title: 4tU-seq_1-NA-PP1_HeatShock_rep1

city: Göttingen

first: Eusra

last: Mohammad

address: Am Faßberg 11

country: Germany

institute: Max Planck Institute for Biophysical Chemistry

description: cerevisiae.feature.orfs.raw.htseq.counts.txt

data_processing:
The raw fastq files of paired-end 75 base reads (for steady state experiment) and 42 base reads (for heat shock experiment) with additional 6 base reads of barcodes were obtained for each of the samples. Reads were demultiplexed and low quality bases (<Q20) removed using Cutadapt (version 1.9.1) with parameters -q 20,20 -o 12 -m 25.
Reads were then mapped to the S. cerevisiae genome (sacCer3, version 64.2.1) using STAR 2.5.2b with parameters -- outFilterMismatchNmax 2 --outFilterMultimapScoreRange 0. Samtools was used to quality filter SAM files. Alignments with MAPQ smaller than 7 (−q 7) were skipped and only proper pairs (−f 2) were selected.
A spike-in (RNAs) normalization strategy was used to allow for observation of global changes in the 4tUSeq signal. Sequencing depth from spike-in RNAs was calculated for each sample j as the median of the ratio read counts kij for the labelled spikeins i in sample j : the length of labelled spike-ins i for the 4tU-seq samples.
Read counts for protein-coding genes (using TIF-seq derived TSS and pA site annotations for 4,928 protein-coding genes and spike-ins were calculated using HTSeq after mapping. Further processing of the 4tU-Seq data was carried out using the R/Bioconductor environment.
Differential gene expression analysis was performed with the DESeq2 package using the spike-in derived normalization factors.
Genome_build: sacCer3 (Saccharomyces Genome Database (SGD) http://sgd-archive.yeastgenome.org/sequence/S288C_reference/genome_releases/)
Supplementary_files_format_and_content: Saccharomyces cerevisiae features (protein-coding genes/ORF-T) for the analysis
Supplementary_files_format_and_content: tab-delimited text file for raw counts for every Saccharomyces cerevisiae features and every sample
Supplementary_files_format_and_content: tab-delimited text files for normatisation factors for differential expression analysis calculated from spike ins for each comparable condition and each replicates
Supplementary_files_format_and_content: tab-delimited text files for normalised counts for every Saccharomyces cerevisiae feature for differential expression analysis for each comparable condition and each replicates
Supplementary_files_format_and_content: tab-delimited text files for results of differential expression analysis
Supplementary_files_format_and_content: text files for heat shock response genes and corresponding ids
Supplementary_files_format_and_content: text files for induced heat shock response genes and corresponding ids from differential expression analysis

organism: Saccharomyces cerevisiae

source_name: Srb10-as1 yeast cell culture

growth_protocol: Srb10-as1 cultures inoculated at a starting OD600 of 0.1 and grown until an OD600 of 0.8 was reached in YPD-Trp growth media at 30°C.

extract_protocol:
4tU-seq as in (Xu et al., 2017)
Libraries were constructed using the Ovation Universal RNA-Seq System (NuGen) according to the manufacturer's protocol starting with 100 ng RNA as input for all samples.

treatment_protocol: 1-NA-PP1 to a final concentration of 6µM or the same volume of DMSO were added to the cultures (as indicated) in 2 replicates, and incubated for 12 minutes. For the heat shock samples, this was followed by 12 minutes of heat shock at 37°C. Samples were then labelled by adding 4-thiouridine (4tU) to a final concentration of 5 mM for 5 minutes.

value: Mat [alpha], [delta] ade2::hisG, his3[delta]200, leu2[delta]0, lys2[delta]0, met15[delta]0, trp1[delta]63, ura3[delta]0, srb10[delta]::KanMX, pSH599 (ars cen TRP1 srb10as-1 (Y236G))

value: 1-NA-PP1/heat shock at 37°C

tag: molecule

value: 4tU-labelled RNA


title: RHH4675 scRNA-Seq

status: Public on Jun 16 2021

type: SRA

city: Singapore

first: Florent

last: Ginhoux

address: 8A Biomedical Grove, Immunos Building, Level 3

country: Singapore

institute: Singapore Immunology Network (SIgN), A*STAR

library_source: transcriptomic

data_processing:
Raw reads were aligned to the human reference genome GRCh38 from GENCODE using RSEM program version 1.3.0 with default parameters. Gene expression values in transcripts per million (TPM) were calculated using the same RSEM program and the human GENCODE annotation version 25.
Genome_build: GRCh38.p7
Supplementary_files_format_and_content: Tab-delimited text files include TPM values for each Sample

molecule: polyA RNA

organism: Homo sapiens

source_name: Human Healthy Liver

extract_protocol:
Cells isolated from organs were indexed-sorted using the Indexed-sorting panel on a BD FACSARIAIII (BD Biosciences) into 96 well plates containing 3 µL Lysis buffer using a 70 µm nozzle
Single cell cDNA libraries were made using the SMARTSeq v2 protocol (Picelli et al., 2014) with the following modification: Use of 200 pg cDNA with 1/5 reaction of Illumina Nextera XT kit (Illumina, San Diego, CA, USA). All samples were subjected to an indexed paired-end sequencing run of 2x151 cycles on an Illumina HiSeq 4000 system (Illumina, San Diego, CA, USA) (300 samples/lane).

tag: tissue

value: Human Healthy Liver

tag: cell type

value: dendritic cells and monocytes


title: RHH4672 scRNA-Seq


title: 4tU-seq_DMSO_HeatShock_rep2

molecule: total RNA

tag: genotype

tag: treatment

value: DMSO/heat shock at 37°C


title: 4tU-seq_DMSO_HeatShock_rep1


title: 4tU-seq_1-NA-PP1_HeatShock_rep2


title: RHH4673 scRNA-Seq


title: RHH4671 scRNA-Seq


title: 4tU-seq_DMSO_SteadyState_rep1

value: DMSO


title: 4tU-seq_1-NA-PP1_SteadyState_rep2


title: RHH4670 scRNA-Seq


title: RHH4669 scRNA-Seq


title: 4tU-seq_1-NA-PP1_SteadyState_rep1


title: RHH4668 scRNA-Seq


title: RHH4667 scRNA-Seq


title: RHH4678 scRNA-Seq


title: RHH4666 scRNA-Seq


title: RHH4665 scRNA-Seq


title: RHH4664 scRNA-Seq


title: RHH4663 scRNA-Seq


title: 4tU-seq_DMSO_SteadyState_rep2


title: RHH4662 scRNA-Seq


title: RHH4659 scRNA-Seq


title: RHH4660 scRNA-Seq


title: RHH4658 scRNA-Seq


title: RHH4661 scRNA-Seq


title: RHH4657 scRNA-Seq


title: RHH4656 scRNA-Seq


title: RHH4655 scRNA-Seq


title: RHH4654 scRNA-Seq


title: RHH4652 scRNA-Seq


title: ΔwhiB4 infected kidney_rep1

city: Shanghai

first: Chen

last: Lin

address: NO.2005 Songhu road

country: China

institute: Fudan university

data_processing:
High-throughput sequencing was carried out on an Illumina NovaSeq 6000 system according to the  manufacturer’s instructions (Illumina HiSeq 6000 User Guide)
The raw reads were fltered by Seqtk and then mapped to the Danio rerio (zebrafish) reference sequence (Ensembl GRCz11.100) using Hisat2
Counting of reads per gene was performed using HTSeq followed by TMM (trimmed mean of M-values) normalization
Genome_build: Danio rerio (zebrafish) reference sequence (Ensembl GRCz11.100)
Supplementary_files_format_and_content: Excel file include FPKM values for all  genes

organism: Danio rerio

source_name: Kidney

extract_protocol:
For RNA extraction of zebrafish kidneys, the samples were removed from RNA-Be-Locker A Reagent by centrifugation and added with 1ml TRIZOL for lysis. The insoluble tissues were removed by centrifugation and supernatants were collected and added with equal volume ethanol. The RNA was then extracted using the Tianmo#TR205-200 kit.
RNA libraries were prepared for sequencing using standard Illumina protocols

tag: strain

value: AB wild type

tag: infection

value: ΔwhiB4 M.marinum

value: Kidney


title: ΔwhiB4 infected kidney_rep2


title: WT infected kidney_rep3

value: wild type M.marinum


title: WT infected kidney_rep2


title: hESC_cont_24h_rep1

type: RNA

city: Giessen

first: Jochen

last: Wilhelm

state: Hessen

address: Aulweg 132

department: Institute for Lung Health

institute: Justus-Liebig University Giessen

hyb_protocol: Hybridization was performed following the Agilent protocol at 65Â°C over-night in an in-situ hybridization oven with slides mounted in Agilent hybridization chambers. Slides were rotated with 2 rpm.

scan_protocol: Slides were scanned using the InnoScan 900 scanner (Innopsys, Carbonne France) at 2 Âµm/pixel resolution and analyzed with Mapix 6.5.0

data_processing: Raw data was further processed using R (http://www.R-project.org) and limma (Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. NAR 43(7), e47). Background correction was performed with the normexp model using negative control spots and and offset of 1. Spot intensities were quantile normalized between arrays.

source_name: Cell line, hES3 NKX2.1-eGFP and FK15 NKX2.1-eGFP cell lines

label_protocol: Purified total RNA was amplified using the Agilent Low-Input QuickAmp Kit (Agilent, Waldbronn, Germany).

growth_protocol: Cells were grown in Stemdiff Basal Medium. The cells required 14 days to differentiate prior to the beginning of the experiment. The induced differentiation of the cells was accomplished following a protocol from Huang et al., 2013.

extract_protocol: QIAgen miRNeasy mini kit

treatment_protocol: After expression of NKX2.1, cells were reseeded in a basal medium with CHIR99021 (3µM) and BMP4 (10 ng/mL). Experimental samples had recombinant FGF10 (250 ng/mL) added to the medium. After either 12 hrs or 24 hrs, the samples were harvested and placed immediately in lysis buffer.

value: hESC

value: control

tag: time


title: ΔwhiB4 infected kidney_rep3


title: hiPSC_FGF10_12h_rep1

value: hiPSC


title: hESC_FGF10_24h_rep1


title: hESC_FGF10_12h_rep1


title: hESC_cont_12h_rep1


title: hiPSC_FGF10_24h_rep1


title: RHH4651 scRNA-Seq


title: hiPSC_cont_12h_rep1


title: Batch3_Lane3

city: Chicago

first: Katherine

last: Rhodes

state: IL

address: 5841 South Maryland Avenue, MC 6092

department: Genetic Medicine

country: USA

institute: University of Chicago

description:
cell_metadata.txt
cell_counts.mtx

data_processing:
Transcripts were aligned to GRCh38 using STARsolo (Dobin et al. 2013)
Demuxlet (Kang et al. 2018) was used to demultiplex the pooled single cell data, and assign each cell a probability that the cell was a doublet as well as a maximum likelihood donor (cell line) assignment
Cells were filtered to include only singlets called by Demuxlet (Kang et al. 2018), cells unlikely to be empty droplets called by EmptyDrops (Lun et al. 2019), cells containing between 3%-20% mitochondrial reads, and cells expressing more than 1,500 genes
Genome_build: GRCh38
Supplementary_files_format_and_content: cell_counts.mtx contains a genesxcells matrix with raw UMI counts for each cell (in the MatrixMarket format)
Supplementary_files_format_and_content: genes.tsv contains the gene names corresponding to the counts matrix (row names for cell_counts.mtx)
Supplementary_files_format_and_content: barcodes.tsv contains the barcodes corresponding to the count matrix (column names for cell_counts.mtx)
Supplementary_files_format_and_content: cell_metadata.txt contains metadata fror each cells. Rows are cells, columns are nCount_RNA (total UMI counts for each cells), nFeature_RNA (total genes per cell), individual, Rep_Lane(the 10X lane corresponding the the library in a particular replicate), replicate, and Seurat Cluster assignments across clustering resolutions.

source_name: iPSC-derived embryoid bodies

growth_protocol: Feeder-free iPSC cultures were maintained on Matrigel Growth Factor Reduced Matrix with Essential 8 Medium and Penicillin/Streptomycin.

extract_protocol:
We harvested and dissociated EBs 21 days after formation. We collected scRNA-seq data using the 10X Genomics V3.0 kit.
Libraries were generated using the 10X Genomics V3.0 kit. Libraries from each Batch of 10X sequencing were processing in parallel. Libraries were sequenced using paired-end 100 base pair sequencing on the HiSeq 4000.

