 |
 |
GEO help: Mouse over screen elements for information. |
|
Status |
Public on Feb 11, 2019 |
Title |
RNA_monkey_fibroblast_rep2 |
Sample type |
SRA |
|
|
Source name |
fibroblast
|
Organism |
Macaca mulatta |
Characteristics |
cell type: fibroblast
|
Extracted molecule |
genomic DNA |
Extraction protocol |
The RNA extraction follows smart-seq2 protocol The RNA-seq libraries were generated using the Smart-seq2 protocol as described previously with minor modification (Picelli et al., 2014). Cells were lysed in hypotonic lysis buffer (Amresco, M334), and the polyadenylated mRNAs were captured by the PolyT primers. After ~3–10 min lysis at 72 °C, the Smart-seq2 reverse transcription reactions were performed. After pre-amplification and AMPure XP beads purification, cDNAs were sheared by Covaris and were subject to Illumina TruSeq library preparation. All libraries were sequenced on Illumina HiSeq 2500 according to the manufacturer’s instruction.
|
|
|
Library strategy |
RNA-Seq |
Library source |
genomic |
Library selection |
cDNA |
Instrument model |
HiSeq X Ten |
|
|
Description |
monkey_fibro_pac_rs_gene.fpkm.txt.gz
|
Data processing |
Basecalls performed using CASAVA version 1.8 For Hi-C sapples: sisHi-C sequencing reads were mapped, processed and iteratively corrected using HiC-Pro, a pipeline developed by Servant et al. Briefly, the read pairs were mapped to the mm9 reference genome in a two-step approach with bowtie2. Then the invalid read pairs including dangling end, self-circle ligation and duplicates were discarded. The genome was divided into bins of specific length to generate the contact maps. For global detection of contacts, a 100Kb bin size was used and a 40Kb bin size was used for examination of local domain level contacts. The raw contact counts are normalized with iterative correction. For methylation samples: STEM-seq reads were aligned to the rheMac2 genome using BSseeker2.0.8, and methylation value in bedGraph files were counted by the number of reads falling into 200bp bin in the genome. For RNA-seq samples: SMART-seq2 reads were aligned to the rheMac2 or mm9 genome assembly using tophat2 version 2.0.11, then replicates were merged together, and transcript abundance (FPKM) were calculated based on Refseq annotation using cufflinks version 2.0.2. Genome_build: rheMac2, mm9 Supplementary_files_format_and_content: The bedgraph files contains the values counted by the number of reads falling into 200bp bin in the genome. The gene fpkm txt file contains FPKM value for all samples. with number for each bin. While the validpair txt file indicates the paired interaction reads for each sample.
|
|
|
Submission date |
Jan 18, 2018 |
Last update date |
Feb 11, 2019 |
Contact name |
Wei Xie |
E-mail(s) |
xiewei121@tsinghua.edu.cn
|
Organization name |
Tsinghua University
|
Street address |
Zhongguancun north street
|
City |
Beijing |
ZIP/Postal code |
100084 |
Country |
China |
|
|
Platform ID |
GPL24522 |
Series (1) |
GSE109344 |
Reprogramming of meiotic chromatin architecture during primate spermatogenesis |
|
Relations |
BioSample |
SAMN08375212 |
SRA |
SRX3591106 |
Supplementary data files not provided |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
|
|
|
|
 |