to and stabilizing BCL-2 gene promoter i-motif. Our further experiments showed that A22 could reduce hepatocyte apoptosis in NAFLD/NASH model possibly through up-regulating BCL-2 expression. A22 could reduce inflammation, endoplasmic reticulum stress and cirrhosis in high-fat diet-fed mice liver model. Our findings provide a potentially new approach of anti-apoptosis for NAFLD/NASH treatment, and A22 could be further developed as a lead compound for NAFLD/NASH therapy. Our present study first demonstrated that gene promoter i-motif could be targeted for gene up-regulation for extended treatment of other important diseases besides cancer.

The advent of single-cell sequencing opened a new era in transcriptomic and genomic research. To understand cell composition using single-cell studies, a variety of cell markers have been widely used to label individual cell types. However, the specific database of cell markers for use by the plant research community remains very limited. To overcome this problem, we developed the Plant Cell Marker DataBase (PCMDB, http://www.tobaccodb.org/pcmdb/), which is based on a uniform annotation pipeline. By manually curating over 130 000 research publications, we collected a total of 81 117 cell marker genes of 263 cell types in 22 tissues across six plant species. Tissue- and cell-specific expression patterns can be visualized using multiple tools: eFP Browser, Bar, and UMAP/TSNE graph. The PCMDB also supports several analysis tools, including SCSA and SingleR, which allows for user annotation of cell types. To provide information about plant species currently unsupported in PCMDB, potential marker genes for other plant species can be searched based on homology with the supported species. PCMDB is a user-friendly hierarchical platform that contains five built-in search engines. We believe PCMDB will constitute a useful resource for researchers working on cell type annotation and the prediction of the biological function of individual cells.

Contact-dependent growth inhibition is a mechanism of interbacterial competition mediated by delivery of the C-terminal toxin domain of CdiA protein (CdiA-CT) into neighboring bacteria. The CdiA-CT of enterohemorrhagic Escherichia coli EC869 (CdiA-CTEC869) cleaves the 3'-acceptor regions of specific tRNAs in a reaction that requires the translation factors Tu/Ts and GTP. Here, we show that CdiA-CTEC869 has an intrinsic ability to recognize a specific sequence in substrate tRNAs, and Tu:Ts complex promotes tRNA cleavage by CdiA-CTEC869. Uncharged and aminoacylated tRNAs (aa-tRNAs) were cleaved by CdiA-CTEC869 to the same extent in the presence of Tu/Ts, and the CdiA-CTEC869:Tu:Ts:tRNA(aa-tRNA) complex formed in the presence of GTP. CdiA-CTEC869 interacts with domain II of Tu, thereby preventing the 3'-moiety of tRNA to bind to Tu as in canonical Tu:GTP:aa-tRNA complexes. Superimposition of the Tu:GTP:aa-tRNA structure onto the CdiA-CTEC869:Tu structure suggests that the 3'-portion of tRNA relocates into the CdiA-CTEC869 active site, located on the opposite side to the CdiA-CTEC869 :Tu interface, for tRNA cleavage. Thus, CdiA-CTEC869 is recruited to Tu:GTP:Ts, and CdiA-CT:Tu:GTP:Ts recognizes substrate tRNAs and cleaves them. Tu:GTP:Ts serves as a reaction scaffold that increases the affinity of CdiA-CTEC869 for substrate tRNAs and induces a structural change of tRNAs for efficient cleavage by CdiA-CTEC869.

In recent years, human regulatory SNPs (rSNPs) have been widely studied. Here, we present database rSNPBase, freely available at http://rsnp.psych.ac.cn/, to provide curated rSNPs that analyses the regulatory features of all SNPs in the human genome with reference to experimentally supported regulatory elements. In contrast with previous SNP functional annotation databases, rSNPBase is characterized by several unique features. (i) To improve reliability, all SNPs in rSNPBase are annotated with reference to experimentally supported regulatory elements. (ii) rSNPBase focuses on rSNPs involved in a wide range of regulation types, including proximal and distal transcriptional regulation and post-transcriptional regulation, and identifies their potentially regulated genes. (iii) Linkage disequilibrium (LD) correlations between SNPs were analysed so that the regulatory feature is annotated to SNP-set rather than a single SNP. (iv) rSNPBase provides the spatio-temporal labels and experimental eQTL labels for SNPs. In summary, rSNPBase provides more reliable, comprehensive and user-friendly regulatory annotations on rSNPs and will assist researchers in selecting candidate SNPs for further genetic studies and in exploring causal SNPs for in-depth molecular mechanisms of complex phenotypes.

