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Characterization of HPV DNA methylation of contiguous CpG sites by bisulfite treatment and massively parallel sequencing-the FRAGMENT approach.

Sun C, McAndrew T, Smith BC, Chen Z, Frimer M, Burk RD - Front Genet (2014)

Bottom Line: DNA methylation is a covalent modification predominantly occurring at CpG dinucleotides and increased methylation across the HPV16 genome is strongly associated with ICC development.Moreover, it provides additional information on methylation "haplotypes." In the current study, we chose 12 random samples, amplified multiple segments in the HPV16 bisulfite treated genome with specific barcodes, inspected the methylation ratio at 31 CpG sites for all samples using Illumina sequencing, and compared the results with quantitative pyrosequencing.In summary, the advantages of Next Gen sequencing compared to pyrosequencing for HPV genome methylation analyses include higher throughput, increased resolution, and improved efficiency of time and resources.

View Article: PubMed Central - PubMed

Affiliation: Department of Pediatrics, Albert Einstein College of Medicine Bronx, NY, USA.

ABSTRACT
Invasive cervix cancer (ICC) is the third most common malignant tumor in women and human papillomavirus 16 (HPV16) causes more than 50% of ICC. DNA methylation is a covalent modification predominantly occurring at CpG dinucleotides and increased methylation across the HPV16 genome is strongly associated with ICC development. Next generation (Next Gen) sequencing has been proposed as a novel approach to determine DNA methylation. However, utilization of this method to survey CpG methylation in the HPV16 genome is not well described. Moreover, it provides additional information on methylation "haplotypes." In the current study, we chose 12 random samples, amplified multiple segments in the HPV16 bisulfite treated genome with specific barcodes, inspected the methylation ratio at 31 CpG sites for all samples using Illumina sequencing, and compared the results with quantitative pyrosequencing. Most of the CpG sites were highly consistent between the two approaches (overall correlation, r = 0.92), thus verifying that Next Gen sequencing is an accurate and convenient method to survey HPV16 methylation and thus can be used in clinical samples for risk assessment. Moreover, the CpG methylation patterns (methylation haplotypes) in single molecules identified an excess of complete-and non-methylated molecules and a substantial amount of partial-methylated ones, thus indicating a complex dynamic for the mechanisms of HPV16 CpG methylation. In summary, the advantages of Next Gen sequencing compared to pyrosequencing for HPV genome methylation analyses include higher throughput, increased resolution, and improved efficiency of time and resources.

No MeSH data available.


Related in: MedlinePlus

The distribution of the differences between observed and expected frequencies for each “methylation haplotype” in assay L1_1 (A), L1_7 (B), L2_1 (C), L2_2 (D), L2_4 (E), and E2_1 (F). Each boxplot indicate one “methylation haplotype” combination. The green and red bars denote positive and negative value, respectively. (A) “Methylation haplotype” frequency differences in assay L1_1. (B) “Methylation haplotype” frequency differences in assay L1_7. (C) “Methylation haplotype” frequency differences in assay L2_1. (D) “Methylation haplotype” frequency differences in assay L2_2. (E) “Methylation haplotype” frequency differences in assay L2_4. (F) “Methylation haplotype” frequency differences in assay E2_1.
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Figure 3: The distribution of the differences between observed and expected frequencies for each “methylation haplotype” in assay L1_1 (A), L1_7 (B), L2_1 (C), L2_2 (D), L2_4 (E), and E2_1 (F). Each boxplot indicate one “methylation haplotype” combination. The green and red bars denote positive and negative value, respectively. (A) “Methylation haplotype” frequency differences in assay L1_1. (B) “Methylation haplotype” frequency differences in assay L1_7. (C) “Methylation haplotype” frequency differences in assay L2_1. (D) “Methylation haplotype” frequency differences in assay L2_2. (E) “Methylation haplotype” frequency differences in assay L2_4. (F) “Methylation haplotype” frequency differences in assay E2_1.

Mentions: The methylation pattern for each single molecule was determined for each sample across six regions of the HPV16 genome. A substantial proportion (10–80%) of molecules in the six assays were partially methylated (possessing a mixture of methylated and unmethylated sites), and the distributions of patterns were varied. However, the site-wise proportions of methylation for a given sample in a given assay were similar and the distribution of patterns in each molecule did exhibit dependence on that methylation level. To address this issue, we calculated the expected frequencies of all possible methylation patterns in each assay and compared them with the observed patterns (Figure 3). In most samples, a relative excess of none- and/or fully methylated molecules was observed (Figure 3). In contrast, despite their high prevalences, there was a relative absence of partial methylated molecules (Figure 3). As a consequence, most of the samples yielded a significant P-value (p < 0.05), thus indicating that CpG sites are not likely to be methylated/demethylated in an independent fashion, but that a more complex process determines the methylation state within a region of the HPV16 genome.


