title: FVB, 8 months, mouse 1

description:
6_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: FVB, 8 months, mouse 5

status: Public on Dec 15 2022

type: SRA

city: Cracow

first: Piotr

last: Berkowicz

address: Bobrzyńskiego 14

country: Poland

institute: Jagiellonian Centre for Experimental Therapeutics

description:
10_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)

library_source: transcriptomic

data_processing:
Adaptor sequences, primers and poly-A tails were trimmed from sequencing raw reads by Cutadapt, and the quality of the raw reads was checked by FastQC.
The raw reads were mapped towards the mouse reference genome using Star.
HTSeq software was used to count reads that mapped to the exons of the coding genes. Normalisation of the count data was performed using the TMM method.
Analysis of differentially expressed genes (DEGs) was performed using Limma Voom software.
Analyses were generated in R environment.
Assembly: GRCm38.p6
Supplementary files format and content: counts_matrix (Excel file) – file involves raw number of reads per gene for each sample
Supplementary files format and content: DEGs_FVB_vs_FVB_analysis (Excel file) – file involves number of DEGs for each measured comparison in FVB vs. FVB analysis
Supplementary files format and content: DEGs_Tg_vs_FVB_analysis (Excel file) – file involves number of DEGs for each measured comparison (month) in Tgαq*44 vs. FVB analysis
Supplementary files format and content: overrepresented_processes_Tg_vs_FVB_analysis (Excel file) - file involves number of overrepresented biological processes (from Gene Ontology database) for each measured comparison (month) in Tgαq*44 vs. FVB analysis
Supplementary files format and content: overrepresented_processes_FVB_vs_FVB_analysis (Excel file) - file involves number of overrepresented biological processes (from Gene Ontology database) for each measured comparison in FVB vs. FVB analysis
Supplementary files format and content: ageing_processes_in_HF (Tg_vs_FVB_analysis) (Excel file) - file involves the number of ‘cardiac ageing processes’ at 4-, 8-, 10-, 12-, 14 months in Tgαq*44 vs. FVB analysis; ratio of the number of 'cardiac ageing processes' to the respective number of overrepresented biological processes at each measured month in Tgαq*44 vs. FVB analysis; number of 'processes of ageing heart' (n=8) that occured as overrepresented biological processes at each measured months (4-, 8-, 10-, 12-, 14 months) in Tgαq*44 vs. FVB analysis; number of 'processes of aged heart' (n=0) that occured as DEGs in each measured months (4-, 8-, 10-, 12-, 14 months) in Tgαq*44 vs. FVB analysis
Supplementary files format and content: ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file) – file involves the number of ‘cardiac ageing genes’ at 4-, 8-, 10-, 12-, 14 months in Tgαq*44 vs. FVB analysis; ratio of the number of 'cardiac ageing genes' to the respective number of DEGs at each measured month in Tgαq*44 vs. FVB analysis; number of 'genes of ageing heart' (n=26) that occured as DEGs at each measured months (4-, 8-, 10-, 12-, 14 months) in Tgαq*44 vs. FVB analysis; number of 'genes of aged heart' (n=8) that occured as DEGs in each measured months (4-, 8-, 10-, 12-, 14 months) in Tgαq*44 vs. FVB analysis
Supplementary files format and content: annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file) – file involves number of DEGs that were or were not annotated to overrepresented biological processes (from Gene Ontology database) in the respective comparisons in FVB vs. FVB analysis
Supplementary files format and content: annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file) – file involves number of DEGs that were or were not annotated to overrepresented biological processes (from Gene Ontology database) in the respective comparisons (months) in Tgαq*44 vs. FVB analysis
Supplementary files format and content: gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file) – file involves 26 biological processes (from Gene Ontology database) which were overrepresented in each measured months (4-, 8-, 10-, 12-, 14 months) in Tgαq*44 vs. FVB analysis. This file also involves values of gene frequency in 26 overrepresented biological processes at 4-, 8-, 10-, 12-, 14 months
Supplementary files format and content: 156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file) – file involves 156 genes which were differentially expressed in each measured months (4-, 8-, 10-, 12-, 14 months) in Tgαq*44 vs. FVB analysis
Supplementary files format and content: genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file) – file involves the number of ‘genes of aged heart’(n=454) and ‘processes of aged heart’ (n=56) which are presented as DEGs or overrepresented biological processes (from Gene Ontology database) that occured only in 14- vs. 4-month-old FVB mice
Supplementary files format and content: genes_and_processes_ageing_heart_FVBvs.FVB (Excel file) - file involves the number of ‘genes of ageing heart’(n=481) and ‘processes of ageing heart’ (n=55) which are presented as DEGs or overrepresented biological processes (from Gene Ontology database) that occured in 14- vs. 4-month-old FVB mice and at least in one comparison between 8-, 10-, 12- vs. 4-month-old FVB mice

molecule: total RNA

organism: Mus musculus

source_name: heart (apex of left ventricle)

growth_protocol: Mice were fed a standard chow diet, given water ad libitum, and kept in pathogen-free conditions (22–25 °C, 45–65% humidity, 12 h light/12 h dark cycle).

extract_protocol:
Apexes of LV were dissected from hearts and homognized in TRIzol reagent. Total RNA was extracted from cardiac tissues (i.e., apex of the heart) using an RNeasy Mini Kit (Qiagen) with DNAse treatment. 1 ug of total RNA was used for the construction of sequencing libraries.
RNA libraries for RNA-seq were prepared with Sense mRNA-Seq Library prep Kit v2 (Lexogen) according to the manufacturer’s protocol. Five biological replicates in each group for a total of 50 samples (5 replicates*(5 time points)*(2 strains)) were submitted for RNA sequencing.

treatment_protocol: x

tag: strain

value: FVB

tag: genotype

value: wild-type

tag: disease

value: x

tag: Sex

value: female

tag: age

value: 8 months

tag: tissue

value: heart (apex of left ventricle)


title: FVB, 4 months, mouse 5

description:
5_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)

value: 4 months


title: FVB, 8 months, mouse 3

description:
8_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: FVB, 14 months, mouse 4

description:
25_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)

value: 14 months


title: FVB, 14 months, mouse 1

description:
22_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: FVB, 4 months, mouse 4

description:
4_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: B6.CAST, E6.5, ExE, H3K36me3, rep2 (ChIP-seq)

city: Cambridge

first: Laura

last: Biggins

address: Babraham Research Campus

department: Bioinformatics

country: United Kingdom

institute: The Babraham Institute

library_source: genomic

data_processing:
bcl2fastq:  FastQ sequence files were quality and adaptor trimmed with Trim Galore v0.4.2 using default parameters.
alignment: Mapping of ChIP-seq data was performed with Bowtie v2.2.9 against the mouse GRCm38 genome assembly. The resulting hits were filtered to remove mappings with a MAPQ scores < 20.
Assembly: GRCm38
Supplementary_files_format_and_content:  tiled_window_report:  SeqMonk annotated probe report over 5kb running windows, quantitated as RPKM values.

molecule: genomic DNA

source_name: Extra-embryonic ectoderm

extract_protocol:
Natural timed matings were set up between C57BL6/Babr and CAST animals, and embryos were collected on embryonic day 6.5 (E6.5). ExE (N=8) samples were pooled (an estimated ~2500 cells), washed in PBS, and then flash frozen in 10µL of nuclear lysis buffer (Sigma).  Samples were thawed on ice and permeabilised with 0.1% Triton-X/0.1% deoxycholate in PBS on ice.  MNase digestion was completed using 200U of micrococcal nuclease (New England Biolabs) in prepared digestion buffer.  Samples were digested at 21°C for 7.5 minutes and the reaction was stopped with 100mM EDTA.  Chromatin samples were precleared with Protein A/G beads rotating at 4°C for 2 hours and antibodies were bound to beads rotating at 4°C for 3 hours.  Prior to the immunoprecipitation with antibody-bound beads, each chromatin sample was divided into 3-4 aliquots: one for each antibody and one 10% input control.  For each immunoprecipitation, 250ng of anti-H3K4me1 (Active Motif, 39298), 125ng of anti-H3K27ac (Abcam, ab4729), 250ng of anti-H3K4me3 (Diagenode K02921004), 125ng of anti-H3K27me3 (Millipore 07-449) or 250ng of anti-H3K36me3 (Diagenode C15410192)  antibodies were used.  Chromatin was added to the antibody-bound beads and rotated overnight at 4°C.  This was proceeded by two low-salt washes, one high-salt wash, and the DNA was then eluted from the beads at 65°C for 1.5 hours.  DNA from immunoprecipitated chromatin or input was purified using solid phase reversible immobilization (SPRI) purification using Sera-Mag carboxylate-modified Magnetic SpeedBeads (Fisher Scientific) at a 1.8:1 ratio.  Library preparation was completed using the MicroPlex Library Preparation kit v2 (Diagenode) using Sanger 8-base indices for multiplexing, as per the manufacturers recommendations, and all libraries were amplified using 14 amplification cycles.  Libraries were purified with SPRI beads at a 1:1 ratio, and size and quality were assessed using a 2100 Bioanalyzer Instrument (Agilent) and Kapa library qPCR quantitation (Illumina).  Samples were multiplexed using 75bp paired-end sequencing on Illumina NextSeq500.
MNase digestion was completed using 200U of micrococcal nuclease (New England Biolabs) in prepared digestion buffer.  Samples were digested at 21°C for 7.5 minutes and the reaction was stopped with 100mM EDTA.  Chromatin samples were precleared with Protein A/G beads rotating at 4°C for 2 hours and antibodies were bound to beads rotating at 4°C for 3 hours.  Prior to the immunoprecipitation with antibody-bound beads, each chromatin sample was divided into 3 aliquots: one for each antibody and one 10% input control.  For each immunoprecipitation, 250ng of anti-H3K4me1 (Active Motif, 39298) or 125ng pf anti-H3K27ac (Abcam, ab4729) antibodies were used.  Chromatin was added to the antibody-bound beads and rotated overnight at 4°C.  This was proceeded by two low-salt washes, one high-salt wash, and the DNA was then eluted from the beads at 65°C for 1.5 hours.  DNA from immunoprecipitated chromatin or input was purified using solid phase reversible immobilization (SPRI) purification using Sera-Mag carboxylate-modified Magnetic SpeedBeads (Fisher Scientific) at a 1.8:1 ratio.  Library preparation was completed using the MicroPlex Library Preparation kit v2 (Diagenode) using Sanger 8-base indices for multiplexing, as per the manufacturers recommendations, and all libraries were amplified using 14 amplification cycles.  Libraries were purified with SPRI beads at a 1:1 ratio, and size and quality were assessed using a 2100 Bioanalyzer Instrument (Agilent) and Kapa library qPCR quantitation (Illumina).  Samples were multiplexed using 75bp paired-end sequencing on Illumina NextSeq500.