To determine early somatic changes in high-grade serous ovarian cancer (HGSOC), we performed whole genome sequencing on a rare collection of 16 low stage HGSOCs. The majority showed extensive structural alterations (one had an ultramutated profile), exhibited high levels of p53 immunoreactivity, and harboured a TP53 mutation, deletion or inactivation. BRCA1 and BRCA2 mutations were observed in two tumors, with nine showing evidence of a homologous recombination (HR) defect. Combined Analysis with The Cancer Genome Atlas (TCGA) indicated that low and late stage HGSOCs have similar mutation and copy number profiles. We also found evidence that deleterious TP53 mutations are the earliest events, followed by deletions or loss of heterozygosity (LOH) of chromosomes carrying TP53, BRCA1 or BRCA2. Inactivation of HR appears to be an early event, as 62.5% of tumours showed a LOH pattern suggestive of HR defects. Three tumours with the highest ploidy had little genome-wide LOH, yet one of these had a homozygous somatic frame-shift BRCA2 mutation, suggesting that some carcinomas begin as tetraploid then descend into diploidy accompanied by genome-wide LOH. Lastly, we found evidence that structural variants (SV) cluster in HGSOC, but are absent in one ultramutated tumor, providing insights into the pathogenesis of low stage HGSOC.

Genome-wide association study (GWAS) is nowadays widely used to identify genes involved in human complex disease. The standard GWAS analysis examines SNPs/genes independently and identifies only a number of the most significant SNPs. It ignores the combined effect of weaker SNPs/genes, which leads to difficulties to explore biological function and mechanism from a systems point of view. Although gene set enrichment analysis (GSEA) has been introduced to GWAS to overcome these limitations by identifying the correlation between pathways/gene sets and traits, the heavy dependence on genotype data, which is not easily available for most published GWAS investigations, has led to limited application of it. In order to perform GSEA on a simple list of GWAS SNP P-values, we implemented GSEA by using SNP label permutation. We further improved GSEA (i-GSEA) by focusing on pathways/gene sets with high proportion of significant genes. To provide researchers an open platform to analyze GWAS data, we developed the i-GSEA4GWAS (improved GSEA for GWAS) web server. i-GSEA4GWAS implements the i-GSEA approach and aims to provide new insights in complex disease studies. i-GSEA4GWAS is freely available at http://gsea4gwas.psych.ac.cn/.

The Shigella bacteria cause bacillary dysentery, which remains a significant threat to public health. The genus status and species classification appear no longer valid, as compelling evidence indicates that Shigella, as well as enteroinvasive Escherichia coli, are derived from multiple origins of E.coli and form a single pathovar. Nevertheless, Shigella dysenteriae serotype 1 causes deadly epidemics but Shigella boydii is restricted to the Indian subcontinent, while Shigella flexneri and Shigella sonnei are prevalent in developing and developed countries respectively. To begin to explain these distinctive epidemiological and pathological features at the genome level, we have carried out comparative genomics on four representative strains. Each of the Shigella genomes includes a virulence plasmid that encodes conserved primary virulence determinants. The Shigella chromosomes share most of their genes with that of E.coli K12 strain MG1655, but each has over 200 pseudogenes, 300 approximately 700 copies of insertion sequence (IS) elements, and numerous deletions, insertions, translocations and inversions. There is extensive diversity of putative virulence genes, mostly acquired via bacteriophage-mediated lateral gene transfer. Hence, via convergent evolution involving gain and loss of functions, through bacteriophage-mediated gene acquisition, IS-mediated DNA rearrangements and formation of pseudogenes, the Shigella spp. became highly specific human pathogens with variable epidemiological and pathological features.

Alternative polyadenylation (APA) is an RNA-processing mechanism on the 3' terminus that generates distinct isoforms of mRNAs and/or other RNA polymerase II transcripts with different 3'UTR lengths. Widespread APA affects post-transcriptional gene regulation in mRNA translation, stability, and localization, and exhibits strong tissue specificity. However, no existing database provides comprehensive information about APA events in a large number of human normal tissues. Using the RNA-seq data from the Genotype-Tissue Expression project, we systematically identified APA events from 9475 samples across 53 human tissues and examined their associations with multiple traits and gene expression across tissues. We further developed APAatlas, a user-friendly database (https://hanlab.uth.edu/apa/) for searching, browsing and downloading related information. APAatlas will help the biomedical research community elucidate the functions and mechanisms of APA events in human tissues.

