GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits

Bidirectional Mendelian randomization to explore the causal relationships between the gut microbiota and male reproductive diseases

Gut bacteria might play an important role in male reproductive disorders, such as male infertility and sperm abnormalities; however, their causal role is unclear. Herein, Mendelian randomization (MR)-Egger, weighted median, inverse variance weighting, Simple mode, and Weighted mode were used to test the causal relationship between gut microbes and male reproductive diseases. The MR results were validated using various metrics. The MR results were also consolidated using reverse causality speculation, conducted using two-way MR analysis and Steiger filtering. Biological function was analysed using enrichment analyses. The results suggested that eight intestinal microflorae were causally associated with male infertility. The Eubacterium oxidoreducens group was associated with an increased risk of male infertility, while the family Bacteroidaceae was negatively associated with male reproductive diseases. Eight intestinal microflorae were causally associated with abnormal spermatozoa. The family Streptococcaceae was associated with a high risk of abnormal spermatozoa, whereas the family Porphyromonadaceae was associated with a low risk of abnormal spermatozoa. No pleiotropy was observed, this study identified a high correlation between the gut flora and the likelihood of male reproductive diseases. Future research will attempt to advance microbial-focused treatments for such diseases.

Integrative Multi-omics Analysis to Characterize Herpes Virus Infection Increases the Risk of Alzheimer's Disease

Evidence suggests that herpes virus infection is associated with an increased risk of Alzheimer's disease (AD), and innate and adaptive immunity plays an important role in the association. Although there have been many studies, the mechanism of the association is still unclear. This study aims to reveal the underlying molecular and immune regulatory network through multi-omics data and provide support for the study of the mechanism of infection and AD in the future. Here, we found that the herpes virus infection significantly increased the risk of AD. Genes associated with the occurrence and development of AD and genetically regulated by herpes virus infection are mainly enrichment in immune-related pathways. The 22 key regulatory genes identified by machine learning are mainly immune genes. They are also significantly related to the infiltration changes of 3 immune cell in AD. Furthermore, many of these genes have previously been reported to be linked, or potentially linked, to the pathological mechanisms of both herpes virus infection and AD. In conclusion, this study contributes to the study of the mechanisms related to herpes virus infection and AD, and indicates that the regulation of innate and adaptive immunity may be an effective strategy for preventing and treating herpes virus infection and AD. Additionally, the identified key regulatory genes, whether previously studied or newly discovered, may serve as valuable targets for prevention and treatment strategies.

A stage-dependent seed defense response to explain efficient seed transmission of Xanthomonas citri pv. fuscans to common bean

Although seed represents an important means of plant pathogen dispersion, the seed-pathogen dialogue remains largely unexplored. A multiomic approach was performed at different seed developmental stages of common bean (Phaseolus vulgaris L.) during asymptomatic colonization by Xanthomonas citri pv. fuscans (Xcf), At the early seed developmental stages, we observed high transcriptional changes both in seeds with bacterial recognition and defense signal transduction genes, and in bacteria with up-regulation of the bacterial type 3 secretion system. This high transcriptional activity of defense genes in Xcf-colonized seeds during maturation refutes the widely diffused assumption considering seeds as passive carriers of microbes. At later seed maturation stages, few transcriptome changes indicated a less intense molecular dialogue between the host and the pathogen, but marked by changes in DNA methylation of plant defense genes, in response to Xcf colonization. We showed examples of pathogen-specific DNA methylations in colonized seeds acting as plant defense silencing to repress plant immune response during the germination process. Finally, we propose a novel plant-pathogen interaction model, specific to the seed tissues, highlighting the existence of distinct phases during seed-pathogen interaction with seeds being actively interacting with colonizing pathogens, then both belligerents switching to more passive mode at later stages.

Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements

Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.

Harbinger transposon insertion in ethylene signaling gene leads to emergence of new sexual forms in cucurbits

In flowering plants, the predominant sexual morph is hermaphroditism, and the emergence of unisexuality is poorly understood. Using Cucumis melo (melon) as a model system, we explore the mechanisms driving sexual forms. We identify a spontaneous mutant exhibiting a transition from bisexual to unisexual male flower, and identify the causal mutation as a Harbinger transposon impairing the expression of Ethylene Insensitive 2 (CmEIN2) gene. Genetics and transcriptomic analysis reveal a dual role of CmEIN2 in both sex determination and fruit shape formation. Upon expression of CmACS11, EIN2 is recruited to repress the expression of the carpel inhibitor, CmWIP1. Subsequently, EIN2 is recruited to mediate stamina inhibition. Following the sex determination phase, EIN2 promotes fruit shape elongation. Genome-wide analysis reveals that Harbinger transposon mobilization is triggered by environmental cues, and integrates preferentially in active chromatin, particularly within promoter regions. Characterization of a large collection of melon germplasm points to active transpositions in the wild, compared to cultivated accessions. Our study underscores the association between chromatin dynamics and the temporal aspects of mobile genetic element insertions, providing valuable insights into plant adaptation and crop genome evolution.

Synergizing drug repurposing and target identification for neurodegenerative diseases

Despite dedicated research efforts, the absence of disease-curing remedies for neurodegenerative diseases (NDDs) continues to jeopardize human society and stands as a challenge. Drug repurposing is an attempt to find new functionality of existing drugs and take it as an opportunity to discourse the clinically unmet need to treat neurodegeneration. However, despite applying this approach to rediscover a drug, it can also be used to identify the target on which a drug could work. The primary objective of target identification is to unravel all the possibilities of detecting a new drug or repurposing an existing drug. Lately, scientists and researchers have been focusing on specific genes, a particular site in DNA, a protein, or a molecule that might be involved in the pathogenesis of the disease. However, the new era discusses directing the signaling mechanism involved in the disease progression, where receptors, ion channels, enzymes, and other carrier molecules play a huge role. This review aims to highlight how target identification can expedite the whole process of drug repurposing. Here, we first spot various target-identification methods and drug-repositioning studies, including drug-target and structure-based identification studies. Moreover, we emphasize various drug repurposing approaches in NDDs, namely, experimental-based, mechanism-based, and in silico approaches. Later, we draw attention to validation techniques and stress on drugs that are currently undergoing clinical trials in NDDs. Lastly, we underscore the future perspective of synergizing drug repurposing and target identification in NDDs and present an unresolved question to address the issue.

Gut microbiota and autism spectrum disorders: a bidirectional Mendelian randomization study

Background

In recent years, observational studies have provided evidence supporting a potential association between autism spectrum disorder (ASD) and gut microbiota. However, the causal effect of gut microbiota on ASD remains unknown.

Methods

We identified the summary statistics of 206 gut microbiota from the MiBioGen study, and ASD data were obtained from the latest Psychiatric Genomics Consortium Genome-Wide Association Study (GWAS). We then performed Mendelian randomization (MR) to determine a causal relationship between the gut microbiota and ASD using the inverse variance weighted (IVW) method, simple mode, MR-Egger, weighted median, and weighted model. Furthermore, we used Cochran's Q test, MR-Egger intercept test, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out analysis to identify heterogeneity and pleiotropy. Moreover, the Benjamin-Hochberg approach (FDR) was employed to assess the strength of the connection between exposure and outcome. We performed reverse MR analysis on the gut microbiota that were found to be causally associated with ASD in the forward MR analysis to examine the causal relationships. The enrichment analyses were used to analyze the biological function at last.

