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| Status |
Public on May 01, 2019 |
| Title |
HSC (Donor A) |
| Sample type |
SRA |
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| Source name |
Bone marrow hematopoietic progenitors
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| Organism |
Homo sapiens |
| Characteristics |
tissue: bone marrow
purification: Lin-CD34+CD38-CD90+CD45RA-
cell type: HSC
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| Treatment protocol |
Bone marrow (BM) samples were collected from adult healthy donors at Children’s Hospital in Boston with the approval of the Committee on Clinical Investigations Children’s Hospital Boston and consent from the subjects under the protocol #09-04-0167. Mononuclear cells (MNCs) were isolated using Ficoll-Hypaque gradient separation (Lymphoprep, STEMCELL Technologies). CD34+ cells were purified from MNCs with the human anti-CD34 MicroBeads Isolation Kit (Miltenyi Biotec) according to the manufacturer’s specifications or were purchased from commercial sources (AllCells). Seven HSPC sub-populations were purified from the CD34+ fraction of a healthy donor (Donor A) BM cells through a two-step four-way sorting using FACSAria II (BD Biosciences). The following combinations of cell surface markers were used to identify and separate the HSPC subsets. Hematopoietic stem cells (HSC): Lin-CD34+CD38-CD90+CD45RA-; multipotent progenitors (MPP): Lin-CD34+CD38-CD90-CD45RA-; multilymphoid progenitors (MLP): Lin-CD34+CD38-CD90-CD45RA+; pre-B lymphocytes / Natural Killer cells (PREB/NK): Lin-CD34+CD38+CD7-CD10+; megakaryocyte-erythroid progenitors (MEP): Lin-CD34+CD38+CD7-CD10-CD135-CD45RA-; common myeloid progenitors (CMP): Lin-CD34+CD38+CD7-CD10-CD135+CD45RA-; granulocyte-monocyte progenitors (GMP): Lin-CD34+CD38+CD7-CD10-CD135-CD45RA+. From healthy Donor B, four cell fractions were purified from BM MNCs through a four-way sorting using the following combinations of cell surface markers: Lin-CD34+CD164+; Lin-CD34lowCD164high; Lin-CD34-CD164high; Lin-CD34-CD164low. CD71 was included to identify erythroid progenitors. Immunophenotyping was performed on BM CD34+ cells labelled with CD164 in combination with HSPC subsets markers by using LSRFortessa (BD Biosciences). CD15 and CD19 were included to identify the lineage positive cells. The antibodies were as follows: CD34 PB, CD38 PE/Cy5, CD90 APC, CD10 PE/Cy7, CD135 PE, Lin BV510 (CD3, CD14, CD16, CD19, CD20, CD56 BV510), CD15 BV510, CD164 (clone 67D2) PE, CD164 FITC, CD71 PerCP/Cy5.5, CD41 APC, CD19 PE/Cy7 (all Biolegend); CD45RA APCH7, CD7 AF700, CD15 PE (all BD Biosciences), Glycophorin A (Miltenyi Biotec).
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| Extracted molecule |
polyA RNA |
| Extraction protocol |
Using inDrops, cells were encapsulated into 4-nL droplets on ice and lysed using a final concentration of 0.4% NP-40. Single-cell lysates were subject to reverse transcription at 50°C without purification of RNA (as previously described in Klein et al., Cell 2015).
Libraries were prepared as in Zilionis et al., Nat. Protoc. 2017, with modifications as described for the "FACS subsets" samples in Khoramian Tusi et al., Nature 2018.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NextSeq 500 |
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| Data processing |
Raw sequencing data were processed using the previously described (Zilionis et al., Nature Protocols 2017) inDrops.py bioinformatics pipeline, available at https://github.com/indrops/indrops, using library version "v3".
The cDNA read was trimmed using Trimomatic (5) (version 0.32; parameters: LEADING:28 SLIDINGWINDOW:4:20 MINLEN:30).
Barcodes for each read were matched against a list of the pre-determined barcodes, and errors of up to two nucleotides mismatch were corrected. Reads with a barcode separated by more than two nucleotides from the reference list were discarded. The reads were then split into barcode-specific files for mapping and UMI filtering.
The trimmed reads were aligned using Bowtie (version 1.1.1, parameters: -n 1 -l 15 -e 100 -m 200 -best -strata -a) to the human transcriptome. The reference transcriptome was built using annotations from ENSEMBL (GRCh38.85).
A custom Python and PySAM script to process mapped reads into counts of UMI-filtered transcripts per gene, as previously described (Zilionis et al., Nature Protocols 2017).
Genome_build: GRCh38.85
Supplementary_files_format_and_content: The supplementary data files include raw unique molecular identifier (UMI)-filtered counts for each single-cell transcriptome that passed filtering. Following the first header row, each row corresponds to one cell barcode. Column 1 contains the library ID. Columns 2+ contain UMI counts for each gene.
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| Submission date |
Jul 25, 2018 |
| Last update date |
May 02, 2019 |
| Contact name |
Luca Biasco |
| E-mail(s) |
l.biasco@ucl.ac.uk
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| Organization name |
Dana-Farber/Boston Children’s Cancer and Blood Disorders Center
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| Street address |
1 Jimmy Fund Way
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| City |
Boston |
| State/province |
MA |
| ZIP/Postal code |
02115 |
| Country |
USA |
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| Platform ID |
GPL18573 |
| Series (1) |
| GSE117498 |
A comprehensive single cell transcriptional landscape of human hematopoietic progenitors |
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| Relations |
| BioSample |
SAMN09714387 |
| SRA |
SRX4455330 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM3305359_HSC.raw_counts.tsv.gz |
1.8 Mb |
(ftp)(http) |
TSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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