OBJECTIVE: Tinnitus, the perception of sound without any external sound source, is a prevalent hearing health concern. Mounting evidence suggests that a confluence of genetic, environmental, and lifestyle factors can influence the pathogenesis of tinnitus. We hypothesized that alteration in DNA methylation, an epigenetic modification that occurs at cytosines of cytosine-phosphate-guanine (CpG) dinucleotide sites, where a methyl group from S-adenyl methionine gets transferred to the fifth carbon of the cytosine, could contribute to tinnitus. DNA methylation patterns are tissue-specific, but the tissues involved in tinnitus are not easily accessible in humans. This pilot study used saliva as a surrogate tissue to identify differentially methylated CpG regions (DMRs) associated with tinnitus. The study was conducted on healthy young adults reporting bilateral continuous chronic tinnitus to limit the influence of age-related confounding factors and health-related comorbidities.
METHODS: The present study evaluated the genome-wide methylation levels from saliva-derived DNA samples from 24 healthy young adults with bilateral continuous chronic tinnitus (> 1 year) and 24 age, sex, and ethnicity-matched controls with no tinnitus. Genome-wide DNA methylation was evaluated for > 850,000 CpG sites using the Infinium Human Methylation EPIC BeadChip. The association analysis used the Bumphunter algorithm on 23 cases and 20 controls meeting the quality control standards. The methylation level was expressed as the area under the curve of CpG sites within DMRs.The FDR-adjusted p-value threshold of 0.05 was used to identify statistically significant DMRs associated with tinnitus.
RESULTS: We obtained 25 differentially methylated regions (DMRs) associated with tinnitus. Genes within or in the proximity of the hypermethylated DMRs related to tinnitus included LCLAT1, RUNX1, RUFY1, NUDT12, TTC23, SLC43A2, C4orf27 (STPG2), and EFCAB4B. Genes within or in the proximity of hypomethylated DMRs associated with tinnitus included HLA-DPB2, PM20D1, TMEM18, SNTG2, MUC4, MIR886, MIR596, TXNRD1, EID3, SDHAP3, HLA-DPB2, LASS3 (CERS3), C10orf11 (LRMDA), HLA-DQB1, NADK, SZRD1, MFAP2, NUP210L, TPM3, INTS9, and SLC2A14. The burden of genetic variation could explain the differences in the methylation levels for DMRs involving HLA-DPB2, HLA-DQB1, and MUC4, indicating the need for replication in large independent cohorts.
CONCLUSIONS: Consistent with the literature on comorbidities associated with tinnitus, we identified genes within or close to DMRs involved in auditory functions, chemical dependency, cardiovascular diseases, psychiatric conditions, immune disorders, and metabolic syndromes. These results indicate that epigenetic mechanisms could influence tinnitus, and saliva can be a good surrogate for identifying the epigenetic underpinnings of tinnitus in humans. Further research with a larger sample size is needed to identify epigenetic biomarkers and investigate their influence on the phenotypic expression of tinnitus.

Phytophthora sansomeana is an emerging oomycete pathogen causing root rot in many agricultural species including soybean. However, as of now, only one potential resistance gene has been identified in soybean, and our understanding of how genetic and epigenetic regulation in soybean contributes to responses against this pathogen remains largely unknown. In this study, we performed whole genome bisulfite sequencing (WGBS) on two soybean lines, Colfax (resistant) and Williams 82 (susceptible) in response to P. sansomeana at two time points: 4 and 16 hours post inoculation to compare their methylation changes. Our findings revealed that there were no significant changes in genome-wide CG, CHG (H = A, T, or C), and CHH methylation. However, we observed local methylation changes, specially an increase in CHH methylation around genes and transposable elements (TEs) after inoculation, which occurred earlier in the susceptible line and later in the resistant line. After inoculation, we identified differentially methylated regions (DMRs) in both Colfax and Williams 82, with a predominant presence in TEs. Notably, our data also indicated that more TEs exhibited changes in their methylomes in the susceptible line compared to the resistant line. Furthermore, we discovered 837 DMRs within or flanking 772 differentially expressed genes (DEGs) in Colfax and 166 DMRs within or flanking 138 DEGs in Williams 82. These DEGs had diverse functions, with Colfax primarily showing involvement in metabolic process, defense response, plant and pathogen interaction, anion and nucleotide binding, and catalytic activity, while Williams 82 exhibited a significant association with photosynthesis. These findings suggest distinct molecular responses to P. sansomeana infection in the resistant and susceptible soybean lines.