Results

Based on the results of IVW results, genetically predicted family Prevotellaceae and genus Turicibacter had a possible positive association with ASD (IVW OR=1.14, 95% CI: 1.00-1.29, P=3.7×10-2), four gut microbiota with a potential protective effect on ASD: genus Dorea (OR=0.81, 95% CI: 0.69-0.96, P=1.4×10-2), genus Ruminiclostridium5 (OR=0.81, 95% CI: 0.69-0.96, P=1.5×10-2), genus Ruminococcus1 (OR=0.83, 95% CI: 0.70-0.98, P=2.8×10-2), and genus Sutterella (OR=0.82, 95% CI: 0.68-0.99, P=3.6×10-2). After FDR multiple-testing correction we further observed that there were two gut microbiota still have significant relationship with ASD: family Prevotellaceae (IVW OR=1.24; 95% CI: 1.09-1.40, P=9.2×10-4) was strongly positively correlated with ASD and genus RuminococcaceaeUCG005 (IVW OR=0.78, 95% CI: 0.67-0.89, P=6.9×10-4) was strongly negatively correlated with ASD. The sensitivity analysis excluded the influence of heterogeneity and horizontal pleiotropy.

Conclusion

Our findings reveal a causal association between several gut microbiomes and ASD. These results deepen our comprehension of the role of gut microbiota in ASD's pathology, providing the foothold for novel ideas and theoretical frameworks to prevent and treat this patient population in the future.

DisVar: an R library for identifying variants associated with diseases using large-scale personal genetic information

Background

Genetic variants may potentially play a contributing factor in the development of diseases. Several genetic disease databases are used in medical research and diagnosis but the web applications used to search these databases for disease-associated variants have limitations. The application may not be able to search for large-scale genetic variants, the results of searches may be difficult to interpret and variants mapped from the latest reference genome (GRCH38/hg38) may not be supported.

Methods

In this study, we developed a novel R library called "DisVar" to identify disease-associated genetic variants in large-scale individual genomic data. This R library is compatible with variants from the latest reference genome version. DisVar uses five databases of disease-associated variants. Over 100 million variants can be simultaneously searched for specific associated diseases.

Results

The package was evaluated using 24 Variant Call Format (VCF) files (215,054 to 11,346,899 sites) from the 1000 Genomes Project. Disease-associated variants were detected in 298,227 hits across all the VCF files, taking a total of 63.58 m to complete. The package was also tested on ClinVar's VCF file (2,120,558 variants), where 20,657 hits associated with diseases were identified with an estimated elapsed time of 45.98 s.

Conclusions

DisVar can overcome the limitations of existing tools and is a fast and effective diagnostic and preventive tool that identifies disease-associated variations from large-scale genetic variants against the latest reference genome.

Whole-genome bisulfite sequencing identified the key role of the Src family tyrosine kinases and related genes in systemic lupus erythematosus

BACKGROUND

As a multisystemic autoimmune illness, the basic mechanisms behind the pathophysiology of systemic lupus erythematosus (SLE) remain poorly understood.

OBJECTIVE

We aimed to investigate the possible significance of SLE's DNA methylation and gain further insight into potential SLE-related biomarkers and therapeutic targets.

METHODS

We used whole genome bisulfite sequencing (WGBS) method to analyze DNA methylation in 4 SLE patients and 4 healthy people.

RESULTS

702 differentially methylated regions (DMRs) were identified, and 480 DMR-associated genes were annotated. We found the majority of the DMR-associated elements were enriched in repeat and gene bodies. The top 10 hub genes identified were LCK, FYB, PTK2B, LYN, CTNNB1, MAPK1, GNAQ, PRKCA, ABL1, and CD247. Compared to the control group, LCK and PTK2B had considerably decreased levels of mRNA expression in the SLE group. Receiver operating characteristic (ROC) curve suggested that LCK and PTK2B may be potential candidate biomarkers to predict SLE.

CONCLUSIONS

Our study improved comprehension of the DNA methylation patterns of SLE and identified potential biomarkers and therapeutic targets for SLE.

Venous thromboembolism-related genetic determinant F11 rs4253417 is a potential prognostic factor in ischaemic stroke

Ischaemic stroke (IS) and venous thromboembolism (VTE) are two forms of thromboembolism that, although distinct, seem to share numerous risk factors. Concerning genetic risk factors, while many VTE genetic markers have been reported, inclusively by genome-wide association studies (GWAS), the identification and validation of genetic determinants underlying IS pathogenesis have been challenging. Considering that IS and VTE shared biological pathways and aetiological factors, the severity of IS might be also influenced by VTE-related genetic variants. Thus, the present study was designed to analyse the impact of six VTE GWAS-identified genetic variants on the clinical outcome of 363 acute IS patients. Results revealed that the single-nucleotide polymorphism (SNP) F11 rs4253417 was an independent predictor of the 5-year risk of death among patients with total anterior circulation infarct (TACI). Namely, the ones carrying the SNP C allele presented a fourfold increase in the 5-year risk of death compared to TT genotype carriers (CC/CT vs. TT; adjusted HR, 4.240; 95% CI, 1.260-14.270; P = 0.020). This SNP is known to be associated with coagulation factor XI (FXI) levels, thus with implications in haemostasis and inflammation. As such, F11 rs4253417 might be a promising prognostic biomarker among TACI patients to aid in clinical decision-making. However, additional investigation is required to confirm the study's results and dissect the underlying mechanisms.

Associations of vitamin D-related single nucleotide polymorphisms with post-stroke depression among ischemic stroke population

Objective

To investigate the relationship between single nucleotide polymorphisms (SNPs) related to vitamin D (VitD) metabolism and post-stroke depression (PSD) in patients with ischemic stroke.

Methods

A total of 210 patients with ischemic stroke were enrolled at the Department of Neurology in Xiangya Hospital, Central South University, from July 2019 to August 2021. SNPs in the VitD metabolic pathway (VDR, CYP2R1, CYP24A1, and CYP27B1) were genotyped using the SNPscan^™ multiplex SNP typing kit. Demographic and clinical data were collected using a standardized questionnaire. Multiple genetic models including dominant, recessive, and over-dominant models were utilized to analyze the associations between SNPs and PSD.

Results

In the dominant, recessive, and over-dominant models, no significant association was observed between the selected SNPs in the CYP24A1 and CYP2R1 genes and PSD. However, univariate and multivariate logistic regression analysis revealed that the CYP27B1 rs10877012 G/G genotype was associated with a decreased risk of PSD (OR: 0.41, 95% CI: 0.18-0.92, p = 0.030 and OR: 0.42, 95% CI: 0.18-0.98, p = 0.040, respectively). Furthermore, haplotype association analysis indicated that rs11568820-rs1544410-rs2228570-rs7975232-rs731236 CCGAA haplotype in the VDR gene was associated with a reduced risk of PSD (OR: 0.14, 95% CI: 0.03-0.65, p = 0.010), whereas no significant association was observed between haplotypes in the CYP2R1 and CYP24A1 genes and PSD.

Conclusion

Our findings suggest that the polymorphisms of VitD metabolic pathway genes VDR and CYP27B1 may be associated with PSD in patients with ischemic stroke.