treatment_protocol: We formed EBs using a modified version of the STEMCELL Aggrewell400 protocol. After 24 hours, we replaced half of the spent media with fresh Aggrewell EB Formation Medium. 48 hours after seeding the Aggrewell plate, we harvested EBs and moved them to an ultra-low attachment 6-well plate in E6 media. We maintained EBs in culture for an additional 19 days, replacing media with fresh E6 every 48 hours.

tag: cell line

value: multiplexed sampled (pool of 18858, 18511, 19160)

tag: replicate

tag: 10x lane


title: Batch3_Lane2

description:
cell_metadata.txt
cell_counts.mtx


title: Batch3_Lane4

description:
cell_metadata.txt
cell_counts.mtx


title: Batch3_Lane1

description:
cell_metadata.txt
cell_counts.mtx


title: Batch2_Lane4

description:
cell_metadata.txt
cell_counts.mtx


title: Batch2_Lane3

description:
cell_metadata.txt
cell_counts.mtx


title: WT infected kidney_rep1


title: RHH4649 scRNA-Seq


title: Batch2_Lane1

description:
cell_metadata.txt
cell_counts.mtx


title: RHH4653 scRNA-Seq


title: RHH4648 scRNA-Seq


title: Batch1_Lane9

description:
cell_metadata.txt
cell_counts.mtx


title: hiPSC_cont_24h_rep1


title: RHH4646 scRNA-Seq


title: RHH4647 scRNA-Seq


title: Batch1_Lane8

description:
cell_metadata.txt
cell_counts.mtx


title: RHH4645 scRNA-Seq


title: RHH4650 scRNA-Seq


title: Batch2_Lane2

description:
cell_metadata.txt
cell_counts.mtx


title: Batch1_Lane7

description:
cell_metadata.txt
cell_counts.mtx


title: RHH4643 scRNA-Seq


title: Batch1_Lane4

description:
cell_metadata.txt
cell_counts.mtx


title: RHH4642 scRNA-Seq


title: Batch1_Lane5

description:
cell_metadata.txt
cell_counts.mtx


title: Batch1_Lane3

description:
cell_metadata.txt
cell_counts.mtx


title: RHH4640 scRNA-Seq


title: RHH4639 scRNA-Seq


title: RHH4637 scRNA-Seq


title: Batch1_Lane6

description:
cell_metadata.txt
cell_counts.mtx


title: RHP7569 scRNA-Seq

source_name: Human Healthy Tonsil

value: Human Healthy Tonsil


title: RHH4641 scRNA-Seq


title: Batch1_Lane1

description:
cell_metadata.txt
cell_counts.mtx


title: RHH4638 scRNA-Seq


title: RHP7568 scRNA-Seq


title: RHH4636 scRNA-Seq


title: RHP7571 scRNA-Seq


title: RHH4644 scRNA-Seq


title: RHP7567 scRNA-Seq


title: RHH4634 scRNA-Seq


title: RHH4635 scRNA-Seq


title: RHH4633 scRNA-Seq


title: RHP7566 scRNA-Seq


title: RHH4632 scRNA-Seq


title: RHP7564 scRNA-Seq


title: RHP7565 scRNA-Seq


title: RHP7570 scRNA-Seq


title: RHP7563 scRNA-Seq


title: RHP7562 scRNA-Seq


title: RHH4630 scRNA-Seq


title: RHH4628 scRNA-Seq


title: RHH4629 scRNA-Seq


title: RHP7561 scRNA-Seq


title: RHP7560 scRNA-Seq


title: RHP7558 scRNA-Seq


title: RHH4626 scRNA-Seq


title: RHP7559 scRNA-Seq


title: RHH4627 scRNA-Seq


title: RHP7556 scRNA-Seq


title: RHH4625 scRNA-Seq


title: RHH4623 scRNA-Seq


title: RHH4624 scRNA-Seq


title: RHH4622 scRNA-Seq


title: RHP7553 scRNA-Seq


title: RHH4620 scRNA-Seq


title: RHP7552 scRNA-Seq


title: RHH4619 scRNA-Seq


title: RHH4631 scRNA-Seq


title: RHH4618 scRNA-Seq


title: RHP7550 scRNA-Seq


title: RHP7549 scRNA-Seq


title: RHH4617 scRNA-Seq


title: RHH4614 scRNA-Seq


title: RHP7557 scRNA-Seq


title: RHH4615 scRNA-Seq


title: RHH4616 scRNA-Seq


title: RHP7548 scRNA-Seq


title: RHP7554 scRNA-Seq


title: RHH4621 scRNA-Seq


title: RHP7546 scRNA-Seq


title: RHP7544 scRNA-Seq


title: RHP7555 scRNA-Seq


title: RHH4611 scRNA-Seq


title: RHH4613 scRNA-Seq


title: RHH4612 scRNA-Seq


title: RHH4609 scRNA-Seq


title: RHP7542 scRNA-Seq


title: RHP7543 scRNA-Seq


title: RHP7551 scRNA-Seq


title: RHP6537 scRNA-Seq

source_name: Human Peripheral Blood

value: Human Peripheral Blood


title: RHP7541 scRNA-Seq


title: RHH4608 scRNA-Seq


title: RHH4607 scRNA-Seq


title: RHP6536 scRNA-Seq


title: RHH4606 scRNA-Seq


title: RHP6535 scRNA-Seq


title: RHH4605 scRNA-Seq


title: RHP6534 scRNA-Seq


title: RHP7547 scRNA-Seq


title: RHP7545 scRNA-Seq


title: RHP6532 scRNA-Seq


title: RHH4604 scRNA-Seq


title: RHP6531 scRNA-Seq


title: RHP6533 scRNA-Seq


title: RHH4603 scRNA-Seq


title: RHH4601 scRNA-Seq


title: RHP6529 scRNA-Seq


title: RHH4599 scRNA-Seq


title: RHH4610 scRNA-Seq


title: RHH4602 scRNA-Seq


title: RHP6530 scRNA-Seq


title: RHH4598 scRNA-Seq


title: RHH4600 scRNA-Seq


title: RHP6528 scRNA-Seq


title: RHH4596 scRNA-Seq


title: RHH4597 scRNA-Seq


title: RHP6527 scRNA-Seq


title: RHP6525 scRNA-Seq


title: RHP6526 scRNA-Seq


title: RHP6524 scRNA-Seq


title: RHH4594 scRNA-Seq


title: RHP6523 scRNA-Seq


title: RHH4593 scRNA-Seq


title: RHP6522 scRNA-Seq


title: RHH4591 scRNA-Seq


title: RHH4589 scRNA-Seq


title: RHP6518 scRNA-Seq


title: RHP6516 scRNA-Seq


title: RHH4587 scRNA-Seq


title: RHP6517 scRNA-Seq


title: RHP6514 scRNA-Seq


title: RHP6519 scRNA-Seq


title: RHH4584 scRNA-Seq


title: RHH4585 scRNA-Seq


title: RHP6513 scRNA-Seq


title: RHH4583 scRNA-Seq


title: RHH4595 scRNA-Seq


title: RHH4582 scRNA-Seq


title: RHP6511 scRNA-Seq


title: RHP6510 scRNA-Seq


title: RHH4581 scRNA-Seq


title: RHH4586 scRNA-Seq


title: RHP6521 scRNA-Seq


title: RHH4580 scRNA-Seq


title: RHP6520 scRNA-Seq


title: RHP6508 scRNA-Seq


title: RHH4578 scRNA-Seq


title: RHH4579 scRNA-Seq


title: RHH4588 scRNA-Seq


title: RHH4590 scRNA-Seq


title: RHP6507 scRNA-Seq


title: RHH4576 scRNA-Seq


title: RHP6505 scRNA-Seq


title: RHH4574 scRNA-Seq


title: RHP6515 scRNA-Seq


title: RHP6504 scRNA-Seq


title: RHH4573 scRNA-Seq


title: RHP6503 scRNA-Seq


title: RHP6502 scRNA-Seq


title: RHP6501 scRNA-Seq


title: RHH4570 scRNA-Seq


title: RHP6500 scRNA-Seq


title: RHH4571 scRNA-Seq


title: RHH4568 scRNA-Seq


title: RHP6499 scRNA-Seq


title: RHP6498 scRNA-Seq


title: RHH4569 scRNA-Seq


title: RHP6496 scRNA-Seq


title: RHH4567 scRNA-Seq


title: RHH4577 scRNA-Seq


title: RHP6506 scRNA-Seq


title: RHP6495 scRNA-Seq


title: RHH4566 scRNA-Seq


title: RHH4565 scRNA-Seq


title: RHP6494 scRNA-Seq


title: RHH4564 scRNA-Seq


title: RHP6493 scRNA-Seq


title: RHH4572 scRNA-Seq


title: RHH4562 scRNA-Seq


title: RHH4561 scRNA-Seq


title: RHP6491 scRNA-Seq


title: RHH4560 scRNA-Seq


title: RHP6490 scRNA-Seq


title: RHH4559 scRNA-Seq


title: RHP6489 scRNA-Seq


title: RHH4557 scRNA-Seq


title: RHP6487 scRNA-Seq


title: RHH4563 scRNA-Seq


title: RHH4558 scRNA-Seq


title: RHP6488 scRNA-Seq


title: RHP6492 scRNA-Seq


title: RHP6485 scRNA-Seq


title: RHP6486 scRNA-Seq


title: RHH4556 scRNA-Seq


title: RHH4555 scRNA-Seq


title: RHP6484 scRNA-Seq


title: RHH4554 scRNA-Seq


title: RHH4553 scRNA-Seq


title: RHP6482 scRNA-Seq


title: RHP6483 scRNA-Seq


title: RHH4552 scRNA-Seq


title: RHP6481 scRNA-Seq


title: RHP6497 scRNA-Seq


title: RHH4551 scRNA-Seq


title: RHP6480 scRNA-Seq


title: RHP6479 scRNA-Seq


title: RHH4575 scRNA-Seq


title: RHP6478 scRNA-Seq


title: RHH4549 scRNA-Seq


title: RHH4548 scRNA-Seq


title: RHP6477 scRNA-Seq


title: RHH4547 scRNA-Seq


title: RHP6476 scRNA-Seq


title: RHP6475 scRNA-Seq


title: RHP6473 scRNA-Seq


title: RHP6474 scRNA-Seq


title: RHP6472 scRNA-Seq


title: RHH4543 scRNA-Seq


title: RHP6470 scRNA-Seq


title: RHH4542 scRNA-Seq


title: RHP6471 scRNA-Seq


title: RHH4541 scRNA-Seq


title: RHH4544 scRNA-Seq


title: RHP6469 scRNA-Seq


title: RHP6468 scRNA-Seq


title: RHH4539 scRNA-Seq


title: RHH4550 scRNA-Seq


title: RHH4538 scRNA-Seq


title: RHP6467 scRNA-Seq


title: RHP6466 scRNA-Seq


title: RHH4546 scRNA-Seq


title: RHH4545 scRNA-Seq


title: RHP6465 scRNA-Seq


title: RHH4535 scRNA-Seq


title: RHH4537 scRNA-Seq


title: RHH4534 scRNA-Seq


title: RHH4533 scRNA-Seq


title: RHP6462 scRNA-Seq


title: RHH4531 scRNA-Seq


title: RHP6461 scRNA-Seq


title: RHH4532 scRNA-Seq


title: RHH4530 scRNA-Seq


title: RHP6463 scRNA-Seq


title: RHH4540 scRNA-Seq


title: RHP6460 scRNA-Seq


title: RHP6459 scRNA-Seq


title: RHH4529 scRNA-Seq


title: RHP6458 scRNA-Seq


title: RHP6457 scRNA-Seq


title: RHH4527 scRNA-Seq


title: RHH4536 scRNA-Seq


title: RHP6456 scRNA-Seq


title: RHP6455 scRNA-Seq


title: RHH4526 scRNA-Seq


title: RHP6464 scRNA-Seq


title: RHH4525 scRNA-Seq


title: RHH4524 scRNA-Seq


title: RHP6453 scRNA-Seq


title: RHP6452 scRNA-Seq


title: RHH4522 scRNA-Seq


title: RHP6454 scRNA-Seq


title: RHP6451 scRNA-Seq


