Methylome Profiling Research Articles

Decoding molecular programs in melanoma brain metastases

Melanoma brain metastases (MBM) variably respond to therapeutic interventions; thus determining patient’s prognosis. However, the mechanisms that govern therapy response are poorly understood. Here, we use a multi-OMICS approach and targeted sequencing (TargetSeq) to unravel the programs that potentially control the development of progressive intracranial disease. Molecularly, the expression of E-cadherin (Ecad) or NGFR, the BRAF mutation state and level of immune cell infiltration subdivides tumors into proliferative/pigmented and invasive/stem-like/therapy-resistant irrespective of the intracranial location. The analysis of MAPK inhibitor-naive and refractory MBM reveals switching from Ecad-associated into NGFR-associated programs during progression. NGFR-associated programs control cell migration and proliferation via downstream transcription factors such as SOX4. Moreover, global methylome profiling uncovers 46 differentially methylated regions that discriminate BRAFmut and wildtype MBM. In summary, we propose that the expression of Ecad and NGFR sub- classifies MBM and suggest that the Ecad-to-NGFR phenotype switch is a rate-limiting process which potentially indicates drug-response and intracranial progression states in melanoma patients.

Integrating High-Throughput Dynamic BH3 Profiling and Molecular Phenotyping to Identify Therapeutic Vulnerabilities in CLL

Despite recent advances in chronic lymphocytic leukemia (CLL) therapy, such as the use of targeted agents including, Bruton's tyrosine kinase (BTK) inhibitor ibrutinib and the potent BCL-2 antagonist venetoclax, this disease remains incurable for most patients, who are refractory or become resistant to the novel agents. Thus, identifying new treatment regimens for CLL and building a precision medicine framework that can match CLL patients to the appropriate drugs are of high priority. To address this challenge, we optimized high-throughput dynamic BH3 profiling (HT-DBP), a functional assay that rapidly measures the initiation of apoptotic signaling after ex vivo exposure to drugs, for interrogation of CLL samples. The main advantages of this assay over other ex vivo assays are: (i) rapidity - under 24 hours, which is especially important in CLL, where cell viability substantially decreases after 24 hours; (ii) miniaturization - a very limited number of primary cells are required; and (iii) scalability - allowing to conduct hundreds of drug response tests in parallel on one 384-well plate. These features collectively maximize the information yield from a given patient sample. We recently identified prognostic genetic alterations and molecular subtypes of CLL, based on multi-omics profiling of >1100 CLL samples (Knisbacher et al., Nat Genet, in press). To determine if these molecular findings were associated with novel therapeutic vulnerabilities in CLL, we performed HT-DBP on 65 primary CLL samples previously characterized by exome, transcriptome and methylome profiling, using 42 FDA approved drugs that were selected for potential relevance to CLL biology. We isolated peripheral blood mononuclear cells (PBMCs) and cultured them in conditioned media derived from stroma cells to reduce spontaneous apoptosis. Target cells were treated with a drug for 20 hours followed by BH3 peptide exposure. Mitochondrial outer membrane permeabilization (MOMP) was then measured on digitonin-permeabilized cells in response to BH3-only synthetic peptides that mimic pro-apoptotic BCL-2 family proteins. Mitochondrial cytochrome c release was quantified as a measure of MOMP by flow cytometry, gating on CD19+ and CD5+ cells. This assay measures if the cell has moved closer to the threshold of apoptosis after drug treatment and thereby identifies drugs that enhance apoptosis priming. The peptides used in each experiment were derived from BIM or PUMA to measure increases in overall apoptotic priming, or BAD and MS1 peptides that identified BCL-2 and MCL-1 dependence, respectively. Our screen revealed differential drug-induced apoptotic priming for various drugs. As expected, venetoclax and ibrutinib were highly effective across CLL. Other drugs that demonstrated high priming included navitoclax (BCL-XL/BCL-2), nutlin-3 (MDM2), abexinostat (HDAC), gandotinib (JAK2), duvelisib (PI3K δ/γ), idelalisib (PI3Kδ) and cerdulatinib (SYK/JAK). The assay was robust, as indicated by an 0.92 median Pearson correlation across replicates. Additionally, the majority of drugs had greater effect on CLL samples than on healthy PBMCs (p<0.001, paired t-test), supporting their specificity. We focused our analysis on the differential drug effects among molecular subtypes of CLL. First, we found that IGHV-mutated CLLs (M-CLLs) became more primed to apoptosis than IGHV-unmutated CLLs (U-CLLs) across the panel of drugs (p<0.001, paired t-test) and significantly in response to fludarabine and umbralisib (FDR<0.1, t-test). Second, we compared drug-induced apoptotic priming among 8 CLL subtypes (i.e. RNA expression clusters (ECs); Knisbacher et al.). Notable among the many drug priming-EC relationships was that within M-CLL ECs, venetoclax was most effective in EC-m3 (high IL-10 expression) and least effective in EC-m2 (low IL-10 and enriched in trisomy 12). Interestingly, EC-m1, associated with high TFEC expression and poor outcome, was most sensitive to nutlin-3. For U-CLLs, EC-u1 was most sensitive to gandotinib and EC-u2 to navitoclax. EC-i, associated with the intermediate methylation subtype of CLL, was the most resistant EC to ibrutinib but was very sensitive to navitoclax, more than to any other drug. Altogether, we present a framework that links ex-vivo drug response with molecular features including expression subtypes to highlight new therapeutic opportunities in CLL.

