title: H12h_1

city: lanzhou

first: jinqiang

last: huang

address: yintanlu stress

institute: Gansu Agricultural University

data_processing:
Reads obtained from the sequencing machines included raw reads containing adapters or low quality bases which would affect the following assembly and analysis. Thus, to get high quality clean reads, reads were further filtered according to the following rules: 1) Removing reads containing adapters; 2) Removing reads consisting of all A bases; 3) Removing reads containing more than 10% of unknown nucleotides (N); 4) Removing low quality reads containing more than 50% of low quality (Q-value≤20) bases
Short reads alignment tool Bowtie2 (2.2.8) was used for mapping reads to ribosome RNA (rRNA) database. The rRNA mapped reads were then removed. The remaining reads were further used in assembly and analysis of transcriptome.
The rRNA removed reads of each sample were then mapped to reference genome by TopHat2 (version 2.1.1), respectively. The alignment parameters were as follows: 1) Maximum read mismatch is 2 2) Disables the coverage based search for junctions 3) The distance between mate-pair reads is 50bp 4) The standard deviation for the distribution on inner distance between mate-pair reads is 80bp
After aligned with reference genome, unmapped reads (or mapped very poorly) were then re-aligned with Bowtie2, the enriched unmapped reads were split into smaller segments which were then used to find potential splice sites. The section and the section position of these short segments were predicted as well. A set of splice sites was built with initial unmapped reads by TopHat2 without relying on the known genes annotation. Not only be used for identifying expressed genes and their quantitative expression, the sequence alignment will also be helpful to find alternative splicing and new transcripts.
Assembly: crucian carp
Supplementary files format and content: tab-delimited text files include FPKM values for each Sample

organism: Carassius auratus

source_name: liver tissues

extract_protocol:
The samples were collected immediately, then flash-frozen in liquid nitrogen,and total RNA was extracted using Trizol reagent.
RNA libraries were prepared for sequencing using standard Illumina protocols

value: liver tissues

value: hypoxia stress

tag: phenotype

value: wild-type


title: H12h_3

status: Public on Oct 15 2022

type: SRA

country: China

library_source: transcriptomic

molecule: total RNA

tag: tissue

tag: treatment


title: Day 3 ARID1A CUT&RUN profiling in SMARCB1 +/+ G401 cell line Rep1

city: Lebanon

first: Xiao feng

last: Wang

state: NH

address: 1 Medical Center Dr

country: USA

institute: Dartmouth College

library_source: genomic

data_processing:
Library strategy: CUT&RUN
Reads were deduplicated with the clumpify tool using flag -dedupe -subs=2, and subsequently trimmed with bbduk using parameters --ktrim=r --k=21 --mink=11 --hdist=1 --tpe --tbo.
The trimmed fastq files were then aligned to the Hg19 human genome using Bowtie2 aligner. Specifically, we used parameter “--end-to-end --very-sensitive --no-mixed --no-discordant -q -I 10 -X 700 --phred33” for the alignment.
Bam files were converted to bed files after removing chrM, chrUn, and reads containing “random” as chromosome position. Bed files were further cleaned by removing regions contained in the hg19 blacklist from ENCODE (v2)
Epic2 software (v.0.0.41) was used for calling histones and SWI/SNF peaks with parameters at default
Genome_build: hg19
Supplementary_files_format_and_content: CUT_RUN_peak.bed, which includes the peaks for all SWI/SNF subunits and AP-1 samples, is linked to the SuperSeries GSE196960 record.

molecule: genomic DNA

organism: Homo sapiens

source_name: G401 cell line

growth_protocol: G401 cell lines were purchased from American Type Culture Collection. Cell lines were cultured in DMEM with 10% FBS. SMARCB1 inducible re-expression stable G401 cell line was created previously and is maintained in media with Tet-free FBS (Gibco, Cat.# 16140071).

extract_protocol:
DNA was extracted using Phenol:Chloroform:Isoamyl Alcohol (Cat.# 15593031, ThermoFisher) and purified using ProNex Purification System (Cat.#NG2003, Promega).
CUT&RUN library was prepared using NEBNext Ultra II DNA Library Prep Kit for Illumina (Cat.# E7645L, New England Labs). Libraries were paired-end sequenced with read lengths of 150 bp (PE 2X150 on the Illumina HiSeq Genome Analyzer). Average of 10 million reads per sample.

treatment_protocol: To induce SMARCB1 re-expression, cells were treated with doxycycline (1 μg/ml, EMD Millipore) for indicated time.

tag: cell line

value: G401 cell line

value: SMARCB1 +/+ G401 cell line

tag: cut&run antibody

tag: time point


title: N_3

value: control


title: Day 7 SMARCC1 CUT&RUN profiling in SMARCB1 +/+ G401 cell line Rep1


title: Day 1 SMARCC1 CUT&RUN profiling in SMARCB1 +/+ G401 cell line Rep1


title: smNPCs, pooled input  [re-used]

city: Bonn

first: Daniele

last: Bano

state: NRW

address: Venusberg Campus 1, Gebaeude 99

country: Germany

institute: DZNE, German Center for Neurodegenerative Diseases

data_processing:
For data pre-processing, FASTQ files were adaptor-trimmed by TrimGalore [https://github.com/FelixKrueger/TrimGalore] with default parameters and aligned to either hg19 or mm10 genome by Bowtie2.
Trimmed FASTQ files were then aligned to Dm6 genome for later calculation of scaling factors. Calculation of scaling factors and aligned BAM files were down-sampled by Picard.
To identify differential binding regions for SMARCA4/BRG1, respectively, down-sampled BAM files were transformed into BED format by Bedtools.
Differential binding regions were then called by diffReps with a window size of 100bp.
Data visualization was done using BigWig files for SMARCA4/BRG1 signal, generated by the bamCompare command in deepTools using input signal as control.
Assembly: mm10 or hg38
Supplementary files format and content: bigWig

source_name: iPSC-derivd NPCs

growth_protocol: Cells were grown under standard cell culture conditions.

extract_protocol: Active Motif

tag: chip antibody

value: SMARCA4/BRG1, ab110641, abcam

tag: cell type

value: iPSC-derivd NPCs


title: N_1


title: smNPCs, BCL7A KO2, SMARCA4/BRG1

tag: genotype

value: BCL7A KO2


title: Day 3 SMARCC1 CUT&RUN profiling in SMARCB1 +/+ G401 cell line Rep1


title: smNPCs, BCL7A KO1, SMARCA4/BRG1

value: BCL7A KO1


title: H12h_2


title: HFD3

city: zhangjiakou

first: xiao

middle: xiao

last: Zhang

state: hebei

address: 11 zuanshi south road

institute: Hebei North University

description: circRNA

data_processing:
Reads obtained from the sequencing machines includes raw reads containing adapters or low quality bases which will affect the following assembly and analysis. Thus, to get high quality clean reads, reads were further filtered by Cutadapt (https://cutadapt.readthedocs.io/en/stable/,version:cutadapt-1.9).
We aligned reads of all samples to the reference genome using Tophat2 (2.0.4) package, remaining reads (unmapped reads) were still mapped to reference genome using tophat-fusion (2.1.0), which was subsequently used to identify circRNA.
CIRCExplorer2 (2.2.6, default) and CIRI (2.0.2, default) was used to denovo assemble the mapped reads to circular RNAs at first; Then, back-spliced junction reads were identified in unmapped reads by tophat-fusion and CIRCExplorer2 or CIRI. All samples were generated unique circular RNAs.
We normalized the back-spliced reads (support for circRNA) by read length and number of mapped reads (spliced reads per billion mapping, denoted as SRPBM), which permits quantitative comparisons between back splicing from different RNA-seq. We counted the total number of reads mapped to the reference genome in each sample and normalized the number of reads spanning the back-spliced junction to the total number of mapped reads (units in billion) and read length. The SRPBM value of each sample circRNA was calculated by the Perl script and used as the expression abundance. SRPBM = number of circular reads/number of mapped reads (units in billion)/read length
Assembly: mm9
Supplementary files format and content: tab-delimited text files include SRPBM and count values for each Sample

organism: Mus musculus

source_name: Liver

extract_protocol:
Total RNA was extracted using Trizol reagent (hermofisher, 15596018) following the manufacturer's procedure. The total RNA quantity and purity were analysis of Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA, 5067-1511) with RIN number > 7.0.
Approximately 5ug of total RNA was used to deplete ribosomal RNA according to the manuscript of the Ribo-Zero Gold rRNA Removal Kit (Illumina, cat.MRZG12324, San Diego, USA). After removing ribosomal RNAs, the left RNAs were fragmented (NEBNext® Magnesium RNA Fragmentation Module, cat.E6150S, USA) into short fragments using divalent cations under high temperature. Then the cleaved RNA fragments were reverse-transcribed to create the cDNA by SuperScript™ II Reverse Transcriptase (Invitrogen, cat. 1896649, USA), which were next used to synthesise U-labeled second-stranded DNAs with E. coli DNA polymerase I (NEB, cat.m0209, USA), RNase H (NEB, cat.m0297, USA) and dUTP Solution (Thermo Fisher, cat.R0133, USA). An A-base was then added to the blunt ends of each strand, preparing them for ligation to the indexed adapters. Each adapter contains a T-base overhang for ligating the adapter to the A-tailed fragmented DNA. Single- or dual-index adapters are ligated to the fragments, and size selection (300-600bp) was performed with AMPureXP beads. After the heat-labile UDG enzyme (NEB, cat.m0280, USA) treatment of the U-labeled second-stranded DNAs, the ligated products were amplified with PCR by the following conditions: initial denaturation at 95℃ for 3 min; 8 cycles of denaturation at 98℃ for 15 sec, annealing at 60℃ for 15 sec, and extension at 72℃ for 30 sec; and then final extension at 72℃ for 5 min. The average insert size for the final cDNA library was 300±50bp. At last, we performed the 2×150bp paired-end sequencing (PE150) on an Illumina Novaseq™ 6000 (LC-Bio Technology CO., Ltd., Hangzhou, China) following the vendor's recommended protocol.

value: Liver

tag: strain

tag: age

value: 12 weeks old

value: high-fat diet


title: Day 1 ARID1A CUT&RUN profiling in SMARCB1 +/+ G401 cell line Rep1


title: LFD1

description: circRNA

value: low fat diet


title: Day 1 PBRM1 CUT&RUN profiling in SMARCB1 +/+ G401 cell line Rep1


title: LFD3

description: circRNA


title: LFD2

description: circRNA


title: Day 0 SMARCC1 CUT&RUN profiling in SMARCB1 -/- G401 cell line Rep1

value: SMARCB1 -/- G401 cell line


title: smNPCs, Parental, SMARCA4/BRG1

value: parental


title: scramble shRNA +TGFB1 + DOX

city: Kansas City

first: Eugene

last: Konorev

state: MISSOURI

address: 1750 Independence Ave

department: Basic Sciences

institute: Kansas City University

data_processing:
The resulting base calling (.bcl) files were converted to FASTQ files using Illumina’s bcl2fastq v2.17.1.14 software
Transcript assembly and abundance estimation and comparing expression were conducted and  reported in Fragments Per Kilobase of exon per Million fragments mapped (FPKM).
Assembly: GRCh38.83
Supplementary files format and content: tab-delimited text file of a matrix table generated and reported in Fragments Per Kilobase of exon per Million fragments mapped (FPKM).

