Methylation Profiles Research Articles

Primary intracranial sarcoma associated with DICER1 mutant: a case report and preclinical investigation.

Primary intracranial sarcoma (PIS) is a rare and aggressive pediatric brain tumor, which is partially associated with DICER1 mutant. Although the molecular genetic characteristics of this tumor have previously been investigated, novel therapeutic targets remain unclear. Further, the lack of faithful preclinical models has hampered the development of novel therapeutic strategies. Herein, we describe a pediatric case of PIS with DICER1 mutant and describe the development of the first novel patient-derived xenograft (PDX) model of this rare tumor. Somatic genomic profiling of the tumor revealed mutations in DICER1, TP53, and ATRX. Germline analysis further revealed a pathogenic variant of DICER1, significant for the diagnosis and management of hereditary tumor predisposition syndrome. Overall, we demonstrated that the PDX model faithfully retained the phenotype and genotype of the patient's tumor, as well as the DNA methylation profile. Through high-throughput drug screening using PDX tumor cells, we found that activation of the retinoic acid receptor (RAR) signaling pathway reduced tumor cell viability. These findings indicate that the RAR signaling pathway is a potential therapeutic target for PIS in DICER1 mutant.

Stability of Blood DNA Methylation Across Two Timepoints in Three Cohorts

Background: DNA methylation mediates the gene–environment interactions, with implications for health and disease. Studies with sampling at more than one timepoint revealed the considerable variability of the blood methylome, but comprehensive resources on genome-wide methylation stability are still lacking. We aimed to identify methylation sites that remain the most stable across two timepoints in human whole blood. Methods: Publicly available blood DNA methylation data from three cohorts were analysed, which included methylation profiles at two timepoints >1 year apart. The cohorts included pre-/post-pubertal children (Illumina 450k array), the elderly (Illumina 450k array), and middle-aged adults with obesity (Illumina EPIC array). Two metrics were used for the stability assessment: the mean absolute difference (MAD) of beta values between two measurements and the intraclass correlation coefficient (ICC). We searched for probes demonstrating high stability (low MAD and high ICC) across the three cohorts. Data from 51 children, 86 elderly adults, and 120 middle-aged participants were re-analysed. Results: The median interquartile range (IQR) of the maximum (from three datasets) MAD was 2.1% (1.5–2.9%), and the median of the minimum ICC agreement coefficient was 0.053 (−0.077–0.304). The Pearson’s correlation coefficient for the ICC vs. maximum MAD was low (r = 0.34, p < 2.2 × 10−16). We found only 239 probes that were highly stable based on both the maximum MAD (<5th percentile, <0.01) and ICC criterion (>95th percentile, >0.74). Conclusions: The whole-blood DNA methylation profile, as measured using microarrays, is dynamic over >1 year, but contains a fraction of stable probes, most of which are related to genomic variation. A resource describing probe stability is made publicly available, with the intention to support biomarker studies and the investigation of early epigenetic programming. The absolute error and correlation are two complementary facets of probe stability that may be considered in further research, especially to determine the stability of probes in health and disease across different tissues and populations.

DeepAge: Harnessing Deep Neural Network for Epigenetic Age Estimation From DNA Methylation Data of Human Blood Samples

Accurate prediction of biological age from DNA methylation data is a critical endeavor in understanding the molecular mechanisms of aging and developing age-related disease interventions. Traditional epigenetic clocks rely on linear regression or basic machine learning models, which often fail to capture the complex, non-linear interactions within methylation data. This study introduces DeepAge, a novel deep learning framework utilizing Temporal Convolutional Networks (TCNs) to enhance the prediction of biological age from DNA methylation profiles using selected CpGs by a Dual-Correlation based apparoach. DeepAge leverages a sequence-based approach with dilated convolutions to effectively capture long-range dependencies between CpG sites, addressing the limitations of prior models by incorporating advanced network architectures including residual connections and dropout regularization. The dual correlation feature selection enhances our model's predictive capabilities by identifying the most age-relevant CpG sites. Our model outperforms existing epigenetic clocks across multiple datasets, offering significant improvements in accuracy and providing deeper insights into the epigenetic determinants of aging. The proposed method not only sets a new standard in age estimation but also highlights the potential of deep learning in biologically relevant feature extraction and interpretation, contributing to the broader field of computational biology and precision medicine.

