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| Status |
Public on Jul 01, 2014 |
| Title |
1308388 Tumor [methylation] |
| Sample type |
SRA |
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| Source name |
liver, HCC tumor
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| Organism |
Homo sapiens |
| Characteristics |
disease status: hepatocellular carcinoma (HCC)
tissue: liver tumor
gender: M
age (y): 48
patient: 1308388
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
Genomic DNA was extracted using the QIAamp DNA Blood Mini Kit (Qiagen). 1µg of genomic DNA was fragmented into approximately 200-300bp using a Covarias sonication system (Covarias). After purification, the fragmented fractions were treated with a mix of T4 DNA polymerase, Klenow Fragment and T4 polynucleotide kinase to repair blunt and phosphorylate ends. The blunt DNA fragments were subsequently 3' adenylated using Klenow Fragment (3'-5' exo-) and then ligated by T4 DNA Ligase to adapters that were synthesized with 5'-methylcytosine instead of 5'-cytosine and contain index sequences inside. After each step, the reaction products were purified using QIAquick PCR purification kit (Qiagen). The constructed libraries were quantified using a Qubit fluorometer with Quant-iT dsDNA HS Assay Kit (Invitrogen). The liquid hybridization capture procedure was then performed as follows. Briefly, 200 ng DNA from each of five adapter-ligated libraries were pooled together. 10 µg human Cot-1 DNA and 1nmol of adapter complementary DNA oligos were added and subsequently were dried using a SpeedVac (eppendorf) at 60°C. After that, the mixture was denatured at 95°C for 10min in a final reaction volume of 10.5µl consisting of 7.5µl 2X SC Hybridization Buffer and 3µl SC Hybridization Component A. After centrifugation, 4.5µl of designed probes were added and the mixture was hybridized in a thermal cycler at 47°C for 72 hours with the lid heated at 57°C. After hybridization, the biotinylated probes bounded with the target DNA were captured using 100µl of Dynabeads® M-280 Streptavidin (Invitrogen), which had been pre-washed two times with a total of 400µl Streptavidin Dynabead Binging and Washing Buffer. The capture program was 47°C for 45min in a thermal cycler with the lid heated at 57°C and vortexing for 3 seconds at 15min intervals. Discarded the unbounded fractions and washed the collected DNA-probe-beads complex with 100µl of 47°C pre-warmed 1X Wash Buffer I for one time and with a total of 400µl of 47°C pre-warmed 1X Stringent Wash Buffer I for two times with the incubations of 47°C for 5min. After discarding the supernatant, the collected beads complex was again washed with 200µl of 1X Wash Buffer I, 1X Wash Buffer II and 1X Wash Buffer III respectively. Finally, the captured DNA was eluted in 50µl of 10M NaOH with incubation at room temperature for 10min. The supernatant was transferred into a new tube and neutralized with 50µl of 10M HAc and then purified using MiniElute PCR purification Kit (Qiagen). For bisulfite conversion, 200ng unmethylated lambda DNA was added into each captured product as carriers and ZYMO EZ DNA Methylation-Gold Kit™ (ZYMO) was employed to convert unmethylated cytosine into uracil according to the instructions.
After purification, PCR was carried out in a final reaction volume of 50µl consisting of 20µl converted products, 4µl 2.5mM dNTP, 5µl 10×buffer, 0.5µl JumpStart™ Taq DNA Polymerase (SIGMA), 1µl PCR primers1.0, 1µl PCR index primers (which were used to identify different captures) and 18.5µl water. The following thermal cycling program was 94°C 1 min, 15 cycles of 94 °C 10s, 58°C 30s, 72°C 30s then prolong at 72°C for 5min and hold at 12°C. The PCR products were purified using AMPure beads (Agencourt), quantified by the Bioanalyzer analysis system (Agilent) and real time PCR assay and then analyzed using Illumina Hiseq 2000. All of these samples were pooled into 7 libraries with a one-to-one correspondence 7bp barcode. The barcode information is following: s02_C-AATAACT-pooling1, s14_P-TGTAATT-pooling1, s96_P-ACTTGAT-pooling1, s00_C-AATAACT-pooling2, s13_C-TGTAATT-pooling2, s95_C-ACTTGAT-pooling2, s09_C-ATAATCT-pooling3, s15_P-TGTAATT-pooling3, s06_P-GTACATT-pooling4, s10_P-TATGCTT-pooling4, s16_C-TGTAATT-pooling4, s01_P-GTACATT-pooling5, s99_P-CGAATAT-pooling5, s95_C-CGAATAT-pooling6, s96_P-ACTTGAT-pooling6, s05_C-GTACATT-pooling7, s11_P-TATGCTT-pooling7, s12_C-TGTAATT-pooling7. The constructed libraries were quantified using a Qubit fluorometer with Quant-iT dsDNA HS Assay Kit (Invitrogen).