source_name: cardiac

extract_protocol:
Total RNA isolation
NEB Library
Whole transcriptome paired end sequencing ( 2 X 101 cycles)

treatment_protocol: TGFbeta1 +/-Doxorubicin

value: cardiac

value: microvascular

value: endothelial

value: TGFB1 + DOX


title: Smad3 shRNA + TGFB1


title: smNPCs, pooled input

data_processing:
For data pre-processing, FASTQ files were adaptor-trimmed by TrimGalore [https://github.com/FelixKrueger/TrimGalore] with default parameters and aligned to either hg19 or mm10 genome by Bowtie2.
Trimmed FASTQ files were then aligned to Dm6 genome for later calculation of scaling factors. Calculation of scaling factors and aligned BAM files were down-sampled by Picard.
To identify differential binding regions for H3K27me3, respectively, down-sampled BAM files were transformed into BED format by Bedtools.
Differential binding regions were then called by diffReps with a window size of 300bp for H3K27me3.
Data visualization was done using BigWig files for H3K27me3 signal, generated by the bamCompare command in deepTools using input signal as control.
Assembly: mm10 or hg38
Supplementary files format and content: bigWig

value: H3K27me3, AB_2561020, Actife Motif


title: smNPCs, BCL7A KO2, H3K27me3


title: Py2T_PBS_replicate_2

city: Basel

first: Ravi Kiran Reddy

last: KALATHUR

state: Basel

address: Mattenstrasse 28

department: Departement Biomedizin

country: Switzerland

institute: University of Basel

data_processing:
Base calling was done using Illumina software
Sequenced reads were mapped to MM10 version of mouse genome using RNA-STAR using parameters (outFilterMultimapNmax=10 and outFilterType="BySJout")
Counts are obtained using qcount in qusaR and CPM (counts per million) was computed for each sample
Genome_build: mm10
Supplementary_files_format_and_content: txt file and contains counts as CPM values for each sample

source_name: Breast cancer cells

growth_protocol: Py2T cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Sigma-Aldrich, D5671) supplemented with 10% Fetal Bovine Serum (FBS, 10%; Sigma-Aldrich), 2 mM glutamine (Sigma-Aldrich, G7513), 100 U penicillin (Sigma-Aldrich) and 0.1 mg/ml streptomycin (Sigma-Aldrich). All cell lines were grown at 37°C, 5% CO2, 95% humidity.

extract_protocol:
Total RNA was isolated from the samples above using the miRNeasy Mini Kit (Qiagen, 217004) with on-column DNAse digestion according to the manufacturer’s instructions. 5g of RNA was then subjected to rRNA depletion using the Ribozero magnetic gold kit (Epicentre, MRZG12324) followed by concentrating it using the  RNeasy MinElute Cleanup Kit (Qiagen, 74204).
Total RNA was isolated from the samples above using the miRNeasy Mini Kit (Qiagen, 217004) with on-column DNAse digestion according to the manufacturer’s instructions. RNA quality control was performed with an RNA ScreenTape on the Agilent 4200 TapeStation and the concentration measured by using the Quanti-iT RiboGreen RNA assay Kit (Life Technologies). 200 ng of RNA were subjected to rRNA depletion and utilized for library preparation with the Truseq Stranded Total RNA Library Prep kit with Ribo-Zero Gold (Illumina). Library QC was performed with a Fragment Analyzer (AATI) using the Standard Sensitivity NGS Fragment Analysis Kit (DNF-473). RNA-seq libraries were sequenced SR81 with NextSeq 500 High Output v2 kit (Illumina) on an Illumina NextSeq 500 using protocols defined by the manufacturer; primary data analysis was done using Illumina RTA Version: 2.4.11.

treatment_protocol: For the H2O2 treatment, Py2T epithelial cells were daily treated during 4 months with 40 µM and 60 µM H2O2 (Py2T C40 and Py2T I60 cells respectively). Untreated cells served as control and were named Py2T PBS.

value: Tumor developed in mammary gland

value: PBS

tag: h2o2 concentration

value: 0 uM

tag: treatment length

value: daily, 4 months


title: smNPCs, BCL7A KO1, H3K27me3

value: iPSC-derivd NPCs


title: scramble shRNA +TGFB1


title: HFD1

description: circRNA


title: Day 0 BRD9 CUT&RUN profiling in SMARCB1 -/- G401 cell line Rep1

value: G401 cell line


title: N_2

value: liver tissues

value: control

value: wild-type


title: STR, MPTP, ISTR_M

city: Guangzhou

first: Shanshan

last: Ma

state: Guangdong Province

address: No. 74 Zhongshan Road 2, Yuexiu District

institute: Sun Yat-sen University (North Campus)

data_processing:
featureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. And then FPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene.
RNA per sample was isolated per sample and quality was assessed on the Agilent Bioanalyzer 2100 system. Sequencing libraries were generated using NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. RNA-seq libraries preparations were sequenced on an Illumina Novaseq platform and 150 bp paired-end reads were generated.
Fastp (version v0.23.1) was adopted to assess the quality of the raw data and used to remove low quality data, adapter, and poly-N sequences. Clean data were collected, and then the basic information, including its value of GC content, Q20 and Q30, was calculated. All analyses of downstream steps were done using the filtered clean data
Assembly: mm10
Supplementary files format and content: tab-delimited text files include count values for each Sample

source_name: striatum

extract_protocol:
RNA was harvested by Translating Ribosome Affinity Purification(TRAP)
RNA libraries for RNA-seq were prepared using NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations

treatment_protocol: Mice were treated with MPTP or saline by i.p. once a day for three consecutive days. Six hours after last MPTP or saline administration, mice were euthanized with avertin and dissected the substantia nigra (SN) and striatum (STR) of midbrain

value: striatum

value: All

value: MPTP


title: smNPCs, Parental, H3K27me3

value: parental


title: Day 0 PBRM1 CUT&RUN profiling in SMARCB1 -/- G401 cell line Rep1

value: SMARCB1 -/- G401 cell line


title: STR, Saline, ISTR_S

value: saline


title: Smad3 shRNA + TGFB1 + DOX

value: cardiac

value: microvascular

value: endothelial

value: TGFB1 + DOX


title: HFD2

description: circRNA

value: Liver

value: 12 weeks old

value: high-fat diet


title: Memory CD8 12h

city: Bethesda

first: Jack

last: Bibby

address: 10 Center Drive

institute: National Institutes of Health

library_source: transcriptomic single cell

data_processing:
Initial quality control was performed on the resulting scRNAseq data from each sample using Cell Ranger (v2.1.0). All data processing parameters and scripts used for processing all samples can be found upon publication at https://github.com/jackbibby1/scpa_paper. Briefly, we excluded any cells with >10% of reads mapping to mitochondrial genes, and filtered cells based on number of genes expressed. Filtered count matrices were then normalized by total UMI counts, multiplied by 10,000 and transformed to natural log space. The top 2000 variable features were determined based on the variance stabilizing transformation function (FindVariableFeatures) by Seurat (Hao et al., 2021) with default parameters. Any cycle genes were removed from the variable features list to reduce cell-cycle associated variation, prior to downstream analysis. For each sorted T cell population, samples were integrated across time points using canonical correlation analysis (CCA), resulting in four integrated datasets. For example, naïve CD4+ T cells at 0, 12, and 24 hours were integrated, followed by memory CD4+ T cells, and so on for CD8+ T cells. Variants arising from cell cycle phases and the percentage of mitochondrial genes were regressed using by the ScaleData function in Seurat. Principal component analysis (PCA) was then performed, and the top 30 Principal components (PCs) were included in a Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction. Clusters were identified by canonical marker genes on a shared nearest neighbor (SNN) modularity graph using the top 30 PCs and the original Louvain algorithm. Markers for each population were calculated using the FindAllMarkers(min.pct = 0.1, logfc.threshold = 0.25, only.pos = T) function within Seurat.
Supplementary files format and content: Data files provided are 1) raw = bam files, 2) processed = barcodes, features, and matrix files from Cell Ranger, and 3) processed = rds files of the integrated and processed Seurat objects

molecule: polyA RNA

source_name: Peripheral blood

growth_protocol: T cells were cultured in RPMI with 10% FCS, L-Glutamine, and pen-strep.

extract_protocol: We prepared single cell transcriptome libraries using the 10xGenomics Chromium Single Cell v3 kit, in accordance with the company’s manual

treatment_protocol: Plate bound anti-CD3 and anti-CD28 were used to stimulate CD4+ (both 2ug/ml), and CD8+ (0.25 and 2 ug/ml, respectively) T cells

value: Memory CD8 T cells

value: Peripheral blood

tag: subject status

value: healthy donor


title: Memory CD8 24h


title: SN, Saline, ISN_S

source_name: substantia nigra

value: substantia nigra


title: ccRCC_607

city: Seoul

first: BYULA

last: JEE

address: 81 Irwon-Ro Gangnam-gu

department: Urology

country: South Korea

institute: Samsung medical center

data_processing:
The reads were mapped to the hg19 human reference genome using STAR with default parameter.
The counts of reads mapping to each gene were calculated using RSEM with default parameter.
Assembly: hg19

source_name: clear cell renal cell carcinoma

extract_protocol:
Total RNA was extracted utilizing the RNA extraction kit (Rneasy Mini Kit, QIAGEN), and RNA integrity was verified using a 2100 Bioanalyzer (Aglient).
The libraries for sequencing were generated using the QuantSeq 3’ Library Prep Kit (Lex-ogen Inc., Vienna, Austria) according to the manufacturer’s instructions

value: clear cell renal cell carcinoma

tag: disease state

value: Tumor

tag: sf status

value: No SF loss


title: STR, Microglia, MPTP, MGSTRM3

value: striatum

value: Microglia

value: MPTP


title: ccRCC_606


title: Day 3 ATAC-seq profiling in SMARCB1 +/+ G401 cell line Rep2

data_processing:
Reads were deduplicated with the clumpify tool using flag -dedupe -subs=2, and subsequently trimmed with bbduk using parameters --ktrim=r --k=21 --mink=11 --hdist=1 --tpe --tbo.
The trimmed fastq files were then aligned to the Hg19 human genome using Bowtie2 aligner. In specific, we used the “very-sensitive” mode for the alignment.
The aligned SAM files were further converted to bedgraph files using Deeptools software by function bamCoverage function and corrected for Tn5 insertion
MACS2 software (v.2.1.1.20160309) was used for calling ATAC peaks with parameters with parameter “-g hs -q 0.01 --nomodel  --shift 0”.
Genome_build: hg19
Supplementary_files_format_and_content: bigwig
Supplementary_files_format_and_content: ATAC_peaks.bed includes the peaks for all ATAC-seq samples.

extract_protocol:
Tagmented DNA was purifed using Monarch® PCR & DNA Cleanup Kit (T1030S)
Tagmented DNA from 100,000 cells per replicate was size selected with Pronex beads (Cat.#NG2003, Promega) prior to paired end sequencing by Illumina HiSeq Genome Analyzer (PE 2X150). Average of ~ 20 million reads per sample.

value: G401 cell line

value: SMARCB1 +/+ G401 cell line


title: Naïve CD8 24h

value: naive CD8 T cells


title: Memory CD8 0h


title: ccRCC_475


title: Day 7 ATAC-seq profiling in SMARCB1 +/+ G401 cell line Rep1


title: Naïve CD8 12h


title: ccRCC_586


title: Day 7 ATAC-seq profiling in SMARCB1 +/+ G401 cell line Rep2


title: STR, Microglia, MPTP, MGSTRM2


title: Day 3 ATAC-seq profiling in SMARCB1 +/+ G401 cell line Rep1


title: Day 1 BRD9 CUT&RUN profiling in SMARCB1 +/+ G401 cell line Rep1


title: STR, Microglia, MPTP, MGSTRM1


title: ccRCC_474


title: Day 0 ARID1A CUT&RUN profiling in SMARCB1 -/- G401 cell line Rep1

value: SMARCB1 -/- G401 cell line


title: Day 1 ATAC-seq profiling in SMARCB1 +/+ G401 cell line Rep2


title: Naïve CD8 0h


title: ccRCC_473


title: STR, Microglia, saline, MGSTRS4

value: saline


title: Day 1 ATAC-seq profiling in SMARCB1 +/+ G401 cell line Rep1


title: SN, MPTP, ISN_M

value: All


title: ccRCC_472


title: STR, Microglia, saline, MGSTRS3


title: Day 0 ATAC-seq profiling in SMARCB1 -/- G401 cell line Rep2


title: Memory CD4 12h

value: Memory CD4 T cells


title: Memory CD4 24h


title: STR, Microglia, saline, MGSTRS2


title: ccRCC_463


title: STR, Microglia, saline, MGSTRS1


title: G401_SMARCB1_Day3_SMARCC1_DA_Rep2

data_processing:
Library strategy: CUT&RUN
Reads were deduplicated with the clumpify tool using flag -dedupe -subs=2, and subsequently trimmed with bbduk using parameters --ktrim=r --k=21 --mink=11 --hdist=1 --tpe --tbo.
The trimmed fastq files were then aligned to the Hg19 human genome using Bowtie2 aligner. Specifically, we used parameter “--end-to-end --very-sensitive --no-mixed --no-discordant -q -I 10 -X 700 --phred33” for the alignment.
Bam files were converted to bed files after removing chrM, chrUn, and reads containing “random” as chromosome position. Bed files were further cleaned by removing regions contained in the hg19 blacklist from ENCODE (v2)
Epic2 software (v.0.0.41) was used for calling histones and SWI/SNF peaks with parameters at default
Genome_build: hg19
Supplementary_files_format_and_content: bigwig

source_name: Day 3 SMARCC1 CUT&RUN profiling in SMARCB1 +/+ G401 cell line under all KD

treatment_protocol: To induce SMARCB1 re-expression, cells were treated with doxycycline (1 μg/ml, EMD Millipore) for indicated time. SMARTpool ON-TARGETplus siRNA targeting JUND, JUNB, JUN and non-targeting control siRNA were purchased from Horizon Disocvery (Cat#:L-003269-00-0005; L-003900-00-0005; L-003268-00-0005; D-001810-10-05) and transfected using Lipofectamine™ RNAiMAX Transfection Reagent (ThermoFisher, Cat# 13778075).