tag: cell type

value: Extra-embryonic ectoderm

value: C57BL6/Babr x CAST/Ei

value: Wildtype

tag: chip antibody


title: FVB, 4 months, mouse 2

description:
2_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: FVB, 4 months, mouse 3

description:
3_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: B6.CAST, E6.5, ExE, H3K4me3, rep2 (ChIP-seq)

value: anti-H3K4me3 (Diagenode K02921004)


title: B6.CAST, E6.5, ExE, H3K36me3, rep1 (ChIP-seq)


title: FVB, 4 months, mouse 1

description:
1_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: B6.CAST, E6.5, ExE, H3K27me3, rep2 (ChIP-seq)

value: anti-H3K27me3 (Millipore 07-449)


title: FVB, 10 months, mouse 5

description:
15_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)

value: 10 months


title: B6.CAST, E6.5, ExE, H3K27me3, rep1 (ChIP-seq)


title: B6.CAST, E6.5, ExE, H3K4me1, rep1 (ChIP-seq)

value: anti-H3K4me1 (Active Motif, 39298)


title: B6.CAST, E6.5, ExE, H3K4me3, rep1 (ChIP-seq)


title: B6.CAST, E6.5, ExE, H3K27ac, rep2 (ChIP-seq)

value: anti-H3K27ac (Abcam, ab4729)


title: B6.CAST, E6.5, ExE, H3K4me1, rep2 (ChIP-seq)


title: B6.CAST, E6.5, ExE, H3K27ac, rep1 (ChIP-seq)


title: FVB, 8 months, mouse 4

description:
9_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)


title: Dnmt3b WT, E12.5, placenta

library_source: transcriptomic single cell

data_processing:
Standard parameters were used for bcl2fastq and for library barcode splitting
Assembly: mm10
Supplementary_files_format_and_content: Mapping and quantitation of 10X single nuclei RNA-Seq data was performed with CellRanger v6.0.0 against the gex-mm10-2020-A transcriptome using the --include-introns option.

source_name: Placenta

extract_protocol:
Natural timed matings between heterozygous females and males were used for the Dnmt3b KO strain to generate KO and WT embryos. E12.5 placentas were collected and a tail clip was used for genotyping. Single nuclei were isolated as described in the ‘Frankenstein’ protocol, available through 10X Genomics (https://www.10xgenomics.com/resources/customer-developed-protocols) and published adaptations for mouse placenta. Following collection and genotyping, Dnmt3b KO and WT E12.5 placentas were processed in parallel immediately for single nuclei isolation and 10X Genomics RNA-seq preparation. Placentas were first chopped with a razor blade in 1mL nuclei EZ lysis buffer (Sigma) for 2 mins, followed by homogenisation in a Dounce homogenizer. Nuclei were filtered through a 30µm filter, and then pelleted by centrifugation at 500g for 5 mins at 4°C. Nuclei were resuspended in fresh nuclei EZ lysis buffer, pelleted and then resuspended in nuclei wash and resuspension buffer (1% BSA, 0.2U/µL RNase Inhibitor, PBS). Nuclei were gently resuspended, pelleted and resuspended in fresh nuclei wash and resuspension buffer. Nuclei were passed again through a 30µm filter, before visual inspection of nuclei with a haemocytometer. Nuclei were then stained with DAPI (adding 1 µL of 1mg/mL DAPI) before a total of 10,000 nuclei per sample were flow sorted using the BD FACSAria Fusion sorter with 70µm nozzle into RT reaction mix (10X Genomics). Samples were immediately processed to cDNA using the Chromium Controller (10X Genomics), followed by 3’ single-nuclei RNA-seq library preparation (10X Genomics).  Libraries were multiplexed for sequencing on an Illumina NextSeq500.
Samples were immediately processed to cDNA using the Chromium Controller (10X Genomics), followed by 3’ single-nuclei RNA-seq library preparation (10X Genomics).  Libraries were multiplexed for sequencing on an Illumina NextSeq500.
single-nuclei RNA-seq

value: Placenta


title: Dnmt3b KO, E12.5, placenta

value: Dnmt3b KO


title: FVB, 8 months, mouse 2

description:
7_sample (column in counts_matrix)
counts_matrix (Excel file)
DEGs_FVB_vs_FVB_analysis (Excel file)
DEGs_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_Tg_vs_FVB_analysis (Excel file)
overrepresented_processes_FVB_vs_FVB_analysis (Excel file)
ageing_processes_in_HF (Tg_vs_FVB_analysis)(Excel file)
ageing_genes_in_HF (Tg_vs_FVB_analysis)(Excel file)
annotated_DEGs_to_overrepresented_processes_in_FVBvsFVB (Excel file)
annotated_DEGs_to_overrepresented_processes_in_Tgvs.FVB (Excel file)
gene_freq_in_common_overrepresented_processes_4-14_months_TgvsFVB (Excel file)
156_common_DEGs_for_4-14months_Tgvs.FVB (Excel file)
genes_and_processes_of_aged_heart_FVBvs.FVB (Excel file)
genes_and_processes_ageing_heart_FVBvs.FVB (Excel file)

value: FVB

value: wild-type


title: T2D+AAV-ctr2

city: La Jolla

first: Christopher

last: Benner

state: California

address: 9500 Gilman Dr. MC 0640

department: Medicine

country: USA

institute: University of California, San Diego (UCSD)

data_processing:
Basecalling, demultiplexing, and adapter trimming was performed using Illumina's bcl2fastq (v2.20.0.422)
RNA-seq reads were aligned to the GRCm38/mm10 assembly of the mouse genome using STAR (version 2.5.2a) with default parameters
Gene expression values were calculated across mouse GENCODE defined transcript exons using HOMERs analyzeRepeats.pl command. Raw read totals per gene were used to identify differentially expressed genes between each sample group using DESeq2 and normalized using DESeq2's rlog function to generate log2 gene expression values.
Genome_build: hg38
Supplementary_files_format_and_content: Table of normalized log2 counts (rlog) per gene and differential expression information (tab-delimited text) Columns: Gene Symbol, Ensembl ID, chr, start, end, strand, transcript length, annotation, sample1 rlog, sample2 rlog…, DESeq2 log2 fold change, DESeq2 p-value, DESeq2 adj. p-value for 3 separate pairwise comparisons, additional annotation columns.

source_name: primary mouse heart tissue

growth_protocol: Type 2 diabetes (T2D) was induced in 12 week old C57BL/6 mice with a high fat diet (HFD, 60% calories from fat) (Envigo) and a single STZ injection of 75mg/kg (Fricovsky ES, Am. J. Phys. Reg. Int. Comp. Phys. 2013). Control groups were maintained on regular lab chow. T2D was defined 20 weeks after starting HFD with: fasting glucose levels >110 mg/dl, elevated glucose levels after glucose challenge, and elevated fed-state insulin (325 pmol/L vs. decreased insulin levels in T1D (32 pmol/L) and vs. control mice (100pmol/L)).

