scholarly journals Bisulfite-free epigenomics and genomics of single cells through methylation-sensitive restriction

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Christoph Niemöller ◽  
Julius Wehrle ◽  
Julian Riba ◽  
Rainer Claus ◽  
Nathalie Renz ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genetic Variants ◽  
Myeloid Leukemia ◽  
Single Cells ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Powerful Means ◽  
Genetic Profiles

AbstractSingle-cell multi-omics are powerful means to study cell-to-cell heterogeneity. Here, we present a single-tube, bisulfite-free method for the simultaneous, genome-wide analysis of DNA methylation and genetic variants in single cells: epigenomics and genomics of single cells analyzed by restriction (epi-gSCAR). By applying this method, we obtained DNA methylation measurements of up to 506,063 CpGs and up to 1,244,188 single-nucleotide variants from single acute myeloid leukemia-derived cells. We demonstrate that epi-gSCAR generates accurate and reproducible measurements of DNA methylation and allows to differentiate between cell lines based on the DNA methylation and genetic profiles.

scholarly journals Genome‐wide analysis of single nucleotide variants on phosphorylation motifs

2018 ◽  
Vol 32 (S1) ◽  
Author(s):  
Hisayoshi Yoshizaki ◽  
Yiwei Ling ◽  
Miyuki Kohno ◽  
Shujiro Okuda
Keyword(s):  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Wide Analysis ◽  
Genome Wide

scholarly journals Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans

2021 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Nayoung Han ◽  
Jung Mi Oh ◽  
In-Wha Kim
Keyword(s):  
Copy Number ◽  
Genome Wide Association Study ◽  
Copy Number Gain ◽  
Copy Number Variations ◽  
Gene Gain ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Haplotype Blocks ◽  
Genome Wide ◽  
Control And Prevention

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.

scholarly journals scSNV: accurate dscRNA-seq SNV co-expression analysis using duplicate tag collapsing

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gavin W. Wilson ◽  
Mathieu Derouet ◽  
Gail E. Darling ◽  
Jonathan C. Yeung
Keyword(s):  
Genetic Variants ◽  
False Positive ◽  
Variant Calling ◽  
Call Rate ◽  
Rna Seq ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Variant Call ◽  
Two Samples ◽  
Co Detection

AbstractIdentifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to “collapse” molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples.

scholarly journals DNA Methylation and Intra-Clonal Heterogeneity: The Chronic Myeloid Leukemia Model

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3587
Author(s):  
Benjamin Lebecque ◽  
Céline Bourgne ◽  
Véronique Vidal ◽  
Marc G. Berger
Keyword(s):  
Dna Methylation ◽  
Chronic Myeloid Leukemia ◽  
Fusion Protein ◽  
Myeloid Leukemia ◽  
Kinase Inhibitors ◽  
Single Gene ◽  
Clonal Heterogeneity ◽  
Sequencing Technologies ◽  
Genome Wide ◽  
The Impact

Chronic Myeloid Leukemia (CML) is a model to investigate the impact of tumor intra-clonal heterogeneity in personalized medicine. Indeed, tyrosine kinase inhibitors (TKIs) target the BCR-ABL fusion protein, which is considered the major CML driver. TKI use has highlighted the existence of intra-clonal heterogeneity, as indicated by the persistence of a minority subclone for several years despite the presence of the target fusion protein in all cells. Epigenetic modifications could partly explain this heterogeneity. This review summarizes the results of DNA methylation studies in CML. Next-generation sequencing technologies allowed for moving from single-gene to genome-wide analyses showing that methylation abnormalities are much more widespread in CML cells. These data showed that global hypomethylation is associated with hypermethylation of specific sites already at diagnosis in the early phase of CML. The BCR-ABL-independence of some methylation profile alterations and the recent demonstration of the initial intra-clonal DNA methylation heterogeneity suggests that some DNA methylation alterations may be biomarkers of TKI sensitivity/resistance and of disease progression risk. These results also open perspectives for understanding the epigenetic/genetic background of CML predisposition and for developing new therapeutic strategies.