title: SN, Microglia, MPTP, MGSN-M3


title: G401_SMARCB1_Day3_SMARCC1_DN_Rep2

source_name: Day 3 SMARCC1 CUT&RUN profiling in SMARCB1 +/+ G401 cell line under non-targeting control


title: ccRCC_460


title: Day 0 ATAC-seq profiling in SMARCB1 -/- G401 cell line Rep1


title: G401_SMARCB1_Day3_ARID1A_DA_Rep2

source_name: Day 3 ARID1A CUT&RUN profiling in SMARCB1 +/+ G401 cell line under all KD


title: SN, Microglia, MPTP, MGSN-M2


title: Memory CD4 0h


title: ccRCC_459


title: Naïve CD4 0h

value: naive CD4 T cells


title: SN, Microglia, MPTP, MGSN-M1


title: ccRCC_462


title: ccRCC_457

value: SF loss


title: Naïve CD4 12h

value: Peripheral blood

value: healthy donor


title: ccRCC_456

value: clear cell renal cell carcinoma


title: G401_SMARCB1_Day0_SMARCC1_NA_Rep2

source_name: Day 0 SMARCC1 CUT&RUN profiling in SMARCB1 -/- G401 cell line under all KD


title: Naïve CD4 24h


title: SN, Microglia, saline, MGSN-S3

value: substantia nigra


title: G401_SMARCB1_Day0_SMARCC1_NN_Rep2

source_name: Day 0 SMARCC1 CUT&RUN profiling in SMARCB1 -/- G401 cell line under non-targeting control


title: SN, Microglia, saline, MGSN-S1


title: SN, Microglia, saline, MGSN-S2


title: ccRCC_455

value: Tumor

value: No SF loss


title: ccRCC_467


title: STR, Astrocyte, MPTP, ASSTR-M3

value: striatum

value: Astrocyte


title: G401_SMARCB1_Day0_ARID1A_NN_Rep2

source_name: Day 0 ARID1A CUT&RUN profiling in SMARCB1 -/- G401 cell line under non-targeting control

value: G401 cell line


title: G401_SMARCB1_Day3_ARID1A_DN_Rep2

source_name: Day 3 ARID1A CUT&RUN profiling in SMARCB1 +/+ G401 cell line under non-targeting control

value: SMARCB1 +/+ G401 cell line


title: ccRCC_454


title: G401_SMARCB1_Day0_ARID1A_NA_Rep2

source_name: Day 0 ARID1A CUT&RUN profiling in SMARCB1 -/- G401 cell line under all KD


title: STR, Astrocyte, MPTP, ASSTR-M2

value: MPTP


title: G401_SMARCB1_Day3_IgG_DA

source_name: Day 3 IgG CUT&RUN profiling in SMARCB1 +/+ G401 cell line under all KD

value: IgG


title: STR, Astrocyte, MPTP, ASSTR-M1


title: VT103_3

city: Charlestown

first: Yang

last: Sun

state: MA

address: 149 13th Street, CBRC 3050E

department: CBRC

institute: Massachusetts General Hospital

data_processing:
"Qphred" represents base quality values of Illunima, the Qphred=-10log10(e). Base Quality and Phred score relationship in illumina Casava 1.8
GC-content is used to detect potential AT/GC separation.
The Sequenced Reads/raw reads often contain low quality reads or reads with adaptors. Raw reads filtering conditions are as follows: (1) Remove reads containing adaptors; (2) Remove reads containing N > 10% (N represents base that could not be determined);(3) The Qscore (Quality value) of over 50% bases of the read is <= 5.
Novogene use STAR to accomplish the mapping. For the spieces(Human and mice) whose gene annotation information are more completed, if only need the differential expression significant genes, can map reads to the transcriptome directly. If research the study of alternative splicing, variation, the fusion gene, the alignment should be carried out at the genome level. In order to avoid losing a lot of effective junction reads, Novogene use STAR software to alignment for RNA-seq sequencing data analysis, the junction reads can be positioned precisely
Reads will be mapped to exon, intron and intergenic.
After getting the information about distribution of mapped reads on genome area, we will focus the distribution of mapped reads on chromosome. On one hand we can get insight into how many regions on chromosome is covered, on the other hand we can get the information about transcription activity on chromosome.We calculate mapped reads density on every chromosome , then plot based on the mapped reads density. In general, the longer the chromosome is, the more reads will be mapped to the chromosome. The statistics of reads mapped to chromosome indicates the relationship between chromosome length and reads number.
Assembly: Homo_sapiens_hg38
Supplementary files format and content: fpkm

growth_protocol: NCI-H226 cells were culture in RPMI supplied with 10% FBS and Penicillin-Streptomycin

extract_protocol:
RNA was harvested using RNeasy Mini Kit (Qiagen 74104)
mRNA from Eukaryote organisms is purified from total RNA using poly-T oligo-attached magnetic beads (For prokaryotes, mRNA was purified through the removal of rRNA by using kit). The mRNA is first fragmented randomly by addition of fragmentation buffer.Then first strand cDNA is synthesized using random hexamer primer and M-MuLV Reverse Transcriptase (RNase H-). Second strand cDNA synthesis is subsequently performed using DNA Polymerase I and RNase H. Double-stranded cDNA is purified using AMPure XP beads. Remaining overhangs of the purified double-stranded cDNA are converted into blunt ends via exonuclease/polymerase activities. After adenylation of 3' ends of DNA fragments, NEBNext Adaptor with hairpin loop structure is ligated to prepare for hybridization(1). In order to select cDNA fragments of preferentially 150~200 bp in length, the library fragments are purified with AMPure XP system (Beckman Coulter, Beverly, USA). Finally, the final library is gotten by PCR amplification and purification of PCR products by AMPure XP beads.

treatment_protocol: Cells were treated with vehicle control, TM2(1uM), K975(1uM) or VT103 (1uM) for 24 hours

value: Mesothelioma cell line

value: WT

value: VT103 1uM

tag: time

value: 24 hours


title: VT103_1


title: K975_3


title: G401_SMARCB1_Day3_IgG_DN

source_name: Day 3 IgG CUT&RUN profiling in SMARCB1 +/+ G401 cell line under non-targeting control


title: STR, Astrocyte, saline, ASSTR-S3

value: saline


title: STR, Astrocyte, saline, ASSTR-S2


title: STR, Astrocyte, saline, ASSTR-S1


title: ccRCC_911


title: ccRCC_912

value: SF loss


title: K975_1


title: ccRCC_910


title: ccRCC_913


title: G401_SMARCB1_Day3_ARID1A_DA_Rep1


title: TM1_3

value: TM2 1uM


title: ccRCC_909

value: clear cell renal cell carcinoma


title: SN, Astrocyte, MPTP, ASSN-M3

value: substantia nigra


title: ccRCC_914

value: Tumor


title: VT103_2


title: G401_SMARCB1_Day3_ARID1A_DN_Rep1


title: ccRCC_908

value: No SF loss


title: SN, Astrocyte, MPTP, ASSN-M2


title: TM1_2


title: ccRCC_906


title: TM1_1


title: G401_SMARCB1_Day0_IgG_NN

source_name: Day 0 IgG CUT&RUN profiling in SMARCB1 -/- G401 cell line under non-targeting control

value: SMARCB1 -/- G401 cell line


title: Control_3 NCI-H226

value: vehicle control


title: SN, Astrocyte, MPTP, ASSN-M1

value: Astrocyte


title: G401_SMARCB1_Day3_SMARCC1_DA_Rep1

value: G401 cell line

value: SMARCB1 +/+ G401 cell line


title: G401_SMARCB1_Day0_IgG_NA

source_name: Day 0 IgG CUT&RUN profiling in SMARCB1 -/- G401 cell line under all KD

value: IgG


title: K975_2

value: Mesothelioma cell line


title: G401_SMARCB1_Day0_SMARCC1_NA_Rep1


title: ccRCC_903


title: SN, Astrocyte, saline, ASSN-S3


title: ccRCC_901


title: G401_SMARCB1_Day3_SMARCC1_DN_Rep1


title: SN, Astrocyte, saline, ASSN-S2


title: ccRCC_900


title: G401_SMARCB1_Day0_SMARCC1_NN_Rep1


title: SN, Dopaminic neuron, MPTP, DANSN-M5

value: Dopaminic neuron

value: MPTP


title: G401_SMARCB1_Day0_ARID1A_NN_Rep1


title: G401_SMARCB1_Day0_ARID1A_NA_Rep1


title: Control_1 NCI-H226

value: WT

value: 24 hours


title: ccRCC_899


title: SN, Dopaminic neuron, MPTP, DANSN-M4


title: ccRCC_897

value: SF loss


title: PRO-seq 5h_Degrader_rep_2

city: Dundee

first: Ralitsa

middle: Radostinova

last: Madsen

address: Dow Street

department: Medical Research Council Protein Phosphorylation and Ubiquitylation Unit

country: United Kingdom

institute: School of Life Sciences, University of Dundee

data_processing:
Using a custom script (trim_and_filter_PE.pl), FASTQ read pairs were trimmed to 41bp per mate, and read pairs with a minimum average base quality score of 20 retained. Read pairs were further trimmed using cutadapt 1.14 to remove adapter sequences and low-quality 3’ bases (--match-read-wildcards -m 20 -q 10). R1 reads, corresponding to RNA 3’ ends, were then aligned to the spiked in Drosophila genome index (dm3) using Bowtie 1.2.2 (-v 2 -p 6 --best --un), with those reads not mapping to the spike genome serving as input to the primary genome alignment step (using Bowtie 1.2.2 options -v 2 --best). Reads mapping to the hg38 reference genome were then sorted, via samtools 1.3.1 (-n), and subsequently converted to bedGraph format using a custom script (bowtie2stdBedGraph.pl) that counts each read once at the exact 3’ end of the nascent RNA. Because R1 in PRO-seq reveals the position of the RNA 3’ end, the “+” and “-“ strands were swapped to generate bedGraphs representing 3’ end positions at single nucleotide resolution. All custom scripts are available on the AdelmanLab Github (https://github.com/AdelmanLab/NIH_scripts).
Annotated transcription start sites were obtained from human (GRCh38.99) GTFs from Ensembl. After removing transcripts with {immunoglobulin, Mt_tRNA, Mt_rRNA} biotypes, PRO-seq signal in each sample was calculated in the window from the annotated TSS to +150 nt downstream, using a custom script, make_heatmap.pl. Given good agreement between replicates and similar return of spike-in reads, bedGraphs were merged within conditions, and depth-normalized, to generate bigWig files binned at 10bp.
Paired-end RNA-seq reads were mapped to the hg38 reference genome via HISAT2 v2.2.1 (--known-splicesite-infile). To select gene-level features for differential expression analysis, and for pairing with PRO-seq data, we assigned a single, dominant TSS and transcription end site (TES) to each active gene. This was accomplished using a custom script, get_gene_annotations.sh (available at https://github.com/AdelmanLab/GeneAnnotationScripts), which uses RNA-seq read abundance and PRO-seq R2 reads (RNA 5’ ends) to identify dominant TSSs, and RNA-seq profiles to define most commonly used TESs. RNA-seq and PRO-seq data from all conditions were used for this analysis, to comprehensively capture gene activity in these samples.
Reads were summed within the TSS to TES window for each active gene using the make_heatmap script (https://github.com/AdelmanLab/NIH_scripts), which counts each read once, at the exact 3’ end location of the nascent RNA.
All subsequent analysis steps using  transcript counts were performed in R. Filtering of low gene expression counts was performed with the TCGAbiolinks package with quantile value 0.1. Subsequent count normalization was performed with the trimmed mean of M (TMM) method. The mean-variance relationship was modelled with voom(), followed by linear modelling and computation of moderated t-statistics using the lmFit() and eBayes() functions in the limma package. Experimental replicate was included as a batch effect term in the linear model. The associated p-values for assessment of differential gene expression were adjusted for multiple comparisons with the Benjamini-Hochberg method at false-discovery rate (FDR) = 0.05. Adjustments were performed separately for each contrast of interest.
Assembly: hg38
Supplementary files format and content: tab-delimited text file containing all transcript counts for each sample
Library strategy: PRO-seq