BACKGROUND: Imprinting disorders are rare diseases resulting from altered expression of imprinted genes, which exhibit parent-of-origin-specific expression patterns regulated through differential DNA methylation. A subgroup of patients with imprinting disorders have DNA methylation changes at multiple imprinted loci, a condition referred to as multi-locus imprinting disturbance (MLID). MLID is recognised in most but not all imprinting disorders and is also found in individuals with atypical clinical features; the presence of MLID often alters the management or prognosis of the affected person. Some cases of MLID are caused by trans-acting genetic variants, frequently not in the patients but their mothers, which have counselling implications. There is currently no consensus on the definition of MLID, clinical indications prompting testing, molecular procedures and methods for epigenetic and genetic diagnosis, recommendations for laboratory reporting, considerations for counselling, and implications for prognosis and management. The purpose of this study is thus to cover this unmet need.
METHODS: A comprehensive literature search was conducted resulting in identification of more than 100 articles which formed the basis of discussions by two working groups focusing on clinical diagnosis (n = 12 members) and molecular testing (n = 19 members). Following eight months of preparations and regular online discussions, the experts from 11 countries compiled the preliminary documentation and determined the questions to be addressed during a face-to-face meeting which was held with the attendance of the experts together with four representatives of patient advocacy organisations.
RESULTS: In light of available evidence and expert consensus, we formulated 16 propositions and 8 recommendations as interim guidance for the clinical and molecular diagnosis of MLID.
CONCLUSIONS: MLID is a molecular designation, and for patients with MLID and atypical phenotypes, we propose the alternative term multi-locus imprinting syndrome. Due to the intrinsic variability of MLID, the guidelines underscore the importance of involving experts from various fields to ensure a confident approach to diagnosis, counselling, and care. The authors advocate for global, collaborative efforts in both basic and translational research to tackle numerous crucial questions that currently lack answers, and suggest reconvening within the next 3-5 years to evaluate the research advancements and update this guidance as needed.

Obesity, characterized by the accumulation of excess fat, is a complex condition resulting from the combination of genetic and epigenetic factors. Recent studies have found correspondence between DNA methylation and cell differentiation, suggesting a role of the former in cell fate determination. There is a lack of comprehensive understanding concerning the underpinnings of preadipocyte differentiation, specifically when cells are undergoing terminal differentiation (TD). To gain insight into dynamic genome-wide methylation, 3T3 L1 preadipocyte cells were differentiated by a hormone cocktail. The genomic DNA was isolated from undifferentiated cells and 4 hours, 2 days postdifferentiated cells, and 15 days TD cells. We employed whole-genome bisulfite sequencing (WGBS) to ascertain global genomic DNA methylation alterations at single base resolution as preadipocyte cells differentiate. The genome-wide distribution of DNA methylation showed similar overall patterns in pre-, post-, and terminally differentiated adipocytes, according to WGBS analysis. DNA methylation decreases at 4 hours after differentiation initiation, followed by methylation gain as cells approach TD. Studies revealed novel differentially methylated regions (DMRs) associated with adipogenesis. DMR analysis suggested that though DNA methylation is global, noticeable changes are observed at specific sites known as \"hotspots.\" Hotspots are genomic regions rich in transcription factor (TF) binding sites and exhibit methylation-dependent TF binding. Subsequent analysis indicated hotspots as part of DMRs. The gene expression profile of key adipogenic genes in differentiating adipocytes is context-dependent, as we found a direct and inverse relationship between promoter DNA methylation and gene expression.