title: RHH4521 scRNA-Seq


title: RHH4520 scRNA-Seq


title: RHH4519 scRNA-Seq


title: RHP6450 scRNA-Seq


title: RHP6449 scRNA-Seq


title: RHP6448 scRNA-Seq


title: RHP6447 scRNA-Seq


title: RHH4518 scRNA-Seq


title: RHP6446 scRNA-Seq


title: RHH4517 scRNA-Seq


title: RHP6445 scRNA-Seq


title: RHH4516 scRNA-Seq


title: RHH4528 scRNA-Seq


title: RHP6512 scRNA-Seq


title: RHH4515 scRNA-Seq


title: RHP6444 scRNA-Seq


title: RHH4514 scRNA-Seq


title: RHH4513 scRNA-Seq


title: RHP6441 scRNA-Seq


title: RHP6442 scRNA-Seq


title: RHH4523 scRNA-Seq


title: RHH4511 scRNA-Seq


title: RHP6443 scRNA-Seq


title: RHH4512 scRNA-Seq


title: RHP6440 scRNA-Seq


title: RHH4510 scRNA-Seq


title: RHP6439 scRNA-Seq


title: RHP6438 scRNA-Seq


title: RHH4508 scRNA-Seq


title: RHP6437 scRNA-Seq


title: RHH4506 scRNA-Seq


title: RHP6436 scRNA-Seq


title: RHH4507 scRNA-Seq


title: RHP6435 scRNA-Seq


title: RHP6434 scRNA-Seq


title: RHH4505 scRNA-Seq


title: RHH4504 scRNA-Seq


title: RHP6433 scRNA-Seq


title: RHH4502 scRNA-Seq


title: RHP6432 scRNA-Seq


title: RHP6431 scRNA-Seq


title: RHP6430 scRNA-Seq


title: RHH4501 scRNA-Seq


title: RHP6428 scRNA-Seq


title: RHP6429 scRNA-Seq


title: RHP6427 scRNA-Seq


title: RHH4499 scRNA-Seq


title: RHH4500 scRNA-Seq


title: RHH4498 scRNA-Seq


title: RHH4497 scRNA-Seq


title: RHH4496 scRNA-Seq


title: RHH4509 scRNA-Seq


title: RHH4495 scRNA-Seq


title: RHP6425 scRNA-Seq


title: RHP6422 scRNA-Seq


title: RHP6424 scRNA-Seq


title: RHH4494 scRNA-Seq


title: RHH4493 scRNA-Seq


title: RHP6423 scRNA-Seq


title: RHH4503 scRNA-Seq


title: RHH4491 scRNA-Seq


title: RHH4592 scRNA-Seq


title: RHP6421 scRNA-Seq


title: RHP6419 scRNA-Seq


title: RHP6420 scRNA-Seq


title: RHH4490 scRNA-Seq


title: RHH4489 scRNA-Seq


title: RHP6418 scRNA-Seq


title: RHP6509 scRNA-Seq


title: RHH4488 scRNA-Seq


title: RHP6417 scRNA-Seq


title: RHP6426 scRNA-Seq


title: RHH4487 scRNA-Seq


title: RHH4486 scRNA-Seq


title: RHP6415 scRNA-Seq


title: RHP6414 scRNA-Seq


title: RHP6413 scRNA-Seq


title: RHH4484 scRNA-Seq


title: RHH4483 scRNA-Seq


title: RHP6416 scRNA-Seq


title: RHH4485 scRNA-Seq


title: RHH4492 scRNA-Seq


title: RHP6412 scRNA-Seq


title: RHH4482 scRNA-Seq


title: RHH4481 scRNA-Seq


title: RHP6410 scRNA-Seq


title: RHP6408 scRNA-Seq


title: RHH4480 scRNA-Seq


title: RHH4479 scRNA-Seq


title: RHP6409 scRNA-Seq


title: RHH4478 scRNA-Seq


title: RHH4476 scRNA-Seq


title: RHP6406 scRNA-Seq


title: RHP6405 scRNA-Seq


title: RHP6404 scRNA-Seq


title: RHP6407 scRNA-Seq


title: RHH4477 scRNA-Seq


title: RHH4474 scRNA-Seq


title: RHP6403 scRNA-Seq


title: RHP6402 scRNA-Seq


title: RHH4473 scRNA-Seq


title: RHH4471 scRNA-Seq


title: RHP6401 scRNA-Seq


title: RHP6400 scRNA-Seq


title: RHP6399 scRNA-Seq


title: RHP6398 scRNA-Seq


title: RHH4470 scRNA-Seq


title: RHH4469 scRNA-Seq


title: RHP6411 scRNA-Seq


title: RHH4468 scRNA-Seq


title: RHP6396 scRNA-Seq


title: RHH4467 scRNA-Seq


title: RHP6395 scRNA-Seq


title: RHH4466 scRNA-Seq


title: RHH4465 scRNA-Seq


title: RHP6394 scRNA-Seq


title: RHH4475 scRNA-Seq


title: RHP6393 scRNA-Seq


title: RHP6392 scRNA-Seq


title: RHH4462 scRNA-Seq


title: RHH4463 scRNA-Seq


title: RHP6391 scRNA-Seq


title: RHH4461 scRNA-Seq


title: RHP6390 scRNA-Seq


title: RHH4472 scRNA-Seq


title: RHH4460 scRNA-Seq


title: RHP6389 scRNA-Seq


title: RHP6388 scRNA-Seq


title: RHH4458 scRNA-Seq


title: RHP6387 scRNA-Seq


title: RHH4457 scRNA-Seq


title: RHP6386 scRNA-Seq


title: RHP6385 scRNA-Seq


title: RHH4456 scRNA-Seq


title: RHH4454 scRNA-Seq


title: RHP6397 scRNA-Seq


title: RHH4455 scRNA-Seq


title: RHH4453 scRNA-Seq


title: RHP6381 scRNA-Seq


title: RHH4451 scRNA-Seq


title: RHP6380 scRNA-Seq


title: RHP6383 scRNA-Seq


title: RHP6382 scRNA-Seq


title: RHP6384 scRNA-Seq


title: RHH4452 scRNA-Seq


title: RHP6378 scRNA-Seq


title: RHP6379 scRNA-Seq


title: RHH4450 scRNA-Seq


title: RHH4448 scRNA-Seq


title: RHP6376 scRNA-Seq


title: RHH4447 scRNA-Seq


title: RHH4446 scRNA-Seq


title: RHH4464 scRNA-Seq


title: RHP6375 scRNA-Seq


title: RHH4445 scRNA-Seq


title: RHH4444 scRNA-Seq


title: RHH4459 scRNA-Seq


title: RHH4443 scRNA-Seq


title: RHH4449 scRNA-Seq


title: RHP6371 scRNA-Seq


title: RHH4442 scRNA-Seq


title: RHH4441 scRNA-Seq


title: RHP6370 scRNA-Seq


title: RHP6377 scRNA-Seq


title: RHH4439 scRNA-Seq


title: RHH4440 scRNA-Seq


title: RHO1163 scRNA-Seq


title: RHO1161 scRNA-Seq


title: RHP6374 scRNA-Seq


title: RHH4438 scRNA-Seq


title: RHH4435 scRNA-Seq


title: RHO1162 scRNA-Seq


title: RHH4437 scRNA-Seq


title: RHP6373 scRNA-Seq


title: RHH4433 scRNA-Seq


title: RHO1157 scRNA-Seq


title: RHO1159 scRNA-Seq


title: RHH4434 scRNA-Seq


title: RHO1155 scRNA-Seq


title: RHO1156 scRNA-Seq


title: RHH4430 scRNA-Seq


title: RHH4432 scRNA-Seq


title: RHH4431 scRNA-Seq


title: RHO1154 scRNA-Seq


title: RHH4429 scRNA-Seq


title: RHP6372 scRNA-Seq


title: RHO1153 scRNA-Seq


title: RHH4428 scRNA-Seq


title: RHO1164 scRNA-Seq


title: RHH4436 scRNA-Seq


title: RHO1160 scRNA-Seq


title: PBMC_3167

type: genomic

city: Badalona, Barcelona

first: Esteban

last: Ballestar

state: N/A = Not Applicable

address: Ctra de Can Ruti, Camí de les Escoles s/n

country: Spain

institute: Josep Carreras Research Institute (IJC)

description: PBMCs

hyb_protocol: Bisulphite converted DNA was amplified, fragmented and hybridised to Illumina Infinium HumanMethylation450/HumanMethylationEPIC Beadchips using standard Illumina protocol.

scan_protocol: Arrays were imaged using BeadArray Reader using standard recommended Illumina scanner settings

data_processing:
Data was processed with the minfi package in R
Normalization was performed with the Illumina method (minfi)

label: Cy3, Cy5

molecule: genomic DNA

source_name: peripheral blood

label_protocol: Standard Illumina Protocol

extract_protocol: Genomic DNA was extracted and purified from PBMCs using the Maxwell RSC Cell DNA kit (Promega) according to standard instructions

tag: age

tag: Sex

value: M

tag: tender joints

tag: swollen joints

tag: esr

tag: crp

tag: rf

value: Negative

tag: pain

tag: disease activity

tag: wellbeing

value: validation

tag: diagnosis at bl

value: UA

tag: diagnosis at year = 1


title: RHO1152 scRNA-Seq

tag: tissue

tag: cell type

value: dendritic cells and monocytes


title: pPDsMMrSNxiNIH1d200516DAPI

city: Cambridge

first: Evan

last: Macosko

state: MA

address: 75 Ames St, Broad Institute

institute: Broad Institute

description:
Macaca_bcd.tsv.gz
Macaca_features.tsv.gz
Macaca_matrix.tsv.gz

data_processing:
Sequencing was performed on either Illumina NovaSeq6000 or Illumina NextSeq
All sequencing reads from substantia nigra samples were demultiplexed and aligned to their respective animal genomes using Drop-Seq Tools
Digital gene expression matrices for all substantia nigra samples were generated from Drop-Seq Tools after alignment with the following genomes per species: human (hg19), rat (Rnor_6.0), macaque (Mmul_10), Tree shrew (tupBel1)
Digital gene expression matrices for all caudate samples were demultiplexed and aligned to hg38_premrna using CellRanger v3. Digital gene expression matrices were generated using CellRanger v3
Digital gene expression matrices were aggregated on a per individual or species basis and analyzed using Seurat v2.3.4, rliger v1.0.0, and Harmony
Genome_build: hg19, hg38
Genome_build: Rnor_6.0
Genome_build: Mmul_10
Genome_build: tupBel1
Supplementary_files_format_and_content: digital gene expression matrix (sparse format): matrix market format, rows = genes/transcripts, columns = barcodes/cells
Supplementary_files_format_and_content: barcodes.txt: names of barcodes/cells for corresponding DGE matrix file
Supplementary_files_format_and_content: genes.txt: names of transcripts/genes for corresponding DGE matrix file
Supplementary_files_format_and_content: Each species (human; rat; macaque; tree shrew) were aggregated into a combined species' matrix

organism: Macaca mulatta

source_name: Rhesus Macaque Substantia nigra pars compacta

extract_protocol:
Please see: https://www.protocols.io/view/frozen-tissue-nuclei-extraction-for-10xv3-snseq-bi62khge
10X Chromium Single Cell 3' (V3), manufacturer's protocol