source_name: breast cancer

growth_protocol: Cells were obtained from ATCC and cultured in RPMI media supplemented with 10% heat inactivated fetal bovine serum without antibiotics at 37 C in the presence of 5 % CO2. Cells were maintained in Corning TC-treated 15 cm culture dishes (08-772-24) in 20 mL medium. Medium was replenished every 3 days, until cells reached 70-90% confluence. To passage, cells were washed once with 10 mL PBS and incubated for 5-10 minutes at 37 C with 0.25% Trypsin 0.1% EDTA and passaged up to 5 times in the same dish. Cells were maintained in culture for up to one month. Cells were routinely tested for mycoplasma using a Mycoplasma Detection Kit (Lonza cat. no. LT07-218).

extract_protocol:
To harvest cell pellets for PRO-seq, cells were washed once with 8 mL room temperature 1X PBS then trypsinized for 5 minutes. Trypsin was quenched with ice cold DMEM + 10% FBS and cells were collected in a 50 mL conical tube and placed onto ice immediately. Cells were spun at 300 x g for 4 min at 4 °C, supernatant was removed, and cells were resuspended in 250 µL Buffer W (10 mM Tris-Cl, pH 8.0; 10 mM KCl; 250 mM Sucrose; 5 mM MgCl2; 1 mM EGTA; 0.5 mM DTT; 10 % (v/v) Glycerol; Protease inhibitor tablet (EDTA-free), 0.02% SUPERase-IN RNase inhibitor) to obtain a single-cell suspension by pipetting. 10 mL of Buffer P (10 mM Tris-Cl, pH 8.0; 10 mM KCl; 250 mM Sucrose; 5 mM MgCl2; 1 mM EGTA; 0.1 % (v/v) Igepal CA-630; 0.5 mM DTT; 0.05 % (v/v) Tween-20; 10 % (v/v) Glycerol; Protease inhibitor tablet (EDTA-free), 0.02% SUPERase-IN RNase inhibitor) was added and cells were incubated on ice for 5 min, then spun at 400 x g for 4 min at 4 °C. Supernatant was removed and Buffer W was added and pipetted gently 2-3 times to resuspend cell suspension. An additional 9 mL of Buffer W was added to each tube, and cells were spun at 400 x g for 4 min at 4 °C. An additional wash with Buffer W was completed as above and supernatant was carefully decanted so cell pellets were not disturbed. Pellets were resuspended in Buffer F (50 mM Tris-Cl, pH 8.0; 40 % (v/v) glycerol; 5 mM MgCl2; 1.1 mM EDTA; 0.5 mM DTT, and SUPERase-IN RNase inhibitor) and transferred to a 1.5 mL tube. The 50mL tube was rinsed once more with 250 µl of Buffer F and added to the corresponding 1.5 mL tube for a final volume of 500 µl per sample. 10 µl were reserved for counting after dilution 1:10 and 1:20 in PBS, both with and without trypan blue to calculate the fraction of permeabilized cells. Cells were diluted to 1E6 permeabilized cells per 100 µl and a total of 5E6 cells were aliquoted in 500 µl of Buffer F and snap frozen in liquid nitrogen and stored at -80 °C until further processing. RNase-free water was used to make all reagents and solutions, and solutions were filter sterilized with 0.2 µM filters into RNase-free plastic bottles.
Aliquots of frozen (-80 °C) permeabilized cells were thawed on ice and pipetted gently to fully resuspend. Aliquots were removed and permeabilized cells were counted using a Luna II, Logos Biosystems instrument. For each sample, 1 million permeabilized cells were used for nuclear run-on, with 50,000 permeabilized Drosophila S2 cells added to each sample for normalization. Nuclear run-on assays and library preparation were performed essentially as described in Reimer et al. [K. A. Reimer, C. A. Mimoso, K. Adelman, K. M. Neugebauer, Molecular Cell (2021)] with modifications noted: 2X nuclear run-on buffer consisted of (10 mM Tris (pH 8), 10 mM MgCl2, 1 mM DTT, 300mM KCl, 40uM/ea biotin-11-NTPs (Perkin Elmer), 0.8 U/µL SuperaseIN (Thermo), 1% sarkosyl).  Run-on reactions were performed at 37 °C.  Adenylated 3' adapter was prepared using the 5' DNA adenylation kit (NEB) and ligated using T4 RNA ligase 2, truncated KQ (NEB, per manufacturers instructions with 15% PEG-8000 final) and incubated at 16 °C overnight.  180 µL of betaine blocking buffer (1.42 g of betaine brought to 10 mL with binding buffer supplemented to 0.6 uM blocking oligo (TCCGACGATCCCACGTTCCCGTGG/3InvdT/)) was mixed with ligations and incubated 5 min at 65°C and 2 min on ice prior to addition of streptavidin beads.  After T4 polynucleotide kinase (NEB) treatment, beads were washed once each with high salt, low salt, and blocking oligo wash (0.25X T4 RNA ligase buffer (NEB), 0.3 µM blocking oligo) solutions and resuspended in 5' adapter mix (10 pmol 5' adapter, 30 pmol blocking oligo, water).  5' adapter ligation was per Reimer but with 15% PEG-8000 final. Eluted cDNA was amplified 5-cycles (NEBNext Ultra II Q5 master mix (NEB) with Illumina TruSeq PCR primers RP-1 and RPI-X) following the manufacturer's suggested cycling protocol for library construction.

value: breast cancer

value: breast cancer, luminal

value: ERpos HER2neg

value: Degrader

tag: replicate


title: PRO-seq 5h_GDC0068_rep_2

tag: tissue


title: G401_SMARCB1_Day7_JUND_Rep2

data_processing:
Library strategy: CUT&RUN
Reads were deduplicated with the clumpify tool using flag -dedupe -subs=2, and subsequently trimmed with bbduk using parameters --ktrim=r --k=21 --mink=11 --hdist=1 --tpe --tbo.
The trimmed fastq files were then aligned to the Hg19 human genome using Bowtie2 aligner. Specifically, we used parameter “--end-to-end --very-sensitive --no-mixed --no-discordant -q -I 10 -X 700 --phred33” for the alignment.
Bam files were converted to bed files after removing chrM, chrUn, and reads containing “random” as chromosome position. Bed files were further cleaned by removing regions contained in the hg19 blacklist from ENCODE (v2)
MACS2 software (v.2.1.1.20160309) was used for calling TF peaks with parameters at default “callpeak -g hs -f BAMPE -q 0.05 -B”. Peaks were further cleaned by using a cutoff of signalValue greater than 5.
Genome_build: hg19
Supplementary_files_format_and_content: bigwig
Supplementary_files_format_and_content: CUT_RUN_peak.bed, which includes the peaks for all SWI/SNF subunits and AP-1 samples, is linked to the SuperSeries GSE196960 record.

source_name: Day 7 JUND CUT&RUN profiling in SMARCB1 +/+ G401 cell line

tag: treatment

value: JUND


title: SN, Dopaminic neuron, MPTP, DANSN-M3

value: substantia nigra


title: PRO-seq 5h_DMSO_rep_2

tag: cell line

value: DMSO


title: ccRCC_896

value: clear cell renal cell carcinoma

value: Tumor

value: No SF loss


title: Control_2 NCI-H226

value: vehicle control


title: ccRCC_895


title: PRO-seq 5h_Degrader_rep_1


title: PRO-seq 5h_GDC0068_rep_1


title: ccRCC_894


title: SN, Dopaminic neuron, MPTP, DANSN-M1


title: G401_SMARCB1_Day3_JUNB_Rep2

source_name: Day 3 JUNB CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: G401 cell line

value: SMARCB1 +/+ G401 cell line

tag: cut&run antibody

value: JUNB


title: G401_SMARCB1_Day7_pJUN_Rep2

source_name: Day 7 pJUN CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: pJUN

tag: time point


title: PRO-seq 5h_DMSO_rep_1


title: SN, Dopaminic neuron, saline, DANSN-S4

source_name: substantia nigra

value: Dopaminic neuron

value: saline


title: SN, Astrocyte, saline, ASSN-S1

value: Astrocyte


title: G401_SMARCB1_Day3_JUND_Rep2

source_name: Day 3 JUND CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: ccRCC_892

source_name: clear cell renal cell carcinoma

value: SF loss


title: 10h_NegCtrl_rep_3

data_processing:
Nextflow (version 20.07.1) nf-core RNAseq pipeline (version 1.4.2), with Spliced Transcripts Aligment to a Reference (STAR) for read alignment to the human genome (Homo_sapiens.GRCh38.96.gtf) and featureCounts for counting of mapped reads (multimapped reads were discarded)
All subsequent analysis steps using the raw gene counts were performed in R. Filtering of low gene expression counts was performed with the TCGAbiolinks package with quantile value 0.75 (chosen empirically based on the observed count distribution).
Read count normalization was performed with the trimmed mean of M (TMM) method.
The mean-variance relationship was modelled with voom(), followed by linear modelling and computation of moderated t-statistics using the lmFit() and eBayes() functions in the limma package.
Experimental replicate was included as a batch effect term in the linear model. The associated p-values for assessment of differential gene expression were adjusted for multiple comparisons with the Benjamini-Hochberg method at false-discovery rate (FDR) = 0.05. Adjustments were performed separately for each contrast of interest.
Assembly: hg38
Supplementary files format and content: tab-delimited text file containing all raw gene counts for each sample

extract_protocol: Takara’s Nucleospin RNA Plus kit (cat. # 740984.50)

value: breast cancer

value: breast cancer, luminal

value: ERpos HER2neg

value: NegCtrl


title: G401_SMARCB1_Day3_pJUN_Rep2

source_name: Day 3 pJUN CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: SN, Dopaminic neuron, saline, DANSN-S2

value: substantia nigra


title: ccRCC_891

value: clear cell renal cell carcinoma


title: 10h_Degrader_rep_3

value: Degrader


title: G401_SMARCB1_Day7_JUNB_Rep2

source_name: Day 7 JUNB CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: G401_SMARCB1_Day1_JUNB_Rep2

source_name: Day 1 JUNB CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: SN, Dopaminic neuron, MPTP, DANSN-M2

value: MPTP


title: ccRCC_890

value: Tumor

value: No SF loss


title: 5h_GDC0068_rep_3


title: MockUP_rep4 [Sample 16]

city: Pamplona

first: Enrique

last: Conde-Gallastegi

address: Av. de Pío XII, 55

country: Spain

institute: CIMA Universidad de Navarra

data_processing:
Aligning with STAR (v2.6.1)
Counting with Subread (v1.6.3)
Assembly: mm10
Supplementary files format and content: Matrix table with raw gene counts for every gene and every sample