Chromosome-scale de novo genome assembly and annotation of three representative Casuarina species: C. equisetifolia, C. glauca, and C. cunninghamiana

Australian pine (Casuarina spp.) is extensively planted in tropical and subtropical regions for wood production, shelterbelts, environmental protection, and ecological restoration due to their superior biological characteristics, such as rapid growth, wind and salt tolerance, and nitrogen fixation. To analyze the genomic diversity of Casuarina, we sequenced the genomes and constructed de novo genome assemblies of the three most widely planted Casuarina species: C. equisetifolia, C. glauca, and C. cunninghamiana. We generated chromosome-scale genome sequences using both Pacific Biosciences (PacBio) Sequel sequencing and chromosome conformation capture technology (Hi-C). The total genome sizes for C. equisetifolia, C. glauca, and C. cunninghamiana are 268 942 579 bp, 296 631 783 bp, and 293 483 606 bp, respectively, of which 25.91, 27.15, and 27.74% were annotated as repetitive sequences. We annotated 23 162, 24 673, and 24 674 protein-coding genes in C. equisetifolia, C. glauca, and C. cunninghamiana, respectively. We then collected branchlets from male and female individuals for whole-genome bisulfite sequencing (BS-seq) to explore the epigenetic regulation of sex determination in these three species. Transcriptome sequencing (RNA-seq) revealed differential expression of phytohormone-related genes between male and female plants. In summary, we generated three chromosome-level genome assemblies and comprehensive DNA methylation and transcriptome datasets from both male and female material for three Casuarina species, providing a basis for the comprehensive investigation of genomic diversity and functional gene discovery of Casuarina in the future.

Acquired crizotinib-resistant pulmonary adenocarcinoma and subsequent primary gallbladder cancer: A case report

RATIONALE

Proto-oncogene-oriented targeted therapy has limited benefits in elderly patients with multiple primary tumors.

PATIENT CONCERNS

A woman with anaplastic lymphoma kinase-positive lung adenocarcinoma developed acquired resistance after 3 years of targeted therapy with crizotinib.

DIAGNOSES

Diagnosis of unexpected subsequent primary gallbladder tumor.

INTERVENTIONS

Lenvatinib was administered therapeutically. Meanwhile, next-generation sequencing results before and after crizotinib treatment were analyzed by comparing the tumor-driving mutation genes with bioinformatics methods.

OUTCOMES

The patient died of ascites and liver failure. Furthermore, bypass activation was found to be the main reason for acquired drug resistance for this patient, and the abnormal expression of tumor suppressor genes and senescence-related genes was the likely cause of the second primary tumor.

LESSONS

A bioinformatic comparison of pre- and post-treatment sequencing in elderly oncology patients is of interest.

CONCLUSIONS

For diagnosing, precision bioinformatics analysis and repeat biopsy are equally valuable. For therapy, potential therapy such as p53 gene replacement therapy and CAR-T therapy need to be practiced for senescence-related conditions.

An autoimmune pleiotropic SNP modulates IRF5 alternative promoter usage through ZBTB3-mediated chromatin looping

Genetic sharing is extensively observed for autoimmune diseases, but the causal variants and their underlying molecular mechanisms remain largely unknown. Through systematic investigation of autoimmune disease pleiotropic loci, we found most of these shared genetic effects are transmitted from regulatory code. We used an evidence-based strategy to functionally prioritize causal pleiotropic variants and identify their target genes. A top-ranked pleiotropic variant, rs4728142, yielded many lines of evidence as being causal. Mechanistically, the rs4728142-containing region interacts with the IRF5 alternative promoter in an allele-specific manner and orchestrates its upstream enhancer to regulate IRF5 alternative promoter usage through chromatin looping. A putative structural regulator, ZBTB3, mediates the allele-specific loop to promote IRF5-short transcript expression at the rs4728142 risk allele, resulting in IRF5 overactivation and M1 macrophage polarization. Together, our findings establish a causal mechanism between the regulatory variant and fine-scale molecular phenotype underlying the dysfunction of pleiotropic genes in human autoimmunity.

Decoding the genetic and epigenetic basis of asthma

Asthma is a complex and heterogeneous chronic inflammatory disease of the airways. Alongside environmental factors, asthma susceptibility is strongly influenced by genetics. Given its high prevalence and our incomplete understanding of the mechanisms underlying disease susceptibility, asthma is frequently studied in genome-wide association studies (GWAS), which have identified thousands of genetic variants associated with asthma development. Virtually all these genetic variants reside in non-coding genomic regions, which has obscured the functional impact of asthma-associated variants and their translation into disease-relevant mechanisms. Recent advances in genomics technology and epigenetics now offer methods to link genetic variants to gene regulatory elements embedded within non-coding regions, which have started to unravel the molecular mechanisms underlying the complex (epi)genetics of asthma. Here, we provide an integrated overview of (epi)genetic variants associated with asthma, focusing on efforts to link these disease associations to biological insight into asthma pathophysiology using state-of-the-art genomics methodology. Finally, we provide a perspective as to how decoding the genetic and epigenetic basis of asthma has the potential to transform clinical management of asthma and to predict the risk of asthma development.

Transcriptional reprogramming of skeletal muscle stem cells by the niche environment

Adult stem cells are indispensable for tissue regeneration, but their function declines with age. The niche environment in which the stem cells reside plays a critical role in their function. However, quantification of the niche effect on stem cell function is lacking. Using muscle stem cells (MuSC) as a model, we show that aging leads to a significant transcriptomic shift in their subpopulations accompanied by locus-specific gain and loss of chromatin accessibility and DNA methylation. By combining in vivo MuSC transplantation and computational methods, we show that the expression of approximately half of all age-altered genes in MuSCs from aged male mice can be restored by exposure to a young niche environment. While there is a correlation between gene reversibility and epigenetic alterations, restoration of gene expression occurs primarily at the level of transcription. The stem cell niche environment therefore represents an important therapeutic target to enhance tissue regeneration in aging.

Somatic Variants in SVIL in Cerebral Aneurysms

Background and Objectives

While somatic mutations have been well-studied in cancer, their roles in other complex traits are much less understood. Our goal is to identify somatic variants that may contribute to the formation of saccular cerebral aneurysms.

Methods

We performed whole-exome sequencing on aneurysm tissues and paired peripheral blood. RNA sequencing and the CRISPR/Cas9 system were then used to perform functional validation of our results.

Results

Somatic variants involved in supervillin (SVIL) or its regulation were found in 17% of aneurysm tissues. In the presence of a mutation in theSVILgene, the expression level of SVIL was downregulated in the aneurysm tissue compared with normal control vessels. Downstream signaling pathways that were induced by knockdown ofSVILvia the CRISPR/Cas9 system in vascular smooth muscle cells (vSMCs) were determined by evaluating changes in gene expression and protein kinase phosphorylation. We found thatSVILregulated the phenotypic modulation of vSMCs to the synthetic phenotype via Krüppel-like factor 4 and platelet-derived growth factor and affected cell migration of vSMCs via the RhoA/ROCK pathway.

Discussion

We propose that somatic variants form a novel mechanism for the development of cerebral aneurysms. Specifically, somatic variants inSVILresult in the phenotypic modulation of vSMCs, which increases the susceptibility to aneurysm formation. This finding suggests a new avenue for the therapeutic intervention and prevention of cerebral aneurysms.

Histone chaperone ASF1 mediates H3.3-H4 deposition in Arabidopsis

Histone chaperones and chromatin remodelers control nucleosome dynamics, which are essential for transcription, replication, and DNA repair. The histone chaperone Anti-Silencing Factor 1 (ASF1) plays a central role in facilitating CAF-1-mediated replication-dependent H3.1 deposition and HIRA-mediated replication-independent H3.3 deposition in yeast and metazoans. Whether ASF1 function is evolutionarily conserved in plants is unknown. Here, we show that Arabidopsis ASF1 proteins display a preference for the HIRA complex. Simultaneous mutation of both Arabidopsis ASF1 genes caused a decrease in chromatin density and ectopic H3.1 occupancy at loci typically enriched with H3.3. Genetic, transcriptomic, and proteomic data indicate that ASF1 proteins strongly prefers the HIRA complex over CAF-1. asf1 mutants also displayed an increase in spurious Pol II transcriptional initiation and showed defects in the maintenance of gene body CG DNA methylation and in the distribution of histone modifications. Furthermore, ectopic targeting of ASF1 caused excessive histone deposition, less accessible chromatin, and gene silencing. These findings reveal the importance of ASF1-mediated histone deposition for proper epigenetic regulation of the genome.

QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes

Deciphering the fine-scale molecular mechanisms that shape the genetic effects at disease-associated loci from genome-wide association studies (GWAS) remains challenging. The key avenue is to identify the essential molecular phenotypes that mediate the causal variant and disease under particular biological conditions. Therefore, integrating GWAS signals with context-specific quantitative trait loci (QTLs) (such as different tissue/cell types, disease states, and perturbations) from extensive molecular phenotypes would present important strategies for full understanding of disease genetics. Via persistent curation and systematic data processing of large-scale human molecular trait QTLs (xQTLs), we updated our previous QTLbase database (now QTLbase2, http://mulinlab.org/qtlbase) to comprehensively analyze and visualize context-specific QTLs across 22 molecular phenotypes and over 95 tissue/cell types. Overall, the resource features the following major updates and novel functions: (i) 960 more genome-wide QTL summary statistics from 146 independent studies; (ii) new data for 10 previously uncompiled QTL types; (iii) variant query scope expanded to fit 195 QTL datasets based on whole-genome sequencing; (iv) supports filtering and comparison of QTLs for different biological conditions, such as stimulation types and disease states; (v) a new linkage disequilibrium viewer to facilitate variant prioritization across tissue/cell types and QTL types.

Index of multiple deprivation contributed to common psychiatric disorders: A systematic review and comprehensive analysis

BACKGROUND

Limited studies have been conducted to explore the interaction effects of social environmental and genetic factors on the risks of common psychiatric disorders.

METHODS

56,613-106,695 individuals were collected from the UK Biobank cohort. Logistic or liner regression models were first used to evaluate the associations of index of multiple deprivation (IMD) with bipolar disorder (BD), depression and anxiety in UK Biobank cohort. Then, for the significant IMD associated with BD, depression and anxiety, genome-wide gene-environment interaction study (GWEIS) was performed by PLINK 2.0.

RESULT

Totally, the higher levels of IMD were significantly associated with higher risks of BD, depression and anxiety. For BD, GWEIS identified multiple significant SNPs interacting with IMD, such as rs75182167 for income and rs111841503 for education. For depression and anxiety, GWEIS found significant SNPs interacting with income and education, such as rs147013419 for income and rs142366753 for education.

CONCLUSION

Social environmental deprivations contributed to the risks of psychiatric disorders. Besides, we reported multiple candidate genetic loci interacting with IMD, providing novel insights into the biological mechanism.

TET enzymes regulate skeletal development through increasing chromatin accessibility of RUNX2 target genes

The Ten-eleven translocation (TET) family of dioxygenases mediate cytosine demethylation by catalyzing the oxidation of 5-methylcytosine (5mC). TET-mediated DNA demethylation controls the proper differentiation of embryonic stem cells and TET members display functional redundancy during early gastrulation. However, it is unclear if TET proteins have functional significance in mammalian skeletal development. Here, we report that Tet genes deficiency in mesoderm mesenchymal stem cells results in severe defects of bone development. The existence of any single Tet gene allele can support early bone formation, suggesting a functional redundancy of TET proteins. Integrative analyses of RNA-seq, Whole Genome Bisulfite Sequencing (WGBS), 5hmC-Seal and Assay for Transposase-Accessible Chromatin (ATAC-seq) demonstrate that TET-mediated demethylation increases the chromatin accessibility of target genes by RUNX2 and facilities RUNX2-regulated transcription. In addition, TET proteins interact with RUNX2 through their catalytic domain to regulate cytosine methylation around RUNX2 binding region. The catalytic domain is indispensable for TET enzymes to regulate RUNX2 transcription activity on its target genes and to regulate bone development. These results demonstrate that TET enzymes function to regulate RUNX2 activity and maintain skeletal homeostasis.

Here the authors investigate the role of the TET family of DNA demethylases in mammalian skeletal development. They find that loss of TETs leads to hypermethylation that results in decreased chromatin accessibility of RUNX2 target genes, repressing osteoblast differentiation and leading to skeletal defects in mouse such as short limbs.

3DFAACTS-SNP: using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of type 1 diabetes (T1D) risk

Background

Genome-wide association studies (GWAS) have enabled the discovery of single nucleotide polymorphisms (SNPs) that are significantly associated with many autoimmune diseases including type 1 diabetes (T1D). However, many of the identified variants lie in non-coding regions, limiting the identification of mechanisms that contribute to autoimmune disease progression. To address this problem, we developed a variant filtering workflow called 3DFAACTS-SNP to link genetic variants to target genes in a cell-specific manner. Here, we use 3DFAACTS-SNP to identify candidate SNPs and target genes associated with the loss of immune tolerance in regulatory T cells (Treg) in T1D.

Results

Using 3DFAACTS-SNP, we identified from a list of 1228 previously fine-mapped variants, 36 SNPs with plausible Treg-specific mechanisms of action. The integration of cell type-specific chromosome conformation capture data in 3DFAACTS-SNP identified 266 regulatory regions and 47 candidate target genes that interact with these variant-containing regions in Treg cells. We further demonstrated the utility of the workflow by applying it to three other SNP autoimmune datasets, identifying 16 Treg-centric candidate variants and 60 interacting genes. Finally, we demonstrate the broad utility of 3DFAACTS-SNP for functional annotation of all known common (> 10% allele frequency) variants from the Genome Aggregation Database (gnomAD). We identified 9376 candidate variants and 4968 candidate target genes, generating a list of potential sites for future T1D or other autoimmune disease research.

Conclusions

We demonstrate that it is possible to further prioritise variants that contribute to T1D based on regulatory function, and illustrate the power of using cell type-specific multi-omics datasets to determine disease mechanisms. Our workflow can be customised to any cell type for which the individual datasets for functional annotation have been generated, giving broad applicability and utility.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-022-00456-5.

Genetic pleiotropy between pulmonary function and age-related traits: The Long Life Family Study

BACKGROUND

Pulmonary function (PF) progressively declines with aging. Forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) are predictors of morbidity of pulmonary and cardiovascular diseases and all-cause mortality. In addition, reduced PF is associated with elevated chronic low-grade systemic inflammation, glucose metabolism, body fatness, and low muscle strength. It may suggest pleiotropic genetic effects between PF with these age-related factors.

METHODS

We evaluated whether FEV1 and FVC share common pleiotropic genetic effects factors with interleukin-6, high-sensitivity C-reactive protein, body mass index, muscle (grip) strength, plasma glucose, and glycosylated hemoglobin in 3,888 individuals (age range: 26-106). We employed sex-combined and sex-specific correlated meta-analyses to test whether combining genome-wide association p-values from two or more traits enhances the ability to detect variants sharing effects on these correlated traits.

RESULTS

We identified 32 loci for PF, including 29 novel pleiotropic loci associated with pulmonary function and (i) body fatness (CYP2U1/SGMS2), (ii) glucose metabolism (CBWD1/DOCK8 and MMUT/CENPQ), (iii) inflammatory markers (GLRA3/HPGD, TRIM9, CALN1, CTNNB1/ZNF621, GATA5/SLCO4A1/NTSR1, and NPVF/C7orf31/CYCS), and (iv) muscle strength (MAL2, AC008825.1/LINC02103, AL136418.1).