extract_protocol:
Mouse hearts were lysed in Trizol (Thermo) and RNA was extracted by adding chloroform. RNA was then precipitated from the aqueous phase using isopropyl alcohol, washed with 70% ethanol and resuspended in diethyl pyrocarbonate (DEPC)-treated ddH20.
RNA libraries were prepared for sequencing using standard Illumina protocols (TruSeq Stranded Total RNA Library kit, ribosomal RNA depleted)

treatment_protocol: MCUb was cloned from mouse heart and subsequently a dominant negative MCUb was generated by introducing two point mutations (CTG>CAG and TGT>AGT) resulting in W246R and V251E using the QuikChange Site-Directed Mutangenesis kit (Stratagene). In vivo AAV transgene delivery was performed by direct jugular vein injection as already described (Suarez J, JBC 2018). Empty AAV (AAV-Empty) or AAV encoding C-terminal FLAG-tagged murine MCUb W246R/V251E (AAV-dnMCU) were injected 16-18 weeks after injection with STZ (3x1011 genome copies in 100 μl). Experiments were carried out 5-6 months after STZ/HFD treatment and 4 weeks after AAV injection.

tag: disease state

value: Type 2 diabetes (T2D)

tag: transgene over expression

value: AAV empty vector

tag: genotype/variation


title: T2D+AAV-ctr1


title: CTR1

value: normal

value: control


title: T2D+AAV-dnMCUb1

value: AAV dnMCUb

value: T2D mice overexpressing dnMCUb


title: T2D+AAV-dnMCUb2


title: Target_HDF_PPIB_mock_BEU

city: BeiJing

first: Kai

last: Li

address: Yi He Yuan Street No.5

department: School of Life Science

country: China

institute: Peking University

data_processing:
Trim_galore (version0.6.6 http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) for quality control and adaptor trimming. The minimum quality threshold was set to 20. The remaining reads were further processed by removing the random barcode. Processed reads were mapped to hg19 or mm10.
For CeU-seq, the data processing requires multiple input and treatment samples (including replicates) that are sequencing separately to give multiple fastq files; the processed data were calculated based on these multiple input and treatment groups data to give a single summarized table. Similarly for Target-seq, each target contains input and treatment groups that produced multiple fastq files; the processed data requires calculating the signal in both input and treatment of multiple data, and all results of all targets were summarized in a single table file.
Assembly: hg19/mm10
Library strategy: Target-seq

organism: Homo sapiens

source_name: primary human dermal fibroblast

growth_protocol: HEK293T cells and primary mouse embryonic fibroblasts (MEFs) were maintained under 5% CO2 at 37 °C in DMEM medium (Corning) supplemented with 10% FBS (Gibco) and 1% penicillin/streptomycin (Gibco). The primary human dermal fibroblasts (HDF) and primary human bronchial epithelial cells (HBE) were cultured in Fibroblast Growth Medium (iXCells, MD-0011) and Bronchial Epithelial Cell Growth Basal Medium (Lonza, CC-3171), respectively. Both media were supplemented with 1% penicillin–streptomycin. The B-Lymphocytes were cultured in 1640 (Corning) with 15% FBS and 1% penicillin–streptomycin.

extract_protocol:
Total RNA was extracted from cells using TRIzol reagent (Life Technologies). The selection of polyA(+) RNA was performed using Dynabeads™ Oligo(dT)25 (Invitrogen).
RNA-seq of transfected HEK293T cells were performed with TRACE-seq method. For CeU-seq and Target-seq, the RNA pellet was dissolved in 20 μl 5 mM EDTA, incubated at 80°C for 5 minutes, and quickly chilled on ice. Next, 10 μl denatured RNA was transferred into 100 μl in BEU buffer (50 mM Bicine, pH 8.5, 4 mM EDTA, 7 M urea) with 0.2 M CMC (Sigma, Cat#C106402, 95%) as the CMC+ sample, or into 100 μl BEU buffer as the CMC- control sample. Both CMC+ and CMC- samples were then incubated at 37 °C for 20 min, followed by purification with ethanol precipitation. The RNA pellets were then dissolved in 50 μl Na2CO3 buffer (50 mM Na2CO3 pH 10.4, 2 mM EDTA) and incubated at 37 °C for 6 h, followed by ethanol precipitation.

treatment_protocol: HEK293T cells were seeded in six-well plates and incubated for 24 h, followed by transfection. 72 h post transfection, total RNA was extracted from cells. For AAV-mediated cell transduction, 24 hours after seeding, HDF, HBE and B-Lymphocytes were transduced by AAV6.2 (EEF2-U1570/EEF2-U2881/PPIB-U272/CFTR-W1282X), and MEFs were transduced by AAVDJ (mIdua-W392X). 7 days after transduction, cells were collected.

value: primary human dermal fibroblast

tag: passages


title: Target_HDF_PPIB_RESTART_CMC


title: Target_HDF_PPIB_mock_CMC


title: Target_HDF_PPIB_RESTART_BEU


title: Target_HBE_PPIB_mock_CMC

source_name: primary human bronchial epithelial cell

value: primary human bronchial epithelial cell


title: Target_HBE_PPIB_mock_BEU


title: Target_HBE_PPIB_RESTART_CMC


title: Target_HDF_EEF2_mock_CMC


title: Target_HBE_PPIB_RESTART_BEU


title: Target_HDF_EEF2_mock_BEU


title: Target_HDF_EEF2_RESTART_BEU


title: Target_HBE_EEF2_mock_CMC


title: Target_HBE_EEF2_mock_BEU


title: Target_HBE_EEF2_RESTART_BEU


title: Target_reporter_TGA_gACA19_DKC1_CMC

source_name: human embryonic kidney cell (HEK293T)

tag: cell line

value: human embryonic kidney cell


title: Target_reporter_TGA_gACA19_DKC1_BEU


title: Target_reporter_TAG_gACA19_DKC1_CMC


title: Target_reporter_TAG_gACA19_DKC1_BEU


title: Target_reporter_TAA_gACA19_DKC1_CMC


title: CTR2


title: Target_reporter_TGA_gCtrl_BEU


title: Target_reporter_TAA_gCtrl_CMC


title: Target_reporter_TAG_gCtrl_CMC


title: Target_reporter_TAA_gCtrl_BEU


title: CeU_gACA19_DKC1_2_CMC

data_processing:
Trim_galore (version0.6.6 http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) for quality control and adaptor trimming. The minimum quality threshold was set to 20. The remaining reads were further processed by removing the random barcode. Processed reads were mapped to hg19 or mm10.
For CeU-seq, the data processing requires multiple input and treatment samples (including replicates) that are sequencing separately to give multiple fastq files; the processed data were calculated based on these multiple input and treatment groups data to give a single summarized table. Similarly for Target-seq, each target contains input and treatment groups that produced multiple fastq files; the processed data requires calculating the signal in both input and treatment of multiple data, and all results of all targets were summarized in a single table file.
Assembly: hg19/mm10
Library strategy: CeU-seq

molecule: polyA RNA


title: CeU_gACA19_DKC1_1_CMC


title: CeU_gACA19_2_CMC


title: CeU_gACA19_DKC1_2_BEU


title: Target_HDF_EEF2_RESTART_CMC


title: Target_reporter_TAG_gCtrl_BEU


title: CeU_gACA19_1_CMC


title: CeU_gACA19_1_BEU


title: Target_HBE_EEF2_RESTART_CMC


title: CeU_gCtrl_2_BEU


title: CeU_gCtrl_2_CMC


title: CeU_gCtrl_1_CMC


title: CeU_gACA19_2_BEU


title: Target_reporter_TAA_gACA19_DKC1_BEU


title: CeU_Vec_2_BEU


title: CeU_Vec_1_CMC


title: CeU_Vec_2_CMC


title: CeU_Vec_1_BEU


title: Target_reporter_TGA_gCtrl_CMC


title: SCLC_PDX#3_ROR2low-2

city: Kumamoto

first: Takaaki

last: Ito

address: 325, Izumi-cho, Kita-ku

country: Japan

institute: Kumamoto Health Science University

data_processing:
Basecalls and conversion to FASTQ files were performed using Basesapce online (Illumina).
Sequencing reads were trimmed for adaptor sequence, and aligned to human transcriptome (GRCh37) and quantified with Salmon (version 1.3.0) with default settings.
Differential expression testing was performed with DESeq2 (version 1.28.1).
Assembly: GRCh37
Supplementary files format and content: Tab-delimited text files include TPM values for every gene and every sample.
Supplementary files format and content: Tab-delimited text files include p-value and q-value for every genes.

source_name: lung

extract_protocol:
For the PDX#3, ROR1high and ROR1low cells were collected directly into CDS Sorting Solution by FACS sorting, then cDNA was synthesized without RNA pulicatino using SMART-seq HT (Takara). For ROR2-KO cells, RNA was extracted using RNeasy Mini Kit (Qiagen).
For the PDX#3, the RNA-seq library was preparad using a Nextera XT Library Prep Kit (Illumina). For ROR2-KO cells, the reverse transcription reaction and NGS library preparation were performed using TruSeq Stranded mRNA Library Prep Kit (Illumina).

