scholarly journals Ultra-low DNA input into whole genome methylation assays and detection of oncogenic methylation & copy number variants in circulating tumour DNA

2020 ◽  
Author(s):  
Celina Whalley ◽  
Karl Payne ◽  
Enric Domingo ◽  
Andrew Blake ◽  
Susan Richman ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Correlation Coefficients ◽  
Differential Methylation ◽  
Cpg Methylation ◽  
Methylation Analysis ◽  
Genome Wide ◽  
Methylation Assay ◽  
Circulating Tumour Dna ◽  
Differential Methylation Analysis

AbstractBackgroundCpG methylation in cancer is ubiquitous and generally detected in tumour specimens using a variety of techniques at a resolution encompassing single CpG loci to genome wide. Analysis of samples with very low DNA inputs, such as formalin fixed (FFPE) biopsy specimens from clinical trials or circulating tumour DNA has been challenging and has only been typically at single CpG sites. Analysis of genome wide methylation in these specimens has been limited because of the relative expense of techniques need to carry this out. We present the results of low input experiments into the Illumina Infinium HD methylation assay on FFPE specimens and ctDNA samples.MethodsFor all experiments, the Infinium HD assay for Methylation was used. In total, forty-eight FFPE specimens were used at varying concentrations (lowest input 50ng), eighteen blood derived specimens (lowest input 10ng) and six matched ctDNA input (lowest input 10ng) / fresh tumour specimens (lowest input 250ng) were processed. Downstream analysis was performed in R/Bioconductor for QC metrics and differential methylation analysis as well as copy number calls.ResultsCorrelation coefficients for CpG methylation at the probe level averaged R2=0.99 for blood derived samples and R2>0.96 for the FFPE samples. When matched ctDNA/fresh tumour samples were compared R2>0.91. Results of differential methylation analysis did not vary significantly by DNA input in either the blood or FFPE groups. There were differences seen in the ctDNA group as compared to their paired tumour sample, possibly because of enrichment for tumour material without contaminating normal. Copy number variants observed in the tumour were generally also seen in the paired ctDNA sample.ConclusionsThe Illumina Infinium HD methylation assay can robustly detect methylation across a range of sample types, including ctDNA, down to a input of 10ng. It can also reliably detect oncogenic methylation changes and copy number variants in ctDNA.

scholarly journals Ultra-Low DNA Input into Whole Genome Methylation Assays and Detection of Oncogenic Methylation and Copy Number Variants in Circulating Tumour DNA

Epigenomes ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 6
Author(s):  
Celina Whalley ◽  
Karl Payne ◽  
Enric Domingo ◽  
Andrew Blake ◽  
Susan Richman ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Differential Methylation ◽  
Cpg Methylation ◽  
Methylation Analysis ◽  
Methylation Array ◽  
Genome Wide ◽  
Methylation Assay ◽  
Circulating Tumour Dna ◽  
Differential Methylation Analysis

Background: Abnormal CpG methylation in cancer is ubiquitous and generally detected in tumour specimens using a variety of techniques at a resolution encompassing single CpG loci to genome wide coverage. Analysis of samples with very low DNA inputs, such as formalin fixed (FFPE) biopsy specimens from clinical trials or circulating tumour DNA is challenging at the genome-wide level because of lack of available input. We present the results of low input experiments into the Illumina Infinium HD methylation assay on FFPE specimens and ctDNA samples. Methods: For all experiments, the Infinium HD assay for methylation was used. In total, forty-eight FFPE specimens were used at varying concentrations (lowest input 50 ng); eighteen blood derived specimens (lowest input 10 ng) and six matched ctDNA input (lowest input 10 ng)/fresh tumour specimens (lowest input 250 ng) were processed. Downstream analysis was performed in R/Bioconductor for quality control metrics and differential methylation analysis as well as copy number calls. Results: Correlation coefficients for CpG methylation were high at the probe level averaged R2 = 0.99 for blood derived samples and R2 > 0.96 for the FFPE samples. When matched ctDNA/fresh tumour samples were compared, R2 > 0.91 between the two. Results of differential methylation analysis did not vary significantly by DNA input in either the blood or FFPE groups. There were differences seen in the ctDNA group as compared to their paired tumour sample, possibly because of enrichment for tumour material without contaminating normal. Copy number variants observed in the tumour were generally also seen in the paired ctDNA sample with good concordance via DQ plot. Conclusions: The Illumina Infinium HD methylation assay can robustly detect methylation across a range of sample types, including ctDNA, down to an input of 10 ng. It can also reliably detect oncogenic methylation changes and copy number variants in ctDNA. These findings demonstrate that these samples can now be accessed by methylation array technology, allowing analysis of these important sample types.