scholarly journals Prediction of genome-wide effects of single nucleotide variants on transcription factor binding

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sebastian Carrasco Pro ◽  
Katia Bulekova ◽  
Brian Gregor ◽  
Adam Labadorf ◽  
Juan Ignacio Fuxman Bass
Keyword(s):  
Binding Sites ◽  
Cancer Type ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Regulatory Regions ◽  
Genome Wide ◽  
Transcriptional Regulatory ◽  
Gene Regulatory ◽  
The Impact ◽  
The Relationship

Abstract Single nucleotide variants (SNVs) located in transcriptional regulatory regions can result in gene expression changes that lead to adaptive or detrimental phenotypic outcomes. Here, we predict gain or loss of binding sites for 741 transcription factors (TFs) across the human genome. We calculated ‘gainability’ and ‘disruptability’ scores for each TF that represent the likelihood of binding sites being created or disrupted, respectively. We found that functional cis-eQTL SNVs are more likely to alter TF binding sites than rare SNVs in the human population. In addition, we show that cancer somatic mutations have different effects on TF binding sites from different TF families on a cancer-type basis. Finally, we discuss the relationship between these results and cancer mutational signatures. Altogether, we provide a blueprint to study the impact of SNVs derived from genetic variation or disease association on TF binding to gene regulatory regions.

scholarly journals Inference of Crosstalk Effects between DNA Methylation and lncRNA Regulation in NSCLC

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Binhua Tang
Keyword(s):  
Clinical Trial ◽  
Dna Methylation ◽  
Lung Carcinoma ◽  
Analytic Functions ◽  
Nsclc Tissue ◽  
Genome Wide Analysis ◽  
Clinical Trial Research ◽  
Omics Integration ◽  
Genome Wide ◽  
Tissue Profiling

Intercellular crosstalk effects between DNA methylation and lncRNA regulation remain elusive in lung carcinoma epigenetics. We present an application toolkit MetLnc in integration and annotation for group-wise NSCLC tissue-based DNA methylation and lncRNA profiling resources, to comprehensively analyze differentially methylated loci and lncRNAs through genome-wide analysis. Together with multiple analytic functions, MetLnc acts as an efficient approach on epigenetic omics integration and interrogation. Via the benchmark with group-wise NSCLC tissue profiling and TCGA cohort resources, we study differentially methylated CpG loci and lncRNAs as meaningful clues for inferring crosstalk effects between DNA methylation and lncRNA regulation; together we conclude with investigated biomarkers for further epigenetics and clinical trial research.

scholarly journals PGC7 suppresses TET3 for protecting DNA methylation

2013 ◽  
Vol 42 (5) ◽  
pp. 2893-2905 ◽  
Author(s):  
Chunjing Bian ◽  
Xiaochun Yu
Keyword(s):  
Dna Methylation ◽  
Molecular Mechanism ◽  
Biological Process ◽  
Cpg Islands ◽  
Binding Motifs ◽  
Genome Wide Analysis ◽  
Dna Motif ◽  
Genome Wide

Abstract Ten-eleven translocation (TET) family enzymes convert 5-methylcytosine to 5-hydroxylmethylcytosine. However, the molecular mechanism that regulates this biological process is not clear. Here, we show the evidence that PGC7 (also known as Dppa3 or Stella) interacts with TET2 and TET3 both in vitro and in vivo to suppress the enzymatic activity of TET2 and TET3. Moreover, lacking PGC7 induces the loss of DNA methylation at imprinting loci. Genome-wide analysis of PGC7 reveals a consensus DNA motif that is recognized by PGC7. The CpG islands surrounding the PGC7-binding motifs are hypermethylated. Taken together, our study demonstrates a molecular mechanism by which PGC7 protects DNA methylation from TET family enzyme-dependent oxidation.

scholarly journals Genome-wide analysis of DNA methylation in obese, lean and miniature pig breeds

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yalan Yang ◽  
Rong Zhou ◽  
Yulian Mu ◽  
Xinhua Hou ◽  
Zhonglin Tang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Miniature Pig ◽  
Genome Wide Analysis ◽  
Pig Breeds ◽  
Genome Wide
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