TNF-alpha gene promoter's hypomethylation mediates a pro-inflammatory phenotype in peripheral blood monocytes from apical periodontitis individuals.

Epigenetic regulation of the key inflammatory genes plays a crucial role in controlling monocyte/macrophage-mediated local and systemic responses to bacterial challenges. However, it has not been addressed in apical periodontitis (AP). We aimed to explore the methylation pattern of the TNF-α gene promoter and its association with the inflammatory phenotype of peripheral blood monocytes from individuals with AP and controls. A cross-sectional study was conducted, including otherwise healthy individuals with AP (n = 25) and controls (n = 29). Monocytes were isolated from the volunteer's blood samples using a Ficoll gradient followed by negative immunoselection. RNA and DNA were extracted. The DNA methylation profiles of the TNF-α gene promoter region were analyzed using bisulfite sequencing PCR. The mRNA expression levels of DNA methyltransferases 3a (DNMT3a) and Ten Eleven Translocation enzymes 1(TET1) were assessed by qPCR. A fraction of primary monocytes was also cultured for 24 h, and the supernatant was collected to measure cytokine levels through a Luminex assay. Generalized structural equation models (GSEM) evaluated the association between AP, DNA methylation, and TNF-α protein expression controlled for potential covariates. Models included the effect of the methylation of TNF-α gene promoter as a mediator of the association between AP and TNF-α protein expression levels. Monocytes from AP individuals exhibited a heightened secretion of TNF-α and IL-1β and hypomethylation of the TNF gene promoter (p < .05). AP diagnosis was associated with the TNF-α gene promoter´s hypomethylated profile and enhanced pro-inflammatory cytokine levels, while lower methylation of the gene promoter region and -163 CpG single site mediated TNF-α overexpression (p < .05). DNA hypomethylation at the TNF-α gene mediates a proinflammatory phenotype in monocytes from AP patients, supporting a role in the systemic response.

Validation and next-generation update of a DNA methylation-based recurrence predictor for meningioma: a multicenter prospective study.

We previously developed a DNA methylation-based risk predictor for meningioma, which has been used locally in a prospective fashion since its original publication. As a follow-up, we validate this model using a large prospective cohort and introduce a streamlined next-generation predictor compatible with newer methylation arrays. Genome-wide methylation profiles were generated with the Illumina EPICArray. The performance of our next-generation predictor was compared with our original model and standard-of-care 2021 WHO grade using time-dependent receiver operating characteristic curves. An nomogram was generated by incorporating our methylation predictor with WHO grade and extent of resection. A total of 1347 meningioma cases were utilized in the study, including 469 prospective cases from 3 institutions and an external cohort of 100 WHO grade 2 cases for model validation. Both the original and next-generation models significantly outperform 2021 WHO grade in predicting early postoperative recurrence. Dichotomizing patients into grade-specific risk subgroups was predictive of outcome within both WHO grades 1 and 2 tumours (p<0.05), while all WHO grade 3 tumours were considered high-risk. Multivariable Cox regression demonstrated benefit of adjuvant radiotherapy in high-risk cases specifically, reinforcing its informative role in clinical decision making. Finally, our next-generation predictor contains nearly 10-fold fewer features than the original model, allowing for targeted arrays. This next-generation DNA methylation-based meningioma outcome predictor significantly outperforms 2021 WHO grading in predicting time to recurrence. We make this available as a point-and-click tool which will improve prognostication, inform patient selection for RT, and allow for molecularly-stratified clinical trials.

