title: FoxM1 +/+_Rep2

first: Maria

middle: Paula

last: Zappia

address: 900 S Ashland Ave

department: Biochemistry and Molecular Genetics

institute: University of Illinos at Chicago

description: Single cell RNA-seq was performed using Drop-seq platform

data_processing:
Illumina Casava1.7 software used for basecalling.
Illumina paired end raw FastQ file were processed for read alignment and gene expression. Drop-seq single-cell data was analyzed using the data anlysis protocol described in Drop-seq cook-book (Macosko et al. 2015)(http://mccarrolllab.com/dropseq/) and used the Drop-seq_tools-1.13. We used STAR aligner to align the reads against Mus musculus GRCm38 genome version Ensm38_90 (From Ensembl) and corresponding gene modle is extracted from Ensembl version 90.
Quality of read and mapping were checked using the program FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
Digital Gene Expression (DGE) data obtained from an aligned library is done using the Dropseq program DigitalExpression (integrated in Drop-seq_tools-1.13). Number of cells that were extracted from aligned BAM file is based on knee plot which extracts the number of reads per cell, then plot the cumulative distribution of reads and select the “knee” of the distribution.
Genome_build: GRCm38.p5 (Ensembl 90: Aug 2017).
Supplementary_files_format_and_content: Tab-delimited text file. Gene expression (as count) of each gene for each extracted cell

source_name: FoxM1 +/+ ; MMTV-PyMT+

growth_protocol: Spontaneous tumor growth driven by MMTV-PyMT

extract_protocol:
Tumors were harvested and dissociated into single-cell suspension. Shortly, tumors were mechanically chopped and digested with 0.1% Collagenase IV and 0.01% DNase in DMEM at 37C for 30 min. Cells were washed twice with PBS followed by lysis of RBCs with ACK Lysing Buffer (Gibco). After two washes, cells were filtered using 40 microm sterile cell strainers and trypan blue staining was performed to asses for the viability of the cells. Drop-seq was performed on the single cell suspension. Libraries were made and sequenced. The DNA sequences for both Cre and PYMT elements were added to the  mouse mm10 genome as chromosomes.
Nextera XT tagmentation using Illumina cat# FC-131-1096 (Drop-seq protocol)

treatment_protocol: No treatment

value: mammary tumors

tag: tumor stage

value: end point tumor

value: female wild-type C57BL6

value: FoxM1 +/+


title: siCTRL_rep2_6h

status: Public on Jun 20 2024

type: SRA

city: Boston

first: Yanqiang

last: Li

state: MA

address: 300 Longwood Ave.

department: Cardiology Department

country: USA

institute: Boston Children's Hospital

library_source: transcriptomic

data_processing:
mRNA half-life of the HEK293T cells and C4-2 cells was computed as described before. In short, the mRNA levels were first normalized to RPKM (Reads Per Kilobase Million). To reduce the noise due to genes that showed a higher expression levels after inhibition of transcription, we then scaled the FPKM values based on the expression levels of top 10 genes which were most stable between time points, so that these genes will have no change of expression between time points. The RNA degradation rate kdecay was defined as the mean values of ratio from RPKM at time 0 over the RPKM value at each other time point (0hour, 6hour, 12hour, 24hour). After that the pseudo-mRNA half-life t1/2 was calculated as ln2/kdecay.
After base-calling using guppy_basecaller (version 3.6.1), the direct RNA-seq of Nanopore reads with quality value more than 7 were aligned to the human genome (Hg38, GRCh38.p13 from GENCODE database) using Minimap with --secondary=no -ax splice -uf -k14 option. Tombo resquiggle was used to assigned to transcript sequence as reference from the website: https://www.gencodegenes.org/human . We extracted the median, standard deviation, mean, and dwell time from Nanopore raw signal data in each direct RNA sequencing read to calculate the probability of Nm modification using the training models from rRNA. The modified base supported by at least 5 modified transcripts were identified as modified Nm sites.
Assembly: hg19 for NGS RNA-seq. hg38 for Nanopore RNA-seq.
Supplementary files format and content: *.count.txt: Tab-delimited text files include abundance measurements.
Supplementary files format and content: *.bw: bigWig files.

molecule: polyA RNA

organism: Homo sapiens

source_name: HEK293T cell line

extract_protocol: RNA was extracted from the HEK293T and C4-2 cells.

tag: cell line

tag: sirna

value: siCTRL

tag: time point


title: FoxM1 DD/DD_Rep2

city: Chicago

state: IL

molecule: total RNA

organism: Mus musculus

source_name: FoxM1 DD/DD; MMTV-PyMT+

tag: tissue

tag: strain

tag: genotype

value: FoxM1 DD/DD


title: HEK293T cells, control siPOOL, 24h glucose starvation, repllicate 4b

city: Zürich

first: Stefanie

last: Jonas

state: Zürich

address: Otto-Stern-Weg 5

department: Biology

country: Switzerland

institute: ETH Zurich

data_processing:
in-house snakemake RNAseq analysis pipeline
FastQC quality control
Cutadapt adapter timming
STAR alignment usiing the parameters: -outFilterMulitmapNmax 20 -quantMode GeneCounts
Assembly: hg38
Supplementary files format and content: bam files include aligned reads for each sample
Supplementary files format and content: Tab-separated value file includes raw read counts for each

growth_protocol: HEK293T cells were maintained in DMEM supplemented with 10% fetal calf serum (FCS) and antibiotics in a humidified atmosphere with 5% CO2 at 37C.

extract_protocol:
Total RNA was extracted by Phenol/Chloroform extraction. 1ug of RNA was used for library preparation.
Ribosomal RNAs were depleted and sequencing libraries were prepared using the Illumina TruSeq Stranded Total RNA kit.

treatment_protocol: Depletions were performed for 72 hours. siPOOLs were transfected to a final concentration of 5nM with RNAiMax

tag: cell type

value: Human embryonic kidney

tag: treatment

value: ctrl siPOOL, 24 hours glucose starvation


title: MUC2761

city: Munich

last: Eyerich

address: Biedersteinderstrasse 29

country: Germany

institute: Center of Allergy and Environment

data_processing:
STAR aligner with human genome reference hg38
Bioconductor package DESeq2
Genome_build: hg38
Supplementary_files_format_and_content: .txt

source_name: lesional skin

growth_protocol: RNA analysis of skin biopsies, skin biopsies were stored at -80°C in RNAlater solution until RNA preparation

extract_protocol:
RNA from skin biopsies was isolated using the QIAzol Lysis Reagent (Qiagen) and miRNeasy Mini Kit (Qiagen) according to manufacturer’s protocol
RNASeq libraries were generated using the TruSeq Stranded Total RNA Kit (Illumina) with Ribo-Zero Depletion (rRNA Removal Mix) according to manufacturer’s high sample protocol. 200 ng of RNA was used as input. DNA was PCR amplified with Illumina primers for 13 cycles. Libraries were sequenced on the Illumina HiSeq 4000 as paired-end with a read length of 2x 150 bp and an average output of 40 Mio reads per sample and end following the manufacturer's protocols.

treatment_protocol: no treatment

tag: diagnosis

value: psoriasis

tag: patient id

tag: age

tag: gender

value: male

tag: batch id


title: MUC2762

source_name: non-lesional skin


title: siCTRL_rep2_24h


title: siCTRL_rep2_12h


title: FoxM1 +/+_Rep1


title: siCTRL_rep2_0h


title: MUC2760

value: female


title: MUC2759


title: siCTRL_rep1_6h


title: mESC_KAS-ATAC-seq_D8, rep1

first: Ruitu

last: Lyu

address: 929 E 57th Street

department: Chemistry

institute: The University of Chicago

library_source: genomic

data_processing:
All data from KAS-ATAC-seq and ATAC-seq were produced in paired-end mode. The preprocessing, read alignment, and read alignments format conversion procedures for KAS-ATAC-seq and ATAC-seq data mirrored those for Opti-KAS-seq and KAS-seq.
Peak calling for KAS-ATAC-seq and ATAC-seq was accomplished via MACS2, targeting sharp peaks with a false discovery rate (FDR) threshold of 0.05.
Deduplicated KAS-seq reads were then transformed into bedGraph and bigWig formats using the deeptools bamCoverage and UCSC tools. Fragment size comparisons within KAS-ATAC-seq and ATAC-seq libraries were facilitated by the ATACseqQC Bioconductor package.
Assembly: mm10
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.
Library strategy: KAS-ATAC-seq

molecule: genomic DNA

source_name: NPC

growth_protocol: Murine embryonic stem (ES) cells were purchased from ATCC (CRL-1821) and were cultured in DMEM (Gibco 11995) supplemented with 10% (v/v) fetal bovine serum (Gibco), 1 mM L-glutamine (Gibco), 0.1 mM β-mercaptoethanol (Gibco), 1% (v/v) nonessential amino acid stock (100x, Gibco), 1% penicillin/streptomycin stock (100x, Gibco), and 1,000 U/mL LIF (Millipore)

extract_protocol:
Subsequently, dilute this lysed solution with 1 ml of cold ATAC-RSB that has 0.1% Tween-20 (but devoid of NP40 or digitonin). Mix by inverting the tube five times. Centrifuge this mixture again at 500 RCF for 5 minutes at 4ºC and discard the supernatant. Resuspend the pellet with 100 µl of 10 mM N3-Kethoxial in PBS and then incubate at 37ºC with 500 rpm shaking for 10 minutes. After incubation, wash the nuclei by adding 1 ml of DPBS. Centrifuge the suspension at 500 RCF for 5 minutes at 4ºC, and subsequently remove the supernatant. Resuspend the nuclei pellet in 50 µl of the previously prepared Transposition Mix. Achieve a uniform mixture by pipetting up and down six times. Incubate the mixture in a thermomixer set to 37°C and 1,000 rpm for 30 minutes. Remove the tubes from the thermomixer, and immediately terminate the transposition reaction by adding 250 µL (five volumes) of DNA Binding Buffer from the DNA Clean and Concentrator-5 Kit and mix well by pipetting or inversion. Mix thoroughly and followed by brief centrifugation to collect the contents at the bottom of the tubes. Proceed with purifying the transposed DNA using the kit, according to the manufacturer's instructions.
Elute the purified DNA in 21 µl of elution buffer and store at -20°C for future use. Finally, utilize this eluted gDNA for the Click reaction and perform library preparation and sequencing according to the established ATAC-seq protocol (https://protocolexchange.researchsquare.com/article/nprot-6107/v1).

treatment_protocol: Initiate the procedure by collecting 50,000 viable cells, wash the collected cells with DPBS and centrifuge at 500 RCF for 5 minutes at 4ºC. Resuspend the cell pellet in 50 µl of ATAC-RSB containing 0.1% NP40, 0.1% Tween-20, and 0.01% Digitonin. Mix thoroughly by pipetting up and down three times and then incubate on ice for 3 minutes.

value: NPC

value: Neural progenitor cell

value: WT

value: No treatment


title: mESC_KAS-ATAC-seq_D8, rep2


title: FoxM1 DD/DD_Rep1

source_name: FoxM1 DD/DD; MMTV-PyMT +


title: HEK293T cells, control siPOOL, 24h glucose starvation, repllicate 3a


title: MUC2758


title: HEK293T cells, control siPOOL repllicate 4b

value: ctrl siPOOL


title: siFBL_rep1_0h

value: siFBL


title: mESC_KAS-ATAC-seq_D6, rep2


title: siCTRL_rep1_12h


title: HEK293T cells, control siPOOL repllicate 4a


title: siCTRL_rep1_0h


title: HEK293T cells, control siPOOL (for ZMYND8 depletion) repllicate 3


title: HEK293T cells, control siPOOL repllicate 3b


title: MUC2757


title: HEK293T cells, control siPOOL, 24h glucose starvation, repllicate 4a


title: MUC2755


title: siCTRL_rep1_24h


title: mESC_KAS-ATAC-seq_D4, rep1

source_name: EB

value: EB

value: Embryoid body


title: HEK293T cells, control siPOOL, 24h glucose starvation, repllicate 3b


title: MUC2754


title: HEK293T cells, control siPOOL repllicate 3a


title: H1650 cells, #3

city: Zhengzhou

first: Junhu

last: Wan

address: No. 1 Jianshe East Road

country: China

institute: The First Affiliated Hospital of Zhengzhou University

data_processing:
Raw sequencing data was first filtered by Trimmomatic (version 0.36), low-quality reads were discarded and the reads contaminated with adaptor sequences were trimmed.
Clean data were mapped to the reference genome of homo sapiens using STRA software (version 2.5.3a) with default parameters.
Reads mapped to the exon regions of each gene were counted by featureCounts (Subread-1.5.1; Bioconductor).
Assembly: hg38
Supplementary files format and content: comma-separated values file includes raw counts

source_name: lung cancer

extract_protocol:
RNAs were extracted using RNAiso Plus(Takara). 2μg total RNAs were used for stranded RNA sequencing library preparation.
RNA libraries for RNA-seq were prepared using KCTM Stranded mRNA Library Prep Kit for Illumina® following the manufacturer’s instruction.