DNA methylation is an important epigenetic modification involved in gene regulation. Advances in the next generation sequencing technology have enabled the retrieval of DNA methylation information at single-base-resolution. However, due to the sequencing process and the limited amount of isolated DNA, DNA-methylation-data are often noisy and sparse, which complicates the identification of differentially methylated regions (DMRs), especially when few replicates are available. We present a varying-coefficient model for detecting DMRs by using single-base-resolved methylation information. The model simultaneously smooths the methylation profiles and allows detection of DMRs, while accounting for additional covariates. The proposed model takes into account possible overdispersion by using a beta-binomial distribution. The overdispersion itself can be modeled as a function of the genomic region and explanatory variables. We illustrate the properties of the proposed model by applying it to two real-life case studies.

Genomic imprinting is an epigenetic regulation in mammals in which a small subset of genes is monoallelically expressed dependent on their parental origin. A large imprinted domain, SGCE/PEG10 locus, is located on human chromosome 7q21s and mouse proximal chromosome 6. However, genomic imprinting of bovine SGCE/PEG10 cluster has not been systematically studied. In this study, we investigated allele expression of 14 genes of the SGCE/PEG10 locus in bovine somatic tissues and term placenta using a single nucleotide polymorphism (SNP)-based sequencing method. In addition to SGCE and PEG10, two conserved paternally expressed genes in human and mice, five other genes (TFPI2, GNG11, ASB4, PON1, and PON3) were paternally expressed. Three genes, BET1, COL1A2, and CASD1, exhibited tissue-specific monoallelic expression. CALCR showed monoallelic expression in tissues but biallelic expression in the placenta. Three genes, GNGT1, PPP1R9A, and PON2, showed biallelic expression in cattle. Five differentially methylated regions (DMRs) were found to be associated with the allelic expression of TFPI2, COL1A2, SGCE/PEG10, PON3, and ASB4 genes, respectively. The SGCE/PEG10 DMR is a maternally hypermethylated germline DMR, but TFPI2, COL1A2, PON3, and ASB4 DMRs are secondary DMRs. In summary, we identified five novel bovine imprinted genes (GNG11, BET1, COL1A2, CASD1, and PON1) and four secondary DMRs at the SGCE/PEG10 locus.

Polyploidy is an important evolutionary force, yet epigenetic mechanisms, such as DNA methylation, that regulate genome-wide expression of duplicated genes remain largely unknown. Here, we use Tragopogon (Asteraceae) as a model system to discover patterns and temporal dynamics of DNA methylation in recently formed polyploids. The naturally occurring allotetraploid Tragopogon miscellus formed in the last 95-100 yr from parental diploids Tragopogon dubius and T. pratensis. We profiled the DNA methylomes of these three species using whole-genome bisulfite sequencing. Genome-wide methylation levels in T. miscellus were intermediate between its diploid parents. However, nonadditive CG and CHG methylation occurred in transposable elements (TEs), with variation among TE types. Most differentially methylated regions (DMRs) showed parental legacy, but some novel DMRs were detected in the polyploid. Differentially methylated genes (DMGs) were also identified and characterized. This study provides the first assessment of both overall and locus-specific patterns of DNA methylation in a recent natural allopolyploid and shows that novel methylation variants can be generated rapidly after polyploid formation. Together, these results demonstrate that mechanisms to regulate duplicate gene expression may arise soon after allopolyploid formation and that these mechanisms vary among genes.