scholarly journals Detection and characterization of copy number variants based on whole-genome sequencing by DNBSEQ platforms

2019 ◽  
Author(s):  
Junhua Rao ◽  
Lihua Peng ◽  
Fang Chen ◽  
Hui Jiang ◽  
Chunyu Geng ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
Whole Genome ◽  
Genome Wide ◽  
Wide Range ◽  
Distribution Sensitivity ◽  
Cnv Detection

AbstractBackgroundNext-generation sequence (NGS) has rapidly developed in past years which makes whole-genome sequencing (WGS) becoming a more cost- and time-efficient choice in wide range of biological researches. We usually focus on some variant detection via WGS data, such as detection of single nucleotide polymorphism (SNP), insertion and deletion (Indel) and copy number variant (CNV), which playing an important role in many human diseases. However, the feasibility of CNV detection based on WGS by DNBSEQ™ platforms was unclear. We systematically analysed the genome-wide CNV detection power of DNBSEQ™ platforms and Illumina platforms on NA12878 with five commonly used tools, respectively.ResultsDNBSEQ™ platforms showed stable ability to detect slighter more CNVs on genome-wide (average 1.24-fold than Illumina platforms). Then, CNVs based on DNBSEQ™ platforms and Illumina platforms were evaluated with two public benchmarks of NA12878, respectively. DNBSEQ™ and Illumina platforms showed similar sensitivities and precisions on both two benchmarks. Further, the difference between tools for CNV detection was analyzed, and indicated the selection of tool for CNV detection could affected the CNV performance, such as count, distribution, sensitivity and precision.ConclusionThe major contribution of this paper is providing a comprehensive guide for CNV detection based on WGS by DNBSEQ™ platforms for the first time.

scholarly journals RefCNV: Identification of Gene-Based Copy Number Variants Using Whole Exome Sequencing

2016 ◽  
Vol 15 ◽  
pp. CIN.S36612 ◽  
Author(s):  
Lun-Ching Chang ◽  
Biswajit Das ◽  
Chih-Jian Lih ◽  
Han Si ◽  
Corinne E. Camalier ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Estimation Methods ◽  
Single Nucleotide Variants ◽  
False Positive Error ◽  
Reference Set ◽  
Genome Wide ◽  
Whole Exome

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly ( r = 0.96–0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman's coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.

scholarly journals Genome-Wide DNA Methylation Analysis in Melanoma Reveals the Importance of CpG Methylation in MITF Regulation

2015 ◽  
Vol 135 (7) ◽  
pp. 1820-1828 ◽  
Author(s):  
Martin Lauss ◽  
Rizwan Haq ◽  
Helena Cirenajwis ◽  
Bengt Phung ◽  
Katja Harbst ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cpg Methylation ◽  
Methylation Analysis ◽  
Genome Wide ◽  
Dna Methylation Analysis

scholarly journals Association of CNVs with methylation variation

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Xinghua Shi ◽  
Saranya Radhakrishnan ◽  
Jia Wen ◽  
Jin Yun Chen ◽  
Junjie Chen ◽  
...  
Keyword(s):  
Association Studies ◽  
Copy Number Variants ◽  
Cpg Methylation ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Cellular Phenotype ◽  
Genome Wide ◽  
A Genome ◽  
Physical Interactions ◽  
Trait Locus

Abstract Germline copy number variants (CNVs) and single-nucleotide polymorphisms (SNPs) form the basis of inter-individual genetic variation. Although the phenotypic effects of SNPs have been extensively investigated, the effects of CNVs is relatively less understood. To better characterize mechanisms by which CNVs affect cellular phenotype, we tested their association with variable CpG methylation in a genome-wide manner. Using paired CNV and methylation data from the 1000 genomes and HapMap projects, we identified genome-wide associations by methylation quantitative trait locus (mQTL) analysis. We found individual CNVs being associated with methylation of multiple CpGs and vice versa. CNV-associated methylation changes were correlated with gene expression. CNV-mQTLs were enriched for regulatory regions, transcription factor-binding sites (TFBSs), and were involved in long-range physical interactions with associated CpGs. Some CNV-mQTLs were associated with methylation of imprinted genes. Several CNV-mQTLs and/or associated genes were among those previously reported by genome-wide association studies (GWASs). We demonstrate that germline CNVs in the genome are associated with CpG methylation. Our findings suggest that structural variation together with methylation may affect cellular phenotype.