source_name: OVA antigen specific CD8 T cell (OT1)

extract_protocol:
RNA was isolated using Maxwell 16 LEV simplyRNA tissue kit (Promega).
RNA libraries were prepared for sequencing using standard Illumina protocols

value: Adoptively transferred CD8 T cells

value: OVA antigen specific CD8 T cell (OT1)


title: G401_SMARCB1_Day1_pJUN_Rep2

source_name: Day 1 pJUN CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: G401 cell line

value: SMARCB1 +/+ G401 cell line

value: pJUN


title: G401_SMARCB1_Day1_JUND_Rep2

source_name: Day 1 JUND CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: JUND


title: SN, Dopaminic neuron, saline, DANSN-S1

value: Dopaminic neuron

value: saline


title: G401_SMARCB1_Day0_JUNB_Rep2

source_name: Day 0 JUNB CUT&RUN profiling in SMARCB1 -/- G401 cell line

value: SMARCB1 -/- G401 cell line

value: JUNB


title: ccRCC_888

value: SF loss


title: 10h_DMSO_rep_3

value: breast cancer

value: breast cancer, luminal

value: ERpos HER2neg

value: DMSO


title: ccRCC_887

value: clear cell renal cell carcinoma

value: Tumor


title: ccRCC_893


title: ccRCC_889

value: No SF loss


title: G401_SMARCB1_Day0_JUND_Rep2

source_name: Day 0 JUND CUT&RUN profiling in SMARCB1 -/- G401 cell line


title: SN, Dopaminic neuron, saline, DANSN-S3

value: substantia nigra


title: 10h_GDC0068_rep_3


title: ccRCC_885


title: Foxp3UP_rep3 [Sample 13]

value: Adoptively transferred CD8 T cells

value: OVA antigen specific CD8 T cell (OT1)


title: 5h_Degrader_rep_3

value: Degrader


title: MockUP_rep3 [Sample 14]


title: 5h_NegCtrl_rep_3

value: NegCtrl


title: G401_SMARCB1_Day0_pJUN_Rep2

source_name: Day 0 pJUN CUT&RUN profiling in SMARCB1 -/- G401 cell line

value: G401 cell line

value: pJUN


title: ccRCC_884


title: 5h_DMSO_rep_3


title: MockDN_rep4 [Sample 12]


title: G401_SMARCB1_Day7_IgG

source_name: Day 7 IgG CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: SMARCB1 +/+ G401 cell line

value: IgG


title: ccRCC_881

value: SF loss


title: 10h_GDC0068_rep_2

source_name: breast cancer

value: breast cancer


title: Foxp3DN_rep4 [Sample 11]


title: Foxp3UP_rep4 [Sample 15]


title: 10h_NegCtrl_rep_2

value: breast cancer, luminal


title: 10h_Degrader_rep_2

value: ERpos HER2neg


title: ccRCC_874


title: Foxp3DN_rep3 [Sample 9]


title: ccRCC_876


title: MockDN_rep3 [Sample 10]


title: G401_SMARCB1_Day1_IgG

source_name: Day 1 IgG CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: ccRCC_880


title: G401_SMARCB1_Day3_IgG

source_name: Day 3 IgG CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: G401_SMARCB1_Day0_IgG

source_name: Day 0 IgG CUT&RUN profiling in SMARCB1 -/- G401 cell line

value: SMARCB1 -/- G401 cell line


title: ccRCC_873

value: clear cell renal cell carcinoma


title: G401_SMARCB1_Day7_JUNB_Rep1

value: JUNB


title: Foxp3UP_rep2 [Sample 7]


title: MockUP_rep2 [Sample 8]


title: 5h_GDC0068_rep_2


title: MockUP_rep1 [Sample 6]


title: G401_SMARCB1_Day7_JUND_Rep1

source_name: Day 7 JUND CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: JUND


title: ccRCC_870

value: Tumor

value: No SF loss


title: 5h_NegCtrl_rep_2


title: 5h_Degrader_rep_2


title: ccRCC_872


title: 5h_DMSO_rep_2

value: DMSO


title: G401_SMARCB1_Day3_JUNB_Rep1

source_name: Day 3 JUNB CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: ccRCC_867

source_name: clear cell renal cell carcinoma


title: G401_SMARCB1_Day7_pJUN_Rep1

source_name: Day 7 pJUN CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: ccRCC_866


title: MockDN_rep2 [Sample 4]

value: Adoptively transferred CD8 T cells

value: OVA antigen specific CD8 T cell (OT1)


title: G401_SMARCB1_Day3_JUND_Rep1

source_name: Day 3 JUND CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: G401 cell line


title: 10h_DMSO_rep_2


title: 10h_GDC0068_rep_1


title: Foxp3DN_rep2 [Sample 3]


title: MockDN_rep1 [Sample 2]


title: ccRCC_863


title: Foxp3DN_rep1 [Sample 1]


title: 10h_Degrader_rep_1

value: Degrader


title: G401_SMARCB1_Day3_pJUN_Rep1

source_name: Day 3 pJUN CUT&RUN profiling in SMARCB1 +/+ G401 cell line

value: SMARCB1 +/+ G401 cell line

value: pJUN


title: 10h_DMSO_rep_1


title: G401_SMARCB1_Day1_JUNB_Rep1

source_name: Day 1 JUNB CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: ccRCC_861

value: SF loss


title: 5h_GDC0068_rep_1

value: breast cancer


title: ccRCC_859


title: Foxp3UP_rep1 [Sample 5]

source_name: OVA antigen specific CD8 T cell (OT1)


title: G401_SMARCB1_Day1_pJUN_Rep1

source_name: Day 1 pJUN CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: ccRCC_860


title: G401_SMARCB1_Day1_JUND_Rep1

source_name: Day 1 JUND CUT&RUN profiling in SMARCB1 +/+ G401 cell line


title: G401_SMARCB1_Day0_JUND_Rep1

source_name: Day 0 JUND CUT&RUN profiling in SMARCB1 -/- G401 cell line


title: D_2608 WT-DOX

data_processing:
The raw base calling (.bcl) files were converted to demultiplexed compressed FASTQ files using CASAVA
Novogene's STAR was used to  map RNA-seq reads against the mouse reference genome
Transcript assembly and abundance estimation and comparing expression were conducted and  reported in Fragments Per Kilobase of exon per Million fragments mapped (FPKM).
Assembly: GRCm38.p4
Supplementary files format and content: tab-delimited text file of a matrix table generated and reported in Fragments Per Kilobase of exon per Million fragments mapped (FPKM).

source_name: cardiac

growth_protocol: 20 weeks old

extract_protocol:
Total RNA isolation
NEB Library ; Whole transcriptome paired end sequencing ( 2 X 150 cycles)

treatment_protocol: Doxorubicin

value: cardiac

value: Cardiac endothelial cells

tag: Sex

value: male

value: Smad3 KO

value: Doxorubicin


title: 5h_Degrader_rep_1

tag: cell type

value: breast cancer, luminal

value: ERpos HER2neg


title: ccRCC_858

value: clear cell renal cell carcinoma

value: Tumor

tag: genotype

value: No SF loss


title: D_2611 WT-Salline

value: WT

value: Saline


title: D_2605 Smad3 KO DOX


title: ccRCC_856


title: G401_SMARCB1_Day0_pJUN_Rep1

source_name: Day 0 pJUN CUT&RUN profiling in SMARCB1 -/- G401 cell line

value: G401 cell line

value: SMARCB1 -/- G401 cell line


title: 5h_DMSO_rep_1

source_name: breast cancer

value: DMSO


title: 10h_NegCtrl_rep_1

value: NegCtrl


title: G401_SMARCB1_Day0_JUNB_Rep1

source_name: Day 0 JUNB CUT&RUN profiling in SMARCB1 -/- G401 cell line

value: JUNB


title: 5h_NegCtrl_rep_1

value: breast cancer


title: D_2606 Smad3 KO Saline

value: cardiac

value: Cardiac endothelial cells


title: ccRCC_857


title: WTCtr biol rep 2

status: Public on Oct 14 2022

city: Madrid

first: Francisco

last: Tenllado

address: Ramiro de Maeztu, 9

institute: CSIC

data_processing:
Illumina NovaSeq 6000 System
Clean sequence reads were obtained from raw data by removing reads containing adapter, reads containing ploy-N and low quality reads using in-house perl scripts.
Trimmed sequence reads were mapped to N. benthamiana V0.4.4 using Hisat2 v2.0.5  (parameters- dta --phred33)
Read count extraction and normalization were performed using featureCounts v1.5.0-p3
Assembly: N. benthamiana V0.4.4
Supplementary files format and content: tab-delimited text files include RPKM values for each Sample

organism: Nicotiana benthamiana

source_name: seed

growth_protocol: Nicotiana benthamiana seeds were maintained at 4C

extract_protocol:
Total RNA was extracted from N. benthamiana seeds (20 mgr) using the procedure described by Suzuki et al. (Biotechniques. 37(4):542, 544).
RNA libraries for RNA-seq were performed at Novogene in United Kingdom. The integrity and quality of the total RNA were checked using NanoDrop 2000 Spectrophotometer. mRNA was purified from total RNA using poly-T oligo-attached magnetic beads.

treatment_protocol:
Seeds derived from Nicotiana benthamiana plants of two different genotypes (WT and DCL3) that were either infected with PVX (WTPVX and DCL3PVX) or mock-inoculated (DCL3Ctr and WTCtr)
Four-week-old parental plants were agro-infiltrated with Agrobacterium tumefaciens bearing either the binary vector pGR107 expressing the infectious cDNA of PVX (PVX) or pCAMBIA1305.1 containing a β-glucuronidase gene (Ctr)

value: seed

tag: group

value: Progenitor healthy

value: Non-infected Progenitor

value: Pregermination


title: DCL3PVX biol rep 3

value: Progenitor infected

value: Dcl3 knockdown

value: PVX-infected Progenitor


title: WTCtr biol rep 1

value: WT


title: DCL3Ctr biol rep 3


title: DCL3Ctr biol rep 1


title: DCL3PVX biol rep 2


title: WTPVX biol rep 1


title: DCL3Ctr biol rep 2


title: WTCtr biol rep 3


title: WTPVX biol rep 3


title: WTPVX biol rep 2


title: Aorta, NPR1 knockout heterozygous, rep1

city: Nanchang

first: Hongfei

last: Liu

state: Jiangxi

address: Nanchang university, 999 Xuefu Avenue, Xinjian District

institute: Nanchang University

data_processing:
Sequencing data was filtered to produce clean reads using SOAPnuke software
The clean reads were mapped and aligned to the reference coding gene set with Bowtie2
The expression level of gene was evaluated by RSEM
Differential expression analysis was executed by DESeq2 (v1.4.5)
Assembly: mm10
Supplementary files format and content: tab-delimited text files include FPKM values ane Reads values for each Sample

source_name: Aorta

extract_protocol:
Aorta were incubated with Trizol reagent and centrifuged at 13000×g for 5 min at 4℃. The supernatant was collected and mixed with chloroform. After centrifugation, RNA in the aqueous phase was precipitated by mixing with isopropanol at -20℃ for 1 h. Then, the RNA pellet was washed for two times and resuspended. The sample was centrifuged at 13000×g for 5 min at 4℃. The dried pellet was dissolved by DEPC-treated water. The quality and quantity of total RNA were assessed using Nano Drop  and Agilent 2100 Bioanalyze.
The mRNA was purified and fragmented into small pieces. Then first-strand cDNA was generated by random hexamer-primed reverse transcription, followed by a second-strand cDNA. The cDNA fragments were amplified by PCR, and the PCR products were purified by Ampure XP Beads. The purified PCR produces were heated denatured and circularized by the splint oligo sequence to get the final library. The final library was amplified with phi29 to make DNA nanoball (DNB) which had more than 300 copies of one molecular. The DNBs ware loaded into the patterned nanoarray

treatment_protocol: NPR1 knockout heterozygous mice was established by CRISPR-Cas9

value: Male

value: Aorta


title: Aorta, NPR1 knockout heterozygous, rep3


title: Aorta, wild type, rep1


title: Aorta, wild type, rep3


title: Aorta, wild type, rep2


title: Aorta, NPR1 knockout heterozygous, rep2


title: DCL3PVX biol rep 1


title: inguinal lymph nodes, ASFV-infected, Day 41, rep1

city: wuhan

first: Changjie

last: Lv

state: hubei

address: shizishan street

institute: huazhong agriculture university

data_processing:
Sequence reads were trimmed for adaptor sequence/low-quality sequence using SOAPnuke (parameter- lowQual=20,nRate=0.005,qualRate=0.5)
Trimmed sequence reads were mapped to GrCM38/mm10 using HISAT2  (parameter-x --no-unal --un-conc)
Read count extraction and normalization were performed using RSEM（V1.3.1）
Differential expression analysis was performed using DESeq2（parameter-FDR <0.05&log2FC>1 || log2FC<-1 ）
Assembly: Sus_scrofa.Sscrofa11.1
Supplementary files format and content: tab-delimited text files include FPKM values for each Sample

organism: Sus scrofa domesticus

source_name: inguinal lymph nodes

extract_protocol:
Total RNA was extracted using Trizol reagent following manufacturer’s recommendations
RNA libraries for RNA-seq were prepared using VAHTS® Universal V6 RNA-seq Library Prep Kit  following manufacturer's protocols.

