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Sample GSM2868878 Query DataSets for GSM2868878
Status Public on Aug 01, 2018
Title scRNAseq_069_cell_67
Sample type SRA
 
Source name neural precursor cell (day 6)
Organism Mus musculus
Characteristics genetic background: BC8 (C57BL/6J x Cast/EiJ)
visual annotation for single cell data: -
Growth protocol NPCs were derived from mESCs according to Bibel M. Richter J. Schrenk K. Tucker K.L. Staiger V. Korte M. Goetz M. Barde Y.A. Differentiation of mouse embryonic stem cells into a defined neuronal lineage. Nat. Neurosci. 2004;7:1003–1009.
Extracted molecule total RNA
Extraction protocol For single cell RNA sequencing, 4000 cells were loaded onto a 10-17 μm Fluidigm C1 Single Cell mRNA Seq IFC, and cells captured according to manufacturer’s instructions. The captured cells were manually annotated under a microscope, to identify capture chambers containing cell debris, dead cells, no cells or multiple cells. Reverse transcription and cDNA preamplification was then performed in the 10-17 μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA Kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1-0.3 ng/μl. Sequencing libraries were then prepared using the Nextera XT DNA Sample Preparation Kit and Nextera XT DNA Sample Preparation Index Kit according to the Fluidigm instructions, “Using the C1™ Single-Cell Auto Prep System to Generate mRNA from Single Cells and Libraries for Sequencing.” The 96 libraries from one IFC were pooled and 150 bp paired-end sequencing performed on the Illumina HiSeq2000.
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina HiSeq 2500
 