value: Substantia nigra pars compacta

value: Male

tag: pmi

tag: disease

tag: status

tag: Cause of death

tag: facs classification

tag: 10x version

tag: genome build


title: RHO1151 scRNA-Seq


title: RHH4427 scRNA-Seq

value: Human Healthy Liver


title: pPDsMMrSNxiNIH1d200516Nurr

tag: Sex

tag: age

value: Positive


title: RHO1158 scRNA-Seq


title: RHH4425 scRNA-Seq


title: RHO1150 scRNA-Seq


title: PBMC_1632

description: PBMCs

tag: tender joints

tag: swollen joints

tag: esr

tag: crp

tag: rf


title: RHH4426 scRNA-Seq


title: PBMC_2475

description: PBMCs

tag: pain

tag: disease activity

tag: wellbeing

tag: diagnosis at bl

value: RA

tag: diagnosis at year = 1


title: RHO1149 scRNA-Seq

tag: tissue

tag: cell type


title: PBMC_2216

description: PBMCs

value: F


title: PBMC_2592

description: PBMCs


title: PBMC_2261

description: PBMCs


title: RHH4424 scRNA-Seq


title: RHO1148 scRNA-Seq


title: RHH4423 scRNA-Seq


title: RHO1147 scRNA-Seq


title: PBMC_2164

description: PBMCs


title: PBMC_2657

description: PBMCs


title: PBMC_2192

description: PBMCs


title: PBMC_2209

description: PBMCs


title: RHO1146 scRNA-Seq


title: PBMC_2057-DM

description: PBMCs


title: PBMC_2258

description: PBMCs


title: RHH4421 scRNA-Seq


title: PBMC_2149

description: PBMCs


title: PBMC_2503

description: PBMCs


title: PBMC_2595

description: PBMCs


title: RHO1145 scRNA-Seq


title: RHH4420 scRNA-Seq


title: PBMC_2491

description: PBMCs


title: RHO1144 scRNA-Seq


title: RHH4419 scRNA-Seq


title: RHH4418 scRNA-Seq


title: RHO1143 scRNA-Seq


title: RHH4417 scRNA-Seq


title: RHO1142 scRNA-Seq


title: RHH4422 scRNA-Seq


title: RHH4416 scRNA-Seq


title: RHO1141 scRNA-Seq


title: RHH4415 scRNA-Seq


title: RHO1140 scRNA-Seq


title: RHO1139 scRNA-Seq


title: RHH4414 scRNA-Seq


title: RHO1138 scRNA-Seq


title: pPDsRatrSNxixd200314x

description:
Rattus_bcd.tsv.gz
Rattus_features.tsv.gz
Rattus_matrix.tsv.gz

organism: Rattus norvegicus

source_name: Rat Substantia nigra pars compacta

tag: pmi

tag: disease

tag: status

tag: Cause of death

tag: facs classification


title: RHO1137 scRNA-Seq


title: RHH4413 scRNA-Seq


title: Whole seedling, HON5_IP2

city: Austin

first: Bo

last: Zhao

state: Texas

address: 2506 Speedway, NMS 5.268

department: Molecular Biosciences, Institute for Cellular and Molecular Biology

institute: The University of Texas

library_source: genomic

data_processing:
For RNA-seq, HISAT2 was used to map the data with the reference genome TAIR 10. Differentially expressed genes were determined by using edgeR.
For ChIP-seq, Bowtie2 was used to map the data with the reference genome TAIR 10. Mapped reads were normalized using Deeptools bamCoverage function. The genome-wide read density profiles were generated with Deeptools plotProfile function.
Genome_build: TAIR 10
Supplementary_files_format_and_content: Tab-delimited text files include FPKM values of each gene for each sample. BW files of ChIP-seq were generated using Deeptool.

organism: Arabidopsis thaliana

source_name: Whole seedling

growth_protocol: Sterilized seeds were germinated on half MS medium with 0.8% agar and grown in growth chamber.

extract_protocol:
Total was extracted with TRIzol (Invitrogen) and purified by using Phenol:Chloroform:Isoamyl Alcohol (25:24:1) . Purified RNA was treated with DNase I to remove genomic DNA and then preciptated with ethanol. Genomic DNA was extracted from formaldehyde cross-linked seedlings by following the Abcam ChIP protocol (https://www.abcam.com/protocols) with minor adjustments. Immunoprecipitations were performed by using c-Myc antibody (9E10, Santa Cruz Biotechnology). Immunoprecipitated DNA samples were purified by PCR purification kits from Qiagen.
RNA-seq libraries were prepared according to NEBNext Poly(A) mRNA Magnetic Isolation Module (NEB #E7420). ChIP-seq libraries were prepared using the NEBNext ChIP-Seq library prep kit (NEB #6240S)

treatment_protocol: Long day condition (16 h light, 8 h dark) at 22 °C.

tag: genotype

value: HON5-Myc transgene

tag: age

value: 10 days after germination

value: Young seedling

tag: chip antibody

value: c-Myc (9E10, Santa Cruz Biotechnology)


title: RHO1136 scRNA-Seq

value: Human Healthy Tonsil


title: RHH4411 scRNA-Seq


title: Whole seedling, hon45_rep1

value: hon45 mutant


title: Whole seedling, HON5_IP1


title: Whole seedling, hon45_rep2


title: Whole seedling, WT_IP

value: Col-0 WT


title: Whole seedling, WT_rep2


title: Whole seedling, WT_rep1


title: RHO1135 scRNA-Seq


title: 10dpi_in_Arabidopsis_biorep5

city: Yokohama

first: Shuta

last: Asai

address: 1-7-22, Suehiro-cho, Tsurumi-ku

country: Japan

institute: RIKEN

data_processing:
Illumina sequence was quality filtered using FASTX Toolkit 0.0.13 with parameters -q20 and -p50, and reads containing “N” are discarded.
Quality-filtered libraries were aligned to the FocnCong:1-1 genome using CLC Genomic Workbench 20.
Genome_build: RSAI00000000 (genome accession at NCBI)
Supplementary_files_format_and_content: Tab-delimited text files include the transcription levels for each transcript as TPM (transcripts per million).  Only Fusarium oxysporum reads were evaluated in each sample.

source_name: root

extract_protocol:
RNAs were extracted by RNeasy Plant Mini Kit (QIAGEN).
library was constructed using a custom high-throughput method (Front Plant Sci 2012, 3:202)

value: root

tag: strain/cultivar

tag: condition

value: infections


title: 10dpi_in_Arabidopsis_biorep3


title: RHB7031 scRNA-Seq

value: Human Peripheral Blood


title: 10dpi_in_Arabidopsis_biorep4


title: RHH4412 scRNA-Seq

value: dendritic cells and monocytes


title: 10dpi_in_Arabidopsis_biorep2


title: RHB7030 scRNA-Seq


title: S2.3-rep2: Sensitive PH039 second passage source tumor (array)

city: Rochester

first: Hu

last: Li

state: MN

address: 200 First Street, Gonda Building G19-408

department: Molecular Pharmacology & Experimental Therapeutics

institute: Mayo Clinic

description: Patient-derived xenograft (PDX) high grade serous ovarian cancer model

hyb_protocol: Infinium Methylation EPIC assay ( WG-317-1001)

scan_protocol: Raw intensity signal from iScan were expoerted to R envirnoment

data_processing:
*.idat files were analyzed using the missmethyl package in R, as outlined in the methods section
annotated beta values normalized using the SWAN method in package missmethyl

label_protocol: DNA was bisulfite converted using the Methylation-Gold kit (Zymo, D5006)

growth_protocol: HGSOC PH039 PDXs were established intraperitoneally utilizing previously described methods.

extract_protocol: Genomic DNA was extracted and purified using Qiagen DNeasy Kit according to standard instructions

treatment_protocol: HGSOC PH039 PDXs were passed and treated with cycles of 100 mg/kg niraparib for 21 days for four treatment cycles. Following niraparib, mice were monitored by transabdominal ultrasound monitored for regrowth of tumors. RNA sequencing was done on matched baseline tumors and niraparib treated tumors in cycles #1, 2 and 3 in triplicates.

value: HGSOC PDX tumor

tag: arm

value: source tumor arm


title: RHH4408 scRNA-Seq

value: Human Healthy Liver


title: 3dpi_in_Arabidopsis_biorep3


title: 3dpi_in_Arabidopsis_biorep4


title: RHB7028 scRNA-Seq


title: RHH4406 scRNA-Seq


title: RHH4407 scRNA-Seq


title: RHH4409 scRNA-Seq


title: 3dpi_in_Arabidopsis_biorep1


title: 3dpi_in_Arabidopsis_biorep2


title: RHB7027 scRNA-Seq


title: 10dpi_in_Arabidopsis_biorep1


title: SGneg  replicate1-5

city: Kyoto

first: Shinya

last: Oki

address: 53 Kawahara-cho, Shogoin

institute: Kyoto University

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_StressGranule.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
SG_neg_1-5_S47

data_processing:
The barcodes and unique-molecular-identifiers in the reads were extracted using UMI-tools (version 1.0.0) with the command: umi_tools extract -I r1.fastq --read2-in=r2.fastq --bc-pattern=NNNNNNCCCCCC --read2-stdout.
The reads were mapped by the aligning software HISAT2 (version 2.1.0) to the reference genome (GRCm38 or GRCh38).
Read counts per gene was performed with featureCounts (version 1.6.4) and UMI-tools with the command: umi_tools count --method=directional --per-gene --per-cell --gene-tag=XT.
The duplicates in unique molecular identifiers were discarded.
Using the resulting counts, differentially expressed genes (those with adjusted p-values < 0.1) were extracted by the R library DESeq2 (version 1.20.0).
Genome_build: GRCh38 or GRCm38
Supplementary_files_format_and_content: count matrix:CSV

source_name: HeLa_Stress Granule

growth_protocol: HeLa cells were cultured in E-MEM+NEAA+10%FBS (KAC: DSGM105 ) with 1% penicillin/streptomycin. NIH3T3 cells were cultured  in high glucose DMEM supplemented with 10%  calf serum, 1% penicilling/streptomycin, and 1% L-Glutamin .These cells were grown at 37°C in a humidified 5% CO2 atmosphere. For PIC experiments, these cells were grown on cover slips.

extract_protocol: Lysis solution(0.1% Tween and 400 ug/ml of ProteinaseK in PBS) were loaded onto the specimens and incubated for 30 min at 55°C cDNA;mRNA hybrids were purified with QIAGEN Mini Elute PCR Purification Kit.

treatment_protocol: Stress granules were induced by addition of 75 mM NaAsO2 for 30 min.

value: HeLa cells

tag: sample type

value: UV + Stress Granule

tag: stimulation

value: 75 mM NaAsO2


title: 3dpi_in_Arabidopsis_biorep5


title: RHH4405 scRNA-Seq


title: Cytoplasm  replicate1-5

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_StressGranule.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
Cytoplasm_1-5_S46


title: RHB7029 scRNA-Seq


title: S2.3-rep1: Sensitive PH039 second passage source tumor (array)


title: 148B: Murine sample (array)

description: mouse model

organism: Mus musculus

source_name: Murine sample

value: murine-mouse model


title: S0.1: Sensitive PH039 source tumor (array)

source_name: Sensitive PH039 source tumor


title: RHB7026 scRNA-Seq


title: C3.1: Resistant PH039 third passage niraparib treated tumor (array)

value: Niraparib arm


title: SGpos  replicate1-5

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_StressGranule.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
SG_pos_1-5_S48


title: C1.2: Sensitive PH039 first passage niraparib treated tumor (array)


title: S2.1: Sensitive PH039 second passage source tumor (array)


title: C2.1: PH039 second passage niraparib treated tumor (array)


title: RHH4404 scRNA-Seq


title: SGnonUV  replicate1-5

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_StressGranule.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
SG_nonUV_1-5_S45

value: UV -


title: RHB7025 scRNA-Seq


title: NSneg  replicate1-5

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_NucSpeckle.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
NSneg_1-5_S43

source_name: HeLa_Nuclear Speckles

value: UV+ Nuclear Speckles

value: non-stimulation


title: RHH4410 scRNA-Seq


title: NS_nonUV replicate1-5

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_NucSpeckle.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
NS_nonUV_1-5_S41


title: NSpos replicate1-5

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_NucSpeckle.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
NSpos_1-5_S44


title: C2.2: PH039 second passage niraparib treated tumor (array)


title: S0.2: Sensitive PH039 source tumor (array)


title: RHH4403 scRNA-Seq


title: Nuclear  replicate1-5

description:
multiplexed sample: cell barcodes for each replicate are included in the file "cell_barcode_sample.csv"
UMI_count_NucSpeckle.csv
cell_barcode_sample.csv
CEL-seq2 protocol
Each fastq file contains multiple samples with cell-barcodes and UMIs at read-1.
Nuclear_1-5_S42


title: RHB7023 scRNA-Seq


title: RHB7022 scRNA-Seq


title: RHB7024 scRNA-Seq


title: RHH4401 scRNA-Seq


title: DD_PB_5

city: Aachen

first: Chao-Chung

last: Kuo

state: NRW

address: Pauwelsstrasse 30

department: IZKF Genomics Facility

institute: RWTH Aachen University Hospital

data_processing:
Library strategy: targeted bisulfite amplicon sequencing (BA-seq)
Raw data quality was assessed with FastQC and trimmed with Trim Galore. Trimmed reads were then aligned to given reference sequences and the DNAm status of each CpGs was identified for each read by Bismark. All samples with less than 50 reads on one of the amplicons were ignored.
Amplicon coordinates are available on the series record.
Genome_build: hg19
Supplementary_files_format_and_content: The processed data are tables for all DNAm patterns on CpGs of individual reads across all samples. Column headers are the position of CpGs on the amplicon.

