Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.

Hyperactive ribosome biogenesis (RiboSis) fuels unrestricted cell proliferation, whereas genomic hallmarks and therapeutic targets of RiboSis in cancers remain elusive, and efficient approaches to quantify RiboSis activity are still limited. Here, we have established an in silico approach to conveniently score RiboSis activity based on individual transcriptome data. By employing this novel approach and RNA-seq data of 14 645 samples from TCGA/GTEx dataset and 917 294 single-cell expression profiles across 13 cancer types, we observed the elevated activity of RiboSis in malignant cells of various human cancers, and high risk of severe outcomes in patients with high RiboSis activity. Our mining of pan-cancer multi-omics data characterized numerous molecular alterations of RiboSis, and unveiled the predominant somatic alteration in RiboSis genes was copy number variation. A total of 128 RiboSis genes, including EXOSC4, BOP1, RPLP0P6 and UTP23, were identified as potential therapeutic targets. Interestingly, we observed that the activity of RiboSis was associated with TP53 mutations, and hyperactive RiboSis was associated with poor outcomes in lung cancer patients without TP53 mutations, highlighting the importance of considering TP53 mutations during therapy by impairing RiboSis. Moreover, we predicted 23 compounds, including methotrexate and CX-5461, associated with the expression signature of RiboSis genes. The current study generates a comprehensive blueprint of molecular alterations in RiboSis genes across cancers, which provides a valuable resource for RiboSis-based anti-tumor therapy.

Auxiliary rehabilitation training after calf contouring with botulinum toxin type A injection reduces adverse reactions and improves satisfaction.

PURPOSE: To analyze the effect of adjuvant rehabilitation training after calf contouring with botulinum toxin type A (BTX-A) injection. METHODS: Clinical data of 48 female beauty seekers who underwent calf contouring at the Plastic Surgery Laser Center of Guangdong Second People's Hospital from January 2021 to June 2022 were retrospectively analyzed. Among them, 24 cases received routine care from January 2021 to December 2021 and were included in a control group, and 24 cases received rehabilitation care with auxiliary rehabilitation training from January 2022 to June 2022 that were in an observation group. The subjects were followed up for 24 weeks to observe the curative effect, and the injection efficacy was compared between the two groups. The maximum calf circumference (MCC) and gastrocnemius muscle thickness (GMT) were comparatively analyzed before and 2, 4, 12, and 24 weeks after treatment. The incidence of adverse reactions and satisfaction rate were also compared. RESULTS: Both groups showed reduced calf circumferences after injection, with soft and uniform calf curves. No inter-group statistical significance was identified in terms of curative effects. Reduced MCC and GMT were observed in both groups at 2, 4, 12, and 24 weeks after treatment, with lower values in the observation group than in the control group at week 2, 4, and 12. The observation group also showed markedly fewer adverse reactions and higher satisfaction rate than the control group. CONCLUSIONS: BTX-A injection is effective in calf contouring and can significantly reduce the MCC and GMT. In addition, post-injection rehabilitation training can significantly reduce the occurrence of adverse reactions and improve patient satisfaction.

Retrospective Study of Vascular Complications Caused by Hyaluronic Acid Injection.

BACKGROUND: Complications from intravascular embolization of hyaluronic acid (HA) are not only no longer uncommon but also devastating. This study aimed to examine clinical aspects of patients referred to our hospital for care following complications from intravascular filler embolization. METHODS: We retrospectively reviewed data from all patients referred to our medical center for the management of complications associated with intravascular embolization of HA fillers including demographics, medical history, clinical features, and treatment between November 2013 and June 2022. RESULTS: A total of 116 patients with vascular complications (27 cases with vision loss and 89 cases with skin necrosis) were assessed. The highest risk injection sites for skin necrosis included the nasal region (58/115, 50.4%), temple (16/115, 13.9%), and forehead (11/115, 9.6%) and for vision loss included the nasal region (18/30, 60.0%) and forehead (7/30, 23.3%). In skin necrosis cases, a needle (60/89, 67.4%) carried a higher risk than that of a cannula (29/89, 32.6%), whereas in vision loss cases, nasal dorsum injections using a cannula (16/27, 59.3%) carried a higher risk than that observed using a needle (11/27, 40.7%). No treatment was completely successful in reversing these complications. CONCLUSION: Intravascular embolization of HA filler is a serious complication. Although some combination treatments have been proposed, there is no standard protocol for treating severe complications. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors http://www.springer.com/00266 .

