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Sample GSM2943942

Query DataSets for GSM2943942

Status

Public on Jan 24, 2018

Title

Quiescent_rep1_GL1_2

Sample type

SRA

Source name

Hepatocytes

Organism

Mus musculus

Characteristics

strain: C57BL/6
genotype: Rosa-LSL-GFP-L10A
cell state: Quiescent
cell type: Hepatocytes

Treatment protocol

Fah-/- mice were hydrodynamically injected with plasmids coexpressing the Fah transgene and either GFP-L10A (for TRAP-seq) or SUN1-GFP (for ATAC-seq) fusion proteins. Liver injury was then induced and the mice were repopulated for one or four weeks prior to extracting repopulating hepatocytes. All quiescent control mice were injected with AAV8.TBG.Cre to induce hepatocyte-specific expression of GFP-L10A (for TRAP-seq) or SUN1-GFP (for ATAC-seq) and livers were harvested one week after virus injection.

Extracted molecule

polyA RNA

Extraction protocol

For TRAP-seq, livers were prepared as previously described (Heiman et al. 2014). Briefly, liver homogenates were incubated with GFP-conjugated magnetic beads to affinity purify GFP-tagged ribosomal subunit L10A along with the attached translating mRNAs. RNAs were then isolated with the Absolutely RNA Nanoprep Kit (#400753, Agilent). For ATAC-seq, hepatocyte nuclei were prepared as previously described (Fang et al. 2014) and GFP-positive nuclei were labeled with Alexa Fluor 647 anti-GFP antibody (#338006, clone FM264G, 1:25, BioLegend) and sorted using BD AriaII.
For TRAP-seq, mRNAs were isolated with the NEBNext® Poly(A) mRNA Magnetic Isolation Module (#E7490, NEB) followed by cDNA library construction with the NEBNext® Ultra RNA Library Prep Kit for Illumina® (#E7530S, NEB). For ATAC-seq, nueclei were tagmented and PCR amplified according to previously published ATAC-seq protocol (Ackermann et al. 2016).

Library strategy

OTHER

Library source

transcriptomic

Library selection

other

Instrument model

Illumina HiSeq 2500

Description

#GL1-A
Samples with the same 'GL#' are the same mouse but prepared by different investigators at separate batches. For instance, #GL1-K and #GL1-A are from the same mouse.
TrapSeqCompare.xls

Data processing

Library strategy: TRAP-Seq
For RNA-seq, poor quality sequences was trimmed from FASTQ files and then aligned to mouse genome mm9 using RUM (Grant et al. 2011). Differential gene expression was identified with EdgeR.
For ATAC-seq, individual FASTQ files were processed with the pipeline developed by the Kundaje lab (https://github.com/kundajelab/atac_dnase_pipelines) first and aligned bam files were obtained. Bam files from the same biological replicate were then merged and analyzed with the same pipeline as described above.
Genome_build: mm9
Supplementary_files_format_and_content: xls file contains the differential gene expression for the TRAP-seq data in the 'Compare' tab. The 'QuantileNormReads' and the 'RawReads' tabs contain the quantile-normalized reads and the raw read counts for the TRAP-seq data, respectively. The BigWig files contain the peak calling results for the pooled control and 1-week regeneration samples, respectively. Peaks were called based on a cut-off of p-value < 0.05.

Submission date

Jan 23, 2018

Last update date

Jan 24, 2018

Contact name

Amber Wang

E-mail(s)

wamber@upenn.edu

Phone

2674323958

Organization name

University of Pennsylvania