Metformin Treatment Abrogates the Competitive Advantage of Dnmt3a R878H HSPCs By Enhancing DNA Methylation Activity

Clonal hematopoiesis of indeterminate potential (CHIP) refers to the clonal expansion of hematopoietic stem and progenitor cells (HSPCs) carrying leukemogenic mutations in individuals without evidence of a blood disorder. CHIP carriers are at an increased risk of blood cancers and cardiovascular diseases. Targeting the clonal expansion of mutant HSPCs has the potential to mitigate CHIP-related illnesses. The most commonly mutated gene in CHIP is DNMT3A, which encodes an enzyme that catalyzes the methyl transfer from S-adenosylmethionine (SAM) to cytosines in DNA. The heterozygous DNMT3A hotspot mutation at R882 exerts a dominant negative effect on the wild-type (WT) allele, resulting in decreased DNA methylation activity. Prior studies have shown that murine HSPCs carrying mutant Dnmt3a R878H (equivalent to R882 in humans) have an advantage over WT cells in competition assays. Here, we aimed to first identify differences in the functional properties between Dnmt3a-mutated and WT HSPCs. Given the crosstalk between mitochondrial metabolism and DNA methylation, we investigated potential differences in mitochondrial activity and found that the level of mitochondrial respiration was higher in Dnmt3aR878H/+ HSPCs than in WT cells. To determine if this translated to differential dependencies, we silenced the expression of critical subunits in the each of five electron transport chain (ETC) complexes. Knockdown of NDUFV1 in Complex I was the most effective in reducing the competitive advantage of Dnmt3aR878H/+ cells in vitro. To explore translational relevance of this finding, we tested the impact of metformin, a pharmacologic inhibitor of Complex I, on Dnmt3a-mutated HSPCs. Treatment with metformin at clinically relevant concentrations suppressed the competitive advantage of mutant cells in vitro. Importantly, this effect was rescued by expression of NDI1, a metformin-resistant yeast analog of Complex I. To extend these findings, we conducted a competitive repopulation assay between CD45.2+ Dnmt3aR878H/+ and CD45.1+ Dnmt3a+/+ HSPCs. Metformin treatment abrogated the in vivo competitive advantage of mutant cells over an 8-month period based on peripheral blood chimerism. To decipher the mechanism of action, we performed transcriptome and metabolome profiling of mutant HSPCs treated with or without metformin for 1 month. GSEA analysis of the transcriptome data revealed a downregulation of genes associated with stemness in metformin-treated cells. Intriguingly, we found that metformin increased the expression of genes involved in one-carbon metabolism, which generates SAM. Consistent with these findings, metabolomics analysis showed that the levels of several key metabolites in one-carbon metabolism, including SAM, were higher in metformin-treated cells compared with controls. Genetic and pharmacologic inhibition of serine hydroxymethyltransferase 2 (SHMT2), a key enzyme in one-carbon metabolism, as well as the addition of exogeneous S-adenosylhomocysteine (SAH), an inhibitor of SAM-dependent methyltransferases, effectively rescued the effect of metformin on mutant cells in vitro. Based on the above findings, we hypothesized that metformin treatment might enhance the residual DNA methylation activity found in Dnmt3aR878H/+ mutated cells by increasing SAM concentration. In support of this hypothesis, we found that exogeneous SAM reproduced the effect of metformin, and HSPCs with homozygous Dnmt3aR878H mutations were insensitive to metformin. Furthermore, we performed DNA methylome profiling of untreated and metformin-treated mutant and WT HSPCs using RRBS. This analysis revealed that the hypomethylated regions (HMRs) in untreated Dnmt3aR878H/+ HSPCs relative to WT controls were enriched for regions of repressed chromatin with H3K27 methylation. Importantly, metformin treatment increased the level of DNA methylation at these regions in mutated HSPCs. In summary, our findings demonstrate that Dnmt3aR878H/+ HSPCs depend on ETC activity and particularly complex I activity to maintain their competitive advantage over WT cells. We propose a model in which inhibition of complex I activity with metformin increases one-carbon metabolism and SAM level, thereby restoring DNA methylation at HMRs and the differentiation of mutant HSPCs. Our findings have important implications for the development of preventive interventions against DNMT3A-mutated CHIP.