value: lung

value: PDX#3 (in house)

value: Small cell lung cancer


title: SCLC_PDX#3_ROR2low-3


title: SCLC_PDX#3_ROR2low-1


title: SCLC_PDX#3_ROR2high-3


title: SCLC_PDX#3_ROR2high-2


title: CeU_gACA19_DKC1_1_BEU


title: SCLC_PDX#3_ROR2high-1


title: HEK293T_SMN1W190X_gACA19_DKC1_CMC

data_processing:
Trim_galore (version0.6.6 http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) for quality control and adaptor trimming. The minimum quality threshold was set to 20. The remaining reads were further processed by removing the first 6nt random barcode in the 5’ end and  4nt random barcode in the 3’ end.
Processed reads were mapped to hg19 (UCSC refseq hg19).
The gene expression level was quantified as FPKM by Cufflinks.
Genome_build: hg19, UCSC Genome Browser

growth_protocol: HEK293T cells were maintained under 5% CO2 at 37 °C in DMEM medium (Corning) supplemented with 10% FBS (Gibco) and 1% penicillin/streptomycin (Gibco)

extract_protocol:
Total RNA was extracted from cells using TRIzol reagent (Life Technologies). The selection of polyA(+) RNA was performed using Dynabeads™ Oligo(dT)25 (Invitrogen).
RNA-seq of transfected HEK 293T cells were performed with recently developed TRACE-seq method3. Briefly, total RNA was first extracted from cells using TRIzol reagent (Life Technologies). Then, TRACE-seq libraries were constructed by seamless steps including reverse transcription by oligo dT primers, Tn5 transposase tagmentation and gap filling & PCR. After enrichment, the library was purified twice using 0.8X Agencourt AMPure XP beads (Beckman Coulter) and eluted in 10 μl nuclease-free water. The concentration of resulting libraries was determined by Qubit 2.0 fluorometer with the Qubit dsDNA HS Assay kit (Invitrogen) and the size distribution of libraries was assessed by Agilent 4150 TapeStation System with High Sensitivity D1000 ScreenTape. Finally, libraries were sequenced on the Illumina Hiseq X10 platform which generated 2 x 150 bp of paired-end raw reads. Targeted amplicon sequencing was also performed in sample 2, 4, 6, 8. The selection of polyA(+) RNA was performed using Dynabeads™ Oligo(dT)25 (Invitrogen). Then, 10 μg polyA(+) RNA was fragmented to ~200 nt at 94 ºC for 2.5 minutes using the magnesium RNA fragmentation buffer (New England Biolabs), purified by ethanol precipitation. To disrupt the RNA secondary structure, the RNA pellet was dissolved in 20 μl 5 mM EDTA, incubated at 80°C for 5 minutes, and quickly chilled on ice. Next, 10 μl denatured RNA was transferred into 100 μl in BEU buffer (50 mM Bicine, pH 8.5, 4 mM EDTA, 7 M urea) with 0.2 M CMC (Sigma, Cat#C106402, 95%) as the CMC+ sample, or into 100 μl BEU buffer as the CMC- control sample. Both CMC+ and CMC- samples were then incubated at 37 °C for 20 min, followed by purification with ethanol precipitation. The RNA pellets were then dissolved in 50 μl Na2CO3 buffer (50 mM Na2CO3 pH 10.4, 2 mM EDTA) and incubated at 37 °C for 6 h, followed by ethanol precipitation. Next, the RNA pellets were dissolved in 10 μl RNase free water. 500ng CMC-labeled RNA was mixed with 1.25 μl 100 μM Random Hexamer primers (Thermo), and the mixtures were denatured at 65°C for 5 min followed by chilling on ice. Next, 8 μl freshly prepared 2.5× reverse transcription buffer (125 mM Tris, pH 8.0, 15 mM MnCl2, 187.5 mM KCl, 1.25 mM dNTPs, 25 mM DTT) were added to the RNA-primer mixtures and the mixture were incubated at 25°C for 2 min. Then 1 μl SuperScript II reverse transcriptases (Thermo) were added, and the reactions were carried out at 25°C for 10 min, 42°C for 3 h and 70°C for 15 min. Next, the first round of on-target or off-target amplicons was PCR amplified for 15 cycles with gene-specific primers according the following reagents: 1 μl cDNA, 5 μl Q5 PCR mix (NEB), 0.4 ul of 10 μM specific primers and 3.6 μl RNase free water. And each primer pair contained a 10-nt unique molecular identifier (UMI) to enhance the accuracy. Purification of PCR products using 1.8x AMPure XP beads and then 8% TBE gel to remove the excess of primers. The purified PCR products were subjected to the second round of PCR amplification with the following primers: 5’AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT3’,5’CAAGCAGAAGACGGCATACGAGATXXXXXXGTGACTGGAGTTCAGACGTGTGCTCTTCCGATC3’ (XXXXXX represents index sequence). PCR products were purified by 1.8x AMPure XP beads (backman) and then 8% TBE gel. The libraries were sequenced on Illumina Hiseq X-ten with PE 2 x 150 bp read length.

treatment_protocol: HEK293T cells were seeded in six-well plates and incubated for 24 h, followed by co-transfection of 2 μg ALDOB-W148X (or SMN1-W190X) and 2 μg gACA19 / gCtrl / empty vector (Vec) together with or without 500 ng DKC1-isoform3 (iso3) constructs. 72 h post transfection, total RNA was extracted from cells.

tag: transfection

value: SMN1W190X, gACA19 and DKC1


title: HEK293T_SMN1W190X_gACA19_DKC1_BEU


title: HEK293T_ALDOBW148X_ACA19_DKC1_BEU

value: ALDOBW148X, ACA19 and DKC1


title: HEK293T_ALDOBW148X_ACA19_DKC1_CMC


title: HEK293T_SMN1W190X_gACA19_BEU

value: SMN1W190X and gACA19


title: HEK293T_ALDOBW148X_gACA19_CMC

value: ALDOBW148X and gACA19


title: HEK293T_SMN1W190X_gACA19_CMC


title: CeU_gCtrl_1_BEU


title: HEK293T_ALDOBW148X_gACA19_BEU


title: HEK293T_SMN1W190X

value: SMN1W190X and Vec


title: HEK293T_SMN1W190X_gCtrl

value: SMN1W190X and gCtrl


title: HEK293T_SMN1W190X_gACA19


title: HEK293T_ALDOBW148X_ACA19_DKC1


title: Canton-S, adult eye, 3-Day old, Male, scRNA-seq

city: Houston

first: Kelvin

last: Yeung

state: TX

address: One Baylor Plaza, Room S242

department: Pathology

institute: Baylor College of Medicine

description:
10x Genomics
total RNA from whole single cell

data_processing:
Cell Ranger software v6.0.1 (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger) was used to process the fastq sequencing files to generate the barcode files, genes files and counts matrix files for each data set.
Assembly: dm6
Supplementary files format and content: Tab-separated values files and matrix files

organism: Drosophila melanogaster

source_name: Adult compound eye

growth_protocol: Flies were raised at 25°C on cornmeal agar food as per standard protocols.

extract_protocol:
40 adult eyes were dissected into 500 μL Rinaldini solution with 1.9 μM Actinomycin D (Sigma-Aldrich, A-1410) in a 2 mL LoBind Eppendorf tube on ice. 25 μL of 100 mg/mL Collagenase (Sigma-Aldrich, C-9697) was added to start the dissociation. The tube was placed flat onto a horizontal shaker and shaken at 250 rpm at 32°C. Adult eyes in dissociation solution were gently pipetted up and down 30 times every 10 minutes with a P1000 tip. Incubation and pipetting were repeated until only single cells were observed in the solution; usually this takes 25-30 minutes. Dissociation was stopped by adding 500 μL of ice cold Rinaldini solution. Dissociated single cells were filtered with an 8 μm filter, where single cells were allowed the flow through by gravity into a new 2 mL LoBind Eppendorf tube. 1mL ice cold Rinaldini solution with 1% bovine serum albumin (BSA) was added to the filter and drain by gravity to wash off any stuck cells on the filter. The flow through was pooled with the filtered single cells. Filtered single cells were pelleted by centrifugation at 50 g for 5 minutes at 4°C. Pelleted single cells were resuspended and washed with 1 mL Rinaldini solution + 1% BSA using a wide-bore P1000 tip. Washed cells were pelleted by centrifugation and resuspended in about 50 μL of Rinaldini solution + 1% BSA. Cell viability was assayed by staining a 2-5 μL aliquot of single cells with Hoescht-PI dye. Samples with higher than 95% viability and a concentration of ~1,000 cells / μL were chosen for cDNA library construction.
Single cell libraries were prepared according to Chromium Next GEM Single Cell 3’ Reagent Kit v3.1 kit (10x Genomics). Briefly, single cells, reverse transcription (RT) reagents, Gel Beads containing bardcoded oligonucleotides and oil were loaded on a 10x Genomics Chromium Controller to generate single cell Gel Beads-In-Emulsions (GEMS). Full length cDNA was synthesized and barcoded for each single cell. GEMs were then broken and cDNAs from each single cell were pooled. Following clean up using Dynabeads MyOne Silane Beads, cDNAs were amplified by PCR. Amplified product was fragmented to optimal size before end-repair, A-tailing and adaptor ligation. Final cDNA libraries were generated by amplification. KAPA Library Quanitification kit (Roche) was used to quantify libraries.