Genome-wide DNA methylation profiling reveals a novel hypermethylated biomarker PRKCB in gastric cancer

Globally, gastric cancer (GC) ranks among the most prevalent forms of malignancy, posing a significant health burden. Epigenetic modifications, predominantly characterized by alterations in DNA methylation patterns, have been linked to a diverse array of neoplastic processes. Here, we undertake a comprehensive analysis of the DNA methylation signature in GC, with the aim to discover the potential diagnostic epigenetic biomarkers. Utilizing the Illumina 935 K BeadChip, we conducted a genome-wide exploration of DNA methylation patterns in four paired samples of GC tissues and adjacent non-cancerous counterparts. The bisulfite-pyrosequencing (n = 7) was employed to the quantification for methylated gene. The pubic databases including GWAS Catalog, TCGA and GEO were used. The immunohistochemistry and qRT-PCR analysis were performed. In contrast to adjacent tissues, GC tissues manifested pronounced hypermethylation patterns specifically within the promoter cytosine-phosphate-guanine (CpG) islands, indicating localized epigenetic alterations. DNA methylome analysis further revealed 4432 differentially-methylated probes (DMPs), with the gene PRKCB exhibited the most prominent average DNA methylation disparity (mean Δβ = 0.353). Pyrosequencing validation confirmed three DMPs within the PRKCB promoter (cg08406370, cg00735962, and cg18526361). Notably, the mean methylation levels of PRKCB were inversely correlated with mRNA expression levels in the GWAS Catalog. Furthermore, both mRNA and protein expression levels of PRKCB were significantly reduced in GCs when compared to their adjacent non-cancerous counterparts, verified by TCGA and GEO database. Our study reveals significant DNA methylation alterations in GC and emphasizes the pivotal role of PRKCB gene hypermethylation in conferring GC risk, which offers fresh perspectives for advancing diagnostic approaches and therapeutic strategies for GC.

Epigenetic Landscape of DNA Methylation in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, characterized by its aggressive progression and dismal prognosis. Advances in epigenetic profiling, specifically DNA methylation analysis, have significantly deepened our understanding of PDAC pathogenesis. This review synthesizes findings from recent genome-wide DNA methylation studies, which have delineated a complex DNA methylation landscape differentiating between normal and cancerous pancreatic tissues, as well as across various stages and molecular subtypes of PDAC. These studies identified specific differentially methylated regions (DMRs) that not only enhance our grasp of the epigenetic drivers of PDAC but also offer potential biomarkers for early diagnosis and prognosis, enabling the customization of therapeutic approaches. The review further explores how DNA methylation profiling could facilitate the development of subtype-tailored therapies, potentially improving treatment outcomes based on precise molecular characterizations. Overall, leveraging DNA methylation alterations as functional biomarkers holds promise for advancing our understanding of disease progression and refining PDAC management strategies, which could lead to improved patient outcomes and a deeper comprehension of the disease’s underlying biological mechanisms.

Epigenetic signatures of asthma: a comprehensive study of DNA methylation and clinical markers

BackgroundAsthma, a complex respiratory disease, presents with inflammatory symptoms in the lungs, blood, and other tissues. We investigated the relationship between DNA methylation and 35 clinical markers of asthma.MethodsThe Illumina Infinium EPIC v1 methylation array was used to evaluate 742,442 CpGs in whole blood from 319 participants from 94 families. They were part of the Netherlands Twin Register from families with at least one member suffering from severe asthma. Repeat blood samples were taken after 10 years from 182 individuals. Principal component analysis on the clinical asthma markers yielded ten principal components (PCs) that explained 92.8% of the total variance. We performed epigenome-wide association studies (EWAS) for each of the ten PCs correcting for familial structure and other covariates.Results221 unique CpGs reached genome-wide significance at timepoint 1 after Bonferroni correction. PC7, which correlated with loadings of eosinophil counts and immunoglobulin levels, accounted for the majority of associations (204). Enrichment analysis via the EWAS Atlas identified 190 of these CpGs to be previously identified in EWASs of asthma and asthma-related traits. Proximity assessment to previously identified SNPs associated with asthma identified 17 unique SNPs within 1 MB of two of the 221 CpGs. EWAS in 182 individuals with epigenetic data at a second timepoint identified 49 significant CpGs. EWAS Atlas enrichment analysis indicated that 4 of the 49 were previously associated with asthma or asthma-related traits. Comparing the estimates of all the significant associations identified across the two time points yielded a correlation of 0.81.ConclusionWe identified 270 unique CpGs that were associated with PC scores generated from 35 clinical markers of asthma, either cross-sectionally or 10 years later. A strong correlation was present between effect sizes at the 2 timepoints. Most associations were identified for PC7, which captured blood eosinophil counts and immunoglobulin levels and many of these CpGs have previous associations in earlier studies of asthma and asthma-related traits. The results point to a robust DNA methylation profile as a new, stable biomarker for asthma.