Chromatin Accessibility Landscapes of B-Cell Acute Lymphoblastic Leukemia Identify Extensive Epigenomic Reprogramming and Heterogeneity Among Subtypes

Acute lymphoblastic leukemia (ALL) is the most common malignancy in pediatric patients and represents about a quarter of all pediatric malignancies. Past work has characterized B-cell lineage ALL (B-ALL) into molecular subtypes spanning a range of aberrant chromosomal rearrangements and oncogene chimeric fusions driving malignancy. While transcriptional and DNA methylome profiling of these subtypes has been extensively examined, the accompanying chromatin landscape and corresponding gene regulatory repertoire are not well characterized for many B-ALL subtypes. To better profile the B-ALL epigenome and gene regulatory networks we examined chromatin accessibility of 11 distinct molecular subtypes (BCR-ABL1, DUX4/ERG, ETV6-RUNX1, Hyperdiploid, Low hypodiploid, KMT2A-rearranged, Ph-like, PAX5-altered, TCF3-PBX1, ZNF384-rearranged and B-other) using 154 primary patient samples from across the United States with assay for transposase-accessible chromatin and high-throughput sequencing (ATAC-seq). We mapped extensive chromatin reprogramming when comparing B-ALL and normal B-cells that drive oncogenic signaling pathways and inhibit normal B-cell functions. Strikingly, we also uncovered chromatin accessibility sites in B-ALL (42,457 sites) with distinct subtype-specific enrichment. A classification model utilizing subtype distinct loci was able to accurately predict B-ALL subtypes with 87% cross-validation accuracy. Transcription factor (TF) footprint profiling and transcriptomic information further identified candidate subtype-enriched TFs, such as DUX4, ZNF384, HOXA9, MEIS1, GATA3 and RARA, along with subtype distinct gene regulatory networks. In connecting these findings with genetic variation, we identified 9080 inherited DNA sequence variants that act as ATAC-seq chromatin accessibility quantitative trait loci (ATAC-QTLs) and contribute to variability in chromatin accessibility among patient samples. Nearly one-third of ATAC-QTLs map to TF footprints and commonly altered DNA consensus motifs impacting chromatin accessibility include ETS family TFs (PU.1, SPI-B, ELF3, EHF), ZNF family (ZNF263, ZNF460) and CTCF. Collectively, using the largest B-ALL chromatin accessibility dataset to date, our investigation offers a unique window into the gene regulatory landscape that highlights the complexity and heterogeneity of chromatin accessibility among B-ALL molecular subtypes.