Genome-wide DNA methylation landscape of four Chinese populations and epigenetic variation linked to Tibetan high-altitude adaptation.

DNA methylation (DNAm) is one of the major epigenetic mechanisms in humans and is important in diverse cellular processes. The variation of DNAm in the human population is related to both genetic and environmental factors. However, the DNAm profiles have not been investigated in the Chinese population of diverse ethnicities. Here, we performed double-strand bisulfite sequencing (DSBS) for 32 Chinese individuals representing four major ethnic groups including Han Chinese, Tibetan, Zhuang, and Mongolian. We identified a total of 604,649 SNPs and quantified DNAm at more than 14 million CpGs in the population. We found global DNAm-based epigenetic structure is different from the genetic structure of the population, and ethnic difference only partially explains the variation of DNAm. Surprisingly, non-ethnic-specific DNAm variations showed stronger correlation with the global genetic divergence than these ethnic-specific DNAm. Differentially methylated regions (DMRs) among these ethnic groups were found around genes in diverse biological processes. Especially, these DMR-genes between Tibetan and non-Tibetans were enriched around high-altitude genes including EPAS1 and EGLN1, suggesting DNAm alteration plays an important role in high-altitude adaptation. Our results provide the first batch of epigenetic maps for Chinese populations and the first evidence of the association of epigenetic changes with Tibetans' high-altitude adaptation.

Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature.

Previous studies have revealed that patients with hypertrophic cardiomyopathy (HCM) exhibit differences in symptom severity and prognosis, indicating potential HCM subtypes among these patients. Here, 793 patients with HCM were recruited at an average follow-up of 32.78 ± 27.58 months to identify potential HCM subtypes by performing consensus clustering on the basis of their echocardiography features. Furthermore, we proposed a systematic method for illustrating the relationship between the phenotype and genotype of each HCM subtype by using machine learning modeling and interactome network detection techniques based on whole-exome sequencing data. Another independent cohort that consisted of 414 patients with HCM was recruited to replicate the findings. Consequently, two subtypes characterized by different clinical outcomes were identified in HCM. Patients with subtype 2 presented asymmetric septal hypertrophy associated with a stable course, while those with subtype 1 displayed left ventricular systolic dysfunction and aggressive progression. Machine learning modeling based on personal whole-exome data identified 46 genes with mutation burden that could accurately predict subtype propensities. Furthermore, the patients in another cohort predicted as subtype 1 by the 46-gene model presented increased left ventricular end-diastolic diameter and reduced left ventricular ejection fraction. By employing echocardiography and genetic screening for the 46 genes, HCM can be classified into two subtypes with distinct clinical outcomes.

Risk modeling of single-cell transcriptomes reveals the heterogeneity of immune infiltration in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies. E2F transcription factors play an important role in the tumorigenesis and progression of HCC, mainly through the RB/E2F pathway. Prognostic models for HCC based on gene signatures have been developed rapidly in recent years; however, their discriminating ability at the single-cell level remains elusive, which could reflect the underlying mechanisms driving the sample bifurcation. In this study, we constructed and validated a predictive model based on E2F expression, successfully stratifying patients with HCC into two groups with different survival risks. Then we used a single-cell dataset to test the discriminating ability of the predictive model on infiltrating T cells, demonstrating remarkable cellular heterogeneity as well as altered cell fates. We identified distinct cell subpopulations with diverse molecular characteristics. We also found that the distribution of cell subpopulations varied considerably across onset stages among patients, providing a fundamental basis for patient-oriented precision evaluation. Moreover, single-sample gene set enrichment analysis revealed that subsets of CD8+ T cells with significantly different cell adhesion levels could be associated with different patterns of tumor cell dissemination. Therefore, our findings linked the conventional prognostic gene signature to the immune microenvironment and cellular heterogeneity at the single-cell level, thus providing deeper insights into the understanding of HCC tumorigenesis.