value: inguinal lymph nodes

value: ASFV-infected


title: inguinal lymph nodes, ASFV-infected, Day 41, rep3


title: inguinal lymph nodes, control, Day 41, rep2

value: ASFV-non-infected


title: inguinal lymph nodes, control, Day 41, rep3


title: inguinal lymph nodes, control, Day 41, rep1


title: spleen, ASFV-infected, Day 41, rep3

source_name: spleen

value: spleen


title: spleen, ASFV-infected, Day 41, rep2


title: inguinal lymph nodes, ASFV-infected, Day 41, rep2


title: spleen, ASFV-infected, Day 41, rep1


title: spleen, control, Day 41, rep3


title: spleen, control, Day 41, rep2


title: spleen, control, Day 41, rep1


title: SGET Day 6 non-PGCLC rep2

city: Cambridge

first: Navin

middle: B

last: Ramakrishna

address: Tennis Court Rd

institute: Gurdon Institute

description: Small RNA (<200 nt)

data_processing:
Fastq files of the same library were merged and reads were trimmed using cutadapt (v3.2) with the following parameters: -a TGGAATTCTCGGGTGCCAAGG --minimum-length 23 (thresholding reads to a minimum of 15 nt), then followed by -u 4 -u -4 to remove the 4 random NNNN adaptor ends.
To identify small RNAs from all datasets, trimmed reads passing quality control were mapped to the GRCm38 mouse genome allowing for up to 100 multi-mappers, and single random-assignment of multimappers, and a stringent mismatch of 2, using STAR (v2.5.3a) with the following parameters:
--outFilterMultimapNmax 100 --winAnchorMultimapNmax 100 --outFilterMismatchNmax 2 --alignIntronMax 1 --alignEndsType EndToEnd --readFilesCommand gunzip -c --scoreDelOpen -10000 --scoreInsOpen -10000 --outSAMtype BAM SortedByCoordinate --outSAMmultNmax 1 --outMultimapperOrder Random
An in-house and open-source custom python (v3.5.3) script (https://gitlab.com/tdido/tstk/-/blob/master/tstk/peterplot.py) was then used to generate collapsed fasta files (with counts per unique small RNA as an additional readout) from the BAM outputs, and to generate either collapsed or uncollapsed small RNA length distribution histograms with the 5′-nucleotide frequency displayed, normalized to all mapping reads.
Assembly: GRCm38
Supplementary files format and content: Tab-delimited txt files per sample of of 2 columns: (1) Unique Mapped Small RNA (2) Counts

source_name: Surrounding EB Cells

growth_protocol: mPGCLCs were isolated from Day 6 trypsin-dossiciated Embryoid Bodies using reporter gating (Stella-GFP positive and Esg1-tdTomato negative) via FACS and sorted directly into Qiazol. Small RNA fractions was isolated using the Qiagen miRNAeasy-micro kit.

extract_protocol:
Elmer NextFlex small RNA Kit v3, following the instructions for low input.These contain 4 random Ns at the adapter ends.
small RNA seq (Single Read 50)

treatment_protocol: Small RNA libraries were made using the Perkin

tag: origin

value: SGET ESC-derived

tag: strain


title: SGET Day 6 non-PGCLC rep1

description: Small RNA (<200 nt)


title: SGET Day 6 mPGCLC rep2

data_processing:
Fastq files of the same library were merged and reads were trimmed using cutadapt (v3.2) with the following parameters: -a TGGAATTCTCGGGTGCCAAGG --minimum-length 23 (thresholding reads to a minimum of 15 nt), then followed by -u 4 -u -4 to remove the 4 random NNNN adaptor ends.
To identify small RNAs from all datasets, trimmed reads passing quality control were mapped to the GRCm38 mouse genome allowing for up to 100 multi-mappers, and single random-assignment of multimappers, and a stringent mismatch of 2, using STAR (v2.5.3a) with the following parameters:
--outFilterMultimapNmax 100 --winAnchorMultimapNmax 100 --outFilterMismatchNmax 2 --alignIntronMax 1 --alignEndsType EndToEnd --readFilesCommand gunzip -c --scoreDelOpen -10000 --scoreInsOpen -10000 --outSAMtype BAM SortedByCoordinate --outSAMmultNmax 1 --outMultimapperOrder Random
An in-house and open-source custom python (v3.5.3) script (https://gitlab.com/tdido/tstk/-/blob/master/tstk/peterplot.py) was then used to generate collapsed fasta files (with counts per unique small RNA as an additional readout) from the BAM outputs, and to generate either collapsed or uncollapsed small RNA length distribution histograms with the 5′-nucleotide frequency displayed, normalized to all mapping reads.
Genome_build: GRCm38
Supplementary_files_format_and_content: Tab-delimited txt files per sample of of 2 columns: (1) Unique Mapped Small RNA (2) Counts

source_name: Primordial Germ Cell Like Cells

extract_protocol:
mPGCs were isolated by microdissection of pooled pairs of male genital ridges away from mesonephros. These were treated in trypsin for 20 min at 37C to achieve single isolates. Cells were then incubated with surface marker antibodies SSEA1-660 and CD61-PE and FACS sorted directly into Qiazol. mPGCLCs were isolated from Day 6 trypsin-dossiciated Embryoid Bodies using reporter gating (Stella-GFP positive and Esg1-tdTomato negative) via FACS and sorted directly into Qiazol. Small RNA fractions was isolated using the Qiagen miRNAeasy-micro kit.
Small RNA libraries were made using the Perkin-Elmer NextFlex small RNA Kit v3, following the instructions for low-input.These contain 4 random Ns at the adapter ends.


title: BG5 Day 6 non-PGCLC rep2

description: Small RNA (<200 nt)

value: BG5 ESC-derived


title: mPGC E15.5 rep1

source_name: Primordial Germ Cells


title: mPGC E13.5 rep1


title: BG5 Day 6 mPGCLC rep1

description: Small RNA (<200 nt)

extract_protocol:
mPGCLCs were isolated from Day 6 trypsin-dossiciated Embryoid Bodies using reporter gating (Stella-GFP positive and Esg1-tdTomato negative) via FACS and sorted directly into Qiazol. Small RNA fractions was isolated using the Qiagen miRNAeasy-micro kit.
Small RNA libraries were made using the Perkin
Elmer NextFlex small RNA Kit v3, following the instructions for low input.These contain 4 random Ns at the adapter ends.
small RNA seq (Single Read 50)


title: SGET Day 6 mPGCLC rep1


title: E14 Day 6 non-PGCLC rep1

description: Small RNA (<200 nt)

value: E14 ESC-derived


title: BG5 Day 6 non-PGCLC rep1

description: Small RNA (<200 nt)


title: mPGC E13.5 rep2


title: BG5 Day 6 mPGCLC rep2

description: Small RNA (<200 nt)


title: mPGC E15.5 rep2


title: E14 Day 6 mPGCLC rep2

description: Small RNA (<200 nt)


title: mPGC E12.5 rep1


title: mmusculus_GASTROC_mdx

city: Halifax

first: Adam

last: Johnston

state: NS

address: 1344 Summer Street

department: Medical Neuroscience

country: Canada

institute: Dalhousie University

data_processing:
Sequencing of cDNA libraries was performed on Illumina NovaSeq 6000 using single-end reads of 91 bp length.
Fiducial frame alignment and capture area selection was performed using Loupe browser software (10x Genomics).
Raw reads were filtered and aligned to the mm10 assembly, followed by UMI counting, barcode counting, and gene expression matrix creation using the spaceranger analysis suite (10x Genomics).
Gene expression matrices were analyzed in python (v3.7) using the scanpy package (v1.8.2). Spots were removed from downstream analysis if they contained less than 1000 UMIs or less than 500 unique genes. Genes expressed in less than 3 cells were also removed. Spatially-variable genes were identified using SpatialDE2 (Kats et al., 2021).
Assembly: mm10
Supplementary files format and content: mdx.h5ad: processed scanpy object containing normalized counts per capture area, senescence/SASP scores, and spatially-variable genes identified by spatialDE2 (Kats et al., 2021).
Supplementary files format and content: outs.tar.gz: cellranger output files required to load Visium data.
Library strategy: Spatial Transcriptomics

source_name: Gastrocnemius muscle

extract_protocol: cDNA libraries were constructed using 10x Genomics Visium Spatial Gene Expression 3' Library Construction kit (10x Genomics).

value: Gastrocnemius muscle

value: M

tag: extraction protocol

value: Gastrocnemius muscle from 8-week-old D2-Mdx mouse was isolated and embedded in OCT compound using liquid nitrogen-cooled 2-methylbutane. A 10µm section of this tissue was then mounted on a 10x Visium Spatial Gene Expression slide (10x Genomics) and underwent normal H&E staining.


title: ID1 +dox 24h biol rep 1

city: Stockholm

first: Maria

last: Genander

address: Tomtebodavägen 16

department: Department of Cell and Molecular Biology

country: Sweden

institute: Karolinska Institutet

description: doxy treatment

data_processing:
Clustering was done by 'cBot' and samples were sequenced on NovaSeq6000 (NovaSeq Control Software 1.6.0/RTA v3.4.4) with a 2x51 setup using 'NovaSeqXp' workflow in 'S1' mode flowcell.
The Bcl to FastQ conversion was performed using bcl2fastq_v2.19.1.403 from the CASAVA software suite.
The quality scale used is Sanger / phred33 / Illumina 1.8+.
Assembly: GRCm38
Supplementary files format and content: Excel file with CPMs for each sample

source_name: epidermis

growth_protocol: Primary epidermal progenitor cells were cultured in Elow media. Differentiation was induced in confluent cultures using calcium.

extract_protocol:
RNA was extracted using Qiagen Rneasy kit.
Illumina True Seq Stranded mRNA

treatment_protocol: ID1 overexpression was induced using doxycyline for three days.

value: epidermis

value: primary keratinocytes

value: keratinocyte

value: ID1 overexpression lentiviral infection


title: ID1 -dox 24h biol rep 3

value: WT


title: ID1 +dox 24h biol rep 2

description: doxy treatment


title: ID1 +dox 24h biol rep 3

description: doxy treatment


title: ID1 -dox 24h biol rep 1


title: ID1 +dox 0h biol rep 3

description: doxy treatment


title: ID1 -dox 24h biol rep 2


title: Old

city: Beijing

first: Yehua

last: Li

address: shengmingkexueyuanlu7hao, changping

institute: NIBS

description: All pituitary cells

data_processing:
Illumina Casava1.9 software used for basecalling.
Reads were aligned mm10 whole genome, filtered, de-duplicted, and converted into a digital count matrix using Cell Ranger 2.2.0 (10XGenomics)
Assembly: mm10
Supplementary files format and content: The processed files are combined digital expression matrix divided in three files. The matrix.mtx file contains the values, barcodes.tsv contains the cell barcodes detected, and genes.tsv contains the list of genes detected.