BACKGROUND: DNA methylation is a biochemical process in which a methyl group is added to the cytosine-phosphate-guanine (CpG) site on DNA molecules without altering the DNA sequence. Multiple CpG sites in a certain genome region can be differentially methylated across phenotypes. Identifying these differentially methylated CpG regions (DMRs) associated with the phenotypes contributes to disease prediction and precision medicine development.
RESULTS: We propose a novel DMR detection algorithm, gbdmr. In contrast to existing methods under a linear regression framework, gbdmr assumes that DNA methylation levels follow a generalized beta distribution. We compare gbdmr to alternative approaches via simulations and real data analyses, including dmrff, a new DMR detection approach that shows promising performance among competitors, and the traditional EWAS that focuses on single CpG sites. Our simulations demonstrate that gbdmr is superior to the other two when the correlation between neighboring CpG sites is strong, while dmrff shows a higher power when the correlation is weak. We provide an explanation of these phenomena from a theoretical perspective. We further applied the three methods to multiple real DNA methylation datasets. One is from a birth cohort study undertaken on the Isle of Wight, United Kingdom, and the other two are from the Gene Expression Omnibus database repository. Overall, gbdmr identifies more DMR CpGs linked to phenotypes than dmrff, and the simulated results support the findings.
CONCLUSIONS: Gbdmr is an innovative method for detecting DMRs based on generalized beta regression. It demonstrated notable advantages over dmrff and traditional EWAS, particularly when adjacent CpGs exhibited moderate to strong correlations. Our real data analyses and simulated findings highlight the reliability of gbdmr as a robust DMR detection tool. The gbdmr approach is accessible and implemented by R on GitHub: https://github.com/chengzhouwu/gbdmr .

Lung cancer poses a global health challenge, necessitating advanced diagnostics for improved outcomes. Intensive efforts are ongoing to pinpoint early detection biomarkers, such as genomic variations and DNA methylation, to elevate diagnostic precision. We conducted long-read sequencing on cancerous and adjacent non-cancerous tissues from a patient with lung adenocarcinoma. We identified somatic structural variations (SVs) specific to lung cancer by integrating data from various SV calling methods and differentially methylated regions (DMRs) that were distinct between these two tissue samples, revealing a unique methylation pattern associated with lung cancer. This study discovered over 40,000 somatic SVs and over 180,000 DMRs linked to lung cancer. We identified approximately 700 genes of significant relevance through comprehensive analysis, including genes intricately associated with many lung cancers, such as NOTCH1, SMOC2, CSMD2, and others. Furthermore, we observed that somatic SVs and DMRs were substantially enriched in several pathways, such as axon guidance signaling pathways, which suggests a comprehensive multi-omics impact on lung cancer progression across various biological investigation levels. These datasets can potentially serve as biomarkers for early lung cancer detection and may hold significant value in clinical diagnosis and treatment applications.

Differentially methylated regions (DMRs) can be used as head and neck squamous cell carcinoma (HNSCC) diagnostic, prognostic and therapeutic targets in precision medicine workflows. DNA from 21 HNSCC and 10 healthy oral tissue samples was hybridized to a genome-wide tiling array to identify DMRs in a discovery cohort. Downstream analyses identified differences in promoter DNA methylation patterns in oral, laryngeal and oropharyngeal anatomical regions associated with tumor differentiation, nodal involvement and survival. Genome-wide DMR analysis showed 2,565 DMRs common to the three subsites. A total of 738 DMRs were unique to laryngeal cancer (n=7), 889 DMRs were unique to oral cavity cancer (n=10) and 363 DMRs were unique to pharyngeal cancer (n=6). Based on the genome-wide analysis and a Gene Ontology analysis, 10 candidate genes were selected to test for prognostic value and association with clinicopathological features. TIMP3 was associated with tumor differentiation in oral cavity cancer (P=0.039), DAPK1 was associated with nodal involvement in pharyngeal cancer (P=0.017) and PAX1 was associated with tumor differentiation in laryngeal cancer (P=0.040). A total of five candidate genes were selected, DAPK1, CDH1, PAX1, CALCA and TIMP3, for a prevalence study in a larger validation cohort: Oral cavity cancer samples (n=42), pharyngeal cancer tissues (n=25) and laryngeal cancer samples (n=52). PAX1 hypermethylation differed across HNSCC anatomic subsites (P=0.029), and was predominantly detected in laryngeal cancer. Kaplan-Meier survival analysis (P=0.043) and Cox regression analysis of overall survival (P=0.001) showed that DAPK1 methylation is associated with better prognosis in HNSCC. The findings of the present study showed that the HNSCC subsites oral cavity, pharynx and larynx display substantial differences in aberrant DNA methylation patterns, which may serve as prognostic biomarkers and therapeutic targets.