treatment_protocol: Freshly eclosed adult flies were set aside and aged in cornmeal agar food vials at 25C. After aging to the appropriate age, adult eyes were dissected.

value: Adult compound eye

value: Canton-S

value: 3 days after eclosion


title: Canton-S, adult eye, 1-Day old, Male, scRNA-seq

value: 1 day after eclosion


title: Canton-S, adult eye, 7-Day old, Male, scRNA-seq

value: 7 days after eclosion


title: HEK293T_ALDOBW148X

value: ALDOBW148X and Vec


title: HEK293T_ALDOBW148X_gACA19


title: ced-6 enhancer libraries rep1 STARR-seq

city: Wien

first: Bernardo

middle: P

last: de Almeida

address: Campus-Vienna-Biocenter 1

country: Austria

institute: Research Institute of Molecular Pathology (IMP)

data_processing:
Dedicated bowtie indices were created for each enhancer position’s N8 library and combined with an oligo library of thousands of wildtype enhancers and negative sequences (de Almeida et al., 2022) for normalization, all 249 bp-long sequences. UMI-STARR-seq RNA and DNA input reads (paired-end 150 bp) were mapped to these dedicated bowtie indices using Bowtie v.1.2.2 (Langmead et al., 2009). Since the N8 variants were all positioned in the last 150 nt of each enhancer, we allowed for flexible mapping in the beginning of the fragments to increase the number of mapped reads while keeping high sensitivity for the different enhancer variants. Specifically, we trimmed the forward reads to 36 bp and mapped them to the indices allowing for 3 mismatches; the full 150 bp-long reverse reads were mapped with no mismatches, to identify all sequence variants; paired-end reads with the correct position, length and strand were kept. This mapping strategy was used for both DNA and RNA reads. For paired-end DNA and RNA reads that mapped to the same variant, we collapsed those that have identical UMIs (10 bp, allowing one mismatch) to ensure the counting of unique molecules.
We excluded oligos with less than 5 reads in any of the input replicates and less than 1 read in any of the RNA replicates. The enhancer activity of each sequence in each screen was calculated as the log2 fold-change over input, using all replicates, with DESeq2 (Love et al., 2014). We used the counts of wildtype negative regions in each library as scaling factors between samples.
Assembly: dm3 (custom library)
Supplementary files format and content: Table of all enhancers with random 8nt variants at different positions (n=536279), with genomic coordinates, DNA sequence of variants, read counts and enhancer activity (log2) in each library.

source_name: S2 cells

growth_protocol: Schneider 2 cells were grown in Schneider’s Medium supplemented with 10% heat inactivated FBS at 27ºC. Cells were passaged every 2-3 days.

extract_protocol:
24h after electroporation, total RNA was extracted using the RNeasy Maxi kit (Qiagen; cat. no. 75162), followed by polyA+ RNA isolation using Invitrogen Dynabeads Oligo(dT)25 (scaling up the manufacturer’s protocol accordingly; cat. no. 61005) and DNase treatment with Ambion Turbo DNase (cat. no. AM2239) at a concentration of at most 200 ng/µl for 30 minutes (min) at 37°C. The reactions were then subjected to Qiagen RNeasy MinElute reaction clean-up (cat. no. 74204), for Turbo DNase inactivation and RNA concentration.  After reverse transcription and second strand synthesis a unique molecular identifier (UMI) was added to each transcript. This is followed by two nested PCR steps, each with primers that are specific to the reporter transcripts such that STARR-seq does not detect endogenous cellular RNAs. See Neumayr et al., Curr. Protoc. Mol. Biol. 2019.
Random 8nt variant libraries were generated using a PCR approach with degenerate oligonucleotides. Forward primers were designed to anneal directly downstream of the enhancer position of interested followed by 8 degenerate bp (creating 65,536 variants) and another 20 bp complementary stretch. Reverse primers were complementary to the 20 bp 5’ of the degenerate stretch. The STARR-seq vector containing the wildtype enhancer of interest (either ced-6 or ZnT63C) was used as a template for the PCR. The PCR was run across the whole STARR-seq plasmid, followed by DpnI digest and a Gibson reaction that re-circularizes the plasmid. Libraries were grown in 2l LB-Amp (final ampicillin concentration 100µg/mL). Variant libraries of the same enhancer i.e. ced-6 enhancer pos110, pos182, pos230, pos241 and ZnT63C enhancer pos142, pos180, pos210 were pooled to equimolar ratio, together with another synthetic oligo library containing wt enhancer sequences and negative regions.
STARR-seq

tag: sample type

value: PCR amplified cDNA (STARR-seq transcript)

tag: promoter

value: developmental (DSCP)


title: Canton-S, adult eye, 1-Day old, Female, scRNA-seq


title: HEK293T_ALDOBW148X_gCtrl

value: ALDOBW148X and gCtrl


title: ZnT63Cenhancer libraries rep1 STARR-seq


title: ZnT63C enhancer libraries rep1 input

source_name: oligo library (in STARR-seq vector)

value: PCR amplified Plasmid library


title: ZnT63C enhancer libraries rep2 input


title: ced-6 enhancer libraries rep2 STARR-seq


title: LibFR012_LibFR015_humantwistmix_STARRseq_rep3

data_processing:
Oligo library UMI-STARR-seq RNA and DNA input reads (150 bp) were mapped to a reference containing 249 bp long sequences containing both wildtype and mutated fragments from the human library using Bowtie v.1.2.2. We demultiplexed reads by the i5 and i7 indexes and subsequently by the oligo identity, since this library contained oligos from other experiments. Mapping reads with the correct length, strand and with no mismatches (to identify all sequence variants) were kept. Both DNA and RNA reads were collapsed by UMI (10 bp, allowing one mismatch; UMI sequences are in the sequencing read name) to ensure the counting of unique reporter transcripts.
We excluded oligos with less than 10 reads in any of the input replicates and added one read pseudocount to oligos with zero RNA counts. The enhancer activity of each oligo in each screen was calculated as the log2 fold-change over input, using both replicates, using DESeq2. We used the counts of wildtype negative regions in each library as scaling factors between samples. This normalization only changes the position of the zero and consequently does not affect the calculation of log2 fold-changes or the p-values for the statistical tests used.
Assembly: hg19 (custom oligo library)
Supplementary files format and content: Table of all human enhancer sequences and their mutant sequences included in the oligo library (n=31709), with genomic coordinates, oligo sequence, experiment, wildtype and pasted motif information, read counts for each screen and final enhancer activity (log2).

source_name: HCT-116 cells

growth_protocol: Human colon cancer cell line HCT116 was grown in DMEM supplemented with 10% heat inactivated FBS and 1% L-Glutamine at 37ºC. Cells were passaged every 2-3 days.

extract_protocol:
6h after electroporation, total RNA was extracted using the RNeasy Maxi kit (Qiagen; cat. no. 75162), followed by polyA+ RNA isolation using Invitrogen Dynabeads Oligo(dT)25 (scaling up the manufacturer’s protocol accordingly; cat. no. 61005) and DNase treatment with Ambion Turbo DNase (cat. no. AM2239) at a concentration of at most 200 ng/µl for 30 minutes (min) at 37°C. The reactions were then subjected to Qiagen RNeasy MinElute reaction clean-up (cat. no. 74204), for Turbo DNase inactivation and RNA concentration.  After reverse transcription and second strand synthesis a unique molecular identifier (UMI) was added to each transcript. This is followed by two nested PCR steps, each with primers that are specific to the reporter transcripts such that STARR-seq does not detect endogenous cellular RNAs. See Neumayr et al., Curr. Protoc. Mol. Biol. 2019.
Oligo libraries were synthesized by Twist Bioscience including 249 bp enhancer sequence and adaptors for library cloning. Following the instructions of NEBNext® DNA Library Prep Reagent Set for Illumina® (NEB; cat. no. E6000L), Illumina Multiplexing Adapters (Illumina Inc; cat. no. PE-400-1001) were ligated and homology arms for In-Fusion® recombination were added by PCR, followed by recombination into the human STARR-seq vector. The In-Fusion® reactions were transformed (MegaX DH10B; Invitrogen), grown in liquid culture and plasmids were isolated.  See Neumayr et al., Curr. Protoc. Mol. Biol. 2019.
STARR-seq


title: ZnT63C enhancer libraries rep2 STARR-seq


title: ced-6 enhancer libraries rep1 input


title: ced-6 enhancer libraries rep2 input


title: HEK293T_SMN1W190X_gACA19_DKC1


title: LibFR012_LibFR015_humantwistmix_STARRseq_rep2


title: LibFR012_LibFR015_humantwistmix_input_rep3

source_name: oligo library (in human STARR-seq vector)


title: LibFR012_LibFR015_humantwistmix_input_rep2


title: SBC3_ROR2KO-3

value: lung

value: Small cell lung cancer

value: ROR2 knockout


title: LibFR012_LibFR015_humantwistmix_input_rep1


title: SBC3_ROR2KO-2


title: SBC3_control-3

value: Control


title: SBC3_control-2


title: SBC3_ROR2KO-1


title: SBC3_control-1


title: nOSKL_FF_2

city: San Francisco

first: Akira

last: Kunitomi

state: CA

address: 1650 Owens Street

institute: The J. David Gladstone Institutes

description: Feeder-free naive induced pluripotent stem cells derived from adult human dermal fibroblasts

data_processing:
FASTQ files were generated from bcl files using bcl2fastq v2.17.1.14 (illumina) and processed using ENCODE long-rna-seq-pipeline v2.3.4.
Sequenced reads were mapped to the human reference genome (GRCh38) using STAR 2.5.1b with GENCODE v24 gene annotations.
Normalized gene expression data was calculated using RSEM 1.2.23.
Gene count data was obtained using featureCounts bundled in Subread 1.5.1.
Genome_build: GRCh38
Supplementary_files_format_and_content: Tab-delimited text files include FPKM values for each sample.