value: lung cancer

value: lung cancer cells


title: H1650 cells, #2


title: MUC2753


title: mESC_KAS-ATAC-seq_D4, rep2


title: H1650 cells, #1


title: HEK293T cells, INTS13 siPOOL, 24h glucose starvation, replicate 4

value: ints13 siPOOL, 24 hours glucose starvation


title: MUC2752


title: RNA-seq_hda6_12-hr_rep3

city: University Park

first: Ha Eun

last: Jeh

state: PA

address: 362 Frear N Bldg

institute: Penn State University

data_processing:
Raw RNA sequencing data was trimmed using Trim Galore! (v0.6.6, --length 30) with Cutadapt (v2.8)
Aligned to the TAIR10 reference genome using STAR (v2.7.10a,--twopassMode Basic -- outFilterMultimapNmax 1).
Read count data was generated with QoRTs (v1.3.6, --minMAPQ 25).
Assembly: TAIR10
Supplementary files format and content: Each row contains read count data with  <GeneID> <read count>

organism: Arabidopsis thaliana

source_name: leaf at bolting stage

growth_protocol: Seeds were stratified in water at 4 ⁰C for 2 - 3 d and sown on soil and grown in growth chambers with 22/20 ⁰C with 12-hr or 16-hr daylength and 120 − 150 μmol m−2 s−1 light.

extract_protocol:
DNA was extracted with NucleoSpin Plant II Kit (Macherey-Nagel, Germany).
Library was constructed and sequenced as paired-end 150-bp

treatment_protocol: For the heat stress experiment, plants were grown at normal condition (22/20 ⁰C) for 10 days for germination. Then, treatment plants were moved to 28/26 ⁰C.

value: leaf at bolting stage

tag: ecotype

value: 12-hr, no heat


title: mESC_KAS-ATAC-seq_D0, rep2

source_name: mESC

value: mESC

value: Mouse embryonic stem cell


title: MUC2751

value: psoriasis

value: male


title: HEK293T cells, INTS13 siPOOL, replicate 4

value: Human embryonic kidney

value: ints13 siPOOL


title: MUC2756


title: mESC_KAS-ATAC-seq_D0, rep1

value: WT


title: MUC2750

value: female


title: RNA-seq_hda6_12-hr_rep1


title: HEK293T cells, HDGF siPOOL, 24h glucose starvation, replicate 4

value: hdgf siPOOL, 24 hours glucose starvation


title: mESC_KAS-ATAC-seq_D2, rep2

value: No treatment


title: MUC2749


title: mESC_ATAC-seq_D8, rep1

data_processing:
All data from KAS-ATAC-seq and ATAC-seq were produced in paired-end mode. The preprocessing, read alignment, and read alignments format conversion procedures for KAS-ATAC-seq and ATAC-seq data mirrored those for Opti-KAS-seq and KAS-seq.
Peak calling for KAS-ATAC-seq and ATAC-seq was accomplished via MACS2, targeting sharp peaks with a false discovery rate (FDR) threshold of 0.05.
Deduplicated KAS-seq reads were then transformed into bedGraph and bigWig formats using the deeptools bamCoverage and UCSC tools. Fragment size comparisons within KAS-ATAC-seq and ATAC-seq libraries were facilitated by the ATACseqQC Bioconductor package.
Assembly: mm10
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.

value: NPC

value: Neural progenitor cell


title: MUC2748


title: mESC_ATAC-seq_D8, rep2


title: HEK293T cells, HDGF siPOOL, 24h glucose starvation, replicate 3


title: RNA-seq_cue1_12-hr_rep2


title: mESC_KAS-ATAC-seq_D2, rep1

value: EB

value: Embryoid body


title: HEK293T cells, HDGF siPOOL, replicate 4

value: hdgf siPOOL


title: MUC2747


title: RNA-seq_cue1_12-hr_rep1

value: leaf at bolting stage


title: MUC2746


title: mESC_ATAC-seq_D6, rep1


title: HEK293T cells, INTS13 siPOOL, 24h glucose starvation, replicate 3

value: ints13 siPOOL, 24 hours glucose starvation


title: RNA-seq_hda6_12-hr_rep2

value: 12-hr, no heat


title: MUC2745


title: HEK293T cells, ZNF687 siPOOL, replicate 2

value: znf687 siPOOL


title: RNA-seq_wildtype_12-hr_rep2

value: wild type


title: HEK293T cells, INTS13 siPOOL, replicate 3


title: mESC_ATAC-seq_D4, rep2


title: mESC_ATAC-seq_D4, rep1


title: HEK293T cells, ZNF687 siPOOL, replicate 1


title: MUC2744

value: psoriasis

value: male


title: RNA-seq_wildtype_12-hr_rep1


title: RNA-seq_cue1_12-hr_rep3


title: mESC_ATAC-seq_D6, rep2


title: HEK293T cells, ZNF609 siPOOL, replicate 2

value: Human embryonic kidney

value: znf609 siPOOL


title: mESC_ATAC-seq_D2, rep2

value: WT


title: MUC2743


title: HEK293T cells, ZNF609 siPOOL, replicate 1


title: hda6_12-hr_rep2

data_processing:
Raw whole-genome bisulfite sequencing data was trimmed using Trim Galore! (v0.6.6) with Cutadapt (v2.8)
Aligned to the TAIR10 reference genome using Bismark (v0.23.1) with Bowtie 2 (v3.5.1) and Samtools (v1.10).
Assembly: TAIR10
Supplementary files format and content: Each row contains read count data with <chromosome> <position> <strand> <count methylated> <count unmethylated> <C-context> <trinucleotide context> in txt format

extract_protocol:
DNA was extracted with NucleoSpin Plant II Kit (Macherey-Nagel, Germany).
Library was constructed and sequenced as paired-end 100-bp for the Batch 1 (WT_12h, cue1_12h, hda6_12h) and paired-end 150-bp for other batches


title: HEK293T cells, ZNF608 siPOOL, replicate 2

value: znf608 siPOOL


title: MUC2742


title: mESC_ATAC-seq_D0, rep2

value: mESC

value: Mouse embryonic stem cell

value: No treatment


title: HEK293T cells, HDGF siPOOL, replicate 3


title: hda6_12-hr_rep3


title: mESC_ATAC-seq_D2, rep1

value: EB


title: hda6_12-hr_rep1


title: mESC_ATAC-seq_D0, rep1


title: RNA-seq_wildtype_12-hr_rep3


title: HEK293T cells, ZNF608 siPOOL, replicate 1


title: MUC2740


title: MUC2741


title: cue1_12-hr_rep3


title: HEK293T cells, ZEB1 siPOOL, replicate 2

value: zeb1 siPOOL


title: mESC_KAS-ATAC-seq, rep2


title: HEK293T cells, ZEB1 siPOOL, replicate 1


title: mESC_KAS-ATAC-seq, rep1


title: cue1_12-hr_rep2


title: MUC2738

value: female


title: cue1_12-hr_rep1

value: leaf at bolting stage


title: HEK293T cells, TSPYL2 siPOOL, replicate 2

value: tspyl2 siPOOL


title: mESC_ATAC-seq, rep2


title: MUC2737


title: wildtype_12-hr_rep3

value: 12-hr, no heat


title: mESC_ATAC-seq, rep1


title: HEK293T cells, TSPYL2 siPOOL, replicate 1


title: MUC2736

value: Nummular Eczema


title: MUC2735


title: wildtype_12-hr_rep1

value: wild type


title: mESC_opti-KAS-seq, rep2

data_processing:
To align Opti-KAS-seq and KAS-seq data to the reference genome of interest, we utilized the trim_galore package to trim off low-quality sequence, adaptor sequence and primer sequence from single-end or paired-end raw fastq files
Subsequently, we employed bowtie2 to perform the read alignment of Opti-KAS-seq and KAS-seq data. Mapped reads in sam files from the aligners are sorted and converted to bam files using ‘samtools sort’, which are subsequently deduplicated using ‘picard MarkDuplicates’ (pair-end data) or ‘samtools rmdup’ (single-end data).
For single-end Opti-KAS-seq or KAS-seq data, mapped reads were extended to 150bp as default, irrespective of the initial sequencing data's read length. For paired-end KAS-seq data, the KAS-Analyzer incorporates a Python script, facilitating the merging of "properly paired" mapped reads into a singular interval
Peak calling for broad KAS-seq was executed using epic2, which identified broad peaks maintaining a false discovery rate (FDR) of 0.05 and a 1.5-fold change relative to the Input. Comprehensive quality control measures, such as library complexity metrics, inter-replicate correlation analyses, fingerprint plots, saturation analyses, genomic distribution of KAS-seq peaks, enrichment within gene-coding regions, and the Fraction of Reads in Peaks (FRiP) metric, were executed with the KAS-Analyzer package.
Deduplicated mapped KAS-seq reads were converted to bedGraph and bigWig using deeptools bamCoverage and UCSC tools.
Assembly: mm10
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.
Library strategy: Opti-KAS-seq

extract_protocol:
Then, 1 µg genomic DNA was suspended in 95 µL DNA elution buffer supplemented with 5 µL 20 mM DBCO-PEG4-biotin (DMSO solution, Sigma, 760749), 25 mM K3BO3, and incubated at 37 °C for 1.5 h while being gently shaken. Next, 5 µL RNase A (Thermo, 12091039) was added into the reaction mixture followed by incubation at 37 °C for 5 min. Biotinylated gDNA was then recovered by DNA Clean & Concentrator-5 kit (Zymo, D4013).
gDNA was suspended into 100 µL water and was fragmented to 150–350 bp size by using Bioruptor Pico at 30s-on/30s-off setting for 30 cycles; 5% of the fragmented DNA was saved as input, and the remaining 95% was used to enrich biotin-tagged DNA by incubation with 10 µL pre-washed Dynabeads MyOne Streptavidin C1 (Thermo, 65001) at room temperature for 15 min. The beads were washed, and DNA was eluted by heating the beads in 15 µL H2O at 95 °C for 10 min. Eluted DNA and its corresponding input were used for library construction by using Accel-NGS Methyl-seq DNA library kit (Swift, 30024).

treatment_protocol: Cells harvested from the culture dish or Fluorescence-activated cell sorting (FACS) cells were washed with DPBS and subsequently resuspended in 50 µL of ATAC-Resuspension Buffer (RSB) containing 0.1% NP40, 0.1% Tween-20, and 0.01% Digitonin. After gentle pipetting, the suspension was incubated on ice for 3 minutes. The cells were then treated with 1 mL of cold ATAC-RSB containing 0.1% Tween-20 and centrifuged at 500 RCF for 5 minutes at 4ºC. Following a wash with 1 mL DPBS, the cells underwent N3-kethoxal labeling at 37 ºC with continuous agitation. The labeling process involved a 15-minute incubation in 5mM N3-kethoxal in PBS.


title: HEK293T cells, control siPOOL repllicate 2

value: ctrl siPOOL


title: wildtype_12-hr_rep2


title: HEK293T cells, control siPOOL repllicate 1b


title: mESC_KAS-seq, rep2

data_processing:
To align Opti-KAS-seq and KAS-seq data to the reference genome of interest, we utilized the trim_galore package to trim off low-quality sequence, adaptor sequence and primer sequence from single-end or paired-end raw fastq files
Subsequently, we employed bowtie2 to perform the read alignment of Opti-KAS-seq and KAS-seq data. Mapped reads in sam files from the aligners are sorted and converted to bam files using ‘samtools sort’, which are subsequently deduplicated using ‘picard MarkDuplicates’ (pair-end data) or ‘samtools rmdup’ (single-end data).
For single-end Opti-KAS-seq or KAS-seq data, mapped reads were extended to 150bp as default, irrespective of the initial sequencing data's read length. For paired-end KAS-seq data, the KAS-Analyzer incorporates a Python script, facilitating the merging of "properly paired" mapped reads into a singular interval
Peak calling for broad KAS-seq was executed using epic2, which identified broad peaks maintaining a false discovery rate (FDR) of 0.05 and a 1.5-fold change relative to the Input. Comprehensive quality control measures, such as library complexity metrics, inter-replicate correlation analyses, fingerprint plots, saturation analyses, genomic distribution of KAS-seq peaks, enrichment within gene-coding regions, and the Fraction of Reads in Peaks (FRiP) metric, were executed with the KAS-Analyzer package.
Deduplicated mapped KAS-seq reads were converted to bedGraph and bigWig using deeptools bamCoverage and UCSC tools.
Assembly: mm10
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.
Library strategy: KAS-seq


title: MUC2739

value: psoriasis

value: male


title: CD4_T_WT_steady_rep1

city: New York City

first: Yiming

last: Huang

state: New York

address: 3960 Broadway

department: Department of Systems Biology

institute: Columbia University

data_processing:
Raw reads were processed by Cutadapt v2.1 to remove low-quality bases and TruSeq adapters
Remaining reads passing quality filtering were then analyzed by Kallisto v0.46.1 with default setting to quantify gene expression
Assembly: GRCm38
Supplementary files format and content: tab-delimited text file includes TPM values for each Sample
Supplementary files format and content: tab-delimited text file includes estimated reads count from pseudo-alignment for each Sample