CNSC-20. PROTEOMIC ANALYSIS OF GLIOMA BIOPSIES SHOWS CONSISTENCY WITH GLIOMA GRADING

Abstract BACKGROUND Glioma are currently classified according to integrated histopathologic and molecular genetic (WHO 2021 classification) as well as methylomic criteria (Capper 2018). However, little is known about proteomic profiling of these subgroups , which may reveal specific biomarkers and pathways potentially activated or inactivated. Material and METHODS Eighty-six glioma biopsy samples were prospectively collected from patients undergoing surgery at the University Hospital of Basel between 2017 and 2019. Samples were classified into seven distinct glioma subgroups based on integrated WHO 2016 and methylome profiling criteria. Proteins were extracted from fresh frozen samples devoid of necrosis/haemorrhage and processed for mass spectrometry analysis. RESULTS For each tumour sample, a total of 8’855 proteins were identified and quantified. 950 proteins were differentially expressed between at least two glioma subgroups. Strikingly, most significant differences in expression are related to tumor grading rather than to glioma subgroups. Proteins SSDH and GABT, involved in Gamma-aminobutyric acid (GABA) catabolism, show the strongest increase between low grade glioma (LGG) and high grade glioma (HGG), whereas S10AA and ANXA2, part of pathways involved in coagulation, cell adhesion and immune response, appear increased in HGG. CONCLUSION Tumor grading turns out to be dominant over genetic and epigenetic criteria for proteomic classification. Most significant protein level variations may represent potential glioma grade-specific therapeutic targets.

A method for early diagnosis of lung cancer from tumor originated DNA fragments using plasma cfDNA methylome and fragmentome profiles

Early detection is critical for minimizing mortality from cancer. Plasma cell-free DNA (cfDNA) contains the signatures of tumor DNA, allowing us to quantify the signature and diagnose early-stage tumors. Here, we report a novel tumor fragment quantification method, TOF (Tumor Originated Fragment) for the diagnosis of lung cancer by quantifying and analyzing both the plasma cfDNA methylation patterns and fragmentomic signatures. TOF utilizes the amount of ctDNA predicted from the methylation density information of each cfDNA read mapped on 6243 lung-tumor-specific CpG markers. The 6243 tumor-specific markers were derived from lung tumor tissues by comparing them with corresponding normal tissues and healthy blood from public methylation data. TOF also utilizes two cfDNA fragmentomic signatures: 1) the short fragment ratio, and 2) the 5′ end-motif profile. We used 298 plasma samples to analyze cfDNA signatures using enzymatic methyl-sequencing data from 201 lung cancer patients and 97 healthy controls. The TOF score showed 0.98 of the area under the curve in correctly classifying lung cancer from normal samples. The TOF score resolution was high enough to clearly differentiate even the early-stage non-small cell lung cancer patients from the healthy controls. The same was true for small cell lung cancer patients.

Whole blood methylome-derived features to discriminate endocrine hypertension

BackgroundArterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches.ResultsUnsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods—Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine—predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL.ConclusionsThe blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

Methylome Profiling of PD-L1-Expressing Glioblastomas Shows Enrichment of Post-Transcriptional and RNA-Associated Gene Regulation.

Glioblastomas are the most frequent primary brain tumors in adults. They show highly malignant behavior and devastating outcomes. Since there are still no targeted therapies available, median survival remains in the range of 12 to 15 months for glioblastoma patients. Programmed Cell Death Ligand 1 (PD-L1) is a promising novel candidate in precision medicine. Here, we performed integrated epigenome-wide methylation profiling of 866,895 methylation-specific sites in 20 glioblastoma samples comparing PD-L1 high- (i.e., TPS (tumor proportion score) &gt; 30%) and PD-L1 low-expressing glioblastomas (i.e., TPS &lt; 10%). We found 12,597 significantly differentially methylated CpGs (DMCG) (Δβ ≥ 0.1 and p-value &lt; 0.05) in PD-L1 high- compared with PD-L1 low-expressing glioblastomas. These DMCGs were annotated to 2546 tiling regions, 139 promoters, 107 genes, and 107 CpG islands. PD-L1 high-expressing glioblastomas showed hypomethylation in 68% of all DMCGs. Interestingly, the list of the top 100 significantly differentially methylated genes showed the enrichment of regulatory RNAs with 19 DMCGs in miRNA, snoRNAs, lincRNAs, and asRNAs. Gene Ontology analysis showed the enrichment of post-transcriptional and RNA-associated pathways in the hypermethylated gene regions. In summary, dissecting the methylomes depending on PD-L1 status revealed significant alterations in RNA regulation and novel molecular targets in glioblastomas.