Superficial Neurocristic FET::ETS Fusion Tumor: Expanding the Clinicopathological and Molecular Genetic Spectrum of a Recently Described Entity

Superficial neurocristic EWSR1::FLI1 fusion tumor is a very recently described, clinically indolent tumor of the skin and superficial soft tissues, which differs in essentially all ways from Ewing sarcoma, despite harboring an identical fusion event. The EWSR1 and FLI1 genes are members of the FET and ETS gene family, respectively, and very rare examples of Ewing sarcoma harbor alternative FET::ETS fusion events, such as EWSR1::ERG, FUS::FLI1, FUS::ERG, EWSR1::ETV4 and others. We report 5 new cases of this very rare entity, harboring in 3 cases alternative FET::ETS fusion events. The tumors occurred in 2 males and 3 females (median age 14 years; range 8-69 years) and presented as solitary dermal/ subcutaneous masses of the thigh, foot, shoulder, arm and back (median size 1.8 cm; range: 1-2 cm). All patients underwent wide excisions; one received adjuvant chemotherapy. Clinical follow-up on 3 patients (median: 24 months; range: 18-31 months) showed all to be without disease. Morphologically, all tumors displayed typical features of this entity as described, with nests of cytologically bland, diffusely S100 protein/SOX10-positive round cells without mitotic activity, surrounded by fibrous bands containing spindled cells with similar nuclear features. The tumors also showed membranous CD99 (4/5) and nuclear NKX2.2 (3/3) expression. RNA sequencing (4 cases) demonstrated FUS::FLI1, FUS::ERG, EWSR1::FLI1, EWSR1::ERG, and a novel FUS::ETV5. Methylation profiling (4 cases) showed all to cluster with previously reported superficial neurocristic EWSR1::FLI1 fusion tumors and apart from conventional and “adamantinoma-like” Ewing sarcoma.Our findings confirm the distinctive clinicopathological features of this very rare, recently described entity and expand its molecular genetic spectrum. Reflecting these findings, we propose modifying the name of this entity to “superficial neurocristic FET::ETS fusion tumor”.

Genomes and epigenomes of matched normal and tumor breast tissue reveal diverse evolutionary trajectories and tumor-host interactions.

Normal tissues adjacent to the tumor (NATs) may harbor early breast carcinogenesis events driven by field cancerization. Although previous studies have characterized copy-number (CN) and transcriptomic alterations, the evolutionary history of NATs in breast cancer (BC) remains poorly characterized. Utilizing whole-genome sequencing (WGS), methylation profiling, and RNA sequencing (RNA-seq), we analyzed paired germline, NATs, and tumor samples from 43 individuals with BC in Hong Kong (HK). We found that single-nucleotide variants (SNVs) were common in NATs, with one-third of NAT samples exhibiting SNVs in driver genes, many of which were present in paired tumor samples. The most frequently mutated genes in both tumor and NAT samples were PIK3CA, TP53, GATA3, and AKT1. In contrast, large-scale aberrations such as somatic CN alterations (SCNAs) and structural variants (SVs) were rarely detected in NAT samples. We generated phylogenetic trees to investigate the evolutionary history of paired NAT and tumor samples. They could be categorized into tumor only, shared, and multiple-tree groups, the last of which is concordant with non-genetic field cancerization. These groups exhibited distinct genomic and epigenomic characteristics in both NAT and tumor samples.Specifically, NAT samples in the shared-tree group showed higher number of mutations, while NAT samples belonging to the multiple-tree group showed a less inflammatory tumor microenvironment (TME), characterized by a higher proportion ofregulatory Tcells (Tregs) and lower presence of CD14 cell populations. In summary, our findings highlight the diverse evolutionary history in BC NAT/tumor pairs and the impact of field cancerization and TME in shaping the genomic evolutionary historyof tumors.