RPA is a critical factor for DNA replication and replication stress response. Surprisingly, we found that chromatin RPA stability is tightly regulated. We report that the GDP/GTP exchange factor DOCK7 acts as a critical replication stress regulator to promote RPA stability on chromatin. DOCK7 is phosphorylated by ATR and then recruited by MDC1 to the chromatin and replication fork during replication stress. DOCK7-mediated Rac1/Cdc42 activation leads to the activation of PAK1, which subsequently phosphorylates RPA1 at S135 and T180 to stabilize chromatin-loaded RPA1 and ensure proper replication stress response. Moreover, DOCK7 is overexpressed in ovarian cancer and depleting DOCK7 sensitizes cancer cells to camptothecin. Taken together, our results highlight a novel role for DOCK7 in regulation of the replication stress response and highlight potential therapeutic targets to overcome chemoresistance in cancer.

Functional enrichment analysis is an essential task for the interpretation of gene lists derived from large-scale genetic, transcriptomic and proteomic studies. WebGestalt (WEB-based GEne SeT AnaLysis Toolkit) has become one of the popular software tools in this field since its publication in 2005. For the last 7 years, WebGestalt data holdings have grown substantially to satisfy the requirements of users from different research areas. The current version of WebGestalt supports 8 organisms and 201 gene identifiers from various databases and different technology platforms, making it directly available to the fast growing omics community. Meanwhile, by integrating functional categories derived from centrally and publicly curated databases as well as computational analyses, WebGestalt has significantly increased the coverage of functional categories in various biological contexts including Gene Ontology, pathway, network module, gene-phenotype association, gene-disease association, gene-drug association and chromosomal location, leading to a total of 78 612 functional categories. Finally, new interactive features, such as pathway map, hierarchical network visualization and phenotype ontology visualization have been added to WebGestalt to help users better understand the enrichment results. WebGestalt can be freely accessed through http://www.webgestalt.org or http://bioinfo.vanderbilt.edu/webgestalt/.

Expression quantitative trait locus (eQTL) analysis, which links variations in gene expression to genotypes, is essential to understanding gene regulation and to interpreting disease-associated loci. Currently identified eQTLs are mainly in samples of blood and other normal tissues. However, no database comprehensively provides eQTLs in large number of cancer samples. Using the genotype and expression data of 9196 tumor samples in 33 cancer types from The Cancer Genome Atlas (TCGA), we identified 5 606 570 eQTL-gene pairs in the cis-eQTL analysis and 231 210 eQTL-gene pairs in the trans-eQTL analysis. We further performed survival analysis and identified 22 212 eQTLs associated with patient overall survival. Furthermore, we linked the eQTLs to genome-wide association studies (GWAS) data and identified 337 131 eQTLs that overlap with existing GWAS loci. We developed PancanQTL, a user-friendly database (http://bioinfo.life.hust.edu.cn/PancanQTL/), to store cis-eQTLs, trans-eQTLs, survival-associated eQTLs and GWAS-related eQTLs to enable searching, browsing and downloading. PancanQTL could help the research community understand the effects of inherited variants in tumorigenesis and development.

Aminoacyl-tRNA synthetases are attractive targets for the development of antibacterial, antifungal, antiparasitic agents and for the treatment of other human diseases. Lysyl-tRNA synthetase (LysRS) from this family has been validated as a promising target for the development of antimalarial drugs. Here, we developed a high-throughput compatible assay and screened 1215 bioactive compounds to identify Plasmodium falciparum cytoplasmic LysRS (PfLysRS) inhibitor. ASP3026, an anaplastic lymphoma kinase inhibitor that was used in clinical trials for the treatment of B-cell lymphoma and solid tumors, was identified as a novel PfLysRS inhibitor. ASP3026 suppresses the enzymatic activity of PfLysRS at nanomolar potency, which is >380-fold more effective than inhibition of the human counterpart. In addition, the compound suppressed blood-stage P. falciparum growth. To understand the molecular mechanism of inhibition by ASP3026, we further solved the cocrystal structure of PfLysRS-ASP3026 at a resolution of 2.49 Å, providing clues for further optimization of the compound. Finally, primary structure-activity relationship analyses indicated that the inhibition of PfLysRS by ASP3026 is highly structure specific. This work not only provides a new chemical scaffold with good druggability for antimalarial development but also highlights the potential for repurposing kinase-inhibiting drugs to tRNA synthetase inhibitors to treat human diseases.