source_name: Human induced pluripotent stem cells

growth_protocol: Primed PSCs were maintained in StemFit AK02N medium (Ajinomoto) on laminin 511-E8 fragments (iMatrix-511, Nippi)-coated plates. Naive PSCs were cultured on iMEFs and maintained in t2iLGö medium. Feeder-free naive iPSCs were maintained on Matrigel (hESC-qualified, Corning)

extract_protocol:
Total RNA were extracted from cell lysates using the AllPrep DNA/RNA Mini Kit (QIAGEN)
RNA libraries were prepared for sequencing using standard Illumina protocols

value: Naive induced pluripotent stem cells

tag: gender

value: Female


title: nOSKL_FF_1


title: CD45p.coculture.CACO-2.untransf.noheat#1

city: Boston

first: CBDM

last: Lab

state: MA

address: 77 Avenue Louis Pasteur

department: Microbiology and Immunobiology

institute: Harvard Medical School

description:
~ 25K CACO-2 293 cells were plated. 24 hours later cells were washed once with PBS and 200K PBMCs from healthy donor were added, cocultured for 13h then stained and sorted then lysed for RNA extraction.
Genes_count_table.tsv

data_processing:
Reads were mapped to the human reference genome (GRCh38) with STAR 2.7.3a
Non-uniquely mapped reads were discarded.
The uniquely mapped reads were assigned to genes using featureCounts (subread 2.0.0) with GENCODE annotation (v34)
Assembly: GRCh38
Supplementary files format and content: raw read counts

source_name: Blood

extract_protocol:
We established a co-culture model in which ex vivo blood immunocytes were placed in direct contact with virus-infected epithelial cells or SARS-CoV2 single protein transfected epithelial cells. We used as a virus SARS-CoV2 and two other relevant viruses for comparison : influenza A virus and Ebola virus. Thirty-five hours after viral infection of the Caco-2 monolayer, unbound virus was removed and peripheral blood mononuclear cells (PBMC) from healthy donors (HD) were added to the cultures. These were harvested 14 h later, and subpopulations (epithelial cells, CD45+CD19+ and CD45+CD14+) were magnetically purified for transcriptome profiling by RNAseq. We used the same coculture model to assess the role of individual SARS-CoV2 proteins : Caco-2 cells were transfected, in biological duplicates, with a panel of 27 plasmids encoding single viral proteins or GFP as a control; Forty-eight hour later, these transfectants were co-cultured with HD PBMCs, and the monocytes as well as the transfected epithelial cells were profiled by RNAseq after 14 h.
total RNA was captured and purified on RNAClean XP beads (Beckman Coulter). Polyadenylated mRNA was then selected using an anchored oligo(dT) primer (5′–AAGCAGTGGTATCAACGCAGAGTACT30VN-3) and converted to cDNA via reverse transcription. First-strand cDNA was subjected to limited PCR amplification followed by Tn5 transposon-based fragmentation using the Nextera XT DNA Library Preparation Kit (Illumina). Samples were then PCR amplified for 18 cycles using barcoded primers such that each sample carried a specific combination of eight-base Illumina P5 and P7 barcodes and were pooled together prior to Smart sequencing. Smart-seq paired-end sequencing was performed on an Illumina NextSeq500 using 2 x 38bp reads with no further trimming.

value: Blood

value: HD

tag: experiment


title: LibFR012_LibFR015_humantwistmix_STARRseq_rep1


title: CD45p.coculture.CACO-2.untransf.heat#1

tag: genotype


title: 3mix-timelapse, 3mix-timelapse-plate4_63

city: Suita

first: Katsuyuki

last: Shiroguchi

state: Osaka

address: 6-2-3 Furuedai

department: Center for Biosystems Dynamics Research (BDR)

institute: RIKEN

description:
3mix-timelapse-plate4_63
3mix_RNA_expression.txt

data_processing:
Basecalls performed by Illumina MiSeq or Hiseq
Sequenced reads were trimmed for adaptor sequence, and were sorted by indexes in Illumina MiSeq or using bcl2fastq for Illumina Hiseq resultes
Reads were aligned to the mm10 genome assebly using STAR
Mapped reads seperated by genes, and the reads mapped for each gene were clusterd by molecular barcode
The number of cluteres for each gene was counted, which provides the number of molecules detected for each gene
Genome_build: mm10
Supplementary_files_format_and_content: The calculated copy number of RNA molecules per cell for each gene is listed (cells which were not filtered out are shown).

source_name: Cell line mixture of murine T cell, murine leukemia cell, and murine hematopoietic progenitor cell

extract_protocol:
RNAs from cell lysate in each well was directly used for library preparation without purification
Libraries were prepared by using molecular barcoding technique. First, for control, the same amount of spike-in RNAs, a known number of External RNA Controls Consortium (ERCC) RNA molecules, was added into every tube which contains an isolated cell. Then, the cells were lysed and RNA molecules were fragmentated by temperature elevation. cDNAs were generated by reverse transcription using a reverse transcription primer, in which the first common primer sequence, molecular barcode, fourteen T bases, and one V (A or G or C) base are tandemly arranged from 5' end. In the reverse transcription, the second common primer sequence was also attached to 3' end of each generated cDNA molecule by template switching. Subsequently, cDNAs were amplified by PCR using two primers; one primer contains an illumina adapter sequence, sample index, and the first common primer sequence, and the other primer has another illumina adapter sequence, sample index, and the second common primer sequence.

treatment_protocol: Murine T cells, leukemia cells, hematopoietic progenitor cells, and PBMCs were isolated by ALPS or FACS

tag: strain

value: random selection

tag: isolation method

value: ALPS


title: 3mix-timelapse, 3mix-timelapse-plate4_64

description:
3mix-timelapse-plate4_64
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_71

description:
3mix-timelapse-plate4_71
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_70

description:
3mix-timelapse-plate4_70
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_53

description:
3mix-timelapse-plate4_53
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_56

description:
3mix-timelapse-plate4_56
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_59

description:
3mix-timelapse-plate4_59
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_67

description:
3mix-timelapse-plate4_67
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_73

description:
3mix-timelapse-plate4_73
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_72

description:
3mix-timelapse-plate4_72
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_66

description:
3mix-timelapse-plate4_66
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_62

description:
3mix-timelapse-plate4_62
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_55

description:
3mix-timelapse-plate4_55
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_57

description:
3mix-timelapse-plate4_57
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_58

description:
3mix-timelapse-plate4_58
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_61

description:
3mix-timelapse-plate4_61
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_68

description:
3mix-timelapse-plate4_68
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_60

description:
3mix-timelapse-plate4_60
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_69

description:
3mix-timelapse-plate4_69
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_65

description:
3mix-timelapse-plate4_65
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_48

description:
3mix-timelapse-plate4_48
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_50

description:
3mix-timelapse-plate4_50
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_49

description:
3mix-timelapse-plate4_49
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_52

description:
3mix-timelapse-plate4_52
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_51

description:
3mix-timelapse-plate4_51
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_45

description:
3mix-timelapse-plate4_45
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_44

description:
3mix-timelapse-plate4_44
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_54

description:
3mix-timelapse-plate4_54
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_43

description:
3mix-timelapse-plate4_43
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_35

description:
3mix-timelapse-plate4_35
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_33

description:
3mix-timelapse-plate4_33
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_47

description:
3mix-timelapse-plate4_47
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_34

description:
3mix-timelapse-plate4_34
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_28

description:
3mix-timelapse-plate4_28
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_40

description:
3mix-timelapse-plate4_40
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_38

description:
3mix-timelapse-plate4_38
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_23

description:
3mix-timelapse-plate4_23
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_22

description:
3mix-timelapse-plate4_22
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_36

description:
3mix-timelapse-plate4_36
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_29

description:
3mix-timelapse-plate4_29
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_39

description:
3mix-timelapse-plate4_39
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_26

description:
3mix-timelapse-plate4_26
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_31

description:
3mix-timelapse-plate4_31
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_27

description:
3mix-timelapse-plate4_27
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_20

description:
3mix-timelapse-plate4_20
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_37