source_name: isolated CD4 T

extract_protocol:
Total mRNA was isolated from 0.5 cm pieces of terminal ileum or distal colon, sorted CD4 T cells, or IECs from ileal scrapings after homogenization in Trizol using standard protocols.
RNA-seq libraries were constructed using Illumina Stranded mRNA Prep Ligation kit following manufacturer’s instructions

value: isolated CD4 T

value: steady state


title: HEK293T cells, control siPOOL repllicate 1a

value: Human embryonic kidney


title: MUC2733

value: Atopic eczema


title: CD4_T_WT_steady_rep2

value: WT


title: MUC2734


title: IEC_WT_steady_rep4

source_name: isolated IEC

value: isolated IEC


title: mESC_KAS-seq, rep1

value: mESC

value: Mouse embryonic stem cell

value: No treatment


title: HEK293T cells, ZNF609 Repllicate 2

data_processing:
FastQC quality control, Trimmomatic adapter trimming (parameters: ILLUMINACLIP:NexteraPE-PE.fa:1:30:4:1:true TRAILING:3 MINLEN:20)
Bowtie alignment (parameters: -X2000 (maximal fragment length) and -very-sensitive)
Removal of duplicate reads and reads with map quality score <10 with Picard tools
MACS2 peak calling with q-value<0.1
Supplementary files format and content: bigwig files contain reads normalized by total library size
Supplementary files format and content: narrow.peak files contain MACS2 called peaks

extract_protocol:
Cells were fixed using 1% formaldehyde for 5 min. The crosslinking reaction was quenched with 125mM glycine. Cells were lysed in swelling buffer 5mM PIPES pH8; 85mM KCL; 0,5% IGEPAL + protease inhibitors). Chromatin was sonicated on a Diagenode Bioruptor300 for 30 min (30s ON/ 30s OFF) on the high setting.
At least 20 mg of DNA were used for library preparation using the NEBNext Ultra DNA library prep kit.
ChIPseq, 150 bp paired-end reads

tag: chip antibody

value: ZNF609 (generated in van den Berg et al. 2017)


title: MUC2728


title: HEK293T cells, ZNF609 Repllicate 1


title: COVM_2

city: Little Rock

first: Stephanie

middle: D

last: Byrum

state: Arkansas

address: 501 Jack Stephens Dr, Jackson T. Stephens Bldg 4th floor

institute: University of Arkansas for Medical Sciences

data_processing:
The samples were sequenced and analyzed by Novogene. The reads were mapped using STAR (v2.5) to the reference genome and HTSeq (v0.6.1) as used to count the reads mapped to each gene. FPKM of each gene was calculated and differential expression analysis performed using DESeq2 (v2_1.6.3). The resulting p-values were adjusted using the Benjamini and Hochberg’s approach for controlling the False Discovery Rate (FDR). Genes with an adjusted p-value < 0.05 were considered differentially expressed.
Assembly: GRCh38
Supplementary files format and content: excel file including fpkm of genes.

source_name: ex vivo human precision-cut lung slices

extract_protocol:
For RNA isolation, 3 to 6 slices of the hPCLS were pooled and treated with 1 ml of TRIzol reagent (Invitrogen) at room temperature for 30 min.  Total RNAs were then isolated according to the manufacturer’s instruction.
The RNA samples were checked for quality using Bioanalyzer (Agilent 2100) and were sent to Novogene for library construction per company's protocol.

value: ex vivo human precision-cut lung slices

value: mock infection


title: IEC_STOP_steady_rep1

value: STOP


title: COVM_1


title: HEK293T cells, ZEB1 Repllicate 2

value: wild type

value: ZEB1 (Proteintech, #21544-1-AP)


title: MUC2726

value: psoriasis

value: female


title: mESC_opti-KAS-seq, rep1


title: COV96H_2

value: 96h post infection


title: MUC2725


title: IEC_STOP_steady_rep3

value: steady state


title: mESC_KAS-ATAC-seq_D6, rep1

value: NPC

value: Neural progenitor cell


title: IEC_STOP_steady_rep2


title: COV96H_1


title: HEK293T cells, INTS13 Repllicate 2

value: Human embryonic kidney

value: INTS13 (Proteintech, #19892-1-AP)


title: MUC2724

value: male


title: COV72H_2

value: 72h post infection


title: IEC_STOP_steady_rep4

value: isolated IEC


title: MUC2723


title: HEK293T cells, ZEB1 Repllicate 1


title: MUC2722

value: Nummular Eczema


title: HEK293T cells, INTS13 Repllicate 1


title: HEK293T cells, INTS11 Repllicate 2

value: INTS11 (Atlas Antibodies, #HPA029025)


title: COV48H_2

value: ex vivo human precision-cut lung slices

value: 48h post infection


title: MUC2727


title: IEC_CD4_steady_rep2


title: MUC2721


title: HEK293T cells, INTS11 Repllicate 1

value: wild type


title: IEC_CD4_steady_rep3


title: COV48H_1


title: HEK293T cells, Input Repllicate 2


title: MUC2720

value: Atopic eczema


title: CD4_T_STOP_steady_rep1

value: isolated CD4 T

value: STOP


title: HEK293T cells, Input Repllicate 1


title: COV24H_1

value: 24h post infection


title: MUC2719


title: HEK293T cells, HDGF ChIP Repllicate 2

value: HDGF (Proteintech, #11344-1-AP)


title: COV72H_1


title: CD4_T_STOP_steady_rep2

value: steady state


title: CD4_T_STOP_steady_rep3


title: Naive spleen, CD8 T cell, scRNAseq

first: Alessandro

last: Alessandrini

address: 55 Fruit Street , WEL 807

institute: Massachusetts General Hospital

description: 10x Genomics

library_source: transcriptomic single cell

data_processing:
The raw sequencing data underwent initial mapping and processing using the CellRanger package (Chromium Genomics).
Assembly: mm10
Supplementary files format and content: Tab-separated values flies and matrix files

source_name: Spleen

extract_protocol:
Prior to tissue collection, the kidney is perfused using a collagenase solution (2ml of 1x HBSS, 1mL of Collagenase A, and 3uL of DNase I). The kidney tissue is collected from the mouse, manually ground down, and digested in the collagenase solution. The remaining undigested tissue is manually ground down using a 70-um strainer, washed 3 times, and resuspended using FACs buffer. The spleen was collected in RPMI and then ground down using a syringe plunger of a syringe and a 70um strainer. 1 mL of ACK Lysis Buffer was added to remove red blood cells from the spleen. Cells were washed three times and resuspended in FACs Buffer. Isolated kidney or spleen cells were sorted for viable CD45+ cells via flow cytometry using an anti-CD45+ antibody and a fixable viability dye.
These cells were used to construct single-cell RNA-seq libraries at Chromium 10x instrument using Chromium Next GEM Single Cell 3’ kit, which were sequenced in paired-end fashion on Illumina HiSeq 2500 instrument to the depth of approximately 100 million read pairs per sample.

tag: celltype

value: CD8 T cells

value: Spleen

value: WT


title: MUC2718

value: male


title: Rejecting kidney grafts, 1 week, CD8 T cell, scRNAseq

description: 10x Genomics

source_name: Kidney grafts

value: Kidney grafts


title: IEC_CD4_steady_rep1

value: isolated IEC


title: 17.6 Wk human fetal, snRNA-seq, rep F6

city: Los Angeles

first: Andrew

middle: P

last: McMahon

state: California

address: 1425 San Pablo St, BCC 312

department: Stem Cell Biol & Regen Med

institute: University of Southern California

description: 10X Chromium Single Cell 3' v3

data_processing:
Sequencing reads were aligned to the human genome (GRCh38-2020-A) with the Cell Ranger software (version 5.0.1) using STAR aligner on the University of Southern California High Performance Cluster. The samples were aggregated using cellranger aggr. The processed files (filtered_feature_bc_matrix.h5) are provided. Controlled access to raw fastq files is available through dbGaP.
Assembly: GRCh38-2020-A
Supplementary files format and content: filtered_feature_bc_matrix.h5

source_name: Kidney tissue

extract_protocol:
Cryopreserved human fetal kidneys were processed with optimized single-nuclei dissociation protocol to minimize potential tissue damage artifacts from frozen samples and loss of intact RNA molecules during the dissociation process. Briefly, the tissues were transported in DMEM (5% FBS, 25mM HEPES), removed from capsules, dissected into <2mm pieces and flash frozen in liquid nitrogen for later isolation. Nuclei isolation from flash frozen tissue was performed by the same protocol used with mouse tissue described above. For sex identification, a small amount of the donor tissue was lysed, and DNA was isolated by incubating in DirectPCR Lysis Reagent (Qiagen, #102-T) with 1% Proteinase K (Roche, 3115879001). Donor tissue was then sexed using primers for Y-specific human SRY (SRY-FOR: CCC ATG AAC GCA TTC ATT GTG TGG/ SRY-REV: ATT TTA GCC TTC CGA CGA GGT CGA TA), and ZFX/ZFY (ZFX/ZFY FOR: GCA CTT CTT TGG TAT CTG AGA AAG T/ ZFX/ZFY REV: ATA ATC ACA TGG AGA GCC ACA AGC T) to confirm DNA isolation quality.
Chromium_SingleCell_3'_ReagentKits_v3_UserGuide (CG000183)

value: Kidney tissue

value: Kidney cells

value: 17.6 Wk human fetal


title: Rejecting recipient spleen, 1 week, CD8 T cell, scRNAseq

description: 10x Genomics


title: MUC2716

value: Nummular Eczema

value: female


title: CD4_T_CD4_steady_rep1


title: 17.1 Wk human fetal, snRNA-seq, rep F5

description: 10X Chromium Single Cell 3' v3

value: 17.1 Wk human fetal


title: IEC_WT_steady_rep1


title: 17.5 Wk human fetal, snRNA-seq, rep M5

description: 10X Chromium Single Cell 3' v3

value: 17.5 Wk human fetal


title: Accept recipient spleen, 24 week, CD8 T cell, scRNAseq

description: 10x Genomics


title: CD4_T_CD4_steady_rep2

value: isolated CD4 T


title: MUC2715


title: Accept recipient spleen, 3 week, CD8 T cell, scRNAseq

description: 10x Genomics


title: MUC2712

value: Atopic eczema


title: HEK293T cells, HDGF ChIP Repllicate 1

value: Human embryonic kidney

value: wild type

value: HDGF (Proteintech, #11344-1-AP)


title: Accept recipient spleen, 1 week, CD8 T cell, scRNAseq

description: 10x Genomics

value: CD8 T cells

value: Spleen


title: IEC_WT_steady_rep2

value: WT

value: steady state


title: 17.1 Wk human fetal, snRNA-seq, rep M4

description: 10X Chromium Single Cell 3' v3


title: IEC_WT_steady_rep3

value: isolated IEC


title: MUC2711

value: male


title: 17.6 Wk human fetal, snATAC-seq, rep F4

description: 10X Chromium Single Cell ATAC v1.1

data_processing:
Sequencing reads were aligned to the mouse genome (atac-GRCh38-1.2.0) with the Cell Ranger atac software (version 1.2.0) using STAR aligner on the University of Southern California High Performance Cluster. The samples were aggregated using cellranger-atac aggr.  Non-nucleotide, processed feature-barcode information is provided. Controlled access to raw fastq files is available through dbGaP. The files used in the analysis are provided (fragments.tsv.gz, fragments.tsv.gz.tbi, singlecell.csv, filtered_peak_bc_matrix.h5) compressed into tar.gz files.
Assembly: atac-GRCh38-1.2.0
Supplementary files format and content: fragments.tsv.gz
Supplementary files format and content: fragments.tsv.gz.tbi
Supplementary files format and content: singlecell.csv
Supplementary files format and content: filtered_peak_bc_matrix.h5

extract_protocol:
From the harvested P0 mouse kidneys, nuclei were isolated as previously described in(Wilson et al., 2019). Briefly, flash frozen kidney pieces were thawed on ice and dissected into smaller pieces (<1mm) with a razor blade and then dounced in cold Nuclei EZ Lysis Buffer (Sigma, N3408) supplemented with protease inhibitor (Roche; 05892791001) and RNAse inhibitors (Promega, N2615; Thermo Fisher Scientific, AM2696). The tissue was dounce grinded 30 times with a loose pestle (Sigma, P0485), and then filtered through a 200um strainer (pluriSelect, 43-50200). The tissue was dounce grinded 10 times with a tight pestle, and then incubated for 5 mins on ice. Cells were filtered through 40uM filter (pluriSelect ,43-50040) and pelleted at 500g for 5min at 4°C in a swinging bucket centrifuge. Supernatant was removed and nuclei pellet resuspended in Nuclei EZ lysis buffer with RNAse inhibitors, incubated an additional 5 mins on ice and pelleted again. The final pellet was resuspended in 4°C Nuclei Buffer (10X Genomics, #2000207).
Chromium_NextGEM_SingleCell_ATAC_ReagentKits_v1.1_UserGuide (CG000209)