CONCLUSIONS

The identified genes/loci for PF and age-related traits suggest their underlying shared genetic effects, which can explain part of their phenotypic correlations. Integration of gene expression and genomic annotation data shows enrichment of our genetic variants in lung, blood, adipose, pancreas, and muscles, among others. Our findings highlight the critical roles of identified gene/locus in systemic inflammation, glucose metabolism, strength performance, PF, and pulmonary disease, which are involved in accelerated biological aging.

Human reproduction is regulated by retrotransposons derived from ancient Hominidae-specific viral infections

Germ cells are essential to pass DNA from one generation to the next. In human reproduction, germ cell development begins with the specification of primordial germ cells (PGCs) and a failure to specify PGCs leads to human infertility. Recent studies have revealed that the transcription factor network required for PGC specification has diverged in mammals, and this has a significant impact on our understanding of human reproduction. Here, we reveal that the Hominidae-specific Transposable Elements (TEs) LTR5Hs, may serve as TEENhancers (TE Embedded eNhancers) to facilitate PGC specification. LTR5Hs TEENhancers become transcriptionally active during PGC specification both in vivo and in vitro with epigenetic reprogramming leading to increased chromatin accessibility, localized DNA demethylation, enrichment of H3K27ac, and occupation of key hPGC transcription factors. Inactivation of LTR5Hs TEENhancers with KRAB mediated CRISPRi has a significant impact on germ cell specification. In summary, our data reveals the essential role of Hominidae-specific LTR5Hs TEENhancers in human germ cell development.

The transcription factor network required for primordial germ cell (PGC) specification is known to diverge in mammals. Here the authors show that hominidae-specific transposable element (TE) LTR5Hs becomes transcriptionally active during PGC specification, and LTR5Hs inactivation abrogates human PGC specification

Integrating Transcriptomics, Genomics, and Imaging in Alzheimer's Disease: A Federated Model

Alzheimer's disease (AD) affects more than 1 in 9 people age 65 and older and becomes an urgent public health concern as the global population ages. In clinical practice, structural magnetic resonance imaging (sMRI) is the most accessible and widely used diagnostic imaging modality. Additionally, genome-wide association studies (GWAS) and transcriptomics-the study of gene expression-also play an important role in understanding AD etiology and progression. Sophisticated imaging genetics systems have been developed to discover genetic factors that consistently affect brain function and structure. However, most studies to date focused on the relationships between brain sMRI and GWAS or brain sMRI and transcriptomics. To our knowledge, few methods have been developed to discover and infer multimodal relationships among sMRI, GWAS, and transcriptomics. To address this, we propose a novel federated model, Genotype-Expression-Imaging Data Integration (GEIDI), to identify genetic and transcriptomic influences on brain sMRI measures. The relationships between brain imaging measures and gene expression are allowed to depend on a person's genotype at the single-nucleotide polymorphism (SNP) level, making the inferences adaptive and personalized. We performed extensive experiments on publicly available Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Experimental results demonstrated our proposed method outperformed state-of-the-art expression quantitative trait loci (eQTL) methods for detecting genetic and transcriptomic factors related to AD and has stable performance when data are integrated from multiple sites. Our GEIDI approach may offer novel insights into the relationship among image biomarkers, genotypes, and gene expression and help discover novel genetic targets for potential AD drug treatments.

Association and functional analysis of angiotensin-converting enzyme 2 genetic variants with the pathogenesis of pre-eclampsia

OBJECTIVE

The aim of this study was to investigate the relationship between potential functional single-nucleotide polymorphisms (SNPs) of the angiotensin-converting enzyme 2 (ACE2) gene and the pathogenesis of pre-eclampsia (PE) in Guangxi, China.

MATERIALS AND METHODS

A case-control study was conducted involving 327 PE cases and 591 age-matched, normal, singleton pregnant women. Potential functional ACE2 gene variants (rs2106809 A>G, rs6632677 G>C, and rs2074192 C>T) were selected and genotyped using kompetitive allele-specific PCR. The strength of the associations between the studied genetic variants and the risk of PE were evaluated using odds ratios (ORs) and corresponding 95% confidence intervals (CIs).

RESULT

After adjusting for age and body mass index (BMI), unconditional logistic regression analysis showed that rs2106809 A>G was significantly associated with PE risk (AG vs. AA, OR = 1.43, 95% CI = 1.03-1.99, p = 0.034; AG/GG vs. AA, OR = 1.45, 95% CI = 1.06-1.99, p = 0.019), especially with severe PE (AG vs. AA, adjusted OR = 1.70, 95% CI = 1.10-2.61; AG/GG vs. AA, adjusted OR = 1.71, 95% CI = 1.14-2.57). Further stratified analysis showed that rs2106809 was even more pronounced in subjects in the pre-pregnancy BMI (pre-BMI) >23 kg/m² (adjusted OR = 2.14, 95% CI = 1.32-3.45) and triglyceride (TG) >2.84 mmol/L subgroups (adjusted OR = 1.81, 95% CI = 1.09-3.01) under the dominant genetic model. We also found that rs2106809 interacted with pre-BMI (p _interaction = 0.040), thereby affecting an individual's genetic susceptibility to PE. Multiple dimension reduction analysis demonstrated that rs2106809 made the best one-locus model, and the three-locus model was the best interaction model for predicting PE risk. Functional analysis suggested that rs2106809 A>G causes a change in the reliability of classifications of two putative splice sites in the ACE2 gene, potentially regulating the expression of functional genes (PIR, ACE2, and CLTRN) in multiple tissues and cell lines (p< 0.05).

CONCLUSION

The ACE2 gene rs2106809 A>G variant is significantly associated with the risk of PE via individual locus effects and/or complex gene-gene and gene-environment interactions. Regulating the expression of functional genes such as PIR, ACE2, and CLTRN may be the molecular mechanism by which rs2106809 increases an individual's susceptibility to PE.

Association of ACE2 gene functional variants with gestational diabetes mellitus risk in a southern Chinese population

OBJECTIVE

To explore the relationship between angiotensin-converting enzyme 2 (ACE2) genetic variants and gestational diabetes mellitus (GDM) in a southern Chinese population.

METHODS

Potential functional variants (rs2106809, rs6632677, and rs2074192) of ACE2 were selected and genotyped in 566 GDM patients and 710 normal pregnaõncies in Guilin, China. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were used to evaluate the association between genetic variant and GDM risk, and then the false positive report probability, multifactor dimensional reduction (MDR), and bioinformatics tools were used to confirm the significant association in the study.

RESULTS

After adjusting for age and prepregnancy body mass index, logistic regression analysis showed that ACE2 rs6632677 was significantly associated with a decreased risk of GDM (CC vs. GG: adjusted OR = 0.09, 95% CI: 0.01 - 0.71, P = .023; GC/CC vs. GG: adjusted OR = 0.68, 95% CI = 0.46 - 0.99, P = .048; and CC vs. GG/GC: adjusted OR = 0.09, 95% CI = 0.01 - 0.72, P = .024), whereas rs2074192 was associated with increased GDM risk (TT vs. CC/CT: adjusted OR = 1.38, 95% CI = 1.08 - 1.75, P = .009). Furthermore, we found that rs6632677 interacted with SBP (P _interaction = .043) and FPG (P _interaction = .021) and rs2074192 interacted with HDL-c (P _interaction = .029) and LDL-c (P _interaction = .035) to influence the GDM risk of the individual. In the MDR analysis, the rs6632677 was the best one-locus model, and the three-loci model was the best interaction model to predict GDM risk. In addition, functional analysis confirmed that rs2074192 may regulate the splicing process of ACE2 gene.