source_name: Pituitary

growth_protocol: Wild-type C57BL/6 mice were housed at the animal center in the National Institute of Biological Sciences in a Specific Pathogen Free (SPF) facility within individually ventilated cages as well as the controlled temperature, humidity and light-dark cycle, and a regular rodent chow diet.

extract_protocol:
For the young and old pituitary sample, anesthetized mice were perfused via the aorta with cold PBS and dissected pituitary was placed into an enzyme mix containing 0.5% w/v collagenase type 2, 0.25% trypsin, in Hanks balanced salt solution for 2-3 hours at 37°C. The tissue and cells were gently triturated and pelleted at 900g for 3 minutes, and resuspended for further single cell sorting. All live cells from young or old pituitary negative for DAPI  staining were sorted for further scRNA-seq.
For the Igha-Cre sample, zsGreen positive and DAPI negative pituitary cells were sorted for sequencing.
For the Epcam sample, old (18-24M) pituitary cells were stained with DAPI and FITC conjugated Epcam antibody, then DAPI negative and Epcam positive cells were sorted for further processing.
Libraries were prepared for sequencing using standard Illumina protocols

value: Pituitary

tag: age

value: 18-24 months


title: Young

description: All pituitary cells

value: 2-3 months


title: E14 Day 6 non-PGCLC rep2

description: Small RNA (<200 nt)

value: Male


title: Igha-Cre

description: ZsGreen+ pituitary cells

value: 4-8 months


title: ID1 +dox 0h biol rep 2

description: doxy treatment


title: mPGC E12.5 rep2


title: ID1 +dox 0h biol rep 1

description: doxy treatment


title: E14 Day 6 mPGCLC rep1

description: Small RNA (<200 nt)


title: shScr 24h biol rep 3

value: shScr lentiviral infection


title: ID1 -dox 0h biol rep 1


title: shId1 24h biol rep 1

value: shId1 lentiviral infection


title: ID1 -dox 0h biol rep 2


title: shScr 24h biol rep 1


title: shId1 0h biol rep 3


title: ID1 -dox 0h biol rep 3


title: shId1 0h biol rep 1


title: shScr 0h biol rep 3


title: shId1 0h biol rep 2


title: shScr 0h biol rep 2


title: shScr 0h biol rep 1


title: Control_3

city: Nagoya

first: Hiroshi

middle: I.

last: Suzuki

address: 65 Tsurumai-cho, Showa-ku

department: DIvision of Molecular Oncology, Graduate School of Medicine

country: Japan

institute: Nagoya University

data_processing:
Small RNA-seq samples were analyzed by Illumina NovaSeq 6000.
Obtained sequences were processed for adaptor removal and size exclusion of sequences < 15 nt with Cutadapt.
Filtered reads were mapped to mm9 genome assembly with bowtie 1.0.1, allowing two mismatches, and further analyzed as previously described using miRBase v21 (Langmead et al., 2009; Zamudio et al., 2014).
Assembly: mm10
Supplementary files format and content: Summary txt file includes normalized miRNA expression values.

source_name: pDCs from Control mouse

growth_protocol: Spleen was dissociated into single-cell suspension by spleen dissociation kit (Mylteni biotec) according to the manufacturer’s instruction. From this suspension, we purified pDCs using plasmacytoid dendritic cell isolation kit (Myltenyi biotec) according to the manufacturer’s instruction.

extract_protocol:
Total RNA was extracted from isolated pDCs by miRNeasy Micro Kit (Qiagen).
Small RNA libraries was prepared with the NEB Next® Multiplex Small RNA Library Prep Set for Illumina® (Set 1) and analyzed by Illumina NovaSeq 6000.

treatment_protocol: FVB/NJcl female mice were purchased from Clea (Tokyo, Japan). The skins on the right ear of the mice of 7-9 weeks of age were treated topically, 3 times weekly, with 1.25 mg of 5% Imiquimod (IMQ) cream (Mochida Pharmaceutical). Vaseline was used for control. Mice were sacrificed at 4 weeks.

tag: condition

value: pDCs from Control mouse

value: splenic pDCs

value: FVB/NJcl

value: female

value: control


title: Control_1


title: Control_2


title: IMQ_1

source_name: pDCs from IMQ mouse

value: pDCs from IMQ mouse

value: IMQ


title: IMQ_2


title: IMQ_3


title: shScr 24h biol rep 2

value: epidermis

value: primary keratinocytes

value: keratinocyte


title: Control_3

city: Heidelberg

first: Ashik Ahmed

last: Abdul Pari

address: Im neuenheimer Feld 280

institute: German Cabcer Research Institute

data_processing:
Sequencing strategy: NovaSeq 6K S1 50bp Paired-End
RTA v3.4.4
The sequenced reads were processed and aligned using DKFZ OTP RNAseq workflow v1.2.0-11  (OTP: An automatized system for managing and processing NGS data. J Biotechnol 261:53-62.)
Assembly: mm10
Supplementary files format and content: The processed data file (Count matrix.tsv) contains the raw counts of sequencing reads for genes from the analyzed samples

source_name: Lung

extract_protocol:
Lung endothelial cells were isolated by FACS, and RNA was harvested using Arcturus PicoPure RNA Isolation Kit (Life Technologies).
Libraries were made SmarTer Ultra Low Input RNA v4 and NEBNext ChIP-Seq kit from takara

value: Lung

value: Endothelial cells

value: Control AAV


title: im_P5

city: Cincinnati

first: Guolun

last: Wang

state: OH

address: 3333 Burnet Avenue

institute: Cincinnati Children's Hospital Medical Center

data_processing:
The standard celllranger mkfastq software version 3.0 used for basecalling.
The standard celllranger count software version 3.0 used to produced raw expression matrix.
The matrix were normalized and scaled by Seurat v4.0 in R4.0.0 environment.
Assembly: mm10 and rn6
Supplementary files format and content: Matrix

source_name: bone marrow

extract_protocol:
The bone marrow cell samples were harvested from tibia and femur of P5. The samples were dissociated into single cell suspension and were sorted by Flow cytometry for library preparation.
The libraries were prepared for sequencing using standard 10X 3'v3 protocols
10x 3'v3 single cell RNAseq

tag: subset

value: stromal and hematopoietic cells


title: NT Treated_4

value: nANGPTL4 AAV


title: NT Treated_2


title: Control_4


title: shId1 24h biol rep 2

value: WT


title: NT Treated_1


title: cm_P5


title: NT Treated_3


title: Control_1


title: KO_2

city: Palo Alto

first: Ewa

last: Bielczyk-Maczynska

state: CA

address: Falk Cardiovascular Research Center, 870 Quarry Rd

department: Division of Cardiovascular Medicine

institute: Stanford University

description: mRNA sequenced

data_processing:
Raw pair-end FASTQ files were filtered to remove reads with adaptor contamination, reads when uncertain nucleotides contitute more than 10% of either read, and reads when low quality nucleotides (base quality <5) constitute more than 50% of the read.
STAR 2.6.1d was used to align clean reads to the mouse reference genome and to generate gene counts.
STAR output for each sample was combined for differential expression testing using DESeq2_1.32.0 R package installed in R v4.1, using default settings.
Genome_build: mm10
Supplementary_files_format_and_content: Matrix table with normalized gene counts for every gene and every sample

source_name: Liver

extract_protocol:
Livers were removed, flash frozen in liquid nitrogen, and RNA was harvested using Trizol reagent. mRNA was enriched by poly(A) capture. Novogene mRNA-Seq pipeline was used to construct sequencing libraries.
RNA libraries were prepared for sequencing using standard Illumina protocols

value: Gpr151 KO

tag: diet

value: high-fat diet

value: 4 weeks

value: Liver


title: mutant1

city: Durham

first: Anne (Maggie)

middle: M

last: Bara

state: NC

address: 307 Research Dr.

department: Cell Biology and Dermatology

institute: Duke University

data_processing:
Novogene: Downstream analysis was performed using a combination of programs including STAR, HTseq, Cufflink and our wrapped scripts. Alignments were parsed using Tophat program and differential expressions were determined through DESeq2/edgeR.
Supplementary files format and content: mutantvscontrol.DEG.all

source_name: Intestinal epithelium, P7

extract_protocol:
Intesinal epithelial cells from proximal, medial, and distal regions of the small intestine were collected from P7 mice and pooled into a single tube per mouse, RNA was isolated using Qiagen RNAeasy kit
Novogene constructed libraries

value: Intestinal epithelium, P7

value: Mixed primary intestinal epithelial

value: VillinCre, MafB fl/fl, cmaf fl/fl


title: control3

value: MafB fl/fl, cMaf fl/fl


title: mutant2


title: control1


title: WT_3

description: mRNA sequenced

value: Gpr151 WT


title: KO_1

description: mRNA sequenced


title: Control_2


title: KO_3

description: mRNA sequenced


title: WT_2

description: mRNA sequenced


title: mm

data_processing:
The standard celllranger mkfastq software version 3.0 used for basecalling.
The standard celllranger count software version 3.0 used to produced raw expression matrix.
The matrix were normalized and scaled by Seurat v4.0 in R4.0.0 environment.
Genome_build: mm10
Supplementary_files_format_and_content: Matrix

extract_protocol:
The Bone marrow cell samples were harvested from tibia and femur of P10 interspecies or intraspecies. The samples were dissociated into single cell suspension. The GFP+ Lineage- (561317, BD) cells were sorted by Flow cytometry for library preparation.
The libraries were prepared for sequencing using standard 10X 3'v3 protocols
10x 3'v3 single cell RNAseq

value: GFP+ Lineage-


title: Pol II-KO2

city: Shanghai

first: Ju

last: Qiu

address: 320 Yueyang Road

institute: Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences

data_processing:
Library strategy: CUT&Tag
Quality control was the first step for processing raw sequence reads by FastQC.
Then adapter sequences and poor-quality reads were removed.
Quality filtered reads were then mapped to mouse genome (mm10) by Bowtie2, and only uniquely mapped reads were saved.
Peak calling was done using MACS2 with an initial threshold q-value of 0.01 as cutoff against IgG control.
Identified peaks were merged with “bedtools Multiple Intersect” followed by “bedtools MergeBED” function
Raw counts based on BED file of merged peaks were extracted using bedtools MultiCovBed
Genome_build: mm10
Supplementary_files_format_and_content: csv, raw counts of sequencing reads from replicates samples with chromosome ID, chromosome start and end positions.

extract_protocol:
Library preparation was performed using HyperactiveTM In-Situ ChIP Library Prep Kit for Illumina (Vanzyme, Nanjing, China). 1.2× VAHTS DNA Clean Beads(Vanzyme) were used to purify libraries for sequencing.
150 paired-end sequencing was performed with Illumina NovaSeq 6000.

treatment_protocol: Nuclei were prepared as previously described63, cells were pelleted at 1400g for 5 minutes at 4°C, supernatant was discarded and cells were resuspended in 200 µL cold nuclear extraction (NE) buffer (20mM HEPES-KOH, pH 7.9, 10mM KCl, 0.5mM Spermidine, 0.1% TritonX-100, 20% glycerol, 1 × Protease inhibitor cocktail) for 10min on ice. Nuclei were pelleted at 1400g for 5 minutes at 4°C.

value: spleen Tregs

tag: gender

value: pooled female and male

value: 8 week

value: spleen


title: Pol II-KO1

tag: tissue


title: Pol II-WT2


title: Pol II-IgG

value: pooled from Foxp3CreSetd2flox/+ and Foxp3CreSetd2flox/flox


title: Pol II-WT1


title: WT_1

description: mRNA sequenced


title: H3K27ac-KO1

description: cells were isolated from steady state large intestine

source_name: large intestine

extract_protocol:
Library preparation was performed using HyperactiveTM In-Situ ChIP Library Prep Kit for Illumina from Vanzyme (TD901-TD902, Nanjing, China). 1.2×VAHTS DNA Clean Beads(Vanzyme) were used to purify libraries for sequencing.
150 paired-end sequencing was performed with Illumina NovaSeq 6000.