value: Kidney tissue

value: Kidney cells


title: Accept kidney grafts, 24 week, CD8 T cell, scRNAseq

description: 10x Genomics

value: Kidney grafts


title: MUC2710

value: psoriasis

value: female


title: MUC2717


title: Accept kidney grafts, 3 week, CD8 T cell, scRNAseq

description: 10x Genomics


title: MUC2709


title: SI_LN_PP_WT_steady_rep1

source_name: SI

value: SI

value: LN/PP WT


title: SI_LN_PP_WT_steady_rep2


title: 17.5 Wk human fetal, snATAC-seq, rep M5

description: 10X Chromium Single Cell ATAC v1.1

value: 17.5 Wk human fetal


title: MUC2708

value: Atopic eczema


title: SI_LN_PP_CD4_steady_rep3

value: LN/PP CD4(dILC3)


title: MUC2707


title: SI_LN_PP_CD4_steady_rep4


title: Naive spleen, total cell, scRNAseq

description: 10x Genomics

value: CD45+ cells


title: 17.1 Wk human fetal, snATAC-seq, rep M4

description: 10X Chromium Single Cell ATAC v1.1

value: 17.1 Wk human fetal


title: Rejecting kidney grafts, 1 week, total cell, scRNAseq

description: 10x Genomics


title: Accept kidney grafts, 1 week, CD8 T cell, scRNAseq

description: 10x Genomics

value: CD8 T cells


title: MUC2704


title: Accept kidney grafts, 24 week, total cell, scRNAseq

description: 10x Genomics

value: WT


title: RL_1D, spatial transciptomics

city: Odense

first: Anne

last: Hartebrodt

address: Campusvej 55

country: Denmark

institute: University of Southern Denmark

description: 10x Genomics

data_processing:
Preprocessing using space ranger pipeline (10x Genomics spaceranger version 1.3.1)
Donwstream analysis using Seurat v3
Assembly: GRCh38
Supplementary files format and content: {sample_name}_raw_feature_barcode_matrix.h5

source_name: white matter

extract_protocol:
Visium Spatial Gene Expression Slides (2000233, 10x Genomics)
Visum Spatial Gene Expression User Guide (CG000239 Rev D, 10x Genomics)
Index adapters pooling of total mRNA sequencing with in situ capture with 1% PhIX

treatment_protocol: Fresh frozen tissue block

value: white matter

tag: lesion type

value: RL

tag: postmortem delay


title: SI_LN_PP_Residual_ILC3_steady_rep4

value: LN/PP residual ILC3

value: steady state


title: Accept kidney grafts, 3 week, total cell, scRNAseq

description: 10x Genomics


title: RL_1C, spatial transciptomics

description: 10x Genomics


title: MUC2703


title: MUC2702

value: Nummular Eczema


title: SI_LN_PP_WT_steady_rep3


title: Accept kidney grafts, 1 week, total cell, scRNAseq

description: 10x Genomics

value: Kidney grafts


title: MUC2701


title: RL_1B, spatial transciptomics

description: 10x Genomics


title: Accept recipient spleen, total cells, integrated of 1 & 3 & 24 weeks, scRNAseq

description: 10x Genomics

value: Spleen


title: SI_LN_PP_WT_steady_rep4


title: SI_LN_PP_STOP_steady_rep3

value: LN/PP STOP


title: 17.1 Wk human fetal, snATAC-seq, rep F3

description: 10X Chromium Single Cell ATAC v1.1

value: Kidney tissue

value: Kidney cells


title: RL_1A, spatial transciptomics

description: 10x Genomics


title: MUC2700

value: psoriasis

value: male


title: 11.2 Wk human fetal, snATAC-seq, rep F2

description: 10X Chromium Single Cell ATAC v1.1

value: 11.2 Wk human fetal


title: NAWM, spatial transciptomics

description: 10x Genomics

value: NAWM


title: MUC2699


title: MUC2698

value: Atopic eczema

value: female


title: SI_LN_PP_Residual_ILC3_steady_rep3

value: SI


title: MUC2697


title: CA_2C, spatial transciptomics

description: 10x Genomics

value: white matter

value: CA


title: mibm_hhv_3

city: wuxi

first: jiangan

last: li

address: No 68, Zhongshan Road

institute: Wuxi NO.2 People's Hospital of Nanjing Medical University

data_processing:
RNA-seq sample quality was assessed using FastQC and MultiQC.
Samples were aligned to mouse reference genome based on STAR RNA-sequencing aligner and sequencing reads were assigned to genomic features by featureCounts.
raw counts were  transfromed to FPKM
Assembly: mm10
Supplementary files format and content: tab-delimited text file includes raw counts for each Sample
Supplementary files format and content: tab-delimited text files include RPKM values for each Sample

source_name: BMMNC

extract_protocol:
Total RNA was extracted using Qiagen miRNeasy Mini kit.
The libraries were generated using TruSeq Stranded mRNA Library Prep kit following manufactory protocol. Briefly, mRNA was first extracted  using oligo-dT magnetic beads and fragmented at high temperature. A cDNA library was then prepared from the fragemented mRNA by revervse transcription, second strand synthesis and ligation of specific adapters.

treatment_protocol: The cell-seeded hHVS and PCL was prepared by incubating the hHVS or PCL in the medium by growing BMMNC cells (3×105 cells/cm2) onto the materials for 10 days, respectively, before implantation.

value: BMMNC

value: WIDETYPE

value: hHVS


title: mibm_hhv_2


title: CA_2B, spatial transciptomics

description: 10x Genomics


title: SI_LN_PP_STOP_steady_rep4

value: steady state


title: Novak_Phgdh_WT_KO_D5_D3_UW_HTO

city: New York

first: Jesse

middle: Stephen Swyer

last: Novak

address: 1230 York Ave.

institute: Weill Cornell Institutional MD-PhD Program/The Rockefeller University

description:
10X genomcis, 28bp Read1 (Cell barcode & UMI), 10bp i7 Index, 10bp i5 index, 90bp Read2
seu_SCT_integrate_post_PhgdhFilter_rmMitoClust_mitoRegres_splitInt_20231115.rds
seuWT_SCT_integrate_rmMitoClust_mitoRegres_splitInt_20240321.rds
barcodes.tsv.gz
features.tsv.gz
matrix.mtx.gz

library_source: other

data_processing:
The scRNA-seq fastq files were processed using the ‘multi’ function from Cell Ranger (10X Genomics, Cell Ranger, version 7.1.0) to deconvolute Hashtag oligos. Reads were aligned to the mm10 mouse genome, filtered, assigned to cells/barcodes, and mapped to genes. Counting matrices with cell counts per gene were generated with Cell Ranger and read into R with the Seurat R package (v4.3.0) (Hao et al., 2021). A gene had to be in at least 10 cells to be included, and a cell required at least 200 genes. Doublets were identified and removed with the Scrublet package (Wolock et al., 2019) and contaminating RNA was estimated and removed using the decontX function from the celda R Bioconductor package (v1.16.1) (Z. Wang et al., 2022). Cells with greater than 10% of reads from mitochondrial genes were also removed from further analysis.
Using the Seurat package, the data for each sample were normalized and scaled using the SCTransform function, and then samples were integrated using the SelectIntegrationFeatures. PrepSCTIntegration, FindIntegrationAnchors (with normalization.method = “SCT” and reduction = “rpca”), and IntegrateData functions. Further quality control was then performed on the integrated object. Cells coming from Phgdh cKO samples with a value greater than 0.5 reads for Phgdh in the normalized and integrated object were removed. Clustering was then performed and a small outlier cluster of cells with high proportions of reads from mitochondrial genes was identified and these cells were removed from the object. The remaining cells were then split by sample into separate Seurat objects and the data were re-normalized while also regressing out the percent of reads in mitochondrial genes with the SCTransform function. The samples were then re-integrated, and clusters were identified using the top 19 PCs and a resolution of 0.5.
Assembly: mm10
Supplementary files format and content: rds and matrix files

molecule: protein

source_name: Skin

extract_protocol:
Unwounded epidermal samples were prepared as above, and single cells were gated on DAPI for dead cell exclusion, negative for non-epidermal markers (CD140a, CD117, CD31, and CD45; hereafter referred to as “Dump gate”) and SCA1 (LY6A/LY6E), and positively selected on high expression of integrin-a6, CD34, CD200, and YFP expression. Single cells from wounded epidermal samples were gated on DAPI for dead cell exclusion, negative for Dump gate markers, and positively selected on high expression of integrin-a6 and YFP expression, which denotes cells lineage traced from the SOX9+ unwounded HFs. No additional EDTA was added to FACS buffer, and DNase I was not added to digestion medium to permit downstream library preparation. TotalSeq-B Hashtag antibodies were also added to the primary antibody staining cocktail. Additionally, cells were collected in with epidermal media to reduce cell death prior library preparation.
Single cells were then encapsulated into nanoliter-scale Gel Beads-in-emulsion (GEMs) using 10x genomics Chromium Controller following manufacture’s protocol. Chromium Single Cell 3’ Library & Gel Bead (PN-1000268), and Single Cell 3' Feature Barcode (PN-1000262) kits were used to prepare single cell 3’ RNA, and single cell surface protein (CSP) libraries following manufacture’s protocol. The quality and quantity of the libraries were assessed with Agilent TapeStation (Agilent Technologies) and Qubit Fluorometer (ThermoFisher Scientific). 3’ RNA-Seq and CSP libraries were sequenced on Illumina NovaSeq 6000 SP flowcell using the read lengths:  28bp Read1 (Cell barcode & UMI), 10bp i7 Index, 10bp i5 index, 90bp Read2.

value: Skin

tag: cell line

value: Hair follicle stem cells

tag: Sex

value: pooled male and female

value: Sox9-CreER;R26-LSL-YFP;Phgdh +/+ or Phgdh fl/fl [C57B6/J]

value: Unwounded, 3 dpw, 5 dpw

tag: library type

value: HTO


title: mibm_hhv_1


title: MUC2692

data_processing:
STAR aligner with human genome reference hg38
Bioconductor package DESeq2
Genome_build: hg38
Supplementary_files_format_and_content: .txt

source_name: lesional skin


title: mibm_PCL_3

value: PCL


title: MUC2693

source_name: non-lesional skin


title: mibm_PCL_2


title: MUC2691

value: male


title: MS7_RL, snRNASeq

description: 10x Genomics

data_processing:
cellranger software version 6.1.2 with the reference refdata-gex-GRCh38-2020-A, using the –include-introns option recommended for single nucleus RNA sequencing data.
Empty droplets were removed using the R package DropletUtils, multiplets predicted using the hybrid method. We included only barcodes with at least 200 and fewer than 4000 genes and a mitochondrial read fraction of less than 1%
Scuttle’s pseudobulk aggregation was used to compute the meta cells for all cell types per sample. EdgeR’s likelihood ratio test accounting for the sex as an additional covariate was used to test for DE for WM vs lesion for each major cell type
Assembly: GRCh38 (refdata-gex-GRCh38-2020-A)
Supplementary files format and content: {sample_name}_raw_feature_bc_matrix.h5, unfiltered cellranger output

extract_protocol:
FANS-sorted nuclei from postmortem human brain tissue
Guidelines from 10x Genomics (CG000183 Rev A)
Indexed adapters pooling single nucleus 3ʹ mRNA-sequencing with 1% PhIX

treatment_protocol: Fresh frozen tissue blocks

tag: tissue

tag: lesion

value: RL


title: Novak_Phgdh_WT_KO_D5_D3_UW

tag: genotype

value: GEX


title: Accept kidney allografts, total cells, integrated of 1 & 3 & 24 weeks, scRNAseq

description: 10x Genomics

value: CD45+ cells

value: Kidney grafts

tag: strain

value: WT


title: mibm_PCL_1

tag: cell type

value: BMMNC

tag: treatment


title: MUC2690

tag: diagnosis

value: Atopic eczema

tag: patient id

tag: age


title: MS7_AL, snRNASeq

description: 10x Genomics

value: white matter

value: AL


title: MS6_RL, snRNASeq

description: 10x Genomics


title: MUC2689

tag: gender

value: female

tag: batch id


title: Splenic MDSC from TNFR2 KO-1

city: ZhengZhou

first: Ming

last: Wang

address: jianshe Road

institute: ZhengZhou university

data_processing:
Single-end read sequences of 50 bp were obtained using the Illumina HiSeq system.
The sequence reads underwent quality checks using FastQC.
The data was analyzed using EdgeR software.
Significantly differentially expressed genes were identified by setting padj < 0.05 and fold change > 1.5.
Assembly: mm10
Supplementary files format and content: Tab-delimited text files includes raw counts for each sample
Supplementary files format and content: Tab-delimited text files includes RPKM values for each sample

source_name: MDSCs

growth_protocol: Primer MDSCs were isoalted by cell sorting without further culture.

extract_protocol:
A total of 1 million MDSCs were used for RNA extraction with the RNeasy Mini Kit (QIAGEN) and subjected to RNA-seq analysis.
RNA libraries for RNA-SEQ were prepared using SMARTER mRNA-seq Library prep kit following manufacturer’s protocols.

treatment_protocol: MDSCs without any treatment.