CONCLUSION

ACE2 gene variants are significantly associated with the risk of GDM via gene-gene and gene-environment combinations. The rs2074192 C > T affects the splicing of the ACE2 gene, which may be a potential mechanism leading to the changed susceptibility of an individual female during pregnancy to GDM.

Genome-wide association and functional interrogation identified a variant at 3p26.1 modulating ovarian cancer survival among Chinese women

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.

Interrogating cell type-specific cooperation of transcriptional regulators in 3D chromatin

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.

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Computational inference of transcriptional regulator (TR) cooperation in 3D chromatin

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A landscape of 3D TR cooperation across 40 human tissue/cell types

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TR cooperation can better interpret the disease-causal variants identified by GWAS

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Cooperation of certain TRs shapes context-specific gene regulation in cell development

Pharmacogenetic loci for rosuvastatin are associated with intima-media thickness change and coronary artery disease risk

Aim: Polymorphisms at LPA, LDLR, APOE, APOC1, MYLIP and ABCG2 are attractive targets for assessment of their impact on lipid-lowering therapy with rosuvastatin. The present study investigated whether polymorphisms at these genes are associated with the risk of coronary artery disease (CAD) development, and reduction of atherogenic lipids and carotid intima-media thickness (CIMT) in CAD patients, taking rosuvastatin. Materials & methods: 190 CAD patients and 1697 subjects were enrolled in pharmacogenetic and genetic association study, respectively. SNP genotyping was done using the MassARRAY-4 system. Results: MYLIP rs6924995, rs3757354, APOC1 rs445925, LDLR rs6511720, APOE rs7412, ABCG2 rs2199936, rs1481012 variants were significantly associated with CAD susceptibility (p = 0.016, 0.0003, <0.0001, <0.0001, 0.013, 0.016, 0.0035, respectively), as well as with CIMT regression (except ABCG2 variants; p = 0.05, 0.039, 0.039, 0.016, 0.0065), and changes in plasma lipids during rosuvastatin therapy. Conclusion: The studied polymorphisms possess pleiotropic effects on plasma lipids and CIMT, CAD susceptibility, and determine lipid-lowering response to rosuvastatin.

Grafting vigour is associated with DNA de-methylation in eggplant

In horticulture, grafting is a popular technique used to combine positive traits from two different plants. This is achieved by joining the plant top part (scion) onto a rootstock which contains the stem and roots. Rootstocks can provide resistance to stress and increase plant production, but despite their wide use, the biological mechanisms driving rootstock-induced alterations of the scion phenotype remain largely unknown. Given that epigenetics plays a relevant role during distance signalling in plants, we studied the genome-wide DNA methylation changes induced in eggplant (Solanum melongena) scion using two interspecific rootstocks to increase vigour. We found that vigour was associated with a change in scion gene expression and a genome-wide hypomethylation in the CHH context. Interestingly, this hypomethylation correlated with the downregulation of younger and potentially more active long terminal repeat retrotransposable elements (LTR-TEs), suggesting that graft-induced epigenetic modifications are associated with both physiological and molecular phenotypes in grafted plants. Our results indicate that the enhanced vigour induced by heterografting in eggplant is associated with epigenetic modifications, as also observed in some heterotic hybrids.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

VannoPortal: multiscale functional annotation of human genetic variants for interrogating molecular mechanism of traits and diseases

Interpreting the molecular mechanism of genomic variations and their causal relationship with diseases/traits are important and challenging problems in the human genetic study. To provide comprehensive and context-specific variant annotations for biologists and clinicians, here, by systematically integrating over 4TB genomic/epigenomic profiles and frequently-used annotation databases from various biological domains, we develop a variant annotation database, called VannoPortal. In general, the database has following major features: (i) systematically integrates 40 genome-wide variant annotations and prediction scores regarding allele frequency, linkage disequilibrium, evolutionary signature, disease/trait association, tissue/cell type-specific epigenome, base-wise functional prediction, allelic imbalance and pathogenicity; (ii) equips with our recent novel index system and parallel random-sweep searching algorithms for efficient management of backend databases and information extraction; (iii) greatly expands context-dependent variant annotation to incorporate large-scale epigenomic maps and regulatory profiles (such as EpiMap) across over 33 tissue/cell types; (iv) compiles many genome-scale base-wise prediction scores for regulatory/pathogenic variant classification beyond protein-coding region; (v) enables fast retrieval and direct comparison of functional evidence among linked variants using highly interactive web panel in addition to plain table; (vi) introduces many visualization functions for more efficient identification and interpretation of functional variants in single web page. VannoPortal is freely available at http://mulinlab.org/vportal.

Genome-wide Association Study Identified Chromosome 8 Locus Associated with Medication-Related Osteonecrosis of the Jaw

Medication‐related osteonecrosis of the jaw (MRONJ) is a rare but serious drug‐related adverse event. To identify pharmacogenomic markers of MRONJ associated with bisphosphonate therapy, we conducted a genomewide association study (GWAS) meta‐analysis followed by functional analysis of 5,008 individuals of European ancestry treated with bisphosphonates, which includes the largest number of MRONJ cases to date (444 cases and 4,564 controls). Discovery GWAS was performed in randomly selected 70% of the patients with cancer and replication GWAS was performed in the remaining 30% of the patients with cancer treated with intravenous bisphosphonates followed by meta‐analysis of all 3,639 patients with cancer. GWAS was also performed in 1,369 patients with osteoporosis treated with oral bisphosphonates. The lead single‐nucleotide polymorphism (SNP), rs2736308 on chromosome 8, was associated with an increased risk of MRONJ with an odds ratio (OR) of 2.71 and 95% confidence interval (CI) of 1.90–3.86 (P = 3.57*10⁻⁸) in the meta‐analysis of patients with cancer. This SNP was validated in the MRONJ GWAS in patients with osteoporosis (OR: 2.82, 95% CI: 1.55–4.09, P = 6.84*10⁻⁴). The meta‐analysis combining patients with cancer and patients with osteoporosis yielded the same lead SNP rs2736308 on chromosome 8 as the top SNP (OR: 2.74, 95% CI: 2.09–3.39, P = 9.65*10⁻¹¹). This locus is associated with regulation of the BLK, CTSB, and FDFT1 genes, which had been associated with bone mineral density. FDFT1 encodes a membrane‐associated enzyme, which is implicated in the bisphosphonate pathway. This study provides insights into the potential mechanism of MRONJ.

Association of GTF2I, NFKB1, and TYK2 Regional Polymorphisms With Systemic Sclerosis in a Chinese Han Population

Objectives

Systemic sclerosis (SSc) is an uncommon autoimmune disease that varies with ethnicity. Single nucleotide polymorphisms (SNPs) in the GTFSI, NFKB1, and TYK2 genes have been reported to be associated with SSc in other populations and in individuals with various autoimmune diseases. This study aimed to investigate the association between these SNPs and susceptibility to SSc in a Chinese Han population.

Method

A case-control study was performed in 343 patients with SSc and 694 ethnically matched healthy controls. SNPs in GTF2I, NFKB1, and TYK2 were genotyped using a Sequenom MassArray iPLEX system. Association analyses were performed using PLINK v1.90 software.