Clinicopathological and epigenetic differences between primary neuroendocrine tumors and neuroendocrine metastases in the ovary.

Currently, the available literature provides insufficient support to differentiate between primary ovarian neuroendocrine tumors (PON) and neuroendocrine ovarian metastases (NOM) in patients. For this reason, patients with a well-differentiated ovarian neuroendocrine tumor (NET) were identified through electronic patient records and a nationwide search between 1991 and 2023. Clinical characteristics were collected from electronic patient files. This resulted in the inclusion of 71 patients with NOM and 17 patients with PON. Histologic material was stained for Ki67, SSTR2a, CDX2, PAX8, TTF1, SATB2, ISLET1, OTP, PDX1, and ARX. DNA methylation analysis was performed on a subset of cases. All PON were unilateral and nine were found within a teratoma (PON-T+). A total of 78% of NOM were bilateral, and none were associated with a teratoma. PON without teratomous components (PON-T-) displayed a similar insular growth pattern and immunohistochemistry as NOM (p > 0.05). When compared with PON-T+, PON-T- more frequently displayed ISLET1 positivity and were larger, and patients were older at diagnosis (p < 0.05). Unsupervised analysis of DNA methylation profiles from tumors of ovarian (n = 16), pancreatic (n = 22), ileal (n = 10), and rectal (n = 7) origin revealed that four of five PON-T- clustered together with NOM and ileal NET, whereas four of five PON-T+ grouped with rectum NET. In conclusion, unilateral ovarian NET within a teratoma should be treated as a PON. Ovarian NET localizations without teratomous components have a molecular profile analogous to midgut NET metastases. For these patients, a thorough review of imaging should be performed to identify a possible undetected midgut NET and a corresponding follow-up strategy may be recommended.

Comprehensive evaluation of the impact of whole-genome bisulfite sequencing (WGBS) on the fragmentomic characteristics of plasma cell-free DNA

BackgroundCell-free DNA (cfDNA) is non-randomly fragmented in human body fluids. Analyzing such fragmentation patterns of cfDNA holds great promise for liquid biopsy. Whole-genome bisulfite sequencing (WGBS) is widely used for cfDNA methylation profiling. However, its applicability for studying fragmentomic characteristics remains largely unexplored. MethodsWe performed paired WGBS and whole-genome sequencing (WGS) on 66 peripheral plasma samples from 58 pregnant women. Then, we systematically compared the fragmentation patterns of cell-free nuclear DNA and mitochondrial DNA (mtDNA) sequenced from these two approaches. Additionally, we evaluated the extent of the size shortening in fetal-derived cfDNA and estimated the fetal DNA fraction in maternal plasma using both sequencing methods. ResultsCompared to WGS samples, WGBS samples demonstrated a significantly lower genome coverage and higher GC content in cfDNA. They also showed a significant decrease in the size of cell-free nuclear DNA, along with alterations in the end motif pattern that were specifically associated with CpG and “CC” sites. While there was a slight shift in the inferred nucleosome footprint from cfDNA coverages in WGBS samples, the cfDNA coverage patterns in CTCF and TSS regions remained highly consistent between these two sequencing methods. Both methods accurately reflected gene expression levels through their TSS coverages. Additionally, WGBS samples exhibited an increased abundance and longer length of mtDNA in plasma. Furthermore, we observed the size shortening of fetal cfDNA in plasma consistently, with a highly correlated fetal DNA fraction inferred by cfDNA coverage between WGBS and WGS samples (r = 0.996). However, the estimated fetal cfDNA fraction in WGBS samples was approximately 7 % lower than in WGS samples. ConclusionsWe confirmed that WGBS can introduce artificial breakages to cfDNA, leading to altered fragmentomic patterns in both nuclear and mitochondrial DNA. However, WGBS cfDNA remains suitable for analyzing certain cfDNA fragmentomic characteristics, such as coverage in genome regulation regions and the essential characteristics of fetal DNA in maternal plasma.

