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Sample GSM3740200

Query DataSets for GSM3740200

Status

Public on May 21, 2019

Title

Human fetal liver (E12_163#928)

Sample type

SRA

Source name

Human fetal liver

Organism

Homo sapiens

Characteristics

sample type: Freshly isolated human fetal liver homegenate
sample id: Human fetal liver 1
Sex: Unknown
age: 15 postconceptional weeks (pcw)
developmental stage: fetal

Extracted molecule

total RNA

Extraction protocol

Human fetal tissue was dissociated by Collagenase XI enzymatic dissociation for 25 minutes at 37˚C with agitation. Samples were stained with the following primary antibodies, CD235a (349104, FITC, mouse; Biolegend), CD45 (304050, BV711, mouse; Biolegend), EpCAM (324208, APC, mouse; Biolegend), NCAM (362524, PE, mouse; Biolegend) all at 1:100 dilution and incubated for 30mins at 4˚C. DAPI (D1306, ThermoFisher Scientific) at 1:1000 dilution was used for live/dead staining. Cells were sorted using a BD FACS Aria II instrument and deposited as single cells into 96-well plates, pre-loaded with lysis buffer (1% Triton X-100, 1mM dNTP, 1μM oligo-dT30, 1:1.2x106 ERCC ExFold RNA spike-in, Recombinant RNase Inhibitor (2313B, Takara Clontech). Single-cell sequencing was performed using SmartSeq2.
RNA was converted into cDNA using SMARTScribe Reverse Transcriptase (639538, Takara Clontech) and amplified for 21 cycles (Kapa HiFi HotStart ReadyMix 2x, KK2602, KAPA Biosystems). Successful single cell libraries were identified by capillary gel electrophoresis (DNF-474-1000, High Sensitivity NGS Fragment Analysis Kit, AATI) and converted into sequencing libraries using a Nextera XT DNA Sample Preparation Kit (FC-131-1096, Illumina). Barcoded libraries were pooled and subjected to 75 base pair paired-end sequencing on a Illumina HiSeq 2500 instrument.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2500

Data processing

Raw sequencing reads were aligned using STAR and per gene counts were calculated using HTSEQ
Gene counts were further analyzed using the R package SCATER for pre-processing, quality control and normalization
To filter out bad cells from scRNA-seq analysis we used median absolute deviations (MADs) on library size, total genes detected, mitochondrial gene percentage and artificial ERCC spike in percentage. Two deviations from the median were used to remove cell outliers. For library size and total genes the lower tail outliers were excluded. For mitochondrial and ERCC spike in percentage upper tail outliers were excluded.
T-SNE analysis, clustering and gene expression performed in R
Genome_build: GRCh38
Supplementary_files_format_and_content: [Series_count_matrix.csv] Raw HTSEQ counts for all samples and feature date
[Series_feature_matrix.csv] MetaData including FACS gating population for each sample

Submission date

Apr 30, 2019

Last update date

May 21, 2019

Contact name

Joe M Segal

E-mail(s)

Joe.segal8@gmail.com

Organization name

Kings college London

Department

Centre of Stem Cell and Regenerative Medicine