source_name: Mixed DNA of AML peripheral blood (5%) and healthy samples

extract_protocol:
Genomic DNA from donors and patients was isolated with the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). DNA of six leukemia cell lines (HL-60, KG-1a, TF-1, K562, U937 and SUP B15) was isolated with the NucleoSpin Tissue Kit (Macherey-Nagel, Düren, Germany).
Assays for targeted amplicon sequencing were designed for four regions with AML associated CpGs. These regions comprise 14 neighboring CpGs around cg15289427, 10 CpGs around cg22797031, 15 CpGs around cg27630153, and 9 CpGs around cg19586199. Genomic DNA (500 ng) of blood samples or cell lines was bisulfite converted with the EZ DNA Methylation Kit (Zymo Research, Irvine, USA). Subsequently, the four AML-associated regions were amplified using the PyroMark PCR Kit (Qiagen) using primers with overhangs for subsequent barcoding. Subsequently, all four regions of a sample were pooled and purified using the Agencourt AMPure XP PCR Purification Kit (Beckman Coulter, Brea, CA, USA). Pooled regions were amplified with a 2nd round of PCR using the PyroMark PCR Kit and primers containing 8-bp long barcodes. Next, all samples were pooled, purified with the Select-a-Size DNA Clean & Concentrator Kit (Zymo Research), and library concentration was measured with the Qubit dsDNA BR Assay Kit (Thermo Fischer Scientific). The prepared amplicon library was denatured and diluted using the MiSeq Reagent Nano Kit v2 or MiSeq Reagent Kit v2 (Illumina, San Diego, CA, USA), according to the manufacturer’s instruction. Due to low library diversity 15-20% of the PhiX Control (Illumina) was spiked-in. Pooled and barcoded samples were analyzed on the Illumina MiSeq Benchtop Sequencer (Illumina) using the 250 bp paired-end sequencing mode.

tag: disease state

value: mixure of AML first diagnosis sample and control sample


title: DD_PB_50

source_name: Mixed DNA of AML peripheral blood (50%) and healthy samples


title: RHH4400 scRNA-Seq

source_name: Human Healthy Liver


title: RHB7021 scRNA-Seq


title: DD_PB_25

source_name: Mixed DNA of AML peripheral blood (25%) and healthy samples


title: RHH4399 scRNA-Seq


title: RHB7020 scRNA-Seq


title: DD_PB_10

source_name: Mixed DNA of AML peripheral blood (10%) and healthy samples


title: DD_PB_100

source_name: Mixed DNA of AML peripheral blood (100%)


title: DD_PB_1

source_name: Mixed DNA of AML peripheral blood (1%) and healthy samples


title: RHH4398 scRNA-Seq


title: RHB7019 scRNA-Seq

source_name: Human Peripheral Blood


title: RHH4397 scRNA-Seq


title: RHB7018 scRNA-Seq


title: DD_PB_0_01

source_name: Mixed DNA of AML peripheral blood (0.01%) and healthy samples


title: RHB7017 scRNA-Seq


title: RHH4395 scRNA-Seq


title: DD_BM_75

source_name: Mixed DNA of AML bone marrow (75%) and healthy samples


title: DD_BM_25

source_name: Mixed DNA of AML bone marrow (25%) and healthy samples


title: RHH4394 scRNA-Seq


title: RHB7015 scRNA-Seq


title: DD_BM_50

source_name: Mixed DNA of AML bone marrow (50%) and healthy samples


title: DD_BM_1

source_name: Mixed DNA of AML bone marrow (1%) and healthy samples


title: RHH4393 scRNA-Seq


title: DD_BM_100

source_name: AML bone marrow (100%)


title: DD_BM_5

source_name: Mixed DNA of AML bone marrow (5%) and healthy samples


title: DD_BM_0_1

source_name: Mixed DNA of AML bone marrow (0.1%) and healthy samples


title: DD_BM_10

source_name: Mixed DNA of AML bone marrow (10%) and healthy samples


title: RHB7014 scRNA-Seq


title: CL_U937

source_name: cell line U937

value: Leukemia cell line

value: cell line U937


title: RHH4392 scRNA-Seq


title: CL_TF-1

source_name: cell line TF-1

value: cell line TF-1


title: RHB7013 scRNA-Seq

value: Human Peripheral Blood


title: RHH4391 scRNA-Seq

source_name: Human Healthy Liver

value: dendritic cells and monocytes


title: RHB7012 scRNA-Seq


title: DD_PB_75

source_name: Mixed DNA of AML peripheral blood (75%) and healthy samples


title: RHH4396 scRNA-Seq


title: RHB7011 scRNA-Seq


title: DD_BM_0_001

source_name: Mixed DNA of AML bone marrow (0.001%) and healthy samples


title: CL_KG1a

source_name: cell line KG1a

value: cell line KG1a


title: RHH4389 scRNA-Seq


title: TR_BX

source_name: PB

value: Control

value: peripheral blood


title: TR_CD


title: CL_K562

source_name: cell line K562

value: cell line K562


title: CL_HL60

source_name: cell line HL 60

value: cell line HL 60


title: RHB7009 scRNA-Seq

source_name: Human Peripheral Blood


title: MP_59b

value: MRD positive


title: MP_60c


title: TR_38a

source_name: BM

value: AML First diagnosis

value: bone marrow


title: TR_30a


title: RHH4387 scRNA-Seq

value: Human Healthy Liver


title: RHB7008 scRNA-Seq


title: RHH4386 scRNA-Seq


title: MP_57b


title: RHB7007 scRNA-Seq


title: CL_SUPB15

source_name: cell line SUPB15

value: cell line SUPB15


title: MP_56e


title: MP_56f


title: RHB7016 scRNA-Seq


title: RHH4388 scRNA-Seq


title: RHB7010 scRNA-Seq


title: MP_56d


title: MP_56c


title: MP_56b


title: RHH4384 scRNA-Seq


title: MP_53c


title: RHB7004 scRNA-Seq


title: RHH4385 scRNA-Seq


title: RHH4383 scRNA-Seq


title: RHB7005 scRNA-Seq


title: RHH4382 scRNA-Seq


title: MP_44b


title: MP_53b


title: RHB7003 scRNA-Seq


title: MP_46b


title: MP_45b


title: MP_43b


title: RHH4381 scRNA-Seq


title: RHH4379 scRNA-Seq


title: MP_42b


title: RHH4380 scRNA-Seq


title: 807A

city: Lublin

first: Martyna

last: Stefaniak

address: Antoniego Gębali 6

department: Laboratory of Genetics Diagnostics

country: Poland

institute: Medical University of Lublin

hyb_protocol: not provided

scan_protocol: not provided

data_processing:
Data Type: affymetrix-multi-data-type-analysis
affymetrix-array-type = CytoScanHD_Array
affymetrix-algorithm-param-ArraySet = CytoScanHD_Array
program-name = C:\Program Files\Affymetrix\ChAS\apt-copynumber-cyto-ssa.exe
program-version = 2.11.4 stash.amer.thermo.com/ma-alg/apt2-copynumber.git/release/APT_2.11.4@8bac27f064(4b83cd1f4a)
program-company = Thermo Fisher Scientific

label: biotin

source_name: blast cells, bone marrow

label_protocol: not provided

extract_protocol: genomic DNA extraction

tag: gender

value: M

value: T-cell acute lymphoblastic leukemia

value: blast cells, bone marrow


title: RHB7006 scRNA-Seq

tag: tissue


title: MP_40b


title: MP_39b


title: RHH4378 scRNA-Seq

tag: cell type


title: MP_38b


title: RHH4390 scRNA-Seq


title: RHB6999 scRNA-Seq


title: MP_37b


title: MP_36b


title: MP_41b


title: MP_35b


title: RHH4376 scRNA-Seq


title: RHH4377 scRNA-Seq


title: RHB6997 scRNA-Seq


title: RHB7000 scRNA-Seq


title: RHB7001 scRNA-Seq


title: RHB6998 scRNA-Seq


title: RHB7002 scRNA-Seq


title: MP_34b


title: MP_31b


title: RHB6996 scRNA-Seq


title: MP_29b


title: MP_28b


title: MP_24b


title: RHB6994 scRNA-Seq


title: U1_149

city: Jerusalem

first: Matan

last: Sorek

address: Edmond J. Safra Campus

department: Genetics

country: Israel

institute: The Hebrew University of Jerusalem

data_processing:
Raw reads that passed the quality controls were aligned to human genome assembly hg19 using STAR (Dobin et al. ,2013, Bioinformatics) with parameters alignIntronMax=1000 and alignMatesGapMax=1000.
unmapped, low quality and non-uniquely mapped reads were removed
RNA-ChIP biological replicates were joined
Genome_build: hg38
Supplementary_files_format_and_content: bigWig

growth_protocol: Cells were cultured in complete DMEM medium (Sigma), 10% fetal bovine serum (Sigma), 2 mg/ml L-alanyl-Lglutamine (Biological Industries Israel), 100 U/ml penicillin, 0.1 mg/ml streptomycin (Biological Industries Israel) at 37 °C in a humidified atmosphere with 5% CO2.

extract_protocol:
Cells from three 10-cm plates were harvested, placed on ice, and crosslinked with 1% FA (Sigma) followed by crosslinking with 0.2 mg/ml AMT (Sigma; A4330) by irradiation with 350 nm UV light (Vilber Lourmat ECX.F20.L; 7 mW/cm2) for 45 min. After isolation of nuclei, 500 µl of MNase buffer (0.32 M sucrose, 50 mM Tris-Cl pH 7.5, 4 mM MgCl2, 1 mM CaCl2, and fresh 0.1 mM PMSF) was added. Chromatin and RNA were digested using 150 U of MNase (Worthington) for 15 min at 37 °C with shaking at 400 RPM on a thermomixer. The enzyme was inactivated by adding 0.8 mM EDTA. The samples were centrifuged at 12,000 g for 5 min, and the nuclei were sonicated using a Bioruptor at 40% amplitude with intervals of 2.2-sec pulses with 9.9-sec pauses for 12 min. This yielded DNA and RNA fragments of 100-500 bp in size. Antibodies used for IP were anti-pol II p-Ser2 (Abcam; ab5095), anti-pol II p-Ser5 (Abcam; ab5408), anti-U2 snRNP A (B-3) X (Santa Cruz; sc-393804X), and anti-HA (Abcam; ab9110). The samples were reverse crosslinked on ice by irradiation with 254 nm UV light for 10 min. RNA was extracted using Trizol reagent. (Sigma).
Deep sequencing libraries were prepared using v2-pico (Takara Bio) library preparation kits. Sequencing of 50-bp single-end reads was performed using an Illumina HiSeq 2000.