Shared and divergent contribution of vitamin A and oxytocin to the aetiology of autism spectrum disorder.

Rare genetic variations contribute to the heterogeneity of autism spectrum disorder (ASD) and the responses to various interventions for ASD probands. However, the associated molecular underpinnings remain unclear. Herein, we estimated the association between rare genetic variations in 410 vitamin A (VA)-related genes (VARGs) and ASD aetiology using publicly available de novo mutations (DNMs), rare inherited variants, and copy number variations (CNVs) from about 50,000 ASD probands and 20,000 normal controls (discovery and validation cohorts). Additionally, given the functional relevance of VA and oxytocin, we systematically compared the similarities and differences between VA and oxytocin with respect to ASD aetiology and evaluated their potential for clinical applications. Functional DNMs and pathogenic CNVs in VARGs contributed to ASD pathogenesis in the discovery and validation cohorts. Additionally, 324 potential VA-related biomarkers were identified, 243 of which were shared with previously identified oxytocin-related biomarkers, while 81 were unique VA biomarkers. Moreover, multivariable logistic regression analysis revealed that both VA- and oxytocin-related biomarkers were able to predict ASD aetiology for individuals carrying functional DNM in corresponding biomarkers with an average precision of 0.94. As well as, convergent and divergent functions were also identified between VA- and oxytocin-related biomarkers. The findings of this study provide a basis for future studies aimed at understanding the pathophysiological mechanisms underlying ASD while also defining a set of potential molecular biomarkers for adjuvant diagnosis and intervention in ASD.

Biofilm formation is a risk factor for late and delayed complications of filler injection.

Introduction: Biofilm formation is a major cause of delayed-graft complications. Similarly to implants, dermal fillers carry the risk of biofilm formation, which can lead to the development of nodules, chronic inflammatory reactions, abscesses and other complications. In this study, we investigated the late or delayed complications associated with biofilm formation on dermal fillers. Methods: In this retrospective analysis, we analyzed all cases of complications caused by filler injections at a single center between January 2017 and December 2022, the majority of which comprised nodule formation and chronic persistent inflammatory reactions. The risk of biofilm formation with fillers was summarized and analyzed based on the results of bacterial culture and pathological examination. Results: Sixty-one patients were enrolled, including 42 cases of nodule formation, 15 of chronic inflammatory reactions, and 4 of active infection. Bacterial culture of the tissue samples obtained from seven patients after surgical treatment were positive, and comprised four cases of Staphylococcus aureus, one case of Staphylococcus epidermidis, one case of Staphylococcus saprophyticus and one case of Mycobacterium abscessus. The corresponding histopathological results indicated extensive mononuclear lymphocyte infiltration, with a giant cell reaction in the fibrous connective tissue. Conclusion: The results of this study suggest that biofilm formation is a significant risk factor for late and delayed complications following filler injection, and is caused by the contamination of resident bacteria and recessive infection at the injection site.

An updated overview of experimental and computational approaches to identify non-canonical DNA/RNA structures with emphasis on G-quadruplexes and R-loops.

Multiple types of non-canonical nucleic acid structures play essential roles in DNA recombination and replication, transcription, and genomic instability and have been associated with several human diseases. Thus, an increasing number of experimental and bioinformatics methods have been developed to identify these structures. To date, most reviews have focused on the features of non-canonical DNA/RNA structure formation, experimental approaches to mapping these structures, and the association of these structures with diseases. In addition, two reviews of computational algorithms for the prediction of non-canonical nucleic acid structures have been published. One of these reviews focused only on computational approaches for G4 detection until 2020. The other mainly summarized the computational tools for predicting cruciform, H-DNA and Z-DNA, in which the algorithms discussed were published before 2012. Since then, several experimental and computational methods have been developed. However, a systematic review including the conformation, sequencing mapping methods and computational prediction strategies for these structures has not yet been published. The purpose of this review is to provide an updated overview of conformation, current sequencing technologies and computational identification methods for non-canonical nucleic acid structures, as well as their strengths and weaknesses. We expect that this review will aid in understanding how these structures are characterised and how they contribute to related biological processes and diseases.

Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality.

Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.

Transcriptomic signatures associated with autoimmune thyroiditis in papillary thyroid carcinoma and cancer immunotherapy-induced thyroid dysfunction.

Up to 20% of patients treated with anti-PD-1/PD-L1 inhibitors suffered from thyroid dysfunctions, yet the mediators associated with their occurrence remain unclear. The increasing coincidence of papillary thyroid carcinoma (PTC) with Hashimoto thyroiditis (HT) and the high vulnerability of thyroid to immunotherapy motivated us to discover the similarities and their underlying transcriptomic basis. Clinical characteristics analysis of 468 PTC patients from two independent cohorts and meta-analysis of 22,155 PTC patients unveiled a strong negative association between HT and recurrence in PTC patients. Transcriptome analysis of both cohorts showed PTC patients with HT were enriched in macrophages, CD8+ and CD4+ cytotoxic T cells, which was further validated by single-cell transcriptome analysis of 17,438 cells from PTC patients, and CD8+ T cells were correlated with disease-free survival of PTC patients. In both cohorts and single-cell dataset, elevated expression of PD-1-related genes was observed in the HT group, and CD3D appeared to be a target for enhancing the activation of CD8+ T cells. Correlation analysis of 3,318 thyroid adverse events from 39,123 patients across 24 tumor types and molecular signatures demonstrated similar signatures associated with autoimmune thyroiditis in PTC and thyroid immune-related adverse events (irAEs), and several multi-omics signatures, including signatures of CD8A and CD8+ T cells, showed positive associations with the odds ratio of thyroid irAEs. Our results unveil shared molecular signatures underlying thyroid dysfunction between patients receiving immunotherapies and PTC patients suffering from HT, which may shed light on managing the adverse events during cancer immunotherapy.

Integrative analysis prioritised oxytocin-related biomarkers associated with the aetiology of autism spectrum disorder.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high phenotypic and genetic heterogeneity. The common variants of specific oxytocin-related genes (OTRGs), particularly OXTR, are associated with the aetiology of ASD. The contribution of rare genetic variations in OTRGs to ASD aetiology remains unclear. METHODS: We catalogued publicly available de novo mutations (DNMs) [from 6,511 patients with ASD and 3,391 controls], rare inherited variants (RIVs) [from 1,786 patients with ASD and 1,786 controls], and both de novo copy number variations (dnCNVs) and inherited CNVs (ihCNVs) [from 15,581 patients with ASD and 6,017 controls] in 963 curated OTRGs to explore their contribution to ASD pathology, respectively. Finally, a combined model was designed to prioritise the contribution of each gene to ASD aetiology by integrating DNMs and CNVs. FINDINGS: The rare genetic variations of OTRGs were significantly associated with ASD aetiology, in the order of dnCNVs > ihCNVs > DNMs. Furthermore, 172 OTRGs and their connected 286 ASD core genes were prioritised to positively contribute to ASD aetiology, including top-ranked MAPK3. Probands carrying rare disruptive variations in these genes were estimated to account for 10∼11% of all ASD probands. INTERPRETATION: Our findings suggest that rare disruptive variations in 172 OTRGs and their connected 286 ASD core genes are associated with ASD aetiology and may be potential biomarkers predicting the effects of oxytocin treatment. FUNDING: Guangdong Key Project, National Natural Science Foundation of China, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province.

Comprehensive characterization of posttranscriptional impairment-related 3'-UTR mutations in 2413 whole genomes of cancer patients.