Methyl Donor Micronutrients Orchestrate Lipid Metabolism: The Role of DNA Methylation Modification

DNA methylation, a key epigenetic modification, plays a crucial role in regulating lipid metabolism. Consistent correlations have been observed between aberrant DNA methylation patterns and lipid metabolic disorders. Emerging evidence indicates that methyl donor micronutrients could influence DNA methylation patterns, consequently exerting an influence on lipid metabolism. Specifically, the deficiency or excesses of methyl donor micronutrients (folate, choline, betaine, B vitamins and methionine) have been associated with altered DNA methylation patterns linked to lipid metabolism. These alteration in DNA methylation levels, occurring globally and within promoter regions, could affect gene expression related to lipid metabolism. However, the mechanisms through which methyl donor micronutrients regulate lipid metabolism via the DNA methylation modification and the role of methyl donor micronutrients supplementation on DNA methylation profiles remain unclear. In this review, we summarized the regulatory role of DNA methylation in lipid metabolism, and highlighted recent findings investigating the impact of methyl donor micronutrients on lipid metabolism, as well as DNA methylation-mediated adipogenesis and adipose deposition. Taken together, this review deepened our understanding of how the complex interplay between methyl donor micronutrients, DNA methylation, and lipid metabolism, and provides valuable information for accurately regulating lipid metabolism of livestock and poultry, thereby improving meat quality, and promoting the development of animal husbandry.

DNA Methylation Classes of Stage II and III Primary Melanomas and Their Clinical and Prognostic Significance.

Patients with stage II and III cutaneous primary melanoma vary considerably in their risk of melanoma-related death. We explore the ability of methylation profiling to distinguish primary melanoma methylation classes and their associations with clinicopathologic characteristics and survival. InterMEL is a retrospective case-control study that assembled primary cutaneous melanomas from American Joint Committee on Cancer (AJCC) 8th edition stage II and III patients diagnosed between 1998 and 2015 in the United States and Australia. Cases are patients who died of melanoma within 5 years from original diagnosis. Controls survived longer than 5 years without evidence of melanoma recurrence or relapse. Methylation classes, distinguished by consensus clustering of 850K methylation data, were evaluated for their clinicopathologic characteristics, 5-year survival status, and differentially methylated gene sets. Among 422 InterMEL melanomas, consensus clustering revealed three primary melanoma methylation classes (MethylClasses): a CpG island methylator phenotype (CIMP) class, an intermediate methylation (IM) class, and a low methylation (LM) class. CIMP and IM were associated with higher AJCC stage (both P = .002), Breslow thickness (CIMP P = .002; IM P = .006), and mitotic index (both P < .001) compared with LM, while IM had higher N stage than CIMP (P = .01) and LM (P = .007). CIMP and IM had a 2-fold higher likelihood of 5-year death from melanoma than LM (CIMP odds ratio [OR], 2.16 [95% CI, 1.18 to 3.96]; IM OR, 2.00 [95% CI, 1.12 to 3.58]) in a multivariable model adjusted for age, sex, log Breslow thickness, ulceration, mitotic index, and N stage. Despite more extensive CpG island hypermethylation in CIMP, CIMP and IM shared similar patterns of differential methylation and gene set enrichment compared with LM. Melanoma MethylClasses may provide clinical value in predicting 5-year death from melanoma among patients with primary melanoma independent of other clinicopathologic factors.