description:
3mix-timelapse-plate4_37
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_30

description:
3mix-timelapse-plate4_30
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_32

description:
3mix-timelapse-plate4_32
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_19

description:
3mix-timelapse-plate4_19
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_25

description:
3mix-timelapse-plate4_25
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_21

description:
3mix-timelapse-plate4_21
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_18

description:
3mix-timelapse-plate4_18
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_46

description:
3mix-timelapse-plate4_46
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_16

description:
3mix-timelapse-plate4_16
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_17

description:
3mix-timelapse-plate4_17
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_42

description:
3mix-timelapse-plate4_42
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_24

description:
3mix-timelapse-plate4_24
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_41

description:
3mix-timelapse-plate4_41
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_15

description:
3mix-timelapse-plate4_15
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_14

description:
3mix-timelapse-plate4_14
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_12

description:
3mix-timelapse-plate4_12
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_13

description:
3mix-timelapse-plate4_13
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_11

description:
3mix-timelapse-plate4_11
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_10

description:
3mix-timelapse-plate4_10
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_9

description:
3mix-timelapse-plate4_9
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_6

description:
3mix-timelapse-plate4_6
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_5

description:
3mix-timelapse-plate4_5
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_8

description:
3mix-timelapse-plate4_8
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_4

description:
3mix-timelapse-plate4_4
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_7

description:
3mix-timelapse-plate4_7
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_95

description:
3mix-timelapse-plate3_95
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_1

description:
3mix-timelapse-plate4_1
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_96

description:
3mix-timelapse-plate3_96
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_2

description:
3mix-timelapse-plate4_2
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_92

description:
3mix-timelapse-plate3_92
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate4_3

description:
3mix-timelapse-plate4_3
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_88

description:
3mix-timelapse-plate3_88
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_93

description:
3mix-timelapse-plate3_93
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_89

description:
3mix-timelapse-plate3_89
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_94

description:
3mix-timelapse-plate3_94
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_90

description:
3mix-timelapse-plate3_90
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_87

description:
3mix-timelapse-plate3_87
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_86

description:
3mix-timelapse-plate3_86
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_84

description:
3mix-timelapse-plate3_84
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_81

description:
3mix-timelapse-plate3_81
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_85

description:
3mix-timelapse-plate3_85
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_83

description:
3mix-timelapse-plate3_83
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_82

description:
3mix-timelapse-plate3_82
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_77

description:
3mix-timelapse-plate3_77
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_76

description:
3mix-timelapse-plate3_76
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_80

description:
3mix-timelapse-plate3_80
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_79

description:
3mix-timelapse-plate3_79
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_91

description:
3mix-timelapse-plate3_91
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_75

description:
3mix-timelapse-plate3_75
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_74

description:
3mix-timelapse-plate3_74
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_73

description:
3mix-timelapse-plate3_73
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_69

description:
3mix-timelapse-plate3_69
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_66

description:
3mix-timelapse-plate3_66
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_70

description:
3mix-timelapse-plate3_70
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_68

description:
3mix-timelapse-plate3_68
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_67

description:
3mix-timelapse-plate3_67
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_65

description:
3mix-timelapse-plate3_65
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_63

description:
3mix-timelapse-plate3_63
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_61

description:
3mix-timelapse-plate3_61
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_64

description:
3mix-timelapse-plate3_64
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_59

description:
3mix-timelapse-plate3_59
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_57

description:
3mix-timelapse-plate3_57
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_62

description:
3mix-timelapse-plate3_62
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_58

description:
3mix-timelapse-plate3_58
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_60

description:
3mix-timelapse-plate3_60
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_78

description:
3mix-timelapse-plate3_78
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_55

description:
3mix-timelapse-plate3_55
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_54

description:
3mix-timelapse-plate3_54
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_56

description:
3mix-timelapse-plate3_56
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_52

description:
3mix-timelapse-plate3_52
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_53

description:
3mix-timelapse-plate3_53
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_72

description:
3mix-timelapse-plate3_72
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_71

description:
3mix-timelapse-plate3_71
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_50

description:
3mix-timelapse-plate3_50
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_49

description:
3mix-timelapse-plate3_49
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_51

description:
3mix-timelapse-plate3_51
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_48

description:
3mix-timelapse-plate3_48
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_45

description:
3mix-timelapse-plate3_45
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_46

description:
3mix-timelapse-plate3_46
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_47

description:
3mix-timelapse-plate3_47
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_43

description:
3mix-timelapse-plate3_43
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_42

description:
3mix-timelapse-plate3_42
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_41

description:
3mix-timelapse-plate3_41
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_44

description:
3mix-timelapse-plate3_44
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_40

description:
3mix-timelapse-plate3_40
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_38

description:
3mix-timelapse-plate3_38
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_32

description:
3mix-timelapse-plate3_32
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_37

description:
3mix-timelapse-plate3_37
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_33

description:
3mix-timelapse-plate3_33
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_34

description:
3mix-timelapse-plate3_34
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_30

description:
3mix-timelapse-plate3_30
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_35

description:
3mix-timelapse-plate3_35
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_31

description:
3mix-timelapse-plate3_31
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_24

description:
3mix-timelapse-plate3_24
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_29

description:
3mix-timelapse-plate3_29
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_26

description:
3mix-timelapse-plate3_26
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_27

description:
3mix-timelapse-plate3_27
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_23

description:
3mix-timelapse-plate3_23
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_28

description:
3mix-timelapse-plate3_28
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_39

description:
3mix-timelapse-plate3_39
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_17

description:
3mix-timelapse-plate3_17
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_18

description:
3mix-timelapse-plate3_18
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_16

description:
3mix-timelapse-plate3_16
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_15

description:
3mix-timelapse-plate3_15
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_13

description:
3mix-timelapse-plate3_13
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_21

description:
3mix-timelapse-plate3_21
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_11

description:
3mix-timelapse-plate3_11
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_36

description:
3mix-timelapse-plate3_36
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_10

description:
3mix-timelapse-plate3_10
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_22

description:
3mix-timelapse-plate3_22
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_25

description:
3mix-timelapse-plate3_25
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_14

description:
3mix-timelapse-plate3_14
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_8

description:
3mix-timelapse-plate3_8
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_7

description:
3mix-timelapse-plate3_7
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_6

description:
3mix-timelapse-plate3_6
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_5

description:
3mix-timelapse-plate3_5
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_2

description:
3mix-timelapse-plate3_2
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_4

description:
3mix-timelapse-plate3_4
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_20

description:
3mix-timelapse-plate3_20
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_12

description:
3mix-timelapse-plate3_12
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_3

description:
3mix-timelapse-plate3_3
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_94

description:
3mix-timelapse-plate2_94
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_93

description:
3mix-timelapse-plate2_93
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_19

description:
3mix-timelapse-plate3_19
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_96

description:
3mix-timelapse-plate2_96
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_95

description:
3mix-timelapse-plate2_95
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_91

description:
3mix-timelapse-plate2_91
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_89

description:
3mix-timelapse-plate2_89
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_87

description:
3mix-timelapse-plate2_87
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_86

description:
3mix-timelapse-plate2_86
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_88

description:
3mix-timelapse-plate2_88
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_83

description:
3mix-timelapse-plate2_83
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_84

description:
3mix-timelapse-plate2_84
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_90

description:
3mix-timelapse-plate2_90
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_9

description:
3mix-timelapse-plate3_9
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate3_1

description:
3mix-timelapse-plate3_1
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_80

description:
3mix-timelapse-plate2_80
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_81

description:
3mix-timelapse-plate2_81
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_82

description:
3mix-timelapse-plate2_82
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_92

description:
3mix-timelapse-plate2_92
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_77

description:
3mix-timelapse-plate2_77
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_85

description:
3mix-timelapse-plate2_85
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_75

description:
3mix-timelapse-plate2_75
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_74

description:
3mix-timelapse-plate2_74
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_76

description:
3mix-timelapse-plate2_76
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_73

description:
3mix-timelapse-plate2_73
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_72

description:
3mix-timelapse-plate2_72
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_70

description:
3mix-timelapse-plate2_70
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_69

description:
3mix-timelapse-plate2_69
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_68

description:
3mix-timelapse-plate2_68
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_67

description:
3mix-timelapse-plate2_67
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_66

description:
3mix-timelapse-plate2_66
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_65

description:
3mix-timelapse-plate2_65
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_63

description:
3mix-timelapse-plate2_63
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_79

description:
3mix-timelapse-plate2_79
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_64

description:
3mix-timelapse-plate2_64
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_62

description:
3mix-timelapse-plate2_62
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_56

description:
3mix-timelapse-plate2_56
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_61

description:
3mix-timelapse-plate2_61
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_58

description:
3mix-timelapse-plate2_58
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_54

description:
3mix-timelapse-plate2_54
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_59

description:
3mix-timelapse-plate2_59
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_78

description:
3mix-timelapse-plate2_78
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_52

description:
3mix-timelapse-plate2_52
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_57

description:
3mix-timelapse-plate2_57
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_55

description:
3mix-timelapse-plate2_55
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_53