The 3' untranslated region (3'-UTR) is the vital element regulating gene expression, but most studies have focused on variations in RNA-binding proteins (RBPs), miRNAs, alternative polyadenylation (APA) and RNA modifications. To explore the posttranscriptional function of 3'-UTR somatic mutations in tumorigenesis, we collected whole-genome data from 2413 patients across 18 cancer types. Our updated algorithm, PIVar, revealed 25,216 3'-UTR posttranscriptional impairment-related SNVs (3'-UTR piSNVs) spanning 2930 genes; 24 related RBPs were significantly enriched. The somatic 3'-UTR piSNV ratio was markedly increased across all 18 cancer types, which was associated with worse survival for four cancer types. Several cancer-related genes appeared to facilitate tumorigenesis at the protein and posttranscriptional regulation levels, whereas some 3'-UTR piSNV-affected genes functioned mainly via posttranscriptional mechanisms. Moreover, we assessed immune cell and checkpoint characteristics between the high/low 3'-UTR piSNV ratio groups and predicted 80 compounds associated with the 3'-UTR piSNV-affected gene expression signature. In summary, our study revealed the prevalence and clinical relevance of 3'-UTR piSNVs in cancers, and also demonstrates that in addition to affecting miRNAs, 3'-UTR piSNVs perturb RBPs binding, APA and m6A RNA modification, which emphasized the importance of considering 3'-UTR piSNVs in cancer biology.

Gnas Promoter Hypermethylation in the Basolateral Amygdala Regulates Reconsolidation of Morphine Reward Memory in Rats.

Impairing reconsolidation may disrupt drug memories to prevent relapse, meanwhile long-term transcription regulations in the brain regions contribute to the occurrence of emotional memories. The basolateral amygdala (BLA) is involved in the drug-cue association, while the nucleus accumbens (NAc) responds to the drug reward. Here, we assessed whether DNA methyltransferases (Dnmts) in these two brain regions function identically in the reconsolidation of morphine reward memory. We show that Dnmts inhibition in the BLA but not in the NAc after memory retrieval impaired reconsolidation of a morphine reward memory. Moreover, the mRNA levels of Dnmt3a and Dnmt3b, rather than Dnmt1, in the BLA were continuously upregulated after retrieval. We further identified the differentially methylated regions (DMRs) in genes in the BLA after retrieval, and focused on the DMRs located in gene promoter regions. Among them were three genes (Gnas, Sox10, and Pik3r1) involved in memory modulation. Furthermore, Gnas promoter hypermethylation was confirmed to be inversely correlated with the downregulation of Gnas mRNA levels. The findings indicate that the specific transcription regulation mechanism in the BLA and NAc on reconsolidation of opiate-associated memories can be dissociable, and DNA hypermethylation of Gnas in the BLA is necessary for the reconsolidation of morphine reward memories.

Comprehensive evaluation of computational methods for predicting cancer driver genes.

Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein-protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http://159.226.67.237/sun/cancer_driver/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.

Mapping of de novo mutations in primary biliary cholangitis to a disease-specific co-expression network underlying homeostasis and metabolism.

Primary biliary cholangitis (PBC) is an autoimmune disease involving dysregulation of a broad array of homeostatic and metabolic processes. Although considerable single-nucleotide polymorphisms have been unveiled, a large fraction of risk factors remains enigmatic. Candidate genes with rare mutations that tend to confer more deleterious effects need to be identified. To help pinpoint cellular and developmental mechanisms beyond common noncoding variants, we integrate whole exome sequencing with integrative network analysis to investigate genes harboring de novo mutations. Prominent convergence has been revealed on a network of disease-specific co-expression comprised of 55 genes associated with homeostasis and metabolism. The transcription factor gene MEF2D and the DNA repair gene PARP2 are highlighted as hub genes and identified to be up- and down-regulated, respectively, in peripheral blood data set. Enrichment analysis demonstrates that altered expression of MEF2D and PARP2 may trigger a series of molecular and cellular processes with pivotal roles in PBC pathophysiology. Our study identifies genes with de novo mutations in PBC and suggests that a subset of genes in homeostasis and metabolism tend to act in synergy through converging on co-expression network, providing novel insights into the etiology of PBC and expanding the pool of molecular candidates for discovering clinically actionable biomarkers.