In vitro transdifferentiated signatures of goat preadipocytes into mammary epithelial cells revealed by DNA methylation and transcriptome profiling

During mammary development, the transdifferentiation of mammary preadipocytes is one of the important sources for lactating mammary epithelial cells (MECs). However, there is limited knowledge about the mechanisms of dynamic regulation of transcriptome and genome-wide DNA methylation in the preadipocyte transdifferentiation process. Here, to gain more insight into these mechanisms, preadipocytes were isolated from adipose tissues from around the goat mammary gland (GM-preadipocytes). The GM-preadipocytes were cultured on Matrigel in conditioned media made from goat MECs to induce GM-preadipocyte-to-MEC transdifferentiation. The transdifferentiated GM-preadipocytes showed high abundance of keratin 18, which is a marker protein of MECs, and formed mammary acinar-like structures after 8days of induction. Then, we performed transcriptome and DNA methylome profiling of the GM-preadipocytes and transdifferentiated GM-preadipocytes, respectively, and the differentially expressed genes and differentially methylated genes that play underlying roles in the process of transdifferentiation were obtained. Subsequently, we identified the candidate transcription factors in regulating the GM-preadipocyte-to-MEC transdifferentiation by transcription factor-binding motif enrichment analysis of differentially expressed genes and differentially methylated genes. Meanwhile, the secretory proteome of GM-preadipocytes cultured in conditioned media was also detected. By integrating the transcriptome, DNA methylome, and proteome, three candidate genes, four proteins, and several epigenetic regulatory axes were further identified, which are involved in regulation of the cell cycle, cell polarity establishment, cell adhesion, cell reprogramming, and adipocyte plasticity. These findings provide novel insights into the molecular mechanism of preadipocyte transdifferentiation and mammary development.

Methylome Profiling in Fabry Disease in Clinical Practice: A Proof of Concept.

Anderson–Fabry disease (FD) is an X-linked disease caused by a functional deficit of the α-galactosidase A enzyme. FD diagnosis relies on the clinical manifestations and research of GLA gene mutations. However, because of the lack of a clear genotype/phenotype correlation, FD diagnosis can be challenging. Recently, several studies have highlighted the importance of investigating DNA methylation patterns for confirming the correct diagnosis of different rare Mendelian diseases, but to date, no such studies have been reported for FD. Thus, in the present investigation, we analyzed for the first time the genome-wide methylation profile of a well-characterized cohort of patients with Fabry disease. We profiled the methylation status of about 850,000 CpG sites in 5 FD patients, all carrying the same mutation in the GLA gene (exon 6 c.901C>G) and presenting comparable low levels of α-Gal A activity. We found that, although the whole methylome profile did not discriminate the FD group from the unaffected one, several genes were significantly differentially methylated in Fabry patients. Thus, we provide here a proof of concept, to be tested in patients with different mutations and in a larger cohort, that the methylation state of specific genes can potentially identify Fabry patients and possibly predict organ involvement and disease evolution.

Dynamic Epigenetic Changes during a Relapse and Recovery Cycle in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex disease with variable severity. Patients experience frequent relapses where symptoms increase in severity, leaving them with a marked reduction in quality of life. Previous work has investigated molecular differences between ME/CFS patients and healthy controls, but not the dynamic changes specific to each individual patient. We applied precision medicine here to map genomic changes in two selected ME/CFS patients through a period that contained a relapse recovery cycle. DNA was isolated from two patients and a healthy age/gender matched control at regular intervals and captured the patient relapse in each case. Reduced representation DNA methylation sequencing profiles were obtained spanning the relapse recovery cycle. Both patients showed a significantly larger methylome variability (10–20-fold) through the period of sampling compared with the control. During the relapse, changes in the methylome profiles of the two patients were detected in regulatory-active regions of the genome that were associated, respectively, with 157 and 127 downstream genes, indicating disturbed metabolic, immune and inflammatory functions. Severe health relapses in the ME/CFS patients resulted in functionally important changes in their DNA methylomes that, while differing between the two patients, led to very similar compromised physiology. DNA methylation as a signature of disease variability in ongoing ME/CFS may have practical applications for strategies to decrease relapse frequency.

Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer

Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA methylome (with > 12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our approach to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, allowing us to learn new features and expand to other cancer types as training cohorts grow.

Genome-wide comparison of DNA methylation patterns between yak and three cattle strains and their potential association with mRNA transcription.