value: MDSCs


title: Splenic MDSC from TNFR2 KO-2


title: MS6_NAWM, snRNASeq

description: 10x Genomics

value: NAWM


title: Splenic MDSC from TNFR1 KO-2


title: MUC2685

extract_protocol:
RNA from skin biopsies was isolated using the QIAzol Lysis Reagent (Qiagen) and miRNeasy Mini Kit (Qiagen) according to manufacturer’s protocol
RNASeq libraries were generated using the TruSeq Stranded Total RNA Kit (Illumina) with Ribo-Zero Depletion (rRNA Removal Mix) according to manufacturer’s high sample protocol. 200 ng of RNA was used as input. DNA was PCR amplified with Illumina primers for 13 cycles. Libraries were sequenced on the Illumina HiSeq 4000 as paired-end with a read length of 2x 150 bp and an average output of 40 Mio reads per sample and end following the manufacturer's protocols.


title: MUC2684


title: MS6_CA, snRNASeq

description: 10x Genomics

value: CA


title: Splenic MDSC from WT-2


title: Splenic MDSC from TNFR1 KO-1


title: Splenic MDSC from WT-1


title: CA_2A, spatial transciptomics

description: 10x Genomics


title: MS6_AL, snRNASeq

description: 10x Genomics


title: MS3_RL, snRNASeq

description: 10x Genomics


title: MS3_CA, snRNASeq

description: 10x Genomics


title: MUC2683

value: Nummular Eczema


title: MS7_CA, snRNASeq

description: 10x Genomics


title: CORT-Ket (#9971-2)

city: San Diego

first: Andiara

last: Espindola de Freitas

address: Gilman Drive

department: Biological Sciences

institute: UC San Diego (UCSD)

data_processing:
The sequencing data were processed using the Cell ranger software to demultiplex the samples, generate fastq.gz files, align the reads to mm9 genome and generate feature-barcode matrices. The filtered featured matrices were individually analyzed using Seurat R package (v3.1.1) and submitted to quality control (gene count per cell, percent of mitochondrial transcripts).
Assembly: mm9
Supplementary files format and content: filtered_feature_bc_matrix folder (barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz)

source_name: Brain (BLA)

extract_protocol:
Brains were harvested, and the prefrontal cortices were rapidly dissected and transferred into ice-cold Hibernate A/B27 medium (60 ml Hibernate A medium with 1ml B27 and 0.15 ml Glutamax). The tissues were enzymatically dissociated into single cell suspension, and the cells were captured with the 10X Chromium platform (10X Genomics, Pleasanton, CA).
Reverse transcription, cDNA amplification and library construction were performed according to the manufacturer’s instructions and used for sequencing.

value: BLA

value: 13 weeks old

value: wild type

value: CORT-Ket


title: MS1_NAWM, snRNASeq

description: 10x Genomics


title: Hemin-MCM, replicate 3

city: Shanghai

first: Chang

last: Liu

address: 1954 Hua Shan Road

department: School of Biomedical Engineering

institute: Shanghai Jiao Tong University

data_processing:
The transcriptome sequencing and analysis were conducted by OE biotech Co., Ltd. (Shanghai, China).
The genome-wide transcriptomic analysis was performed on a set of 3 separate experiments.
Differential expression analysis was identified using the DESeq (2012) R package functions estimate Size Factors and nbinom Test.
p value < 0.05 and fold change > 2 or fold change < 0.5 was set as the threshold for significantly differential expression.
Assembly: mm10
Supplementary files format and content: tab-delimited text files include FPKM values for each Sample

source_name: Brain

extract_protocol:
Resting-MCM, LPS-MCM, and Hemin-MCM treated astrocytes were harvested, and total RNA was isolated using TRIzol (Invitrogen). RNA integrity was evaluated using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
The libraries were constructed using TruSeq Stranded mRNA LTSample Prep Kit (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions.

value: Brain

value: Astrocytes

value: Hemin-MCM


title: MUC2681


title: Hemin-MCM, replicate 2

value: WT


title: CORT-Ket (#9968-2)


title: MS1_AL, snRNASeq

description: 10x Genomics


title: CORT-Ket (#9967-2)


title: MUC2680


title: Hemin-MCM, replicate 1


title: MUC2688


title: C4_WM, snRNASeq

description: 10x Genomics

value: WM


title: MUC2679

value: Atopic eczema

value: male


title: CORT-Sal (#9970-2)

value: CORT-Sal


title: LPS-MCM, replicate 3

value: LPS-MCM


title: C3_WM, snRNASeq

description: 10x Genomics

value: white matter


title: MUC2678


title: CORT-Sal (#9969-2)


title: LPS-MCM, replicate 2


title: MUC2682

value: female


title: MUC2677


title: BCD-Ket (#9986-2)

value: BCD-Ket


title: C1_WM, snRNASeq

description: 10x Genomics


title: MS7_RL, snATACSeq

description: 10x Genomics

data_processing:
Raw data processing was performed using cellranger-atac pipeline (version 2.0.0, with reference refdata-cellranger-arc-GRCh38-2020-A-2.0.0)
Data processing using Seurat in Signac, cells with fewer than 3000 or more that 20000 fragments per peak, blacklist ratio of more than 0.05, nucleosome signal of less than 4, TSS enrichment of more than 2, and predicted doublets (scDblFinder) were removed.
Batch integration and label transfer from matching scRNA data using harmony.
Differential accessibiliy, motifs and footprints where called using Signac
Assembly: GRCh38
Supplementary files format and content: filtered_peak_bc_matrix.h5; filtered_tf_bc_matrix.h5; the cellranger output

extract_protocol:
FANS-sorted nuclei from postmortem human brain tissue with anti-lamin A/C antibody
Guidelines from 10x Genomics (CG000209 Rev C, 10x Genomics)
Indexed adaptor pooling for transposase-accessible DNA sequencing with 1% PhIX

value: RL


title: MUC2676


title: LPS-MCM, replicate 1


title: MS6_RL, snATACSeq

description: 10x Genomics


title: C2H4.etr17.4h.R3.R1

city: Richmond

first: Wright Center for Clinical and Translational Research

last: Bioinformatics Core

state: VA

address: 203 E Cary St

institute: Virginia Commonwealth University

data_processing:
FastQC v0.11.8 and MultiQC v1.7 were used for assessing read quality.
Adaptors were trimmed from reads using CutAdapt v1.18, and reads trimmed to less than 25bp were removed.
Trimmed reads were then processed with the BBMap tool BBDuk to identify and remove rRNA contamination.
Read quantification was performed directly on the processed fastq files with the Salmon v0.12.0 “quant” algorithm in mapping mode using the “--validateMapping” flag, setting the library type to “IU”.
Counts were imported into R v3.6.0 using the tximport R package v1.12.3 and summarized to the gene level.
Genome_build: TAIR10 reference transcriptome
Supplementary_files_format_and_content: Contains raw read counts from Salmon summarized to the gene level in a tab-delimited format.  No normalization or other transformations were done to the processed data for this submission.  Raw fastq files are original and unprocessed.

source_name: whole root tissue from seedlings (age 5 days + length of treatment)

growth_protocol: Plants were grown on 1x Murashige and Skoog medium, pH 5.6, Murashige and Skoog vitamins, and 0.8% agar, buffered with 0.05% MES and supplemented with 1% Suc, on top of a nylon filter (03-100/32; Sefar Filtration) pressed against the plate. Approximately 100 sterilized seeds were placed on each filter; 2 plates were combined for each biological replicate. After stratification for 72 h at 4C, plants were grown under 100umol m-2s-1 continuous cool-white light.

extract_protocol:
Frozen samples were ground in liquid nitrogen, and RNA isolation was performed according to the Qiagen plant RNeasy kit protocol, with the addition of the Qiagen RNase-free DNase treatment. After RNA isolation, samples were quantified by A260 using a Nanodrop spectrophotometer. Each sample yielded at least 3ug, and on average 15ug, of RNA. One Col-0 ethylene 4 hour treatment had an RNA integrity number (RIN) less than 6 and was not sequenced.
Library prep was performed by GENEWIZ, LLC as part of sequencing services.

treatment_protocol: Plants were treated on day 5 after germination. For time 0 treatments, the nylon filter containing 5-day-old plants was transferred to new control medium and root tissue was immediately harvested. For ACC treatment, the plants on nylon were transferred to growth medium with 1uM ACC for the given treatment time and then root tissue was harvested. For ethylene treatment, the nylon was transferred to new control medium, and plants were placed in clear treatment tanks with constant flow-through of 0.3 ppm ethylene gas for the given treatment time and then root tissue was harvested. At ttime of harvesting, roots were cut from seedlings and flash frozen in liquid nitrogen.

value: Ethelyene Gas (C2H4), 3ppm

tag: time point

tag: biological replicate


title: BCD-Ket (#9946-2)

value: BLA

value: 13 weeks old


title: Resting-MCM, replicate 2

value: Resting-MCM


title: C2H4.etr17.4h.R2.R1


title: MS6_NAWM, snATACSeq

description: 10x Genomics

value: NAWM

tag: postmortem delay


title: BCD-Ket (#9949-2)

value: wild type


title: BCD-Sal (#9947-2)

value: BCD-Sal


title: MS6_CA, snATACSeq

description: 10x Genomics

value: CA


title: C2H4.etr17.4h.R1.R1


title: BCD-Sal (#9901-2)


title: MS3_NAWM, snATACSeq

description: 10x Genomics


title: C2H4.etr17.24h.R3.R1


title: WiT49, DMSO, 2wk, rep3, riboseq

city: Dallas

first: Kenneth

middle: S

last: Chen

state: TX

address: 5323 Harry Hines Blvd

department: Pediatrics

institute: UT Southwestern

description:
WiT49_2wkRIBO_DMSO3_S3
ribosome footprints

data_processing:
Trimmed reads from ribosome profiling and RNA sequencing were aligned to the hg38 reference genome using HISAT2.
For ribosome profiling, reads longer than 30 nt were filtered out.
Remaining reads were assembled to GENCODE v26 transcript annotations using StringTie.
Assembly: hg38
Supplementary files format and content: comma-separated text file containing raw counts for each gene for each sample

molecule: other

growth_protocol: The anaplastic Wilms tumor cell line WiT49 was maintained in Dulbecco’s Modified Eagle Medium (DMEM) with 1000 mg/L glucose, 4mM L-glutamine, 1mM pyruvate supplemented with antibiotic-antimycotic and 10% FBS in 37°C at 5% CO2.

extract_protocol:
For total RNA sequencing, RNA was extracted using the Direct-zol RNA Miniprep Kit (ZymoResearch R2050) or the miRneasy Mini Kit (Qiagen 217004) according to manufacturer protocols. Ribosome footprints were isolated based on previous publications (McGlincy et al, 2017; Ingolia et al, 2012).
Ttotal RNA sequencing libraries were prepared with the TruSeq Stranded Total RNA LT or TruSeq Stranded Total RNA-seq (Illumina) Sample Prep Kit from Illumina. For ribosome proifiling, rRNA depletion was performed using the Low Input RiboMinus™ Eukaryote System v2, and sequencing libraries were generated using the NEBNext® Small RNA Library Prep Set for Illumina.
ribosome profiling + total RNA seq

treatment_protocol: WiT49 cells were incubated in complete growth medium with 2nM actD or DMSO for 6 or 72 hours, in three replicates per condition. For 2-week long treatments, WiT49 were maintained and passaged in two 7-day cycles of drug/vehicle-supplemented media for 3 days, followed by no additive complete growth media for 4 days.