tag: cell line


title: RHB6995 scRNA-Seq


title: pol2_input_AMT_rep2

tag: treatment

value: AMT


title: RHB6993 scRNA-Seq


title: pol2_ser2_AMT_rep2


title: MN_59e

value: MRD negative


title: MN_59d


title: MN_60b


title: pol2_ser2_U1_AMT_rep2


title: RHB6992 scRNA-Seq

value: Human Peripheral Blood


title: control_149


title: MN_59c


title: MN_58c


title: F453: Resistant PH039 third passage niraparib treated tumor

data_processing:
Fastq files of pair-end RNA-Seq reads were aligned with Tophat 2.0.14 to the reference genome UCSC hg38 or UCSC MM10 using Bowtie2 2.2.6 with default parameters.
Reads that aligned to the mouse genome were then removed and the unaligned reads were mapped to the human genome.
Gene level counts were obtained using featureCounts 1.4.6 from the subRead package with gene models from corresponding UCSC annotation packages.
Genome_build: hg38
Supplementary_files_format_and_content: raw counts in tab-delimited text file

extract_protocol:
RNA was column-extracted using Rneasy Mini kit (qiagen)
RNA-seq libraries were prepared from 100-200 ng high-quality RNA using TruSeq RNA Library Prep Kit v2 (Illumina)

tag: disease

value: high-grade serous ovarian cancer (HGSOC)

value: PDX tumor


title: RHB6991 scRNA-Seq

value: dendritic cells and monocytes


title: F452: Resistant PH039 third passage niraparib treated tumor


title: MN_58b


title: RHB6990 scRNA-Seq


title: MP_27b


title: RHH4402 scRNA-Seq


title: MN_57c


title: F451: Resistant PH039 third passage niraparib treated tumor


title: MP_25b


title: MN_55b


title: RHB6989 scRNA-Seq


title: F352: Resistant PH039 second passage niraparib treated tumor


title: MN_54c


title: RHB6988 scRNA-Seq


title: MN_60d


title: F351: Resistant PH039 second passage niraparib treated tumor


title: MN_32b


title: MN_30b

value: peripheral blood


title: RHB6987 scRNA-Seq


title: MN_26b


title: MN_23b


title: RHB6986 scRNA-Seq


title: F1A5: Mixed phenotype PH039 first passage niraparib treated tumor


title: MN_57d


title: RHB6985 scRNA-Seq


title: F1A4: Sensitive PH039 first passage niraparib treated tumor


title: RHB6984 scRNA-Seq


title: FD_60a


title: FD_59a


title: FD_7a


title: FD_58a


title: FD_56a


title: RHB6982 scRNA-Seq


title: P2A2: Sensitive PH039 third passage source tumor


title: FD_9a


title: RHB6981 scRNA-Seq


title: FD_54a


title: P2A1: Sensitive PH039 third passage source tumor


title: F1A3: Sensitive PH039 first passage niraparib treated tumor


title: RHB6980 scRNA-Seq


title: MN_21b


title: MN_22b


title: FD_55a


title: FD_52a


title: FD_51a


title: RHB6979 scRNA-Seq


title: RHB6983 scRNA-Seq


title: FD_49a


title: FD_4a


title: FD_50a


title: P2A3: Sensitive PH039 third passage source tumor


title: RARA_RA_Chipseq

city: San Antonio

first: Zhijie

middle: Jason

last: Liu

state: TEXAS

address: 7703 Floyd Curl Drive

department: Department of Molecular Medicine

institute: Universality of Texas Health Science Center at San Antonio

description: ChIP-seq Experiment 1: 24hrs treatment with 5uM retinoic acid

data_processing:
Basecalls performed using Illuminal CASAVA software.
ChIP-seq reads were aligned to the hg19 genome assembly using bowtie v1.1.2 with only uniquely mapped reads retained.
Peaks were called using MACS2 with q-value less than 1e-5. The peaks overlapped with the blacklist regions downloaded from UCSC were removed
Genome_build: hg19
Supplementary_files_format_and_content: bigWig file

growth_protocol: NTera2 cell line was obtained from ATCC were cultured in Minimum Essential Media (MEM) media supplemented with 10% FBS in a 5% CO2 humidified incubator at 37°C.

extract_protocol:
For RARA ChIP, cell lysates were clarified from sonicated nuclei and protein-DNA complexes were isolated with RARa antibody. For Pontin ChIP, we set up BLRP-tagged stable cell lines for in vivo biotinylation of Pontin protein and cell lysates were clarified from sonicated nuclei and protein-DNA complexes were isolated by streptavidin magnet beads pull-down.
The extracted ChIP DNA was ligated to specific adaptors using KAPA LTP Library Preparation Kit (KK8230) or KAPA Hyper Prep Kit (KK8504), according to the manufacturer’s instructions.

treatment_protocol: Before experiments, the NTera2 cells were maintained in regular growing medium to get the appropriate conflency, followed by treatemnt of cells with either 5μM all-trans Retinoic Acid (RA), or Dimethyl sulfoxide (DMSO) as vehcile control for 24 hour. To perform Biotin-ChIP experiments through Biotin-streptaviding pull-down, we used the BLRP-tagged NTera2 Tet-On inducibe stable lines that can in vivo biotinylate BLRP-tagged proteins. To induce BLRP-tagged protein expression, 2μg/ml doxycycline was added into culture media for about 24 hours.

tag: chip antibody or biotin-streptavidin pulldown of blrp-tagged proteins

value: Santa Cruz Biotech., SC-551

value: Full media +5uM retinoic acid for 24 hours

value: RARA


title: FD_53a

value: AML First diagnosis


title: RARA_Veh_Chipseq

description: ChIP-seq Experiment 1: 24hrs treatment with DMSO

value: Full media +DMSO vehicle control for 24 hours


title: FD_57a


title: FD_46a

value: bone marrow


title: donor13

city: Amsterdam

first: Joe

last: Butler

address: Meibergdreef 9

department: Infectious diseases

country: Netherlands

institute: Amsterdam UMC

description: Total RNA was isolated from RPE (macular and periphery combined) and ribosomal RNA was depelted using Ribo-Zero kit.

data_processing:
Raw fastq files were trimmed for the presence of Illumina adapter sequences using Cutadapt version 1.2.1
The reads are further trimmed using Sickle version 1.200 (window quality score > 20)
Mapping of paired-end reads to the human reference genome (hg19) was performed using TopHat2 version 1.3.0
Read counts were measured with HTSeq, using the genome annotation by Ensembl (GRCh37.72)
Genome_build: hg19
Supplementary_files_format_and_content: Tab-delimited matrix of raw counts of sequencing reads (Ensembl gene IDs)

source_name: RPE

extract_protocol:
RNeasy Plus Mini kit
Ribosomal RNA was depleted from total RNA using the Ribo-Zero rRNA Removal kit. Library preparation performed using Illumina HiSeq 2000.

tag: batch

tag: Sex


title: FD_45a


title: donor12

tag: age

value: F


title: A-485 Input (biological replicate 2)

city: Gainesville

first: Daiqing

last: Liao

state: Florida

address: 2033 Mowry Road

department: Anatomy and Cell Biology

institute: University of Florida

data_processing:
The quality of the sequencing reads was assessed by FastQC.
The fastq reads were aligned to the Genome Reference Consortium Human Build 38 (hg38) using Bowtie2.
In Bowtie2, the default parameters were used, expect that we used the local alignment option, which doesn't require reads to align end-to-end, and the low-quality reads or adaptor reads could be trimmed at one or both extremes to optimize the alignment score.
The alignment results of the biological replicates for the same ChIP-seq sample were merged.
To identify antibody binding peaks (regions of the genome which contain more ChIP-Seq reads than what would be expected by chance) for A485 treated p300 sample, DMSO treated p300 sample, A485 treated H3K27ac sample, DMSO treated H3K27ac sample, we employed the HomeR software.
Genome_build: hg38
Supplementary_files_format_and_content: Peak text files
Supplementary_files_format_and_content: Bigwig files

growth_protocol: MCF-7 cells were grown at 37 °C with 5% CO2 in a humidified atmosphere. MCF-7 cells were cultured in Dulbecco's Modified Eagle Medium (DMEM with 4.5 g/L glucose, L-glutamine and sodium pyruvate, Corning) supplemented with 10% bovine calf serum (HyClone, GE Healthcare Bio-Sciences), penicillin (10 units/ml), and streptomycin (10 µg/ml) (designated as complete media).

extract_protocol:
Cells were fixed in 1% formaldehyde (final concentration) for 10 minutes; cells were lysed, and chromatin was sonicated to an average 200 bp. Immunoprecipitation was performed using H3K27ac (Cell Signaling Technologies, 8173) and normal rabbit IgG (Bethyl Laboraties, P120-101). Input samples (1%) were also saved for library production. Immunoprecipitated complexes were washed, eluted from beads, treated with Proteinase K and crosslinks were reversed. DNA was purified using a PCR Cleanup Kit (Qiagen, 28104).
Two independent experiments (n=2) were used for library production and sequencing. DNA libraries were produced according to manufacturer instructions using the NebNext Ultra II DNA Library Prep Kit for Illumina (New England Biolabs). Multiplex Oligos for Illumina (Index Primers Set 1 and Set 2) from New England Biolabs were used as index primers during library preparation.

treatment_protocol: MCF-7 cells were incubated with A-485 (3 µM) or DMSO control for 24 hours in complete media (two biological replicates).

tag: drug treatment

tag: cancer type

value: breast cancer

tag: chip antibody

value: Input


title: DMSO Input (biological replicate 2)

value: DMSO


title: FD_43a


title: donor11

value: M


title: MP_33b

value: MRD positive


title: DMSO Input (biological replicate 1)


title: FD_41a


title: FD_44a


title: FD_42a


title: FD_40a


title: donor10


title: FD_3a


title: donor9


title: FD_39a


title: FD_37a


title: FD_38a


title: donor7


title: FD_36a


title: donor8


title: DMSO (biological replicate 1)

description:
H3_DMSO_peaks.txt
H3_DMSO.ucsc.bigWig

value: H3K27ac (Cell Signaling Technologies, 8173)


title: A-485 Input (biological replicate 1)


title: FD_35a


title: donor6


title: A-485 (biological replicate 1)

description:
H3_A485_peaks.txt
H3_A485.ucsc.bigWig


title: FD_34a


title: FD_33a


title: donor5


title: FD_32a


title: donor4


title: FD_31a


title: MN_54b

value: MRD negative


title: FD_30a


title: FD_2a


title: A-485 (biological replicate 2)

description:
H3_A485_peaks.txt
H3_A485.ucsc.bigWig


title: donor3


title: DMSO (biological replicate 2)

description:
H3_DMSO_peaks.txt
H3_DMSO.ucsc.bigWig


title: FD_29a


title: BRCA1_WT2 Hi-C

city: Lausanne

first: George

last: Coukos

state: VD

address: Rue du Bugnon 46

department: Department of Oncology

country: Switzerland

institute: Ludwig Institute for Cancer Research, and University of Lausanne

description: WT

data_processing:
As a preliminary analysis, the hg38 reference human genome was divided into fragments delimited by GATC sites, which are sites recognized by the MboI restriction enzyme which was used for the HiC protocol.  This produced a table for the 24 chromosomes, with start and end position of each fragment.  In order to account for potential bias among the fragments, the table also contains the fragment length, the count of GC nucleotide pairs, and a measure of mappability which counts the number of sub-fragments of 36 nucleotides that can be uniquely mapped to each fragment.  The table was further annotated by the average nucleotide coverage from two whole genome sequencing runs, one for the mutated BRCA1 condition and one for the rescued wild-type condition.  These coverages are useful to determine copy number variations in the genomes of the cell lines.  The number of read pairs received as input for each sample was the following:  UWB1.289 BRCA1wt replicate 1: 832,401,844 / UWB1.289 BRCA1wt replicate 2 : 730,444,209/ UWB1.289 BRCA1Mut replicate 1: 622,942,922/ / SRC195/ UWB1.289 BRCA1mut replicate 2: 735,638,573  The HiC protocol causes two spatially close but genomically distant pieces of DNA to be cut at an enzymatic recognition site and ligated together at the cutting point.  Thus, we expect to find GATCGATC motifs in the reads and the genomic origin of the fragments on each side of the motif will be different.  At first we searched for the GATCGATC double motif in each read and discarded the end of the read after the first GATC motif.  If the remaining piece became too short (< 32 nucleotides) for unambiguous placement on the reference genome, the whole read pair was discarded. If no double GATCGATC motif was detected, it was assumed that the motif lied within the unsequenced part of the fragment between the two reads of the pair, and so those reads were kept for further processing.  The number of read pairs remaining after this first filtering step was as follows: UWB1.289 BRCA1wt replicate 1: 709,361,979/ UWB1.289 BRCA1mut replicate 1: 555,857,566/ UWB1.289 BRCA1wt replicate 2: 639,748,714/ UWB1.289 BRCA1mut replicate 2: 655,781,263  We next mapped the reads on the hg38 human genome reference.  We used an in-house derivative of our fetchGWI (Iseli et al., 2007) tool.  For each read pair we obtain the position and orientation of the match on the reference genome.  We also pre-computed a table containing the positions of all the GATC sites present in the hg38 reference human genome.  The current analysis aimed to determine cis-interactions at a maximum distance of 1,000,000 nucleotides, so we then selected mapped read pairs where both reads were mapped on the same chromosome and at a distance of no longer than 1 million base pairs.  Read pairs that formed a usual illumina sequencing fragment (reads in opposing orientation and defining a fragment length of 2 kilobases or less) were discarded as probably not originating from ligation.  At this point a table was produced containing the list of remaining read pairs, with their mapping position and orientation, as well as the position of the closest GATC restriction site.
Genome_build: hg38
Supplementary_files_format_and_content: tab-delimited text files with 8 columns; columns 1-3 give the chromosome name, position and orientation of the mapping of the first read; column 4 is the position of the closest next GATC motif; columns 5-7 give the chromosome name, position and orientation of the mapping of the second read; column 8 is the position of the next closest GATC motif

source_name: UWB1.289 with forced expression of wild-type BRCA1 - replicate 2

extract_protocol: Harvested cells were washed once with PBS, fixed with 2% formaldehyde for 10 min in PBS at room temperature, quenched with 0.2M glycine for 5 min. After washing once with PBS, pelleted cells were flash frozen and stored at -80°C for further processing. Nuclei were isolated with lysis buffer (10mM Tris-HCl (pH 8.0), 10mM NaCl, 0.2% IGEPAL CA630) with incubation on ice for 5 min, washed once same lysis buffer. Pelleted nuclei were permeabilized with 0.5% SDS for 10 min at 62°C, quenched with Triton X-100 for 15 min at 37 °C. Chromatin was digested with a 4 cutter restriction enzyme (MboI, 100U, NEB) overnight at 37°C with mixing. After inactivating digestion at 62°C for 20 min, the 5’ overhangs were filled in with biotinylated-14-dATP (Life Tech) and Klenow (40U, NEB) for 90 min at 37°C with mixing. Biotinylated ends were ligated with T4 DNA ligase (2000U, NEB) for 4 hours at room temperature with mixing. DNA was reverse crosslinked with Proteinase K (400mg, NEB) and 1% SDS for 30 min at 55 °C, followed by an overnight incubation at 68°C with NaCl. DNA was purified with ethanol precipitation, and sheared on an ultrasonicator (Covaris S220; duty cycle: 10; intensity: 4; cycles/burst: 200; duration: 55s; number of cycles: 1) to a fragment range of 300-700 bp. Double size selection was performed using SPRI beads (Beckman Coulter). Biotinylated fragments were enriched by pulldown with Dynabeads MyOne T1 Streptavidin beads (Life Technologies), followed by library preparation (Quick Ligation Kit, NEB). Final library was amplified by PCR (Phusion DNA Polymerase, Thermo). Libraries were sequenced on HiSeq4000 Paired-End for 100bp (Illumina).