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| Library strategy |
Bisulfite-Seq |
| Library source |
genomic |
| Library selection |
RANDOM |
| Instrument model |
Illumina HiSeq 2000 |
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| Description |
s12_C
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| Data processing |
After removing the adapter sequences and filtering out the low-quality reads, the bisulfite sequencing reads were directly aligned to the human reference genome (UCSC hg19) using BSMAP 2.73 with default parameters (Xi and Li 2009), which combines genome hashing and bitwise masking to achieve fast and accurate bisulfite mapping.
We extracted methylation ratios of all coveraged cytosines on the genome (*.cout.gz files) using the script included in BSMAP 2.73. Then we filtered out the CpG sites with less than 4X sequencing depth in order to guarantee accurate calculation of methylation levels. Then analysed differential promoter DNA methylation between HCCs (Tumor) and peripheral normal tissues (NTL) as following. DMRs were searched using a sliding window strategy: firstly, we selected the both covered CpG sites in two samples with sequencing depth >= 5X as candidate sites. For each of candidate site, the ChiqX or Fisher test was performed to calculate the significant test P-value. Secondly, we selected the first differentially methylated CpG (P-value < 0.05) as an initial locus of DMR, and began to merge these candidate sites into a candidate DMR with following criterion: 1, the distance between two neighbouring candidate sites <= 300bp; 2, all of candidate sites in the candidate DMR kept the same methylation status (hyper- or hypo-); and 3, a candidate DMR must harbor 5 or more candidate sites. Last, for each of the above candidate DMR, we performed a Fisher test again, and filtered out those regions whose test P-value >0.05 and difference of mean methylation levels between two sample < 0.2.
Integration of promoter methylomic and transcriptomic profiling. To further clarify the genes that are potentially regulated by promoter methylation, we further performed pair-wise comparisons on promoter methylomes to identify specific DMRs between HCCs and peripheral normal tissues. Furthermore, we evaluated differential gene expression between 8 pairs of HCC and PN samples using Illumina high-throughput RNA-seq technology.
Genome_build: GRCh37
Supplementary_files_format_and_content: *.cout.txt.gz files include the extracted methylation ratios for all coveraged cytosines on the genome. Each of these files contain 8 columns. The format is: (1) Chromosome ID; (2) Cytosine position; (3) Watson/Crick chain; (4) Type (CG/CHH/CHG); (5) Base pattern; (6) Methylation Ratio; (7) Methylated reads num; and (8) Un-methylated reads num.
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| Submission date |
Mar 10, 2014 |
| Last update date |
May 15, 2019 |
| Contact name |
Desheng Gong |
| E-mail(s) |
[email protected]
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| Organization name |
Agricultural Genomes Institute at Shenzhen
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| Street address |
No.7 PengFei road
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| City |
Shenzhen |
| ZIP/Postal code |
518120 |
| Country |
China |
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| Platform ID |
GPL11154 |
| Series (2) |
| GSE55752 |
Promoter methylome and integrative transcriptome profiling identify key epigenetics-regulated genes in human HCCs [methylation] |
| GSE55759 |
Promoter methylome and integrative transcriptome profiling identify key epigenetics-regulated genes in human HCCs |
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| Relations |
| BioSample |
SAMN02680077 |
| SRA |
SRX483869 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM1342805_s12_C.cout.txt.gz |
596.2 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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