value: LI Tregs

value: 2 week

value: large intestine


title: H3K27ac-KO2


title: H3K27ac-WT1


title: control2

tag: treatment


title: mutant3

tag: cell line


title: WT(*) 6 months IPTG Striatum male mRNA rep4

city: Princeton

first: Jeff

last: Aaronson

state: New Jersey

address: 155 Village Boulevard, Suite 200

department: Discovery & Systems Biology

institute: CHDI

description:
WT_6M_IPTG_STR_56_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt

data_processing:
Libraries for RNA-seq were sequenced using an Illumina NovaSeq6000.
Sequenced reads were trimmed for adaptor sequence using Omitsoft aligner and then mapped to mouse genome Mouse.B38 (GeneModel Ensembl.R94).
a) Trimmed low-quality bases from the reads, aligned reads to the mouse genome GRCm38 with OmicSoft Aligner and quantitated the reads per gene with OmicSoft Quantitate. b) Fragments Per Kilobase of exon model per million reads mapped were calculated with OmicSoft. c) Generated the QC plots (PCA, Volcano, Bar charts of QC metrics).
Genome_build: Mouse.B38 (GeneModel Ensembl.R94)
Supplementary_files_format_and_content: Tab-delimited text files include Count values for each Sample.

source_name: Right Striatum

extract_protocol:
Tissue specimens were removed, flash frozen on dry ice, and total RNA was harvested using the Qiagen mRNeasy kit. RNA quality and integrity were monitored via Agilent Bioanalyzer.
RNA libraries were prepared for sequencing using standard Illumina protocols.

value: Corpus Striatum

value: Hdh(LacO-+/+):beta-actin-LacIR tg

tag: strain/background

value: 6 months

value: Male

value: IPTG

tag: treatment initiation

tag: treatment withdrawal

value: 6 months (Never)

tag: batch


title: H3K27ac-IgG

tag: cell type

tag: genotype


title: WT(*) 6 months IPTG Striatum male mRNA rep3

description:
WT_6M_IPTG_STR_42_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt

tag: Sex


title: WT(*) 6 months IPTG Striatum male mRNA rep5

description:
WT_6M_IPTG_STR_91_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Striatum male mRNA rep1

description:
WT_6M_IPTG_STR_40_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Striatum male mRNA rep2

description:
WT_6M_IPTG_STR_41_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Striatum female mRNA rep3

description:
WT_6M_IPTG_STR_51_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt

value: Female


title: WT(*) 6 months IPTG Cortex male mRNA rep4

description:
WT_6M_IPTG_COR_56_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt

source_name: Right Cortex

value: Cerebral Cortex


title: WT(*) 6 months IPTG Cortex male mRNA rep5

description:
WT_6M_IPTG_COR_91_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Striatum female mRNA rep5

description:
WT_6M_IPTG_STR_88_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Cortex male mRNA rep2

description:
WT_6M_IPTG_COR_41_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Cortex male mRNA rep3

description:
WT_6M_IPTG_COR_42_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: H3K27ac-WT2

tag: strain


title: WT(*) 6 months IPTG Cortex male mRNA rep1

description:
WT_6M_IPTG_COR_40_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: shId1 24h biol rep 3

value: epidermis

value: primary keratinocytes

value: keratinocyte

value: WT

value: shId1 lentiviral infection


title: WT(*) 6 months IPTG Cortex female mRNA rep5

description:
WT_6M_IPTG_COR_88_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Striatum female mRNA rep2

description:
WT_6M_IPTG_STR_50_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Cortex female mRNA rep3

description:
WT_6M_IPTG_COR_51_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Cortex female mRNA rep2

description:
WT_6M_IPTG_COR_50_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Cortex female mRNA rep1

description:
WT_6M_IPTG_COR_49_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 12 months IPTG Striatum male mRNA rep5

description:
WT_12M_IPTG_STR_248_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt

source_name: Striatum

value: 12 months

value: 12 months (Never)


title: WT(*) 12 months IPTG Striatum male mRNA rep4

description:
WT_12M_IPTG_STR_247_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Striatum male mRNA rep2

description:
WT_12M_IPTG_STR_245_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Striatum male mRNA rep3

description:
WT_12M_IPTG_STR_246_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Striatum male mRNA rep1

description:
WT_12M_IPTG_STR_244_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Striatum female mRNA rep3

description:
WT_12M_IPTG_STR_278_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex male mRNA rep5

description:
WT_12M_IPTG_COR_248_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt

source_name: Cortex


title: WT(*) 6 months IPTG Striatum female mRNA rep1

description:
WT_6M_IPTG_STR_49_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 12 months IPTG Striatum female mRNA rep5

description:
WT_12M_IPTG_STR_280_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Striatum female mRNA rep2

description:
WT_12M_IPTG_STR_277_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Striatum female mRNA rep1

description:
WT_12M_IPTG_STR_276_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex male mRNA rep2

description:
WT_12M_IPTG_COR_245_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex female mRNA rep5

description:
WT_12M_IPTG_COR_280_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex female mRNA rep3

description:
WT_12M_IPTG_COR_278_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex female mRNA rep2

description:
WT_12M_IPTG_COR_277_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex male mRNA rep3

description:
WT_12M_IPTG_COR_246_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Striatum female mRNA rep4

description:
WT_12M_IPTG_STR_279_F_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex male mRNA rep4

description:
WT_12M_IPTG_COR_247_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 6 months MOCK Striatum male mRNA rep5

description:
WT_6M_MOCK_STR_39_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Striatum male mRNA rep4

description:
WT_6M_MOCK_STR_38_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 12 months IPTG Cortex male mRNA rep1

description:
WT_12M_IPTG_COR_244_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex female mRNA rep1

description:
WT_12M_IPTG_COR_276_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 12 months IPTG Cortex female mRNA rep4

description:
WT_12M_IPTG_COR_279_F_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 6 months MOCK Striatum male mRNA rep1

description:
WT_6M_MOCK_STR_35_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Striatum male mRNA rep3

description:
WT_6M_MOCK_STR_37_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Striatum female mRNA rep5

description:
WT_6M_MOCK_STR_75_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Striatum female mRNA rep4

description:
WT_6M_MOCK_STR_74_F_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Striatum female mRNA rep3

description:
WT_6M_MOCK_STR_73_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT(*) 6 months IPTG Cortex female mRNA rep4

description:
WT_6M_IPTG_COR_87_F_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Striatum male mRNA rep2

description:
WT_6M_MOCK_STR_36_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex male mRNA rep4

description:
WT_6M_MOCK_COR_38_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Striatum female mRNA rep1

description:
WT_6M_MOCK_STR_71_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex male mRNA rep3

description:
WT_6M_MOCK_COR_37_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex male mRNA rep1

description:
WT_6M_MOCK_COR_35_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex female mRNA rep3

description:
WT_6M_MOCK_COR_73_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex male mRNA rep2

description:
WT_6M_MOCK_COR_36_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex female mRNA rep5

description:
WT_6M_MOCK_COR_75_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex female mRNA rep2

description:
WT_6M_MOCK_COR_72_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 12 months MOCK Striatum male mRNA rep4

description:
WT_12M_MOCK_STR_311_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Striatum male mRNA rep3

description:
WT_12M_MOCK_STR_310_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Striatum male mRNA rep2

description:
WT_12M_MOCK_STR_309_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Striatum male mRNA rep1

description:
WT_12M_MOCK_STR_308_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 6 months MOCK Cortex female mRNA rep1

description:
WT_6M_MOCK_COR_71_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 12 months MOCK Striatum female mRNA rep3

description:
WT_12M_MOCK_STR_230_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Striatum male mRNA rep5

description:
WT_12M_MOCK_STR_312_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Striatum female mRNA rep5

description:
WT_12M_MOCK_STR_232_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Striatum female mRNA rep2

description:
WT_12M_MOCK_STR_229_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Striatum female mRNA rep1

description:
WT_12M_MOCK_STR_228_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Cortex male mRNA rep5

description:
WT_12M_MOCK_COR_312_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Cortex male mRNA rep3

description:
WT_12M_MOCK_COR_310_M_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 6 months MOCK Striatum female mRNA rep2

description:
WT_6M_MOCK_STR_72_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 12 months MOCK Cortex male mRNA rep1

description:
WT_12M_MOCK_COR_308_M_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Cortex female mRNA rep5

description:
WT_12M_MOCK_COR_232_F_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 6 months MOCK Cortex male mRNA rep5

description:
WT_6M_MOCK_COR_39_M_R5
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 12 months MOCK Cortex female mRNA rep3

description:
WT_12M_MOCK_COR_230_F_R3
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Cortex female mRNA rep4

description:
WT_12M_MOCK_COR_231_F_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT(*) 6 months IPTG Striatum female mRNA rep4

description:
WT_6M_IPTG_STR_87_F_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 6 months MOCK Cortex female mRNA rep4

description:
WT_6M_MOCK_COR_74_F_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 12 months MOCK Cortex female mRNA rep2

description:
WT_12M_MOCK_COR_229_F_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Cortex female mRNA rep1

description:
WT_12M_MOCK_COR_228_F_R1
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: LacQ140I 6 months Striatum male mRNA rep5

description:
Q140_6M_ALW_STR_70_M_R5
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt

value: Hdh(LacO-140Q/+):beta-actin-LacIR tg


title: LacQ140I 6 months Striatum male mRNA rep3

description:
Q140_6M_ALW_STR_32_M_R3
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Striatum male mRNA rep4

description:
Q140_6M_ALW_STR_34_M_R4
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Striatum male mRNA rep2

description:
Q140_6M_ALW_STR_31_M_R2
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Striatum female mRNA rep4

description:
Q140_6M_ALW_STR_67_F_R4
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Striatum male mRNA rep1

description:
Q140_6M_ALW_STR_30_M_R1
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Striatum female mRNA rep3

description:
Q140_6M_ALW_STR_64_F_R3
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Cortex male mRNA rep4

description:
Q140_6M_ALW_COR_34_M_R4
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Striatum female mRNA rep2

description:
Q140_6M_ALW_STR_63_F_R2
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Cortex male mRNA rep5

description:
Q140_6M_ALW_COR_70_M_R5
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Cortex male mRNA rep3

description:
Q140_6M_ALW_COR_32_M_R3
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Striatum female mRNA rep1

description:
Q140_6M_ALW_STR_62_F_R1
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: WT 12 months MOCK Cortex male mRNA rep2

description:
WT_12M_MOCK_COR_309_M_R2
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: WT 12 months MOCK Cortex male mRNA rep4

description:
WT_12M_MOCK_COR_311_M_R4
Hdh(LacO-+/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: LacQ140I 6 months Cortex male mRNA rep2

description:
Q140_6M_ALW_COR_31_M_R2
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Cortex female mRNA rep3

description:
Q140_6M_ALW_COR_64_F_R3
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Cortex female mRNA rep2

description:
Q140_6M_ALW_COR_63_F_R2
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Cortex female mRNA rep1

description:
Q140_6M_ALW_COR_62_F_R1
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 6 months Cortex female mRNA rep5

description:
Q140_6M_ALW_COR_68_F_R5
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 12 months Striatum male mRNA rep5

description:
Q140_12M_ALW_STR_304_M_R5
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: LacQ140I 12 months Striatum male mRNA rep4

description:
Q140_12M_ALW_STR_303_M_R4
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: LacQ140I 12 months Striatum male mRNA rep3

description:
Q140_12M_ALW_STR_302_M_R3
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: LacQ140I 12 months Striatum male mRNA rep2

description:
Q140_12M_ALW_STR_301_M_R2
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt


title: LacQ140I 6 months Cortex female mRNA rep4

description:
Q140_6M_ALW_COR_67_F_R4
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco6m_counts.txt


title: LacQ140I 12 months Striatum female mRNA rep5

description:
Q140_12M_ALW_STR_224_F_R5
Hdh(LacO-140Q/+):β-actin-LacIR tg
mRNA
processed data file: laco12m_counts_unswapped.txt