Deconvoluted methylation profiles discriminate between closely related melanocytic nevi

Deconvoluted methylation profiles discriminate between closely related melanocytic nevi

Severe traumatic injury is associated with profound changes in DNA methylation

Whether DNA methylation changes follow human physical trauma is uncertain. We aimed to investigate if severe trauma was associated with DNA methylation changes. In a prospective, observational, clinical study, we included severely injured adults and adults undergoing elective surgery (controls). Blood was obtained from trauma patients (n = 60) immediately- and 30-45 days post-trauma, and from surgical patients (n = 57) pre-, post-, and 30-45 days post-surgery. Epigenome-wide DNA methylation profiling was performed and analyzed for significant differentially methylated CpGs and -regions (DMRs) within and between groups. Within the trauma group we identified 10,126 significant differentially methylated CpGs and 1169 DMRs. No significant differential methylation was found in the surgical group. In the trauma group, differentially methylated sites were enriched in genes and pathways involved in blood coagulation and inflammatory response. Severe trauma was associated with profound alterations in the DNA methylome of circulating leucocytes, and differential methylation was located in trauma-relevant genes.

Resolution of ring chromosomes, Robertsonian translocations, and complex structural variants from long-read sequencing and telomere-to-telomere assembly.

Delineation of structural variants (SVs) at sequence resolution in highly repetitive genomic regions has long been intractable. The sequence properties, origins, and functional effects of classes of genomic rearrangements such as ring chromosomes and Robertsonian translocations thus remain unknown. To resolve these complex structures, we leveraged several recent milestones in the field, including (1) the emergence of long-read sequencing, (2) the gapless telomere-to-telomere (T2T) assembly, and (3) a tool (BigClipper) to discover chromosomal rearrangements from long reads. We applied these technologies across 13 cases with ring chromosomes, Robertsonian translocations, and complex SVs that were unresolved by short reads, followed by validation using optical genome mapping (OGM). Our analyses resolved 10 of 13 cases, including a Robertsonian translocation and all ring chromosomes. Multiple breakpoints were localized to genomic regions previously recalcitrant to sequencing such as acrocentric p-arms, ribosomal DNA arrays, and telomeric repeats, and involved complex structures such as a deletion-inversion and interchromosomal dispersed duplications. We further performed methylation profiling from long-read data to discover phased differential methylation in a gene promoter proximal to a ring fusion, suggesting a long-range position effect (LRPE) with heterochromatin spreading. Breakpoint sequences suggested mechanisms of SV formation such as microhomology-mediated and non-homologous end-joining, as well as non-allelic homologous recombination. These methods provide some of the first glimpses into the sequence resolution of Robertsonian translocations and illuminate the structural diversity of ring chromosomes and complex chromosomal rearrangements with implications for genome biology, prediction of LRPEs from integrated multi-omics technologies, and molecular diagnostics in rare disease cases.

Enhancing the differential diagnosis of small pulmonary nodules: a comprehensive model integrating plasma methylation, protein biomarkers, and LDCT imaging features

BackgroundAccurate differentiation between malignant and benign pulmonary nodules, especially those measuring 5–10 mm in diameter, continues to pose a significant diagnostic challenge. This study introduces a novel, precise approach by integrating circulating cell-free DNA (cfDNA) methylation patterns, protein profiling, and computed tomography (CT) imaging features to enhance the classification of pulmonary nodules.MethodsBlood samples were collected from 419 participants diagnosed with pulmonary nodules ranging from 5 to 30 mm in size, before any disease-altering procedures such as treatment or surgical intervention. High-throughput bisulfite sequencing was used to conduct DNA methylation profiling, while protein profiling was performed utilizing the Olink proximity extension assay. The dataset was divided into a training set and an independent test set. The training set included 162 matched cases of benign and malignant nodules, balanced for sex and age. In contrast, the test set consisted of 46 benign and 49 malignant nodules. By effectively integrating both molecular (DNA methylation and protein profiling) and CT imaging parameters, a sophisticated deep learning-based classifier was developed to accurately distinguish between benign and malignant pulmonary nodules.ResultsOur results demonstrate that the integrated model is both accurate and robust in distinguishing between benign and malignant pulmonary nodules. It achieved an AUC score 0.925 (sensitivity = 83.7%, specificity = 82.6%) in classifying test set. The performance of the integrated model was significantly higher than that of individual methylation (AUC = 0.799, P = 0.004), protein (AUC = 0.846, P = 0.009), and imaging models (AUC = 0.866, P = 0.01). Importantly, the integrated model achieved a higher AUC of 0.951 (sensitivity = 83.9%, specificity = 89.7%) in 5–10 mm small nodules. These results collectively confirm the accuracy and robustness of our model in detecting malignant nodules from benign ones.ConclusionsOur study presents a promising noninvasive approach to distinguish the malignancy of pulmonary nodules using multiple molecular and imaging features, which has the potential to assist in clinical decision-making.Trial registration: This study was registered on ClinicalTrials.gov on 01/01/2020 (NCT05432128). https://classic.clinicaltrials.gov/ct2/show/NCT05432128.