value: UWB1.289 BRCA1

tag: genotype

value: WT


title: BRCA1_MUT2 Hi-C

description: MUT

source_name: UWB1.289 with mutation in BRCA1 - replicate 2

value: BRCA1 2594delC


title: FD_28a


title: BRCA1_MUT1 Hi-C

description: MUT

source_name: UWB1.289 with mutation in BRCA1 - replicate 1


title: BRCA1_WT1 Hi-C

description: WT

source_name: UWB1.289 with forced expression of wild-type BRCA1 - replicate 1


title: donor1


title: FD_27a

value: peripheral blood


title: FD_24a


title: donor2


title: FD_23a


title: BRCA1_MUT_control1

data_processing:
H3K27ac epigenetic marks indicative of active enhancers were located using ChIP-seq. Chromatin precipitation with H3K27ac-specific antibodies on 289 BRCA1mut and 289 BRCA1wt cells was performed as described above. Two replicates for each sample were processed as follows: ~50 million 50 nucleotide long sequence reads were aligned to the GRCh38 reference genome using the short read aligner bowtie2 (http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml), with a mapping efficiency of ~90%. Regions enriched “broad peaks” of mapped reads were identified using the MACS2 software (https://github.com/taoliu/MACS). The --broad option (for broad peaks) in the callpeak module was used to call significant regions (experimental versus input control) at an FDR (q-value) of 0.05. The PAVIS website (http://manticore.niehs.nih.gov/pavis2) was used to annotate the enriched regions (gene-relative location; chromosome location; transcript ID; gene symbol; strand; distance to TSS).
Genome_build: hg38
Supplementary_files_format_and_content: Annotated enriched peaks in tab-delimited text format

source_name: UWB1.289 with mutation in BRCA1 - input

extract_protocol: Harvested cells were washed with PBS, fixed with 1% formaldehyde for 10 min, quenched with 0.125 M glycine for 5 min at room temperature, and washed twice with PBS. Fixed cells were pelleted, flash frozen, and stored at -80°C for further processing. Crosslinked cells were lysed with lysis buffer (1% SDS, 50 mM Tris-HCl, pH 8.0, 20 mM EDTA, 1x complete EDTA-free protease inhibitor (Roche)) on ice for 10 min, diluted with TE buffer, then sheared using a Branson Tip Sonifier 450 on ice (15 cycles, 15s on, 45s off/cycle at power 3). For bead preparation, Protein G Dynabeads (Life Tech) were incubated with 3 ug of H3K27ac pAb (31933, Active Motif) overnight at 4°C. Incubated beads were washed 3 times with PBS with BSA. Detailed protocols for immunoprecipitation and library preparation are available on the ENCODE homepage.1,2

value: MUT

tag: cell l line

tag: antibody


title: FD_22a

tag: disease state


title: U2AF65

data_processing:
Raw reads that passed the quality controls were aligned to human genome assembly hg19 using bowtie2 (Langmead and Salzberg , 2012) with parameter -very-sensitive
Only uniquely aligned reads were kept and duplicated reads were removed
multiple reads that were mapped to the same location in the genome with the same UMI in the same sample were removed
Sequencing depth files at single-base resolution were created using bam2wig.pl tool (http://search.cpan.org/~tjparnell/Bio-ToolBox-1.44) and for each base a normalized reads-per-million value was calculated and assigned considering all the reads that span that base.
The normalized input coverage was subtracted from the normalized ChIP-seq and RNA-Seq coverage to represent the difference between the two samples and the final occupancy value for each base.
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text files include normalized RPM values for each sample

extract_protocol:
Approximately 10×106 cells per sample were trypsinized, washed with PBS, and crosslinked with 1% FA at 37 °C. After incubation for 10 min, the reaction was stopped by addition of glycine (0.125 M) and incubated at 37 °C for 5 min. Samples were centrifuged at 2300 x g, washed with cold PBS, and centrifuged again. Nuclei isolation, MNase (Worthington) digestion, and IP were done as described (Kfir et al. 2015) with the following minor adaptations: After suspension in IP buffer, the samples were sonicated using a Bioruptor (Diagenode) at 40% amplitude in intervals of 1.5-sec pulses with 9.9-sec pauses for 10 min.
For the double ChIP-seq, ChIP was performed as described previously (Yearim et al. 2015) with the following adaptations: Approximately 7×106 HEK293 cells were used per sample. After nuclei purification and MNase digestion, samples were sonicated using a Bioruptor at 40% amplitude with intervals of 2.2-sec pulses with 9.9-sec pauses for 12 min. For anti-pol II p-Ser2 IP, 80 µl of a mixture of protein A and G Dynabeads (Invitrogen) were used with 18 µg anti-pol II p-Ser2 antibody (Abcam; ab5095). After IP, 1 µl of 10 mg/ml RNase A (Sigma) was added, and samples were incubated for 30 min at 37 °C. Following washes, the samples were eluted with 50 μl fresh 0.1 M DTT. As previously described (Sadeh et al. 2016), 50 µl of freshly prepared 2X Chromatin Release Buffer (500 mM NaCl, 2% deoxycholate, 2% SDS, 2 mM EDTA) with fresh EDTAfree protease inhibitor cocktail and PMSF (from the RNA ChIP-IT kit) were added, and samples were incubated at 37 °C for 55 min. The elution step was repeated and samples were incubated for 30 min at a temperature higher than 15 °C to prevent SDS precipitation. This step releases bound chromatin and inactivates the antibodies used in the first ChIP. To the eluted samples 1.5 µl Proteinase K (NEB) was added, and samples were incubated for 16 h at 65 ºC. DNA was purified using phenol:chloroform:isoamyl alcohol (Sigma) extraction. For the second ChIP, 50 µl of a mixture of protein A and G Dynabeads (Invitrogen) were used with 10 µg anti-U1C antibody (Abcam; ab157116). After incubation for 16 h at 4 ºC, the samples were washed and eluted as described previously (Yearim et al. 2015).
Deep sequencing libraries were prepared using Illumina TruSeq library preparation kits as per the manufacturer’s instructions. Sequencing of 50-bp single-end reads was performed using an Illumina HiSeq 2000.


title: BRCA1_MUT2

value: H3K27ac pAb (31933, Active Motif)


title: pol2_U2AF65

value: pol2 U2AF65


title: BRCA1_WT_control2

source_name: UWB1.289 with forced expression of wild-type BRCA1 - input


title: BRCA1_MUT1


title: FD_1a

value: AML First diagnosis


title: FD_19a

value: bone marrow


title: FD_17a


title: pol2_PTPBP1

value: pol2 PTPBP1


title: FD_26a


title: FD_15a


title: FD_25a


title: BRCA1_MUT_control2


title: Ctrl_Y

value: Control


title: Ctrl_X


title: FD_11a


title: FD_14a


title: input_AMT

data_processing:
Raw reads that passed the quality controls were aligned to human genome assembly hg19 using STAR (Dobin et al. ,2013, Bioinformatics) with parameters alignIntronMax=1000 and alignMatesGapMax=1000.
unmapped and low quality read were removed
multiple reads that were mapped to the same location in the genome with the same UMI in the same sample were removed
Filtered reads were passed to the End Sequence Analysis Toolkit (ESAT, Derr et al., 2016, Genome Research)  with parameters wLen=400, wOlap=50, wExt=2000 and sigTest=0.05.
Reads Per Megabase of library size (RPM) were calculated, and further normalized using quantile normalization.
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text files include normalized RPM values for each sample

value: AMT


title: HEK293_RNA_Seq

data_processing:
paired reads were trimmed to keep only the first 100 bps
Raw reads were aligned to human genome assembly hg19 using tophat2 (Kim et al. 2013) with default parameters
Only uniquely mapped reads were kept and PCR duplicated were removed
Fragments Per Kilobase Million (FPKM) normalized reads were calculated using Cufflinks (Trapnell et al. 2010)
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text files include FPKM values for each sample

extract_protocol:
RNA was extracted using Trizol reagent (Sigma).
Deep sequencing libraries were prepared using TruSeq Stranded mRNA library preparation kits as per the manufacturer’s instructions. Sequencing of 125-bp paired-end reads was performed using an Illumina HiSeq 2000.


title: FD_21a


title: Pol2_ser2_AMT


title: Ctrl_V


title: 27HC_2_5

city: Urbana

first: Erik

last: Nelson

state: Illinois

address: 407 S Goodwin Ave

department: Molecular and Integrative Physiology

institute: University of Illinois at Urbana Champaign

data_processing:
Alignment and Quantification: Kallisto v0.44.0 using build GRCm38
tximport was used to summarize the transcript-level abundance from Kallisto to gene-level
DEG analysis was carried out using EdgeR and Limma-voom
Genome_build: GRCm38
Supplementary_files_format_and_content: Tab-delimited tsv file of gene counts of each sample

source_name: Breast tumor

extract_protocol:
Tumors were removed, flash frozen on dry ice, and RNA was harvested using Trizol reagent. ITruSeq Stranded mRNA Sample Prep Kit was used for the construction of sequencing libraries
The RNAseq libraries were prepared with Illumina's 'TruSeq Stranded mRNAseq Sample Prep kit' (Illumina). Read 1 aligns to the ANTISENSE strand and Read 2 aligns to the SENSE strand. * The libraries were quantitated by qPCR and sequenced on two lanes for 101 cycles from each end of the fragments on a HiSeq 4000 using a HiSeq 4000 sequencing kit version 1.