tag: cell line

value: Wilms tumor

tag: time

value: DMSO


title: Resting-MCM, replicate 1

value: Brain

value: Astrocytes

value: WT


title: WiT49, DMSO, 2wk, rep2, riboseq

description:
WiT49_2wkRIBO_DMSO2_S2
ribosome footprints


title: LysM-Cre x R26-stop-EYFP x Tgfbr2-fl/fl inflammatory cardiac macrophages biol rep 4

city: Cracow

first: Karolina

last: Tkacz

address: ul. Wielicka 256

country: Poland

institute: Jagiellonian University Medical College

data_processing:
Sequence reads were trimmed to remove possible adapter sequences and nucleotides with poor quality using Trimmomatic v.0.36. The trimmed reads were mapped to the Mus musculus GRCm38 reference genome available on ENSEMBL using the STAR aligner v.2.5.2b. The STAR aligner is a splice aligner that detects splice junctions and incorporates them to help align the entire read sequences. BAM files were generated as a result of this step. Below are the statistics of mapping the reads to the reference genome.
Assembly: Mus musculus GRCm38 reference genome
Supplementary files format and content: tab-delimited text file includes raw counts for each Sample

source_name: heart

extract_protocol:
RNA was isolated using Total Genomic DNA Isolation Kits (Norgen Biotek Corp., Thorold, Canada) following the manufacturer’s protocol
The mRNA samples were initially fragmented, and double-stranded cDNA synthesis was performed. The 5' end of the cDNA was phosphorylated, and a polyA tail was attached to the 3' end for PolyA selection rRNA removal

value: heart

value: inflammatory cardiac macrophages

value: LysM-Cre x R26-stop-EYFP x Tgfbr2-fl/fl


title: MS3_CA, snATACSeq

description: 10x Genomics

value: white matter


title: C2H4.etr17.24h.R2.R1

value: Ethelyene Gas (C2H4), 3ppm


title: WiT49, DMSO, 2wk, rep1, riboseq

description:
WiT49_2wkRIBO_DMSO1_S1
ribosome footprints


title: C2H4.etr17.24h.R1.R1


title: LysM-Cre x R26-stop-EYFP x Tgfbr2-fl/fl inflammatory cardiac macrophages biol rep 3


title: LysM-Cre x R26-stop-EYFP x Tgfbr2-fl/fl inflammatory cardiac macrophages biol rep 2


title: Resting-MCM, replicate 3


title: MS1_NAWN, snATACSeq

description: 10x Genomics


title: C4_WM, snATACSeq

description: 10x Genomics

value: WM


title: WiT49, actD, 2wk, rep3, riboseq

description:
WiT49_2wkRIBO_ACTD3_S6
ribosome footprints

value: actD


title: LysM-Cre x R26-stop-EYFP x Tgfbr2-fl/fl inflammatory cardiac macrophages biol rep 1


title: WiT49, actD, 2wk, rep2, riboseq

description:
WiT49_2wkRIBO_ACTD2_S5
ribosome footprints


title: C1_WM, snATACSeq

description: 10x Genomics


title: C2H4.etr17.1h.R2.R1


title: C2H4.etr17.1h.R3.R1


title: WiT49, actD, 2wk, rep1, riboseq

description:
WiT49_2wkRIBO_ACTD1_S4
ribosome footprints


title: EJ_Cas9_3

city: WuHan

first: Guosong

last: Jiang

state: Hubei Province

address: Jiefang Road, No. 1277

department: Department of Urology

institute: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

data_processing:
Illumina Casava1.7 software used for basecalling.
Low-complexity or low-quality sequence of the original data were filtered to obtain high-quality clean data, which were then compared to the reference genome of human species to obtain comprehensive transcript information using bowtie v0.12.2.
We took RPKM (Reads per Kilobase per Million Reads) as A measure of gene expression (Mortazavi a. et al. 2008).
The differentially expressed genes were screened from the difference multiples and the significant levels. Here, we use the absolute value of logFC >1 and pvalue<0.05 as the standard to indicate that the gene is a differentially expressed gene.
Genome_build: human NCBI genome

source_name: EJ

growth_protocol: All the cells were cultured in RPMI-1640 medium supplemented with 10% FBS and 1% penicillin/streptomycin.

extract_protocol:
Total RNA was isolated from hMSH2-deficient and wild-type EJ cells using TRIzol reagent.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: EJ cells transfected with sgRNA-hMSH2 and compaired vector

value: bladder cancer cell

value: wild-type EJ cells

value: EJ


title: C2H4.etr17.1h.R1.R1


title: WiT49, DMSO, 72hr, rep3, riboseq

description:
WiT49_72hribo_DMSO3_S2
ribosome footprints


title: EJ_Cas9_2

value: wild type


title: C2H4.etr17.0h.R3.R1


title: WiT49, DMSO, 72hr, rep2, riboseq

description:
WiT49_72hribo_DMSO2_S1
ribosome footprints


title: EJ_Cas9_1


title: C2H4.etr17.0h.R2.R1


title: WiT49, DMSO, 72hr, rep1, riboseq

description:
WiT49_72hRIBO_DMSO1_S7
ribosome footprints


title: WiT49, actD, 72hr, rep3, riboseq

description:
WiT49_72hribo_ACTD3_S5
ribosome footprints


title: WiT49, actD, 72hr, rep2, riboseq

description:
WiT49_72hribo_ACTD2_S4
ribosome footprints


title: EJ_KO_3

value: hMSH2-deficient EJ cell


title: C2H4.etr13.4h.R3.R1


title: Dam 52, IAV-X31, E16.5 fetal whole brains

city: Urbana

first: Adrienne

last: Antonson

address: 1201 W Gregory Dr

institute: University of Illinois Urbana-Champaign

data_processing:
Raw sequencing runs were demultiplexed with bcl2fastq v2.20 conversion Software (Illumina)
Adaptors were trimmed from 3-end of the reads. FASTQC v0.11.8 indicated no adaptor sequence contamination
Trimmed reads were quasi-mapped to GRCm39 (mouse); A/X-31(H3N2)
The gene model file “GCF_000001635.27_GRCm39_genomic.gff.gz; influenza_A_X-31_H3N2.gff3” was used to generate transcript-gene mapping table (“trx_EGids_GRCm39_annot109.txt”) for gene-level counts.
Assembly: GRCm39 (mm39)
Supplementary files format and content: tab-delimited text file contains raw counts for each sample

source_name: Pooled E16.5 fetal brains

extract_protocol:
RNA from pooled E16.5 fetal whole brains was extracted using the RNeasy Mini Kit (Qiagen).
Construction of the strand-specific RNAseq libraries and sequencing on the Illumina NovaSeq 6000 were performed at the Roy J. Carver Biotechnology Center at the University of Illinois at Urbana-Champaign.Purified DNAsed total RNAs were run on a Fragment Analyzer (Agilent) to evaluate RNA integrity. The total RNAswere converted into individually barcoded polyadenylated mRNAseq libraries with theKapa HyperPrep mRNA kit (Roche). Libraries were barcoded with Unique Dual Indexes (UDI’s) which have been developed to prevent index switching.The adaptor-ligated double-stranded cDNAs were amplified by PCR for 10 cycles with the Kapa HiFi polymerase (Roche). The final libraries were quantitated with Qubit (ThermoFisher) and the average cDNA fragment sizes were determined on a Fragment Analyzer. The libraries were diluted to 10nM and further quantitated by qPCR on a CFX Connect Real-Time qPCR system (Biorad) for accurate pooling of barcoded libraries and maximization of number of clusters in the flowcell.

value: Pooled E16.5 fetal brains


title: LysM-Cre x R26-stop-EYFP inflammatory cardiac macrophages biol rep 1

value: LysM-Cre x R26-stop-EYFP


title: Dam 38, IAV-X31, E16.5 fetal whole brains


title: EJ_KO_2


title: Dam 43, IAV-X31, E16.5 fetal whole brains


title: C2H4.etr13.4h.R2.R1


title: WiT49, actD, 72hr, rep1, riboseq

description:
WiT49_72hribo_ACTD1_S3
ribosome footprints

value: Wilms tumor


title: Dam 60, IAV-X31, E16.5 fetal whole brains


title: C2H4.etr17.0h.R1.R1


title: EJ_CDDP_Cas9_2

data_processing:
Illumina Casava1.7 software used for basecalling.
Low-complexity or low-quality sequence of the original data were filtered to obtain high-quality clean data, which were then compared to the reference genome of human species to obtain comprehensive transcript information using bowtie v0.12.2.
We took RPKM (Reads per Kilobase per Million Reads) as A measure of gene expression (Mortazavi a. et al. 2008).
The differentially expressed genes were screened from the difference multiples and the significant levels. Here, we use the absolute value of logFC >1 and pvalue<0.05 as the standard to indicate that the gene is a differentially expressed gene.
Genome_build: human NCBI genome
Supplementary_files_format_and_content: tab-delimited text files include RPKM values for each Sample ...

source_name: wild-type EJ cells treated with CDDP

growth_protocol: All the cells were administered with CDDP for 24h at the dose of 5μM and cultured in RPMI-1640 medium supplemented with 10% FBS and 1% penicillin/streptomycin.

value: CDDP


title: C2H4.etr13.4h.R1.R1


title: WiT49, DMSO, 6hr, rep3, riboseq

description:
WiT49_6hDMSO3_S3
ribosome footprints

value: DMSO


title: Dam 2, IAV-X31, E16.5 fetal whole brains


title: C2H4.etr13.24h.R3.R1


title: C2H4.etr13.24h.R2.R1


title: LysM-Cre x R26-stop-EYFP inflammatory cardiac macrophages biol rep 3

value: heart


title: EJ_CDDP_Cas9_1


title: LysM-Cre x R26-stop-EYFP inflammatory cardiac macrophages biol rep 2

value: inflammatory cardiac macrophages


title: WiT49, DMSO, 6hr, rep1, riboseq

description:
WiT49_6hDMSO1_S1
ribosome footprints


title: LysM-Cre x R26-stop-EYFP inflammatory cardiac macrophages biol rep 4


title: Dam 18, IAV-X31, E16.5 fetal whole brains


title: EJ_KO_1


title: EJ_CDDP_KO_3

source_name: hMSH2-deficient EJ cell treated with CDDP


title: EJ_CDDP_Cas9_3


title: Dam 7, saline, E16.5 fetal whole brains

value: Saline


title: C2H4.etr13.1h.R3.R1


title: EJ_CDDP_KO_1


title: Dam 35, saline, E16.5 fetal whole brains


title: C2H4.etr13.1h.R2.R1


title: WiT49, DMSO, 6hr, rep2, riboseq

description:
WiT49_6hDMSO2_S2
ribosome footprints


title: WiT49, actD, 6hr, rep3, riboseq

description:
WiT49_6hACTD3_S6
ribosome footprints


title: Dam 36, saline, E16.5 fetal whole brains


title: WiT49, actD, 6hr, rep2, riboseq

description:
WiT49_6hACTD2_S5
ribosome footprints


title: EJ_CDDP_KO_2


title: WiT49, actD, 6hr, rep1, riboseq

description:
WiT49_6hACTD1_S4
ribosome footprints


title: C2H4.etr13.1h.R1.R1


title: C2H4.etr13.0h.R3.R1


title: HepG2-NTCP +HBV, 30uM FG-4592 (B)

city: Oxford

first: James

last: Harris

state: Oxfordshire

address: Old Road Campus, Roosevelt Drive

country: United Kingdom

institute: University of Oxford

data_processing:
Illumina adapters were removed and data transformed to sequencing reads by CASAVA base recognition
Reads were mapped against the reference human genome (hg38) using STAR aligner.
Non-human reads were aligned to the HBV (strain ayw) reference; NC_003977.2
Read counts were transformed to FPKM to account for sequencing depth and gene length (Mortazavi et al. 2008)
Genome_build: Human hg38
Supplementary_files_format_and_content: fpkm_samples.xls and reacount.xls contain all FPKM and readcount values for every gene in n=12 samples, respectively.

growth_protocol: HepG2-NTCP cells were seeded, and left overnight to adhere. Media was replaced and cells were transferred to culture conditions for 72 hours.

extract_protocol:
Following treatment as described above, cells were lysed in RLT buffer and RNA extracted using Qiagen RNAeasy kit. RNAs were treated with on-column DNAse (Qiagen), and 2uG of material was used for the construction of sequencing libraries.
Libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: Hypoxic culture or drug treatment were applied for 72 hours.

value: Human hepatoma cell line

tag: culture condition

tag: infection

value: + HBV


title: WiT49, DMSO, 2wk, rep1


title: Ripk1/Casp8 KO, ADT

city: Ghent

first: Bruno

last: Verstraeten

state: Oost-Vlaanderen

address: Technologiepark 71

country: Belgium

institute: Ghent University

description: Antibody-derived tag (ADT)

data_processing:
The Cell Ranger pipeline (10x Genomics, version 5.0.0) was used to perform sample demultiplexing and to generate FASTQ files for read 1, read 2 and the i7 sample index for the gene expression, cell surface and hashing protein libraries. Read 2 of the gene expression libraries was mapped to the mouse reference genome (GRCm38.99).
Subsequent barcode processing, unique molecular identifiers filtering and gene counting was performed using the Cell Ranger suite. The average of the mean reads per cell across all gene expression libraries was 33800, with an average sequencing saturation of 62%, as calculated by Cell Ranger. In total, 4 individual single-cell libraries were created in this study, entailing 56740 cells.
Assembly: GRCm38.99
Supplementary files format and content: h5 matrices and fastq files
Library strategy: CITE-seq

source_name: mesenteric lymph nodes

extract_protocol:
Half of the cells were used for enrichment of T cells using the MagniSort™ Mouse T cell Enrichment Kit (8804-6820-74, eBioscience) according to the manufacturer’s instructions. The other half of the single cell suspensions were not enriched. Cells were subsequently stained with fluorochrome-conjugated monoclonal antibodies recognizing CD4 (clone RM4-5, BD Biosciences) and CD8β (clone YTS156.7.7, Biolegend), DAPI for cell viability, TruStain FcX Block (101320, BioLegend), the mouse cell surface protein antibody panel containing 165 oligo-conjugated antibodies and 9 TotalSeq-A isotype controls (TotalSeq-A, BioLegend) and a unique TotalSeq-A cell hashing antibody (BioLegend). Sorting of live CD4+ and CD8+ T cells from the enriched cells and sorting of total live cells from the unenriched cells was performed using FACSAria™ II and FACSAria™ III cell sorters (BD Biosciences). This resulted in two suspension of sorted cells per mouse which were tagged with unique hashing antibodies and combined in a 1:1 ratio to ensure enough T cells would be available for sequencing as T cell numbers are significantly reduced in the mLN of Ripk1ΔCD4 mice.
Three biological replicates per sample were loaded (consisting of a 1:1 combination of total live cells and enriched T cells) were multiplexed per lane using TotalSeq-A cell hashing antibodies. In the final analysis, only two of the three Ripk1FL/FLCasp8FL/FL samples had sufficient cells to analyse. Sorted single-cell suspensions at an estimated final concentration of 1500 cells/µl were loaded on a Chromium GemCode Single Cell Instrument (10x Genomics) to generate single-cell gel beads-in-emulsion (GEM). The scRNA-Seq libraries were prepared using the GemCode Single Cell 3’ Gel Bead and Library kit, version 3.1 (10x Genomics) according to the manufacturer’s instructions with the addition of amplification primers (3nM each, 5’CCTTGGCACCCGAGAATT*C*C - 5’GTGACTGGAGTTCAGACGTGTGC*T*C) during cDNA amplification to enrich the TotalSeq-A cell surface and hashing protein oligos, respectively. Size selection with SPRIselect Reagent Kit (B23318, Beckman Coulter, Brea, CA, US) was used to separate amplified cDNA molecules for 3’ gene expression and cell surface protein construction. TotalSeq-A protein library construction including sample index PCR using Illumina’s Truseq Small RNA primer sets and SPRIselect size selection was performed according to the manufacturer’s instructions. The cDNA content of pre-fragmentation and post-sample index PCR samples was analyzed using the 2100 BioAnalyzer (Agilent, Santa Clara, CA, US). Sequencing libraries were loaded on an Illumina NovaSeq flow cell at VIB Nucleomics core with sequencing settings according to the recommendations of 10x Genomics, pooled in a 70:20:10 ratio for the combined 3’ gene expression, cell surface and hashing protein samples, respectively.