DNA methylation is an important epigenetic mechanism for regulating gene expression. Aberrant DNA methylation has been observed in various human diseases, including cancer. Single-nucleotide polymorphisms can contribute to tumor initiation, progression and prognosis by influencing DNA methylation, and DNA methylation quantitative trait loci (meQTL) have been identified in physiological and pathological contexts. However, no database has been developed to systematically analyze meQTLs across multiple cancer types. Here, we present Pancan-meQTL, a database to comprehensively provide meQTLs across 23 cancer types from The Cancer Genome Atlas by integrating genome-wide genotype and DNA methylation data. In total, we identified 8 028 964 cis-meQTLs and 965 050 trans-meQTLs. Among these, 23 432 meQTLs are associated with patient overall survival times. Furthermore, we identified 2 214 458 meQTLs that overlap with known loci identified through genome-wide association studies. Pancan-meQTL provides a user-friendly web interface (http://bioinfo.life.hust.edu.cn/Pancan-meQTL/) that is convenient for browsing, searching and downloading data of interest. This database is a valuable resource for investigating the roles of genetics and epigenetics in cancer.

Expression quantitative trait locus (eQTL) analysis is a powerful tool used to investigate genetic variations in complex diseases, including cancer. We previously developed a comprehensive database, PancanQTL, to characterize cancer eQTLs using The Cancer Genome Atlas (TCGA) dataset, and linked eQTLs with patient survival and GWAS risk variants. Here, we present an updated version, PancanQTLv2.0 (https://hanlaboratory.com/PancanQTLv2/), with advancements in fine-mapping causal variants for eQTLs, updating eQTLs overlapping with GWAS linkage disequilibrium regions and identifying eQTLs associated with drug response and immune infiltration. Through fine-mapping analysis, we identified 58 747 fine-mapped eQTLs credible sets, providing mechanic insights of gene regulation in cancer. We further integrated the latest GWAS Catalog and identified a total of 84 592 135 linkage associations between eQTLs and the existing GWAS loci, which represents a remarkable ∼50-fold increase compared to the previous version. Additionally, PancanQTLv2.0 uncovered 659516 associations between eQTLs and drug response and identified 146948 associations between eQTLs and immune cell abundance, providing potentially clinical utility of eQTLs in cancer therapy. PancanQTLv2.0 expanded the resources available for investigating gene expression regulation in human cancers, leading to advancements in cancer research and precision oncology.

Proper DNA damage response is essential for the maintenance of genome integrity. The E3 ligase RNF168 deficiency fully prevents both the initial recruitment and retention of 53BP1 at sites of DNA damage. In response to DNA damage, RNF168-dependent recruitment of the lysine-specific demethylase LSD1 to the site of DNA damage promotes local H3K4me2 demethylation and ubiquitination of H2A/H2AX, facilitating 53BP1 recruitment to sites of DNA damage. Alternatively, RNF168-mediated K63-linked ubiquitylation of 53BP1 is required for the initial recruitment of 53BP1 to sites of DNA damage and for its function in repair. We demonstrated here that phosphorylation and dephosphorylation of LSD1 at S131 and S137 was mediated by casein kinase 2 (CK2) and wild-type p53-induced phosphatase 1 (WIP1), respectively. LSD1, RNF168 and 53BP1 interacted with each other directly. CK2-mediated phosphorylation of LSD1 exhibited no impact on its interaction with 53BP1, but promoted its interaction with RNF168 and RNF168-dependent 53BP1 ubiquitination and subsequent recruitment to the DNA damage sites. Furthermore, overexpression of phosphorylation-defective mutants failed to restore LSD1 depletion-induced cellular sensitivity to DNA damage. Taken together, our results suggest that LSD1 phosphorylation modulated by CK2/WIP1 regulates RNF168-dependent 53BP1 recruitment directly in response to DNA damage and cellular sensitivity to DNA damaging agents.

Bacteria express large numbers of non-coding, regulatory RNAs known as 'small RNAs' (sRNAs). sRNAs typically regulate expression of multiple target messenger RNAs (mRNAs) through base-pairing interactions. sRNA:mRNA base-pairing often results in altered mRNA stability and/or altered translation initiation. Computational identification of sRNA targets is challenging due to the requirement for only short regions of base-pairing that can accommodate mismatches. Experimental approaches have been applied to identify sRNA targets on a genomic scale, but these focus only on those targets regulated at the level of mRNA stability. Here, we utilize ribosome profiling (Ribo-seq) to experimentally identify regulatory targets of the Escherichia coli sRNA RyhB. We not only validate a majority of known RyhB targets using the Ribo-seq approach, but also discover many novel ones. We further confirm regulation of a selection of known and novel targets using targeted reporter assays. By mutating nucleotides in the mRNA of a newly discovered target, we demonstrate direct regulation of this target by RyhB. Moreover, we show that Ribo-seq distinguishes between mRNAs regulated at the level of RNA stability and those regulated at the level of translation. Thus, Ribo-seq represents a powerful approach for genome-scale identification of sRNA targets.