description:
3mix-timelapse-plate2_53
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_50

description:
3mix-timelapse-plate2_50
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_71

description:
3mix-timelapse-plate2_71
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_47

description:
3mix-timelapse-plate2_47
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_48

description:
3mix-timelapse-plate2_48
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_49

description:
3mix-timelapse-plate2_49
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_46

description:
3mix-timelapse-plate2_46
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_44

description:
3mix-timelapse-plate2_44
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_45

description:
3mix-timelapse-plate2_45
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_43

description:
3mix-timelapse-plate2_43
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_42

description:
3mix-timelapse-plate2_42
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_40

description:
3mix-timelapse-plate2_40
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_39

description:
3mix-timelapse-plate2_39
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_60

description:
3mix-timelapse-plate2_60
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_38

description:
3mix-timelapse-plate2_38
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_37

description:
3mix-timelapse-plate2_37
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_51

description:
3mix-timelapse-plate2_51
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_35

description:
3mix-timelapse-plate2_35
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_36

description:
3mix-timelapse-plate2_36
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_34

description:
3mix-timelapse-plate2_34
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_33

description:
3mix-timelapse-plate2_33
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_31

description:
3mix-timelapse-plate2_31
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_27

description:
3mix-timelapse-plate2_27
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_28

description:
3mix-timelapse-plate2_28
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_30

description:
3mix-timelapse-plate2_30
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_41

description:
3mix-timelapse-plate2_41
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_25

description:
3mix-timelapse-plate2_25
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_24

description:
3mix-timelapse-plate2_24
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_29

description:
3mix-timelapse-plate2_29
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_23

description:
3mix-timelapse-plate2_23
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_20

description:
3mix-timelapse-plate2_20
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_22

description:
3mix-timelapse-plate2_22
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_18

description:
3mix-timelapse-plate2_18
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_21

description:
3mix-timelapse-plate2_21
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_17

description:
3mix-timelapse-plate2_17
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_19

description:
3mix-timelapse-plate2_19
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_16

description:
3mix-timelapse-plate2_16
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_14

description:
3mix-timelapse-plate2_14
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_11

description:
3mix-timelapse-plate2_11
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_10

description:
3mix-timelapse-plate2_10
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_13

description:
3mix-timelapse-plate2_13
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_8

description:
3mix-timelapse-plate2_8
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_32

description:
3mix-timelapse-plate2_32
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_5

description:
3mix-timelapse-plate2_5
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_6

description:
3mix-timelapse-plate2_6
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_4

description:
3mix-timelapse-plate2_4
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_12

description:
3mix-timelapse-plate2_12
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_9

description:
3mix-timelapse-plate2_9
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_26

description:
3mix-timelapse-plate2_26
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_7

description:
3mix-timelapse-plate2_7
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_1

description:
3mix-timelapse-plate2_1
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_95

description:
3mix-timelapse-plate1_95
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_96

description:
3mix-timelapse-plate1_96
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_94

description:
3mix-timelapse-plate1_94
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_92

description:
3mix-timelapse-plate1_92
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_93

description:
3mix-timelapse-plate1_93
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_15

description:
3mix-timelapse-plate2_15
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_89

description:
3mix-timelapse-plate1_89
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_87

description:
3mix-timelapse-plate1_87
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_91

description:
3mix-timelapse-plate1_91
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_88

description:
3mix-timelapse-plate1_88
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_86

description:
3mix-timelapse-plate1_86
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_84

description:
3mix-timelapse-plate1_84
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_83

description:
3mix-timelapse-plate1_83
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_81

description:
3mix-timelapse-plate1_81
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_82

description:
3mix-timelapse-plate1_82
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_3

description:
3mix-timelapse-plate2_3
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_80

description:
3mix-timelapse-plate1_80
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate2_2

description:
3mix-timelapse-plate2_2
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_79

description:
3mix-timelapse-plate1_79
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_77

description:
3mix-timelapse-plate1_77
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_78

description:
3mix-timelapse-plate1_78
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_76

description:
3mix-timelapse-plate1_76
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_75

description:
3mix-timelapse-plate1_75
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_74

description:
3mix-timelapse-plate1_74
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_69

description:
3mix-timelapse-plate1_69
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_73

description:
3mix-timelapse-plate1_73
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_71

description:
3mix-timelapse-plate1_71
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_90

description:
3mix-timelapse-plate1_90
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_70

description:
3mix-timelapse-plate1_70
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_72

description:
3mix-timelapse-plate1_72
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_67

description:
3mix-timelapse-plate1_67
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_68

description:
3mix-timelapse-plate1_68
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_64

description:
3mix-timelapse-plate1_64
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_65

description:
3mix-timelapse-plate1_65
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_85

description:
3mix-timelapse-plate1_85
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_66

description:
3mix-timelapse-plate1_66
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_62

description:
3mix-timelapse-plate1_62
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_63

description:
3mix-timelapse-plate1_63
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_60

description:
3mix-timelapse-plate1_60
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_59

description:
3mix-timelapse-plate1_59
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_55

description:
3mix-timelapse-plate1_55
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_56

description:
3mix-timelapse-plate1_56
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_54

description:
3mix-timelapse-plate1_54
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_53

description:
3mix-timelapse-plate1_53
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_52

description:
3mix-timelapse-plate1_52
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_51

description:
3mix-timelapse-plate1_51
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_49

description:
3mix-timelapse-plate1_49
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_47

description:
3mix-timelapse-plate1_47
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_48

description:
3mix-timelapse-plate1_48
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_45

description:
3mix-timelapse-plate1_45
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_44

description:
3mix-timelapse-plate1_44
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_43

description:
3mix-timelapse-plate1_43
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_41

description:
3mix-timelapse-plate1_41
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_50

description:
3mix-timelapse-plate1_50
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_39

description:
3mix-timelapse-plate1_39
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_36

description:
3mix-timelapse-plate1_36
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_37

description:
3mix-timelapse-plate1_37
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_46

description:
3mix-timelapse-plate1_46
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_42

description:
3mix-timelapse-plate1_42
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_35

description:
3mix-timelapse-plate1_35
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_32

description:
3mix-timelapse-plate1_32
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_38

description:
3mix-timelapse-plate1_38
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_40

description:
3mix-timelapse-plate1_40
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_58

description:
3mix-timelapse-plate1_58
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_61

description:
3mix-timelapse-plate1_61
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_30

description:
3mix-timelapse-plate1_30
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_34

description:
3mix-timelapse-plate1_34
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_57

description:
3mix-timelapse-plate1_57
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_29

description:
3mix-timelapse-plate1_29
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_33

description:
3mix-timelapse-plate1_33
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_27

description:
3mix-timelapse-plate1_27
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_25

description:
3mix-timelapse-plate1_25
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_28

description:
3mix-timelapse-plate1_28
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_26

description:
3mix-timelapse-plate1_26
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_24

description:
3mix-timelapse-plate1_24
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_23

description:
3mix-timelapse-plate1_23
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_15

description:
3mix-timelapse-plate1_15
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_22

description:
3mix-timelapse-plate1_22
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_16

description:
3mix-timelapse-plate1_16
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_21

description:
3mix-timelapse-plate1_21
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_17

description:
3mix-timelapse-plate1_17
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_31

description:
3mix-timelapse-plate1_31
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_18

description:
3mix-timelapse-plate1_18
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_20

description:
3mix-timelapse-plate1_20
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_10

description:
3mix-timelapse-plate1_10
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_7

description:
3mix-timelapse-plate1_7
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_8

description:
3mix-timelapse-plate1_8
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_13

description:
3mix-timelapse-plate1_13
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_14

description:
3mix-timelapse-plate1_14
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_11

description:
3mix-timelapse-plate1_11
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_5

description:
3mix-timelapse-plate1_5
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_12

description:
3mix-timelapse-plate1_12
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_3

description:
3mix-timelapse-plate1_3
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_9

description:
3mix-timelapse-plate1_9
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_4

description:
3mix-timelapse-plate1_4
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_6

description:
3mix-timelapse-plate1_6
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_2

description:
3mix-timelapse-plate1_2
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_1

description:
3mix-timelapse-plate1_1
3mix_RNA_expression.txt


title: 3mix-FACS, 3mix-FACS-plate2_95

description:
3mix-FACS-plate2_95
3mix_RNA_expression.txt

value: hematopoietic progenitor cell

value: FACS


title: 3mix-FACS, 3mix-FACS-plate2_91

description:
3mix-FACS-plate2_91
3mix_RNA_expression.txt


title: 3mix-FACS, 3mix-FACS-plate2_92

description:
3mix-FACS-plate2_92
3mix_RNA_expression.txt


title: 3mix-timelapse, 3mix-timelapse-plate1_19

description:
3mix-timelapse-plate1_19
3mix_RNA_expression.txt


title: 3mix-FACS, 3mix-FACS-plate2_94

description:
3mix-FACS-plate2_94
3mix_RNA_expression.txt


title: 3mix-FACS, 3mix-FACS-plate2_90

description:
3mix-FACS-plate2_90
3mix_RNA_expression.txt