Characterization of HPV DNA methylation of contiguous CpG sites by bisulfite treatment and massively parallel sequencing-the FRAGMENT approach.

Sun C, McAndrew T, Smith BC, Chen Z, Frimer M, Burk RD - Front Genet (2014)

The distribution of the differences between observed and expected frequencies for each “methylation haplotype” in assay L1_1 (A), L1_7 (B), L2_1 (C), L2_2 (D), L2_4 (E), and E2_1 (F). Each boxplot indicate one “methylation haplotype” combination. The green and red bars denote positive and negative value, respectively. (A) “Methylation haplotype” frequency differences in assay L1_1. (B) “Methylation haplotype” frequency differences in assay L1_7. (C) “Methylation haplotype” frequency differences in assay L2_1. (D) “Methylation haplotype” frequency differences in assay L2_2. (E) “Methylation haplotype” frequency differences in assay L2_4. (F) “Methylation haplotype” frequency differences in assay E2_1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4042685&req=5

Figure 3: The distribution of the differences between observed and expected frequencies for each “methylation haplotype” in assay L1_1 (A), L1_7 (B), L2_1 (C), L2_2 (D), L2_4 (E), and E2_1 (F). Each boxplot indicate one “methylation haplotype” combination. The green and red bars denote positive and negative value, respectively. (A) “Methylation haplotype” frequency differences in assay L1_1. (B) “Methylation haplotype” frequency differences in assay L1_7. (C) “Methylation haplotype” frequency differences in assay L2_1. (D) “Methylation haplotype” frequency differences in assay L2_2. (E) “Methylation haplotype” frequency differences in assay L2_4. (F) “Methylation haplotype” frequency differences in assay E2_1.
Mentions: The methylation pattern for each single molecule was determined for each sample across six regions of the HPV16 genome. A substantial proportion (10–80%) of molecules in the six assays were partially methylated (possessing a mixture of methylated and unmethylated sites), and the distributions of patterns were varied. However, the site-wise proportions of methylation for a given sample in a given assay were similar and the distribution of patterns in each molecule did exhibit dependence on that methylation level. To address this issue, we calculated the expected frequencies of all possible methylation patterns in each assay and compared them with the observed patterns (Figure 3). In most samples, a relative excess of none- and/or fully methylated molecules was observed (Figure 3). In contrast, despite their high prevalences, there was a relative absence of partial methylated molecules (Figure 3). As a consequence, most of the samples yielded a significant P-value (p < 0.05), thus indicating that CpG sites are not likely to be methylated/demethylated in an independent fashion, but that a more complex process determines the methylation state within a region of the HPV16 genome.

Bottom Line: DNA methylation is a covalent modification predominantly occurring at CpG dinucleotides and increased methylation across the HPV16 genome is strongly associated with ICC development.Moreover, it provides additional information on methylation "haplotypes." In the current study, we chose 12 random samples, amplified multiple segments in the HPV16 bisulfite treated genome with specific barcodes, inspected the methylation ratio at 31 CpG sites for all samples using Illumina sequencing, and compared the results with quantitative pyrosequencing.In summary, the advantages of Next Gen sequencing compared to pyrosequencing for HPV genome methylation analyses include higher throughput, increased resolution, and improved efficiency of time and resources.

View Article: PubMed Central - PubMed

Affiliation: Department of Pediatrics, Albert Einstein College of Medicine Bronx, NY, USA.

ABSTRACT
Invasive cervix cancer (ICC) is the third most common malignant tumor in women and human papillomavirus 16 (HPV16) causes more than 50% of ICC. DNA methylation is a covalent modification predominantly occurring at CpG dinucleotides and increased methylation across the HPV16 genome is strongly associated with ICC development. Next generation (Next Gen) sequencing has been proposed as a novel approach to determine DNA methylation. However, utilization of this method to survey CpG methylation in the HPV16 genome is not well described. Moreover, it provides additional information on methylation "haplotypes." In the current study, we chose 12 random samples, amplified multiple segments in the HPV16 bisulfite treated genome with specific barcodes, inspected the methylation ratio at 31 CpG sites for all samples using Illumina sequencing, and compared the results with quantitative pyrosequencing. Most of the CpG sites were highly consistent between the two approaches (overall correlation, r = 0.92), thus verifying that Next Gen sequencing is an accurate and convenient method to survey HPV16 methylation and thus can be used in clinical samples for risk assessment. Moreover, the CpG methylation patterns (methylation haplotypes) in single molecules identified an excess of complete-and non-methylated molecules and a substantial amount of partial-methylated ones, thus indicating a complex dynamic for the mechanisms of HPV16 CpG methylation. In summary, the advantages of Next Gen sequencing compared to pyrosequencing for HPV genome methylation analyses include higher throughput, increased resolution, and improved efficiency of time and resources.

No MeSH data available.


Related in: MedlinePlus