Yak has evolved specific adaptative mechanisms to high-altitude environment. Up to date, only a few studies reported the DNA methylation in yak. In the present study, genome-wide DNA methylome and transcriptome profiles in lung, mammary, and biceps brachii muscle tissues were compared between yak and three cattle breeds (Tibetan cattle, Sanjiang cattle, and Holstein cattle). The association between differentially expressed genes (DEGs) and differentially methylated regions (DMRs) was analyzed, and the biological functions of DEGs potentially driven by DMRs were explored by KEGG enrichment analysis. Finally, we found that yak-specific DMRs-driven DEGs were mainly involved in neuromodulation, respiration, lung development, blood pressure regulation, cardiovascular protection, energy metabolism, DNA repair, and immune functions. The higher levels of the key genes associated with these functions were observed in yak than in cattle, suggesting that DNA methylation might regulate these genes. Overall, the present study contributes basic data at the DNA methylation level to further understand the physiological metabolism in yak.

Transcriptome-Wide m6A Methylome Profiling in Sorghum following GA3 Treatment under Salt Stress.

Sorghum (“Jitian 3”) is a salt-tolerant seed cultivar used regularly in marginal lands, such as those with saline soils. Herein, we examined the potential of employing gibberellic acid (GA3) as an inducer of sorghum development during salt stress. Thus far, there have been no reports on the signaling network involved in the GA3-mediated regulation of sorghum development. In this study, we demonstrated that the stimulating properties of 50 mg/L GA3 on sorghum development was far superior to other GA3 concentrations under a 150 mM NaCl salinity condition. Furthermore, using methylated RNA immunoprecipitation sequencing (MeRIP-seq), we established an m6A methylation (m6A-M) profile in sorghum following exposure to 50 mg/L GA3. Overall, 23,363 m6A peaks and 16,200 m6A genes were screened among the GA3-treated and control leaves. These identified peaks were shown to be primarily enriched in the coding, as were the 3′- and 5′-untranslated regions. In addition, we employed m6A and transcript expression cross-analysis to identify 70 genes with differential transcript expression and simultaneous m6A-M. Intriguingly, the principal gene, LOC8066282, which is associated with LOC8084853, was shown to be intricately linked to the phosphatidylinositol signaling, which in turn regulates sorghum development and response to salt stress. This investigation presents a novel RNA m6A-M profile in sorghum, which may facilitate new insights into the underlying signaling behind salt stress resistance. This work will also benefit future investigations on foreign GA3 administration of sorghum.

Comparative Methylome Analysis Reveals Epigenetic Signatures Associated with Growth and Shell Color in the Pacific Oyster, Crassostrea gigas.

Fast growth is one of the most important breeding goals for all economic species such as the Pacific oyster (Crassostrea gigas), an aquaculture mollusk with top global production. Although the genetic basis and molecular mechanisms of growth-related traits have been widely investigated in the oyster, the role of DNA methylation involved in growth regulation remains largely unexplored. In this study, we performed a comparative DNA methylome analysis of two selectively bred C. gigas strains with contrasted phenotypes in growth and shell color based on whole-genome bisulfite sequencing (WGBS). Genome-wide profiling of DNA methylation at the single-base resolution revealed that DNA methylations were widely spread across the genome with obvious hotspots, coinciding with the distribution of genes and repetitive elements. Higher methylation levels were observed within genic regions compared with intergenic and promoter regions. Comparative analysis of DNA methylation allowed the identification of 339,604 differentially methylated CpG sites (DMCs) clustering in 27,600 differentially methylated regions (DMRs). Functional annotation analysis identified 11,033 genes from DMRs which were enriched in biological processes including cytoskeleton system, cell cycle, signal transduction, and protein biosynthesis. Integrative analysis of methylome and transcriptome profiles revealed a positive correlation between gene expression and DNA methylation within gene-body regions. Protein-protein interaction (PPI) analysis of differentially expressed and methylated genes allowed for the identification of integrin beta-6 (homolog of human ITGB3) as a hub modulator of the PI3K/Akt signaling pathway that was involved in various growth-related processes. This work provided insights into epigenetic regulation of growth in oysters and will be valuable resources for studying DNA methylation in invertebrates.