tag: tissue

value: mesenteric lymph nodes

value: mLN cells

tag: library type

value: ADT


title: HepG2-NTCP +HBV, 5uM QC6352 (C)


title: C2H4.etr13.0h.R1.R1

tag: genotype

value: Ethelyene Gas (C2H4), 3ppm


title: HepG2-NTCP +HBV, 30uM FG-4592 (A)

tag: cell type


title: C2H4.etr13.0h.R2.R1

tag: treatment


title: WiT49, actD, 2wk, rep3

value: actD


title: Ripk1/Casp8 KO, cDNA

description: polyA RNA

data_processing:
The Cell Ranger pipeline (10x Genomics, version 5.0.0) was used to perform sample demultiplexing and to generate FASTQ files for read 1, read 2 and the i7 sample index for the gene expression, cell surface and hashing protein libraries. Read 2 of the gene expression libraries was mapped to the mouse reference genome (GRCm38.99).
Subsequent barcode processing, unique molecular identifiers filtering and gene counting was performed using the Cell Ranger suite. The average of the mean reads per cell across all gene expression libraries was 33800, with an average sequencing saturation of 62%, as calculated by Cell Ranger. In total, 4 individual single-cell libraries were created in this study, entailing 56740 cells.
Assembly: GRCm38.99
Supplementary files format and content: h5 matrices and fastq files

value: mRNA


title: C2H4.Col0.4h.R3.R1

value: wild type (Col-0)


title: HepG2-NTCP +HBV, 5uM QC6352 (B)


title: C2H4.etr13.24h.R1.R1


title: Dam 21, saline, E16.5 fetal whole brains

value: Pooled E16.5 fetal brains

tag: strain


title: WiT49, DMSO, 2wk, rep3


title: HepG2-NTCP +HBV, 5uM QC6352 (A)


title: Ripk1/Casp8 WT, HTO

description: Hashtag-derived oligonucleotide (HTO)

value: HTO


title: Ripk1/Casp8 KO, HTO

description: Hashtag-derived oligonucleotide (HTO)


title: C2H4.Col0.24h.R3.R1


title: WiT49, actD, 2wk, rep2

value: Wilms tumor


title: HepG2-NTCP +HBV, 30uM FG-4592 (C)


title: WiT49, actD, 2wk, rep1


title: WiT49, DMSO, 72hr, rep3


title: Ripk1/Casp8 WT, ADT

description: Antibody-derived tag (ADT)


title: HepG2-NTCP +HBV, 1% Oxygen (C)

value: 1% Oxygen


title: WiT49, DMSO, 2wk, rep2

value: DMSO


title: C2H4.Col0.24h.R2.R1


title: HepG2-NTCP +HBV, 1% Oxygen (A)


title: WiT49, DMSO, 72hr, rep2


title: C2H4.Col0.24h.R1.R1


title: Ripk1 KO, HTO

description: Hashtag-derived oligonucleotide (HTO)


title: Ripk1 KO, ADT

description: Antibody-derived tag (ADT)


title: WiT49, DMSO, 72hr, rep1


title: HepG2-NTCP +HBV, Control (C)

value: Untreated (Control)


title: Ripk1 KO, cDNA

description: polyA RNA


title: WiT49, actD, 72hr, rep3


title: C2H4.Col0.1h.R2.R1


title: Ripk1 WT, HTO

description: Hashtag-derived oligonucleotide (HTO)


title: HepG2-NTCP +HBV, Control (B)


title: C2H4.Col0.4h.R1.R1


title: WiT49, actD, 72hr, rep2


title: HepG2-NTCP +HBV, Control (A)


title: Ripk1/Casp8 WT, cDNA

description: polyA RNA


title: C2H4.Col0.1h.R1.R1


title: Ripk1 WT, ADT

description: Antibody-derived tag (ADT)


title: WiT49, actD, 72hr, rep1


title: HepG2-NTCP +HBV, 1% Oxygen (B)


title: Ripk1 WT, cDNA

description: polyA RNA


title: C2H4.Col0.0h.R2.R1


title: WiT49, DMSO, 6hr, rep3


title: C2H4.Col0.0h.R3.R1


title: Mouse_lung_opti-KAS-seq_Input, rep2

city: Chicago

first: Ruitu

last: Lyu

address: 929 E 57th Street

institute: The University of Chicago

data_processing:
To align Opti-KAS-seq and KAS-seq data to the reference genome of interest, we utilized the trim_galore package to trim off low-quality sequence, adaptor sequence and primer sequence from single-end or paired-end raw fastq files
Subsequently, we employed bowtie2 to perform the read alignment of Opti-KAS-seq and KAS-seq data. Mapped reads in sam files from the aligners are sorted and converted to bam files using ‘samtools sort’, which are subsequently deduplicated using ‘picard MarkDuplicates’ (pair-end data) or ‘samtools rmdup’ (single-end data).
For single-end Opti-KAS-seq or KAS-seq data, mapped reads were extended to 150bp as default, irrespective of the initial sequencing data's read length. For paired-end KAS-seq data, the KAS-Analyzer incorporates a Python script, facilitating the merging of "properly paired" mapped reads into a singular interval
Peak calling for broad KAS-seq was executed using epic2, which identified broad peaks maintaining a false discovery rate (FDR) of 0.05 and a 1.5-fold change relative to the Input. Comprehensive quality control measures, such as library complexity metrics, inter-replicate correlation analyses, fingerprint plots, saturation analyses, genomic distribution of KAS-seq peaks, enrichment within gene-coding regions, and the Fraction of Reads in Peaks (FRiP) metric, were executed with the KAS-Analyzer package.
Deduplicated mapped KAS-seq reads were converted to bedGraph and bigWig using deeptools bamCoverage and UCSC tools.
Assembly: mm10
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.
Library strategy: Opti-KAS-seq

source_name: Lung

extract_protocol:
Then, 1 µg genomic DNA was suspended in 95 µL DNA elution buffer supplemented with 5 µL 20 mM DBCO-PEG4-biotin (DMSO solution, Sigma, 760749), 25 mM K3BO3, and incubated at 37 °C for 1.5 h while being gently shaken. Next, 5 µL RNase A (Thermo, 12091039) was added into the reaction mixture followed by incubation at 37 °C for 5 min. Biotinylated gDNA was then recovered by DNA Clean & Concentrator-5 kit (Zymo, D4013).
gDNA was suspended into 100 µL water and was fragmented to 150–350 bp size by using Bioruptor Pico at 30s-on/30s-off setting for 30 cycles; 5% of the fragmented DNA was saved as input, and the remaining 95% was used to enrich biotin-tagged DNA by incubation with 10 µL pre-washed Dynabeads MyOne Streptavidin C1 (Thermo, 65001) at room temperature for 15 min. The beads were washed, and DNA was eluted by heating the beads in 15 µL H2O at 95 °C for 10 min. Eluted DNA and its corresponding input were used for library construction by using Accel-NGS Methyl-seq DNA library kit (Swift, 30024).

value: Lung

value: Mouse Lung

value: WT

value: No treatment


title: WiT49, DMSO, 6hr, rep2


title: C2H4.Col0.0h.R1.R1


title: rep2 H2O+

first: Tao

last: Pan

state: Illinois

address: 929 E. 57th Street

department: Biochemistry and Molecular Biology

institute: University of Chicago

data_processing:
*library strategy: multiplex small RNA sequencing (MSR-seq)
Raw sequences reads were demultiplexed using Je to detect encoded barcode reads. Following this, reads were aligned to curated Streptomyces Venezuelae tRNA and 5s rRNA reference genome.
The aligned reads were then used to determine RNA sequence abundance using custom python script. RNA modifications were detected based on aligned reads using samtools sort (http://www.htslib.org/,Li et al., 2009) feature sort the reads in a bam file format. Then IGVtools count (https://software.broadinstitute.org/software/igv/igvtools) count feature was utilized to output a wig files using the following parameters: -z 5 -w 1 -e 250 —bases. The resulting wig files were processed using a custom python script to identify nucleotide mutations as well as coverage of aligned reads.
Assembly: Streptomyces venezuelae ATCC 10712
Supplementary files format and content: tsv files with gene name and abundance per sample
Supplementary files format and content: .sam.tsv files with mutation, deletion, coverage for each gene position per sample

organism: Streptomyces venezuelae

growth_protocol: Streptomyces venezuelae strains (WT and mutant derivaties; ATCC 10712) were cultured in both ISP2 media and Glucose-Isoleucine media under standard and stress conditions (6% EtOH or 42oC)

extract_protocol:
Total RNA was extracted from samples using a Trizol extraction along with bead beating.
MSR-seq (PMID 35513407)

treatment_protocol: Total RNA was extracted from each sample and used as input material for the sequencing libraries

value: H2O +DM


title: WiT49, DMSO, 6hr, rep1


title: rep2 EtOH+

value: EtOH +DM


title: rep2 42oC+

value: 42oC +DM


title: rep2 Ctrl+

value: Ctrl +DM


title: Mouse_lung_opti-KAS-seq, rep2


title: ACC.etr17.4h.R4.R1

value: ACC, 1uM


title: rep2 H2O-

value: H2O -DM


title: ACC.etr17.4h.R3.R1


title: Mouse_lung_opti-KAS-seq, rep1


title: WiT49, actD, 6hr, rep2

value: actD


title: rep2 42oC-

value: 42oC -DM


title: ACC.etr17.4h.R2.R1


title: ACC.etr17.24h.R4.R1


title: rep2 EtOH-

value: EtOH -DM


title: Mouse_lung_KAS-seq_Input, rep1

data_processing:
To align Opti-KAS-seq and KAS-seq data to the reference genome of interest, we utilized the trim_galore package to trim off low-quality sequence, adaptor sequence and primer sequence from single-end or paired-end raw fastq files
Subsequently, we employed bowtie2 to perform the read alignment of Opti-KAS-seq and KAS-seq data. Mapped reads in sam files from the aligners are sorted and converted to bam files using ‘samtools sort’, which are subsequently deduplicated using ‘picard MarkDuplicates’ (pair-end data) or ‘samtools rmdup’ (single-end data).
For single-end Opti-KAS-seq or KAS-seq data, mapped reads were extended to 150bp as default, irrespective of the initial sequencing data's read length. For paired-end KAS-seq data, the KAS-Analyzer incorporates a Python script, facilitating the merging of "properly paired" mapped reads into a singular interval
Peak calling for broad KAS-seq was executed using epic2, which identified broad peaks maintaining a false discovery rate (FDR) of 0.05 and a 1.5-fold change relative to the Input. Comprehensive quality control measures, such as library complexity metrics, inter-replicate correlation analyses, fingerprint plots, saturation analyses, genomic distribution of KAS-seq peaks, enrichment within gene-coding regions, and the Fraction of Reads in Peaks (FRiP) metric, were executed with the KAS-Analyzer package.
Deduplicated mapped KAS-seq reads were converted to bedGraph and bigWig using deeptools bamCoverage and UCSC tools.
Assembly: mm10
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.
Library strategy: KAS-seq


title: Mouse_lung_KAS-seq_Input, rep2


title: N2_IL1_B_S4

city: Buffalo

first: Jie

last: Yu

state: NY

address: 955 Main Street

department: Department of Obstetrics and Gynecology

institute: SUNY Buffalo

description: cell lysate were colleted for RNAseq analysis after IL-1β treatment 24 hours

data_processing:
Basecalling using bcl2fastq w/ default parameters
Alignments done using hisat2 v2.2.1 and samtools v1.16.1 command (provided in the readme.txt).
Quantification done using featureCounts v2.0.0 Command used: "featureCounts" "-T" "12" "-p" "-s" "2" "-t" "exon" "-g" "gene_name" "-a" "/projects/academic/gbcstaff/igenome-041714/Homo_sapiens/NCBI/GRCh38/Annotation/Genes/genes.gtf" "-Q" "60" "-o" "Taylor_RT2323_featureCounts.tsv" "-B" "-C" "E5_C_S5.sorted.bam" "E5_IL1_B_S6.sorted.bam" "E9_C_S7.sorted.bam" "E9_IL1_B_S8.sorted.bam" "N1_C_S1.sorted.bam" "N1_IL1_B_S3.sorted.bam" "N2_C_S2.sorted.bam" "N2_IL1_B_S4.sorted.bam"
Assembly: GRCh38
Supplementary files format and content: Feature count gene quantification is in a tab separated file.