scholarly journals Genome-wide survey implicates the influence of copy number variants (CNVs) in the development of early-onset bipolar disorder

2011 ◽  
Vol 17 (4) ◽  
pp. 421-432 ◽  
Author(s):  
L Priebe ◽  
F A Degenhardt ◽  
S Herms ◽  
B Haenisch ◽  
M Mattheisen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Early Onset ◽  
Copy Number ◽  
Copy Number Variants ◽  
Genome Wide ◽  
Genome Wide Survey

Genome-Wide DNA Methylation Analysis Shows Enrichment of Differential Methylation in “Open Seas” and Enhancers and Reveals Hypomethylation in DNMT3A Mutated Cytogenetically Normal AML (CN-AML)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 653-653 ◽  
Author(s):  
Ying Qu ◽  
Andreas Lennartsson ◽  
Verena I. Gaidzik ◽  
Stefan Deneberg ◽  
Sofia Bengtzén ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Methylation Analysis ◽  
Cpg Sites ◽  
Genome Wide ◽  
Genomic Regions ◽  
Methylation Patterns

Abstract Abstract 653 DNA methylation is involved in multiple biologic processes including normal cell differentiation and tumorigenesis. In AML, methylation patterns have been shown to differ significantly from normal hematopoietic cells. Most studies of DNA methylation in AML have previously focused on CpG islands within the promoter of genes, representing only a very small proportion of the DNA methylome. In this study, we performed genome-wide methylation analysis of 62 AML patients with CN-AML and CD34 positive cells from healthy controls by Illumina HumanMethylation450K Array covering 450.000 CpG sites in CpG islands as well as genomic regions far from CpG islands. Differentially methylated CpG sites (DMS) between CN-AML and normal hematopoietic cells were calculated and the most significant enrichment of DMS was found in regions more than 4kb from CpG Islands, in the so called open sea where hypomethylation was the dominant form of aberrant methylation. In contrast, CpG islands were not enriched for DMS and DMS in CpG islands were dominated by hypermethylation. DMS successively further away from CpG islands in CpG island shores (up to 2kb from CpG Island) and shelves (from 2kb to 4kb from Island) showed increasing degree of hypomethylation in AML cells. Among regions defined by their relation to gene structures, CpG dinucleotide located in theoretic enhancers were found to be the most enriched for DMS (Chi χ2<0.0001) with the majority of DMS showing decreased methylation compared to CD34 normal controls. To address the relation to gene expression, GEP (gene expression profiling) by microarray was carried out on 32 of the CN-AML patients. Totally, 339723 CpG sites covering 18879 genes were addressed on both platforms. CpG methylation in CpG islands showed the most pronounced anti-correlation (spearman ρ =-0.4145) with gene expression level, followed by CpG island shores (mean spearman rho for both sides' shore ρ=-0.2350). As transcription factors (TFs) have shown to be crucial for AML development, we especially studied differential methylation of an unbiased selection of 1638 TFs. The most enriched differential methylation between CN-AML and normal CD34 positive cells were found in TFs known to be involved in hematopoiesis and with Wilms tumor protein-1 (WT1), activator protein 1 (AP-1) and runt-related transcription factor 1 (RUNX1) being the most differentially methylated TFs. The differential methylation in WT 1 and RUNX1 was located in intragenic regions which were confirmed by pyro-sequencing. AML cases were characterized with respect to mutations in FLT3, NPM1, IDH1, IDH2 and DNMT3A. Correlation analysis between genome wide methylation patterns and mutational status showed statistically significant hypomethylation of CpG Island (p<0.0001) and to a lesser extent CpG island shores (p<0.001) and the presence of DNMT3A mutations. This links DNMT3A mutations for the first time to a hypomethylated phenotype. Further analyses correlating methylation patterns to other clinical data such as clinical outcome are ongoing. In conclusion, our study revealed that non-CpG island regions and in particular enhancers are the most aberrantly methylated genomic regions in AML and that WT 1 and RUNX1 are the most differentially methylated TFs. Furthermore, our data suggests a hypomethylated phenotype in DNMT3A mutated AML. Disclosures: No relevant conflicts of interest to declare.

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