Heat selection enables highly scalable methylome profiling in cell-free DNA for noninvasive monitoring of cancer patients.

Genome-wide analysis of cell-free DNA methylation profile is a promising approach for sensitive and specific detection of many cancers. However, scaling such assays for clinical translation is impractical because of the high cost of whole-genome bisulfite sequencing. We show that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbors most of the cancer-specific methylation signature. Here, we report on the simple and effective heat enrichment of CpG-rich regions for bisulfite sequencing (Heatrich-BS) platform that allows for focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable accurate tumor burden estimation and quantitative tracking of colorectal cancer patient’s response to treatment at much reduced sequencing cost suitable for frequent monitoring. We also show tumor epigenetic subtyping using Heatrich-BS, which could enable patient stratification. Heatrich-BS holds great potential for highly scalable screening and monitoring of cancer using liquid biopsy.

CfDNA methylome profiling for detection and subtyping of small cell lung cancers

Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients’ circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.

Maternal prenatal immunity, neonatal trained immunity, and early airway microbiota shape childhood asthma development.

The path to childhood asthma is thought to initiate in utero and be further promoted by postnatal exposures. However, the underlying mechanisms remain underexplored. We hypothesized that prenatal maternal immune dysfunction associated with increased childhood asthma risk (revealed by low IFN-γ:IL-13 secretion during the third trimester of pregnancy) alters neonatal immune training through epigenetic mechanisms and promotes early-life airway colonization by asthmagenic microbiota. We examined epigenetic, immunologic, and microbial features potentially related to maternal prenatal immunity (IFN-γ:IL-13 ratio) and childhood asthma in a birth cohort of mother-child dyads sampled pre-, peri-, and postnatally (N=155). Epigenome-wide DNA methylation and cytokine production were assessed in cord blood mononuclear cells (CBMC) by array profiling and ELISA, respectively. Nasopharyngeal microbiome composition was characterized at age 2-36 months by 16S rRNA sequencing. Maternal prenatal immune status related to methylome profiles in neonates born to non-asthmatic mothers. A module of differentially methylated CpG sites enriched for microbe-responsive elements was associated with childhood asthma. In vitro responsiveness to microbial products was impaired in CBMCs from neonates born to mothers with the lowest IFN-γ:IL-13 ratio, suggesting defective neonatal innate immunity in those who developed asthma during childhood. These infants exhibited a distinct pattern of upper airway microbiota development characterized by early-life colonization by Haemophilus that transitioned to a Moraxella-dominated microbiota by age 36 months. Maternal prenatal immune status shapes asthma development in her child by altering the epigenome and trained innate immunity at birth, and is associated with pathologic upper airway microbial colonization in early life.

Completing Single-Cell DNA Methylome Profiles via Transfer Learning Together With KL-Divergence.

The high level of sparsity in methylome profiles obtained using whole-genome bisulfite sequencing in the case of low biological material amount limits its value in the study of systems in which large samples are difficult to assemble, such as mammalian preimplantation embryonic development. The recently developed computational methods for addressing the sparsity by imputing missing have their limits when the required minimum data coverage or profiles of the same tissue in other modalities are not available. In this study, we explored the use of transfer learning together with Kullback-Leibler (KL) divergence to train predictive models for completing methylome profiles with very low coverage (below 2%). Transfer learning was used to leverage less sparse profiles that are typically available for different tissues for the same species, while KL divergence was employed to maximize the usage of information carried in the input data. A deep neural network was adopted to extract both DNA sequence and local methylation patterns for imputation. Our study of training models for completing methylome profiles of bovine oocytes and early embryos demonstrates the effectiveness of transfer learning and KL divergence, with individual increase of 29.98 and 29.43%, respectively, in prediction performance and 38.70% increase when the two were used together. The drastically increased data coverage (43.80–73.6%) after imputation powers downstream analyses involving methylomes that cannot be effectively done using the very low coverage profiles (0.06–1.47%) before imputation.

Diagnostic DNA methylome profiling and the WHO 5th edition CNS tumor classification.

The long-awaited 5th edition of the WHO brain tumor classification has put considerable emphasis on the importance of diagnostic DNA methylation profiling. In this article, the authors comparatively discuss selected practical aspects as well as general advantages and limitations of array- versus nanopore sequencing-based approaches to methylome profiling.