| Literature DB >> 25324297 |
Fumihito Miura1, Takashi Ito2.
Abstract
The current gold standard method for methylome analysis is whole-genome bisulfite sequencing (WGBS), but its cost is substantial, especially for the purpose of multi-sample comparison of large methylomes. Shotgun bisulfite sequencing of target-enriched DNA, or targeted methylome sequencing (TMS), can be a flexible, cost-effective alternative to WGBS. However, the current TMS protocol requires a considerable amount of input DNA and hence is hardly applicable to samples of limited quantity. Here we report a method to overcome this limitation by using post-bisulfite adaptor tagging (PBAT), in which adaptor tagging is conducted after bisulfite treatment to circumvent bisulfite-induced loss of intact sequencing templates, thereby enabling TMS of a 100-fold smaller amount of input DNA with far fewer cycles of polymerase chain reaction than in the current protocol. We thus expect that the PBAT-mediated TMS will serve as an invaluable method in epigenomics.Entities:
Keywords: DNA methylation; massively parallel sequencing; target enrichment
Mesh:
Substances:
Year: 2014 PMID: 25324297 PMCID: PMC4379973 DOI: 10.1093/dnares/dsu034
Source DB: PubMed Journal: DNA Res ISSN: 1340-2838 Impact factor: 4.458
Figure 1.Two strategies for TMS. (A) Conventional procedures comprise adaptor tagging of fragmented genomic DNAs (Steps 1 and 2), target enrichment by hybridization (Steps 3 and 4) and bisulfite treatment of enriched library DNAs (Step 5) followed by PCR amplification (Step 6). The bisulfite treatment (Step 5) induces DNA breaks, inevitably leading to severe loss of intact sequencing template molecules. (B) PBAT-mediated procedure comprises target enrichment by hybridization (Steps 1–3), bisulfite treatment (Step 4) and adaptor tagging (Step 5), thereby circumventing the bisulfite-induced loss of intact sequencing template molecules.
Summary of library construction
| Target species (Target size) | Method for library construction | DNA source | Amount of input DNA (ng) | Library yield before PCR amplificationa (amol) | Equivalent number of lanesb | Number of PCR cycles to have DNA enough for a single lane | Number of reads (% uniquely mapped reads) | Average depth of mapped reads obtained from a half lane of HiSeq2500 rapid mode | ||
|---|---|---|---|---|---|---|---|---|---|---|
| On target | Off target (near, ≤400 bp) | Off target (far, >400 bp) | ||||||||
| Human (84 Mb) | Methyl-Seq | Promega human genomic DNA | 3,000 | 1,340.0 | 1.00 | 11 | 110.3 M (91.1%) | 98.2× | 9.6× | 0.2× |
| PBAT | 3,000 | 5,649.2 | 4.35 | 0 | 73.1 M (78.9%) | 43.4× | 9.3× | 0.1× | ||
| 1,000 | 2,607.3 | 2.01 | 0 | 73.0 M (77.0%) | 42.7× | 8.9× | 0.1× | |||
| 300 | 477.3 | 0.37 | 2 | 68.6 M (76.2%) | 39.6× | 8.2× | 0.1× | |||
| 100 | 259.6 | 0.20 | 3 | 79.4 M (74.1%) | 44.2× | 9.2× | 0.2× | |||
| 30 | 140.5 | 0.11 | 4 | 77.3 M (63.5%) | 37.1× | 7.9× | 0.2× | |||
| 10 | 70.8 | 0.05 | 5 | 67.0 M (38.4%) | 18.2× | 4.1× | 0.2× | |||
| IMR90 | 300 | 220.0 | 0.17 | 4 | 70.8 M (85.6%) | 46.3× | 9.4× | 0.1× | ||
| Mouse (109 Mb) | PBAT | Promega mouse genomic DNA | 3,000 | 3,645.3 | 2.80 | 0 | nd | nd | nd | nd |
| 1,000 | 2,353.3 | 1.81 | 0 | nd | nd | nd | nd | |||
| 300 | 679.5 | 0.52 | 2 | nd | nd | nd | nd | |||
| 100 | 285.2 | 0.22 | 3 | nd | nd | nd | nd | |||
| 30 | 151.9 | 0.12 | 4 | nd | nd | nd | nd | |||
| 10 | 71.2 | 0.05 | 5 | nd | nd | nd | nd | |||
M: million.
Yield of the library amplified by 11 cycles of PCR was shown for Methyl-Seq.
Based on an assumption that a single lane requires 1,300 amol of library DNA.
Figure 2.Performance of PBAT-mediated TMS. (A) Target coverage. The fraction of the targets covered by differing minimal depth of reads was shown for the six PBAT and one Methyl-Seq libraries generated from the indicated amount of input DNA. Note that the average read depth of the Methyl-Seq library was twice or more higher than those of the PBAT libraries (Table 1). (B) Consistency among TMS data. Methylation levels were compared among the six TMS libraries generated from 3,000 to 10 ng of human genomic DNA using the PBAT-mediated procedure as well as the one generated from 3,000 ng of input DNA using the original Methyl-Seq protocol (DRA002274-002280). The numbers and the images in the boxes above and below the diagonal indicated the coefficients of determination (R2) and the scatter plot of methylation levels, respectively, between all the possible combinations among the seven data sets. The moving averages of methylation levels (window size, 500 bp; step size, 250 bp) were calculated based on CpGs covered by 20 or more reads. (C) A snapshot of TMS data. Data around the imprinted control region (ICR) for PEG3 were compared among the seven libraries generated with either PBAT or Methyl-Seq using the indicated amount of input DNA. Red bars and grey shadows indicated the methylation levels of individual CpG sites and the depth of reads, respectively. Note that most reads were mapped to the bottom strand, as the RNA probes used in the experiment were designed from the top strand. As expected, a region around the PEG3 promoter showed ∼50% methylation level due to the imprinted monoallelic methylation. The green dashed box denoted the ICR of PEG3 (chr.19: 57,351,728 to 57,352,173 in hg19 human reference genome sequence).
Figure 3.Consistency between TMS and WGBS data. Methylation levels were compared between the TMS data (DRA002281) (Table 1) and a publicly available WGBS data (DRA002248) on human IMR90 cells using the CpG sites covered by 20 or more reads. Methylation levels were plotted for moving windows (window size, 500 bp; stepping size, 250 bp) (A) and for individual CpG sites (B).