Cross-Disorder Analysis of De Novo Mutations in Neuropsychiatric Disorders.

The clinical similarity among different neuropsychiatric disorders (NPDs) suggested a shared genetic basis. We catalogued 23,109 coding de novo mutations (DNMs) from 6511 patients with autism spectrum disorder (ASD), 4,293 undiagnosed developmental disorder (UDD), 933 epileptic encephalopathy (EE), 1022 intellectual disability (ID), 1094 schizophrenia (SCZ), and 3391 controls. We evaluated that putative functional DNMs contribute to 38.11%, 34.40%, 33.31%, 10.98% and 6.91% of patients with ID, EE, UDD, ASD and SCZ, respectively. Consistent with phenotype similarity and heterogeneity in different NPDs, they show different degree of genetic association. Cross-disorder analysis of DNMs prioritized 321 candidate genes (FDR < 0.05) and showed that genes shared in more disorders were more likely to exhibited specific expression pattern, functional pathway, genetic convergence, and genetic intolerance.

The hepatic AMPK-TET1-SIRT1 axis regulates glucose homeostasis.

Ten-eleven translocation methylcytosine dioxygenase 1 (TET1) is involved in multiple biological functions in cell development, differentiation, and transcriptional regulation. Tet1 deficient mice display the defects of murine glucose metabolism. However, the role of TET1 in metabolic homeostasis keeps unknown. Here, our finding demonstrates that hepatic TET1 physically interacts with silent information regulator T1 (SIRT1) via its C-terminal and activates its deacetylase activity, further regulating the acetylation-dependent cellular translocalization of transcriptional factors PGC-1α and FOXO1, resulting in the activation of hepatic gluconeogenic gene expression that includes PPARGC1A, G6PC, and SLC2A4. Importantly, the hepatic gluconeogenic gene activation program induced by fasting is inhibited in Tet1 heterozygous mice livers. The adenosine 5'-monophosphate-activated protein kinase (AMPK) activators metformin or AICAR-two compounds that mimic fasting-elevate hepatic gluconeogenic gene expression dependent on in turn activation of the AMPK-TET1-SIRT1 axis. Collectively, our study identifies TET1 as a SIRT1 coactivator and demonstrates that the AMPK-TET1-SIRT1 axis represents a potential mechanism or therapeutic target for glucose metabolism or metabolic diseases.

A new approach to decode DNA methylome and genomic variants simultaneously from double strand bisulfite sequencing.

Genetic and epigenetic contributions to various diseases and biological processes have been well-recognized. However, simultaneous identification of single-nucleotide variants (SNVs) and DNA methylation levels from traditional bisulfite sequencing data is still challenging. Here, we develop double strand bisulfite sequencing (DSBS) for genome-wide accurate identification of SNVs and DNA methylation simultaneously at a single-base resolution by using one dataset. Locking Watson and Crick strand together by hairpin adapter followed by bisulfite treatment and massive parallel sequencing, DSBS simultaneously sequences the bisulfite-converted Watson and Crick strand in one paired-end read, eliminating the strand bias of bisulfite sequencing data. Mutual correction of read1 and read2 can estimate the amplification and sequencing errors, and enables our developed computational pipeline, DSBS Analyzer (https://github.com/tianguolangzi/DSBS), to accurately identify SNV and DNA methylation. Additionally, using DSBS, we provide a genome-wide hemimethylation landscape in the human cells, and reveal that the density of DNA hemimethylation sites in promoter region and CpG island is lower than that in other genomic regions. The cost-effective new approach, which decodes DNA methylome and genomic variants simultaneously, will facilitate more comprehensive studies on numerous diseases and biological processes driven by both genetic and epigenetic variations.