Epigenetic insights into creep-feeding: methylation profiling of Longissimus thoracis muscle at weaning in crossbred cattle

IntroductionThis study investigated the impact of creep-feeding supplementation on the genome methylation of the Longissimus thoracis (LT) muscle in crossbred beef cattle (Bos taurus × Bos indicus).MethodsThe experiment involved 48 uncastrated F1 Angus-Nellore males (half-siblings), which were divided into two groups: NCF – no creep-feeding (n = 24) and CF – creep-feeding (n = 24). After weaning at 210 days, all animals were feedlot finished for 180 days under identical conditions. LT muscle biopsies were collected at weaning for genomic DNA methylation analysis by reduced representation bisulfite sequencing (RRBS).Results and discussionThe groups differed significantly (CF &amp;gt; NCF: p &amp;lt; 0.05) to weaning weight (243.57±5.70 vs. 228.92±5.07kg), backfat thickness (12.96±0.86 vs. 10.61±0.42mm), LT muscle marbling score (366.11±12.39 vs. 321.50±13.65), and LT intramuscular fat content (5.80±0.23 vs. 4.95±0.20%). The weights at the beginning of the experiment and at slaughter (390 days) did not differ significantly. Mean methylation levels were higher in CF with 0.18% more CpG, 0.04% CHG, and 0.03% CHH. We identified 974 regions with differential methylation (DMRs: &amp;gt; 25% and q &amp;lt; 0.05), which overlapped with 241 differentially methylated genes (DMGs). Among these genes, 108 were hypermethylated and 133 were hypomethylated in CF group. Notably, 39 of these DMGs were previously identified as differentially expressed genes (DEGs: log2 fold change [0.5]) in the same animal groups. Over-representation analysis highlighted epigenetic regulations related to muscle growth, PPAR signaling, adipogenesis, insulin response, and lipid metabolism. Key DMGs/DEGs included: ACAA1, SORBS1, SMAD3, TRIM63, PRKCA, DNMT3A, RUNX1, NRG3, and SLC2A8. These epigenetic changes improved the performance of supplemented animals up to weaning and enhanced meat quality traits, particularly higher intramuscular fat. The results provided insights into the intricate interplay between nutrition, epigenetics, gene expression and phenotypes in beef cattle production.

Single-nucleus RNA-seq dissection of choroid plexus tumor cell heterogeneity.

The genomic, genetic and cellular events regulating the onset, growth and survival of rare, choroid plexus neoplasms remain poorly understood. Here, we examine the heterogeneity of human choroid plexus tumors by single-nucleus transcriptome analysis of 23,906 cells from four disease-free choroid plexus and eleven choroid plexus tumors. The resulting expression atlas profiles cellular and transcriptional diversity, copy number alterations, and cell-cell interaction networks in normal and cancerous choroid plexus. In choroid plexus tumor epithelial cells, we observe transcriptional changes that correlate with genome-wide methylation profiles. We further characterize tumor type-specific stromal microenvironments that include altered macrophage and mesenchymal cell states, as well as changes in extracellular matrix components. This first single-cell dataset resource from such scarce samples should be valuable for divising therapies against these little-studied neoplasms.