Result

Our study demonstrated that the GTF2I rs117026326 T allele and the GTF2I rs73366469 C allele were strongly associated with patients with SSc (P = 6.97E-10 and P = 1.33E-08, respectively). Patients carrying the GTF2I rs117026326 TT genotype and the GTF2I rs73366469 CC genotype had a strongly increased risk of SSc (P = 6.25E-09 and P = 1.67E-08, respectively), and those carrying the NFKB1 rs1599961 AA genotype had a suggestively significantly increased risk of SSc (P = 0.014). Moreover, rs117026326 and rs73366469 were associated with SSc in different genetic models (additive model, dominant model, and recessive model) (P < 0.05) whereas rs1599961 was associated with SSc in the dominant genetic model but not in the addictive and recessive models (P = 0.0026). TYK2 rs2304256 was not significantly associated with SSc in this study.

Conclusion

GTF2I rs117026326 and rs73366469 SNPs were strongly associated with SSc in this Chinese Han population. NFKB1 rs1599961 showed a suggestive association with SSc, and no significant association was found between TYK2 rs2304256 and SSc in this Chinese Han population.

Triangulating molecular evidence to prioritize candidate causal genes at established atopic dermatitis loci

Genome-wide association studies for atopic dermatitis (AD) have identified 25 reproducible loci. We attempt to prioritize candidate causal genes at these loci using extensive molecular resources compiled into a bioinformatics pipeline. We identified a list of 103 molecular resources for AD aetiology, including expression, protein and DNA methylation QTL datasets in skin or immune-relevant tissues which were tested for overlap with GWAS signals. This was combined with functional annotation using regulatory variant prediction, and features such as promoter-enhancer interactions, expression studies and variant fine-mapping. For each gene at each locus, we condensed the evidence into a prioritization score. Across the investigated loci, we detected significant enrichment of genes with adaptive immune regulatory function and epidermal barrier formation among the top prioritized genes. At 8 loci, we were able to prioritize a single candidate gene (IL6R, ADO, PRR5L, IL7R, ETS1, INPP5D, MDM1, TRAF3). In addition, at 6 of the 25 loci, our analysis prioritizes less familiar candidates (SLC22A5, IL2RA, MDM1, DEXI, ADO, STMN3). Our analysis provides support for previously implicated genes at several AD GWAS loci, as well as evidence for plausible additional candidates at others, which may represent potential targets for drug discovery.

Exploring Common Therapeutic Targets for Neurodegenerative Disorders Using Transcriptome Study

Alzheimer's disease (AD) and Parkinson's disease (PD) are well-known neuronal degenerative disorders that share common pathological events. Approved medications alleviate symptoms but do not address the root cause of the disease. Energy dysfunction in the neuronal population leads to various pathological events and ultimately results in neuronal death. Identifying common therapeutic targets for these disorders may help in the drug discovery process. The Brodmann area 9 (BA9) region is affected in both the disease conditions and plays an essential role in cognitive, motor, and memory-related functions. Analyzing transcriptome data of BA9 provides deep insights related to common pathological pathways involved in AD and PD. In this work, we map the preprocessed BA9 fastq files generated by RNA-seq for disease and control samples with reference hg38 genomic assembly and identify common variants and differentially expressed genes (DEG). These variants are predominantly located in the 3' UTR (non-promoter) region, affecting the conserved transcription factor (TF) binding motifs involved in the methylation and acetylation process. We have constructed BA9-specific functional interaction networks, which show the relationship between TFs and DEGs. Based on expression signature analysis, we propose that MAPK1, VEGFR1/FLT1, and FGFR1 are promising drug targets to restore blood-brain barrier functionality by reducing neuroinflammation and may save neurons.

Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas

The evolution of DNA methylome and methylation intra-tumor heterogeneity (ITH) during early carcinogenesis of lung adenocarcinoma has not been systematically studied. We perform reduced representation bisulfite sequencing of invasive lung adenocarcinoma and its precursors, atypical adenomatous hyperplasia, adenocarcinoma in situ and minimally invasive adenocarcinoma. We observe gradual increase of methylation aberrations and significantly higher level of methylation ITH in later-stage lesions. The phylogenetic patterns inferred from methylation aberrations resemble those based on somatic mutations suggesting parallel methylation and genetic evolution. De-convolution reveal higher ratio of T regulatory cells (Tregs) versus CD8 + T cells in later-stage diseases, implying progressive immunosuppression with neoplastic progression. Furthermore, increased global hypomethylation is associated with higher mutation burden, copy number variation burden and AI burden as well as higher Treg/CD8 ratio, highlighting the potential impact of methylation on chromosomal instability, mutagenesis and tumor immune microenvironment during early carcinogenesis of lung adenocarcinomas.

Implications of venous thromboembolism GWAS reported genetic makeup in the clinical outcome of ovarian cancer patients

Ovarian cancer (OC) represents the most lethal gynaecological neoplasia. Conversely, venous thromboembolism (VTE) and OC are intricately connected, with many haemostatic components favouring OC progression. In light of this bilateral relationship, genome-wide association studies (GWAS) have reported several single-nucleotide polymorphisms (SNPs) associated with VTE risk that could be used as predictors of OC clinical outcome for better therapeutic management strategies. Thus, the present study aimed to analyse the impact of VTE GWAS-identified SNPs on the clinical outcome of 336 epithelial ovarian cancer (EOC) patients. Polymorphism genotyping was performed using the TaqMan^® Allelic Discrimination methodology. Carriers with the ZFPM2 rs4734879 G allele presented a significantly higher 5-year OS, 10-year OS and disease-free survival (DFS) compared to AA genotype patients with FIGO I/II stages (P = 0.009, P = 0.001 and P = 0.003, respectively). Regarding SLC19A2 rs2038024 polymorphism, carriers with the CC genotype presented a significantly lower 5-year OS, 10-year OS and DFS compared to A allele carriers in the same FIGO subgroup (P < 0.001, P = 0.004 and P = 0.005, respectively). As for CNTN6 rs6764623 polymorphism, carriers with the CC genotype presented a significantly lower 5-year OS compared to A allele carriers with FIGO I/II stages (P = 0.015). As for OTUD7A rs7164569, F11 rs4253417 and PROCR rs10747514, no significant impact on EOC patients' survival was observed. However, future studies are required to validate these results and uncover the biological mechanisms underlying our results.

Prioritizing long range interactions in noncoding regions using GWAS and deletions perturbed TADs

Genome-wide association studies (GWAS) have contributed significantly to predisposing the disease etiology by associating single nucleotide polymorphisms (SNPs) with complex diseases. However, most GWAS-SNPs are in the noncoding regions that may affect distal genes via long range enhancer-promoter interactions. Thus, the common practice on GWAS discoveries cannot fully reveal the molecular mechanisms underpinning complex diseases. It is known that perturbations of topological associated domains (TADs) lead to long range interactions which underlie disease etiology. To identify the probable long range interactions in noncoding regions via GWAS and TADs perturbed by deletions, we integrated datasets from GWAS-SNPs, enhancers, TADs, and deletions. After ranking and clustering, we prioritized 201,132 high confident pairs of GWAS-SNPs and target genes. In this study, we performed a systematic inference on noncoding regions via GWAS-SNPs and deletion-perturbed TADs to boost GWAS discovery power. The high confident pairs of GWAS-SNPs and target genes (SE-Gs) provide the promising candidates to understand the molecular mechanisms underlying complex diseases with emphasis on the three-dimensional genome.

Ultrafast and scalable variant annotation and prioritization with big functional genomics data

The advances of large-scale genomics studies have enabled compilation of cell type–specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.