Description Illumina i7 index: N704-TCCTGAGC
Illumina i5 index: S504-AGAGTAGA
Data processing Single-cell RNA-seq data processing: Paired-end reads were preprocessed using Trimmomatic, with the following settings: ILLUMINACLIP:Nextera_PE_adapters.fa:2:30:10:1:true LEADING:28 TRAILING:28 SLIDINGWINDOW:1:28 MINLEN:50. The reads were then aligned to mm10 using gsnap version 2015-09-29 with the following settings: --suboptimal-levels=5 -n 1 -Q –nofails, and providing splice sites from a reference file including Ensembl annotations (GRCm38 release 75) and lncRNA annotations from "Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, Rinn JL, Lander ES, Regev A. Nat Biotechnol. 2010 May;28(5):503-10" and "The evolution of lncRNA repertoires and expression patterns in tetrapods. Necsulea A, Soumillon M, Warnefors M, Liechti A, Daish T, Zeller U, Baker JC, Grützner F, Kaessmann H. Nature. 2014 Jan 30;505(7485):635-40".
Bulk RNA-seq data processing for ES to NPC timecourse: reads were mapped to mm10 using tophat version 2.0.14 with the settings --mate-inner-dist -30 --mate-std-dev 80 --library-type fr-firststrand , and providing a --transcriptome-index from a reference file including Ensembl annotations (GRCm38 release 75) and lncRNA annotations from "Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, Rinn JL, Lander ES, Regev A. Nat Biotechnol. 2010 May;28(5):503-10" and "The evolution of lncRNA repertoires and expression patterns in tetrapods. Necsulea A, Soumillon M, Warnefors M, Liechti A, Daish T, Zeller U, Baker JC, Grützner F, Kaessmann H. Nature. 2014 Jan 30;505(7485):635-40". Uniquely mapping reads from concordant read pairs were retained by filtering for a quality of 50 and the 0x2 flag (samtools view -b -q 50 -f 0x2).
Bulk RNA-seq data for cell lines with HHRz integrations or deletions: reads were mapped to mm10 using gsnap-2015-09-29 and the settings --suboptimal-levels=5 -B 5 -t 8 -n 1 -Q --nofails, and providing splice sites from a reference file including Ensembl annotations (GRCm38 release 75) and lncRNA annotations from "Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, Rinn JL, Lander ES, Regev A. Nat Biotechnol. 2010 May;28(5):503-10" and "The evolution of lncRNA repertoires and expression patterns in tetrapods. Necsulea A, Soumillon M, Warnefors M, Liechti A, Daish T, Zeller U, Baker JC, Grützner F, Kaessmann H. Nature. 2014 Jan 30;505(7485):635-40".
Bulk RNA-seq data for actinomycin D timecourse (half life calculations): reads were mapped to mm10 using gsnap-2015-09-29 and the settings --suboptimal-levels=5 -B 5 -t 8 -n 1 -Q --nofails, and providing splice sites from a reference file including Ensembl annotations (GRCm38 release 75) and lncRNA annotations from "Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, Rinn JL, Lander ES, Regev A. Nat Biotechnol. 2010 May;28(5):503-10" and "The evolution of lncRNA repertoires and expression patterns in tetrapods. Necsulea A, Soumillon M, Warnefors M, Liechti A, Daish T, Zeller U, Baker JC, Grützner F, Kaessmann H. Nature. 2014 Jan 30;505(7485):635-40".
CRAC and NET-seq data: Sequencing reads were preprocessed for standard analyses as follows:
(i) The 3’ adapter was removed (if present) using fastx_clipper.
(ii) Low quality sequence was removed using the fastx toolkit, specifically fastq_quality_trimmer -t 25, fastq_quality_filter -q 20 -p 90 and fastx_artifacts_filter.
(iii) Reads with identical sequence and 5’ inline unique molecule identifier, UMI, were collapsed, as they are likely to arise from duplication during PCR.
(iv) For CRAC, low complexity regions were trimmed from the 3’ end of reads (regions of 2 nt or more where 80 % or more of the sequence comprises one nucleotide). This is because many Mtr4-bound RNA fragments contain non-genome-encoded oligo(A) tails that can lead to apparently unique mapping of repeat RNAs.
(v) Homopolymers and dinucleotide-rich sequences were removed using prinseq-lite, with settings -min_len 18 -lc_threshold 20 -lc_method dust.
To obtain a set of reads that do not map to repetitive regions of the genome or small non-coding RNAs (e.g. retrotransposons, tRNAs, snoRNAs, rRNA), we then filtered reads as follows. Reads were mapped separately, using novoalign, to three indexes: (i) the mm10 genome, (ii) mm10 protein-coding transcripts (cDNAs), and (iii) pseudochromosomes assembled from RepeatMasker repeats, the ribosomal DNA repeat (Grozdanov et al, 2003) and gencode.vM9 small non-coding RNAs (e.g. miRNA, snoRNA, snRNA, rRNA). “Nonrepeat” reads were then defined as those that mapped better to the mm10 genome or cDNAs, than to any of the repeat RNAs or small non-coding RNAs.
We then mapped reads (either after standard preprocessing, or “nonrepeat” reads filtered as described) using bowtie2 (mode: --sensitive) with mm10.
Genome_build: mm10
Supplementary_files_format_and_content: bigWig files for single-cell RNA-seq: alignments were converted to bigWig files using picard-tools and bedtools, accounting for library size by dividing the depth at each position by the number of mapped reads then multiplying by 1000000.
bigWig files for bulk RNA-seq of the ES to NPC differentiation: IGVtools was used to convert BAM files into bigWig format. The bigWigs are not normalised for library size, and one bigWig file is provided for plus and minus strand mapping reads.
bigWig files for bulk RNA-seq of cell lines with HHRz integrations or deletions were generated from BAM files using bedtools, accounting for library size by dividing the depth at each position by the number of mapped reads then multiplying by 1000000.
bigWig files for bulk RNA-seq of cells treated with actinomycin D for RNA half life calculations were generated from BAM files using bedtools, accounting for library size by dividing the depth at each position by the number of mapped reads then multiplying by 1000000.
bigWig files for CRAC and NET-seq data: generally, bigWig files were obtained by taking uniquely mapping reads and converting to bigWig with samtools and bedtools. The "mixed" bigWig files contain data from replicate experiments that has been combined prior to generating the bigWig
 
Submission date Nov 29, 2017
Last update date May 15, 2019
Contact name Alex Charles Tuck
Organization name Friedrich Miescher Institute for Biomedical Research
Street address Maulbeerstrasse 66
City Basel
ZIP/Postal code 4058
Country Switzerland
 
Platform ID GPL17021
Series (1)
GSE107493 Deconstructing lincRNA regulation during ESC to NPC differentiation
Relations
BioSample SAMN08110104
SRA SRX3429528

Supplementary file Size Download File type/resource
GSM2868878_069_cell_67.bigWig 24.5 Mb (ftp)(http) BIGWIG
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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