source_name: human endometrium biopsy

extract_protocol:
Trizol
TruSeq Stranded RNA Library Preparation

value: human endometrium biopsy

value: primary human endometrial stromal cells

value: recombinate IL-1β


title: rep2 Ctrl-

value: Ctrl -DM


title: WiT49, actD, 6hr, rep1

value: Wilms tumor


title: rep1 H2O+


title: Mouse_lung_opti-KAS-seq_Input, rep1

value: Lung

value: Mouse Lung


title: ACC.etr17.24h.R2.R1


title: Mouse_lung_KAS-seq, rep1

value: WT

value: No treatment


title: N1_IL1_B_S3


title: Mouse_lung_KAS-seq, rep2


title: N2_C_S2

description: control

value: Control


title: ACC.etr17.24h.R3.R1


title: N1_C_S1

description: control


title: Mouse_heart_opti-KAS-seq_Input, rep2

source_name: Heart

value: Heart

value: Mouse heart


title: WiT49, actD, 6hr, rep3


title: Mouse_heart_opti-KAS-seq_Input, rep1


title: ACC.etr17.1h.R3.R1

value: ACC, 1uM


title: rep1 EtOH+

value: EtOH +DM


title: ACC.etr17.1h.R4.R1


title: HEK293T_cell_cycle_S_KAS-seq_Input, rep2

data_processing:
To align Opti-KAS-seq and KAS-seq data to the reference genome of interest, we utilized the trim_galore package to trim off low-quality sequence, adaptor sequence and primer sequence from single-end or paired-end raw fastq files
Subsequently, we employed bowtie2 to perform the read alignment of Opti-KAS-seq and KAS-seq data. Mapped reads in sam files from the aligners are sorted and converted to bam files using ‘samtools sort’, which are subsequently deduplicated using ‘picard MarkDuplicates’ (pair-end data) or ‘samtools rmdup’ (single-end data).
For single-end Opti-KAS-seq or KAS-seq data, mapped reads were extended to 150bp as default, irrespective of the initial sequencing data's read length. For paired-end KAS-seq data, the KAS-Analyzer incorporates a Python script, facilitating the merging of "properly paired" mapped reads into a singular interval
Peak calling for broad KAS-seq was executed using epic2, which identified broad peaks maintaining a false discovery rate (FDR) of 0.05 and a 1.5-fold change relative to the Input. Comprehensive quality control measures, such as library complexity metrics, inter-replicate correlation analyses, fingerprint plots, saturation analyses, genomic distribution of KAS-seq peaks, enrichment within gene-coding regions, and the Fraction of Reads in Peaks (FRiP) metric, were executed with the KAS-Analyzer package.
Deduplicated mapped KAS-seq reads were converted to bedGraph and bigWig using deeptools bamCoverage and UCSC tools.
Assembly: hg19
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.
Library strategy: KAS-seq

growth_protocol: HEK293T cells were purchased from ATCC (CRL11268) and were cultured in DMEM (Gibco 11995) supplemented with 10% (v/v) fetal bovine serum (Gibco), 1% penicillin and streptomycin (Gibco) and grown at 37 °C with 5% CO2.

value: Human embryonic kidney


title: rep1 Ctrl+

value: Ctrl +DM


title: ACC.etr17.1h.R2.R1


title: Mouse_heart_opti-KAS-seq, rep2


title: HEK293T_cell_cycle_S_KAS-seq_Input, rep1


title: rep1 H2O-

value: H2O -DM


title: ACC.etr17.0h.R4.R1


title: rep1 42oC+

value: 42oC +DM


title: ACC.etr17.0h.R3.R1


title: HEK293T_cell_cycle_G1_KAS-seq_Input, rep2


title: rep1 42oC-

value: 42oC -DM


title: Mouse_heart_KAS-seq_Input, rep2


title: HEK293T_cell_cycle_S_KAS-seq


title: rep1 Ctrl-


title: ACC.etr17.0h.R2.R1


title: HEK293T_cell_cycle_G1_KAS-seq_Input, rep1


title: HEK293T_cell_cycle_G1_KAS-seq, rep2


title: Mouse_heart_KAS-seq_Input, rep1


title: ACC.etr13.4h.R3.R1


title: Mouse_heart_KAS-seq, rep2


title: ACC.etr13.4h.R4.R1


title: HEK293T_cell_cycle_G1_KAS-seq, rep1


title: Mouse_heart_KAS-seq, rep1


title: rep2 SVWT1 42oC


title: ACC.etr13.4h.R2.R1


title: MSH2KO

city: Bloomington

first: Ahmed

middle: H

last: Ghobashi

state: IN

institute: Indiana University

description: 10x Genomics

data_processing:
Read alignment and gene-expression quantification of mouse scRNA-seq data was performed using the CellRanger Count pipeline (version 6.1.2, 10X Genomics)
Cells were filtered to include only cells with no more than 20% mitochondrial gene expression and doublets were removed using DoubletFinder. The data were normalized, and highly variable genes were identified and scaled using SCTransform. Next, dimensionality reduction by principal components (PCs) was calculated using RunPCA and to estimate the significant number of PCs to be used ElbowPlot function was used. Next, the uniform manifold approximation and projection (UMAP) embedding were calculated and visualized using RunUMAP and DimPlot. Unsupervised Louvain clustering was carried out using FindNeighbors and FindClusters.
In our analysis (Seurat_colon_1.RDS), we used Seurat v4.3.0.1 to perform batch-effect correction. 3000 highly variable genes were defined within the 4 mouse samples with the Seurat FindVariableFeatures function. We also identified unsupervised integration “anchors” for similar cell states using shared nearest neighbor graphs (FindIntegrationAnchors), and then integrated our 4 different datasets using these anchors using IntegrateData. The output was then transformed into principal component analysis (PCA) space for further evaluation and visualization
Assembly: mm10
Supplementary files format and content: RDS file

source_name: colon

extract_protocol:
To obtain single cell solutions of tumor cells, pooled distal (Min, MSH2KO), distal and proximal (BLM) or proximal (BLM2) tumors were washed in HBSS, incubated in 0.25% trypsin-EDTA for 10 minutes at 37oC, followed by the addition of FBS to inactivate the trypsin. Next, the tumors were digested by incubation in liberase TM (0.05 mg/ml; Roche, #05401119001)+DNAse (0.2 mg/ml) in DMEM at 37oC for 2H while rotating. Following washing in HBSS and an additional incubation in 0.25% trypsin-EDTA for 10 minutes at 37oC, cells were resuspended in DMEM+10%FBS and filtered through a 40 mM mesh cell strainer. Cells were then washed with DPBS+0.1% BSA and viable cells were counted. Cells were resuspended at 1,000 cell per ml in DPBS+0.1% BSA
All single cell preparations used for sequencing had a viability of > 80%. 10,000 cells per sample were targeted for input to the 10X Genomics Chromium system using the Chromium Next GEM Single Cell 30 Kit v3.1 at the Indiana University School of Medicine (IUSM) Center for Medical Genomics core

tag: disease

value: colon tumor

tag: group

value: colon


title: HEK293T_PBS_labeling_KAS-seq, rep2


title: rep1 SVWT1 42oC


title: Min

description: 10x Genomics

value: Min


title: rep3 SVWT1 EtOH

value: EtOH


title: rep1 EtOH-

value: EtOH -DM


title: HEK293T_PBS_labeling_KAS-seq, rep1

value: WT


title: ACC.etr13.24h.R3.R1


title: rep2 SVWT1 EtOH


title: HEK293T_opti-KAS-seq, rep2

data_processing:
To align Opti-KAS-seq and KAS-seq data to the reference genome of interest, we utilized the trim_galore package to trim off low-quality sequence, adaptor sequence and primer sequence from single-end or paired-end raw fastq files
Subsequently, we employed bowtie2 to perform the read alignment of Opti-KAS-seq and KAS-seq data. Mapped reads in sam files from the aligners are sorted and converted to bam files using ‘samtools sort’, which are subsequently deduplicated using ‘picard MarkDuplicates’ (pair-end data) or ‘samtools rmdup’ (single-end data).
For single-end Opti-KAS-seq or KAS-seq data, mapped reads were extended to 150bp as default, irrespective of the initial sequencing data's read length. For paired-end KAS-seq data, the KAS-Analyzer incorporates a Python script, facilitating the merging of "properly paired" mapped reads into a singular interval
Peak calling for broad KAS-seq was executed using epic2, which identified broad peaks maintaining a false discovery rate (FDR) of 0.05 and a 1.5-fold change relative to the Input. Comprehensive quality control measures, such as library complexity metrics, inter-replicate correlation analyses, fingerprint plots, saturation analyses, genomic distribution of KAS-seq peaks, enrichment within gene-coding regions, and the Fraction of Reads in Peaks (FRiP) metric, were executed with the KAS-Analyzer package.
Deduplicated mapped KAS-seq reads were converted to bedGraph and bigWig using deeptools bamCoverage and UCSC tools.
Assembly: hg19
Supplementary files format and content: bed, peaks list.
Supplementary files format and content: bigWig, read density.
Library strategy: Opti-KAS-seq

value: No treatment


title: BLM2

description: 10x Genomics


title: ACC.etr13.24h.R2.R1


title: rep3 SVWT1 42oC


title: HEK293T_opti-KAS-seq, rep1


title: ACC.etr13.1h.R4.R1


title: blood  leukocyte, CIA model 3,Non-irradiation3

city: xi'an

first: Qi

last: Zhang

address: No. 28 Xianning West Road

institute: Xi’an Jiaotong University

data_processing:
Illumina bcl2fastq 2.0 software used for basecalling.
Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to mm10 whole genome using HISAT2
Transcript abundance values were obtained from gene-level count matrices were generated by StringTie
Gene counts were normalized using geometric mean in DESeq2 package
Differential gene expression by DEseq2 was performed on normalized gene counts
Assembly: Genome_build: mm10
Supplementary files format and content: Supplementary_files_format_and_content: tab-delimited text file includes gene abundance for samples
Supplementary files format and content: Supplementary_files_format_and_content:  excel file includes gene abundance for samples

source_name: blood leukocyte

extract_protocol:
Total blood RNA samples were extracted using the TruSeq RNA Sample Preparation Kit V2 (Illumina, USA) in strict accordance with the manufacturer's instructions.
A library was constructed on the Illumina HiSeq 2500 (Illumina Inc., San Diego, CA) platform and RNA-sequencing procedures were performed in a 2×150 bp paired-end sequencing mode and obtained FastQ data

value: blood leukocyte

tag: Sex

value: male

tag: age

value: CIA model,Non-irradiation


title: BLM

description: 10x Genomics

value: BLM


title: ACC.etr13.1h.R3.R1

data_processing:
FastQC v0.11.8 and MultiQC v1.7 were used for assessing read quality.
Adaptors were trimmed from reads using CutAdapt v1.18, and reads trimmed to less than 25bp were removed.
Trimmed reads were then processed with the BBMap tool BBDuk to identify and remove rRNA contamination.
Read quantification was performed directly on the processed fastq files with the Salmon v0.12.0 “quant” algorithm in mapping mode using the “--validateMapping” flag, setting the library type to “IU”.
Counts were imported into R v3.6.0 using the tximport R package v1.12.3 and summarized to the gene level.
Genome_build: TAIR10 reference transcriptome
Supplementary_files_format_and_content: Contains raw read counts from Salmon summarized to the gene level in a tab-delimited format.  No normalization or other transformations were done to the processed data for this submission.  Raw fastq files are original and unprocessed.

value: ACC, 1uM

tag: time point


title: HEK293T_KAS-seq, rep1

value: Human embryonic kidney


title: rep1 SVWT1 EtOH


title: HEK293T_KAS-seq, rep2


title: blood  leukocyte, CIA model 2,Non-irradiation2


title: blood  leukocyte, CIA model 1,Non-irradiation1


title: rep3 SVWT1 Ctrl

value: Ctrl


title: ACC.etr13.1h.R2.R1

tag: biological replicate


title: rep1 SVWT1 Ctrl