Multiomics dissection of molecular regulatory mechanisms underlying autoimmune-associated noncoding SNPs

More than 90% of autoimmune-associated variants are located in noncoding regions, leading to challenges in deciphering the underlying causal roles of functional variants and genes and biological mechanisms. Therefore, to reduce the gap between traditional genetic findings and mechanistic understanding of disease etiologies and clinical drug development, it is important to translate systematically the regulatory mechanisms underlying noncoding variants. Here, we prioritized functional noncoding SNPs with regulatory gene targets associated with 19 autoimmune diseases by incorporating hundreds of immune cell-specific multiomics data. The prioritized SNPs are associated with transcription factor (TF) binding, histone modification, or chromatin accessibility, indicating their allele-specific regulatory roles. Their target genes are significantly enriched in immunologically related pathways and other known immunologically related functions. We found that 90.1% of target genes are regulated by distal SNPs involving several TFs (e.g., the DNA-binding protein CCCTC-binding factor [CTCF]), suggesting the importance of long-range chromatin interaction in autoimmune diseases. Moreover, we predicted potential drug targets for autoimmune diseases, including 2 genes (NFKB1 and SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. Taken together, these findings may provide useful information for future experimental follow-up and drug applications on autoimmune diseases.

Turning genome-wide association study findings into opportunities for drug repositioning

Drug development is a very costly and lengthy process, while repositioned or repurposed drugs could be brought into clinical practice within a shorter time-frame and at a much reduced cost. Numerous computational approaches to drug repositioning have been developed, but methods utilizing genome-wide association studies (GWASs) data are less explored.

The past decade has observed a massive growth in the amount of data from GWAS; the rich information contained in GWAS has great potential to guide drug repositioning or discovery. While multiple tools are available for finding the most relevant genes from GWAS hits, searching for top susceptibility genes is only one way to guide repositioning, which has its own limitations.

Here we provide a comprehensive review of different computational approaches that employ GWAS data to guide drug repositioning. These methods include selecting top candidate genes from GWAS as drug targets, deducing drug candidates based on drug-drug and disease-disease similarities, searching for reversed expression profiles between drugs and diseases, pathway-based methods as well as approaches based on analysis of biological networks. Each method is illustrated with examples, and their respective strengths and limitations are discussed. We also discussed several areas for future research.

Significance of Single-Nucleotide Variants in Long Intergenic Non-protein Coding RNAs

Single-nucleotide variants (SNVs) are the most common genetic variants and universally present in the human genome. Genome-wide association studies (GWASs) have identified a great number of disease or trait-associated variants, many of which are located in non-coding regions. Long intergenic non-protein coding RNAs (lincRNAs) are the major subtype of long non-coding RNAs; lincRNAs play crucial roles in various disorders and cellular models via multiple mechanisms. With rapid growth in the number of the identified lincRNAs and genetic variants, there is great demand for an investigation of SNVs in lincRNAs. Hence, in this article, we mainly summarize the significant role of SNVs within human lincRNA regions. Some pivotal variants may serve as risk factors for the development of various disorders, especially cancer. They may also act as important regulatory signatures involved in the modulation of lincRNAs in a tissue- or disorder-specific manner. An increasing number of researches indicate that lincRNA variants would potentially provide additional options for genetic testing and disease risk assessment in the personalized medicine era.

OncoBase: a platform for decoding regulatory somatic mutations in human cancers

Whole-exome and whole-genome sequencing have revealed millions of somatic mutations associated with different human cancers, and the vast majority of them are located outside of coding sequences, making it challenging to directly interpret their functional effects. With the rapid advances in high-throughput sequencing technologies, genome-scale long-range chromatin interactions were detected, and distal target genes of regulatory elements were determined using three-dimensional (3D) chromatin looping. Herein, we present OncoBase (http://www.oncobase.biols.ac.cn/), an integrated database for annotating 81 385 242 somatic mutations in 68 cancer types from more than 120 cancer projects by exploring their roles in distal interactions between target genes and regulatory elements. OncoBase integrates local chromatin signatures, 3D chromatin interactions in different cell types and reconstruction of enhancer-target networks using state-of-the-art algorithms. It employs informative visualization tools to display the integrated local and 3D chromatin signatures and effects of somatic mutations on regulatory elements. Enhancer-promoter interactions estimated from chromatin interactions are integrated into a network diffusion system that quantitatively prioritizes somatic mutations and target genes from a large pool. Thus, OncoBase is a useful resource for the functional annotation of regulatory noncoding regions and systematically benchmarking the regulatory effects of embedded noncoding somatic mutations in human carcinogenesis.

regBase: whole genome base-wise aggregation and functional prediction for human non-coding regulatory variants

Predicting the functional or pathogenic regulatory variants in the human non-coding genome facilitates the interpretation of disease causation. While numerous prediction methods are available, their performance is inconsistent or restricted to specific tasks, which raises the demand of developing comprehensive integration for those methods. Here, we compile whole genome base-wise aggregations, regBase, that incorporate largest prediction scores. Building on different assumptions of causality, we train three composite models to score functional, pathogenic and cancer driver non-coding regulatory variants respectively. We demonstrate the superior and stable performance of our models using independent benchmarks and show great success to fine-map causal regulatory variants on specific locus or at base-wise resolution. We believe that regBase database together with three composite models will be useful in different areas of human genetic studies, such as annotation-based casual variant fine-mapping, pathogenic variant discovery as well as cancer driver mutation identification. regBase is freely available at https://github.com/mulinlab/regBase.

Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction

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.

QTLbase: an integrative resource for quantitative trait loci across multiple human molecular phenotypes

Recent advances in genome sequencing and functional genomic profiling have promoted many large-scale quantitative trait locus (QTL) studies, which connect genotypes with tissue/cell type-specific cellular functions from transcriptional to post-translational level. However, no comprehensive resource can perform QTL lookup across multiple molecular phenotypes and investigate the potential cascade effect of functional variants. We developed a versatile resource, named QTLbase, for interpreting the possible molecular functions of genetic variants, as well as their tissue/cell-type specificity. Overall, QTLbase has five key functions: (i) curating and compiling genome-wide QTL summary statistics for 13 human molecular traits from 233 independent studies; (ii) mapping QTL-relevant tissue/cell types to 78 unified terms according to a standard anatomogram; (iii) normalizing variant and trait information uniformly, yielding >170 million significant QTLs; (iv) providing a rich web client that enables phenome- and tissue-wise visualization; and (v) integrating the most comprehensive genomic features and functional predictions to annotate the potential QTL mechanisms. QTLbase provides a one-stop shop for QTL retrieval and comparison across multiple tissues and multiple layers of molecular complexity, and will greatly help researchers interrogate the biological mechanism of causal variants and guide the direction of functional validation. QTLbase is freely available at http://mulinlab.org/qtlbase.

Method for Bisulfite Sequencing Data Analysis for Whole-Genome Level DNA Methylation Detection in Legumes

Methylation of cytosines in DNA is the most stable type of epigenetic modification that is established and maintained by different enzymes. In plants, DNA methylation is inherited from one generation to another leaving an epigenetic mark as a memory of previous state, which may include encounter with stress or pathogen. Advancement in the next generation sequencing technologies has enabled the profiling of methylation marks. Whole-genome bisulfite sequencing (WGBS) has the potential to unravel the patterns of DNA methylation at single-base resolution. Though the sequencing technologies have evolved drastically, analysis of WGBS data still remains challenging. Here, we provide a methodology for performing WGBS data analysis along with critical steps for identification of methylation marks in plant genomes including legumes.