value: Breast tumor


title: BRCA1_WT_control1


title: Ctrl_W


title: BRCA1_WT1


title: Ctrl_U


title: Pol2_ser2_U1_AMT

value: noAMT


title: Ctrl_T


title: Ctrl_S


title: 27HC_2_4


title: Ctrl_R


title: Ctrl_Z


title: Pol2_ser2_U1_noAMT


title: input


title: BRCA1_WT2


title: Ctrl_P


title: input_noAMT


title: 27HC_2_2


title: Ctrl_Q


title: 27HC_2_3


title: Ctrl_N


title: Ctrl_M


title: 27HC_2_1


title: pol2_ser2-U1


title: Ctrl_K


title: 27HC_1_5


title: Ctrl_J


title: Pol2-ser2


title: Ctrl_L


title: 27HC_1_4


title: Ctrl_H8


title: Ctrl_H9


title: SCC60A-Resistant-rep3

city: Beer Sheva

first: Moshe

last: Elkabets

address: Ben-Gurion

institute: Ben-Gurion University

data_processing:
Analysis of the raw sequence reads was carried out using the NeatSeq-Flow platform
The sequences were quality trimmed and filtered using Trim Galore (V0.4.5). Alignment of the reads to the human genome (version GRCh38.91) was done with STAR
The number of reads per gene per sample was counted using RSEM
Quality assessment (QA) of the process was carried out using FASTQC and MultiQC
Gene annotation was done based on the human genome assembly downloaded from Ensembl/BioMart. Statistical analysis for identification of differentially expressed genes was performed using the DESeq2 R package via the NeatSeq-Flow platform
Genome_build: Alignment of the reads to the human genome (version GRCh38.91) was done with STAR
Supplementary_files_format_and_content: Resist.vs.Sensitive_RLOG_Normalized_counts.txt

source_name: Head and neck cancer cells

extract_protocol:
RNA was extracted from sensitive and isiPI3K-acquired resistance UM-SCC47 and UT-SCC60A cell lines and sequenced. Three replicates of each of the sensitive and resistant cell lines were cultured in drug-free medium for 48 h, after which RNA was extracted using the RNeasy mini kit (74104, Qiagen, Hilden, Germany) according to the manufacturer’s instructions.
RNA-seq libraries were prepared using the TruSeq RNA Sample Preparation kit (Illumina, San Diego, CA, USA) according to the manufacturer’s protocol. Briefly, 1ug of total RNA was fragmented, followed by reverse transcription and second-strand cDNA synthesis. The DS-cDNA was subjected to end repair, a base addition, adapter ligation, and PCR amplification to create libraries. Qubit and Bioanalyzer were evaluated. Sequencing libraries were constructed with barcodes to allow multiplexing of 6 samples in one lane

value: Tonsil

tag: phenotype

value: Resistant


title: 27HC_1_3

tag: tissue


title: Ctrl_H7


title: Ctrl_H6


title: 27HC_1_2


title: SCC60A-Resistant-rep2

growth_protocol: Three replicates of each of the sensitive and resistant cell lines were cultured in drug-free medium for 48 h, after which RNA was extracted using the RNeasy mini kit (74104, Qiagen, Hilden, Germany) according to the manufacturer’s instructions.


title: SCC60A-Resistant-rep1


title: Ctrl_H5


title: Ctrl_H4


title: 27HC_1_1


title: Ctrl_H3


title: Ctrl_H2


title: SCC60A-parental-rep3

value: parental


title: DMSO_2_4

value: DMSO


title: U1


title: Ctrl_H10


title: Ctrl_H


title: Ctrl_I


title: SCC60A-parental-rep2


title: DMSO_2_3


title: DMSO_2_2


title: SCC60A-parental-rep1


title: SCC47-Resistant-rep3

value: lateral tongue


title: Ctrl_CP


title: Ctrl_G


title: DMSO_2_1


title: Ctrl_CK


title: Ctrl_CN


title: Ctrl_CM


title: Ctrl_CO


title: SCC47-Resistant-rep2


title: DMSO_1_5


title: Ctrl_CI


title: Ctrl_CJ


title: SCC47-parental-rep3


title: Ctrl_CG


title: SCC47-parental-rep2


title: DMSO_1_2


title: F251: Mixed phenotype PH039 first passage niraparib treated tumor

value: high-grade serous ovarian cancer (HGSOC)

value: PDX tumor


title: Ctrl_CH

value: peripheral blood


title: DMSO_1_3


title: Ctrl_CD


title: Ctrl_CC


title: Ctrl_CE


title: SCC47-parental-rep1


title: Ctrl_CF


title: DMSO_1_1


title: BRA124

city: Bethesda

first: Thomas

middle: John

last: Pranzatelli

state: MD

address: 10 Center Dr

department: Molecular Physiology and Therapeutics Branch

institute: National Institute of Dental and Craniofacial Research

data_processing:
Samples were run on an Illumina NextSeq500 configured for 37 x 37 PE reads.
FASTQ files were extracted using bcl2fastq, and the FASTQ files were further processed using this SNAKEMAKE_FILE pipeline using the snakemake/3.8 utility in the Biowulf2 cluster.
Quality of the reads was evaluated using the FastQC software. The reads satisfy all critical parameters and are deemed of sufficient quality to proceed with further processing and analysis.
Read mapping against a recent ENCODE human release was performed using the STAR v2.5.2a aligner using the standard mode with mapping parameters derived from the GENCODE project
For read counting we used the quantMode utility of the STAR aligner.
Supplementary_files_format_and_content: The counts are generated during mapping, producing one count file per sample, which are then merged as RAWCOUNTFILE.
Supplementary_files_format_and_content: Normalized counts per gene (CPM, or counts per million reads) in the TMMNORMALIZEDCOUNTS file

source_name: minor salivary glands

extract_protocol:
Minor salivary glands were obtained from study participants and stored in RNAlater (Qiagen) until RNA extraction. Samples were homogenized with a Bullet-Blender (Next Advance) or an Omni TH (Omni International). Total RNA was extracted with an RNeasy Mini kit according to the instructions of the manufacturer (Qiagen). The quality of RNA was measured using a 2100 Bioanalyzer (Agilent). Only RNA samples with a 28S/18S ribosomal RNA ratio of 1.7 and an RNA integrity number of ≥ 6.5 were used for the arrays.
The cDNA libraries were produced by the Genomics and Computational Biology Core (GCBC) using the Nextera XT method.

value: minor salivary glands

tag: diagnosis

value: primary Sjogren's syndrome

tag: gender

value: Female


title: BRA123


title: PARPi-ICB-aVEGF treated mouse - replicate 4

first: David

last: Barras

state: Vaud

address: AGORA, Bugnon 25A

department: Oncology

institute: Centre hospitalier universitaire vaudois

data_processing:
Illumina single-end sequencing reads were aligned to the mouse reference GRCm38 genome using STAR aligner (Dobin et al. Bioinformatics. 2013) and the 2-pass method as briefly followed: the reads were aligned in a first round using the --runMode alignReads parameter, then a sample-specific splice-junction index was created using the --runMode genomeGenerate parameter. Finally, the reads were aligned using this newly created index as a reference.
The number of counts was summarized at the gene level using htseq-count (Anders et al. Bioinformatics. 2015). The number of uniquely-mapped, non-mitochondrial and non-ribosomal reads averaged 28’343’252 ± 2’135’822 (s.d.). Read counts were normalized into reads per kilobase per million (RPKM) and log2 transformed after addition of a pseudocount value of 1.
Genome_build: GRCm38
Supplementary_files_format_and_content: RPKM: Processed coding gene expression log2(RPKM+1) with Gene Symbol mapping
Supplementary_files_format_and_content: RAW COUNTS: Raw counts with Ensembl ID mapping

source_name: ID8 Trp53-/-Brca1-/- tumor

growth_protocol: We injected 5×10e6 ID8 derivative cancer cells expressing luciferase i.p. in C57/BL6 female mice.

extract_protocol:
Total RNA was isolated from 100 to 500 mg of frozen tissue  with TRIzol reagent followed by RNA purification using the RNA Easy Mini Kit.
Truseq Stranded RNA. Whole transcriptome sequencing method with depletion of cytoplasmic RNA.

treatment_protocol: PARPi (Olaparib) was administered orally at 40mg/kg/day. All antibodies were injected i.p. twice a week at the following amounts: 100µg of αCTLA-4 mAb; 200µg of αPD-L1 mAb; 20µg of αVEGFA mAb;

value: tumor

tag: icb

value: yes

tag: parpi

tag: avegf

tag: treatment

value: Combo


title: Ctrl_CB

source_name: PB

value: Control


title: Ctrl_CA


title: Ctrl_BZ


title: PARPi-ICB-aVEGF treated mouse - replicate 3


title: PARPi-ICB-aVEGF treated mouse - replicate 2


title: SCC47-Resistant-rep1

tag: cell line


title: Ctrl_BQ


title: Ctrl_BX


title: Ctrl_BJ


title: DMSO_1_4

value: Breast tumor


title: BRA109

tag: age


title: BRA108


title: Ctrl_BF


title: PARPi-ICB-aVEGF treated mouse - replicate 1


title: BRA107


title: Ctrl_BA


title: Ctrl_B7b


title: BRA106


title: PARPi-ICB treated mouse - replicate 3

value: no


title: Ctrl_B9b


title: Ctrl_B15a


title: BRA104


title: Ctrl_AT


title: PARPi-ICB treated mouse - replicate 2


title: Ctrl_BY


title: PARPi-ICB treated mouse - replicate 1


title: BRA103


title: Ctrl_AW


title: Ctrl_AR


title: PARPi-aVEGF treated mouse - replicate 4


title: BRA102


title: Ctrl_AL


title: Ctrl_AF


title: Ctrl_AO


title: Ctrl_AC


title: Ctrl_AQ


title: Ctrl_AP


title: PARPi-aVEGF treated mouse - replicate 3


title: BRA100


title: BRA99


title: C4.3: Resistant PH039 fourth passage niraparib treated tumor (rrbs)

data_processing:
Demultiplexed reads were merged and grouped using AmpliVar genotyping mode (PMID: 25664426).
Processed using a custom script, available on github (https://github.com/okon/MethAmplicons).
Reads with deletions, insertions or substitutions variants in CpG positions were filtered out.
Epialleles below 5% frequency were grouped together for individual epiallele plots.
Genome_build: hg38 and mm9
Supplementary_files_format_and_content: raw counts for epiallele detected (13 CpG sites of interest)

extract_protocol:
Nextera XT libraries were prepared from Nextera Index Kit v2 set B or set C barcoding primers were integrated  into amplicons to create illumina sequecing libraries (Iluumina, cat #FC-131-2002 or FC-131-2003).
RRBS sequenced on the Illumina MiSeq using Miseq Nano Reagent Kit v2 (Illumina; Cat# MS-102-2002).

value: HGSOC PDX samples

tag: arm

value: Niraparib arm


title: C4.2: Resistant PH039 fourth passage niraparib treated tumor (rrbs)


title: BRA98


title: Ctrl_B16b

data_processing:
Library strategy: targeted bisulfite amplicon sequencing (BA-seq)
Raw data quality was assessed with FastQC and trimmed with Trim Galore. Trimmed reads were then aligned to given reference sequences and the DNAm status of each CpGs was identified for each read by Bismark. All samples with less than 50 reads on one of the amplicons were ignored.
Amplicon coordinates are available on the series record.
Genome_build: hg19
Supplementary_files_format_and_content: The processed data are tables for all DNAm patterns on CpGs of individual reads across all samples. Column headers are the position of CpGs on the amplicon.


title: C3.2: Resistant PH039 third passage niraparib treated tumor (rrbs)


title: C3.1: Resistant PH039 third passage niraparib treated tumor (rrbs)


title: BRA96


title: Immune Checkpoint Blockade (ICB) treated mouse - replicate 3

value: CB


title: C2.2: PH039 second passage niraparib treated tumor (rrbs)


title: BRA94


title: Immune Checkpoint Blockade (ICB) treated mouse - replicate 2


title: PARPi-aVEGF treated mouse - replicate 2


title: C2.1: PH039 second passage niraparib treated tumor (rrbs)


title: C1.2: PH039 first passage niraparib treated tumor (rrbs)


title: Immune Checkpoint Blockade (ICB) treated mouse - replicate 1


title: BRA92


title: PARPi treated mouse - replicate 3

value: PARPi


title: C1.1: PH039 first passage niraparib treated tumor (rrbs)


title: S5.4: Sensitive PH039 fifth passage source tumor (rrbs)

value: source tumor arm


title: BRA91


title: PARPi-aVEGF treated mouse - replicate 1


title: PARPi treated mouse - replicate 2


title: S5.3: Sensitive PH039 fifth passage source tumor (rrbs)


title: S0.2: Sensitive PH039 source tumor (rrbs)

source_name: Sensitive PH039 source tumor


title: S2.1: Sensitive PH039 second passage source tumor (rrbs)


title: BRA89


title: Pontin_RA_Chipseq

description: ChIP-seq Experiment 2: 24hrs treatment with 2μg/ml doxycycline and 5uM retinoic acid

value: NTera2 Tet-On Inducible BLRP stable line

tag: chip antibody or biotin-streptavidin pulldown of blrp-tagged proteins

value: Biotin-ChIP using Streptavidin Magnetic beads (Solulink)

value: Full media +2ug/ml Dox and 5uM retinoic acid for 24 hours

value: Pontin


title: Pontin_Veh_Chipseq

description: ChIP-seq Experiment 2: 24hrs treatment with 2μg/ml doxycycline and DMSO

value: Full media +2ug/ml Dox and DMSO vehicle control for 24 hours

tag: chip antibody


title: BRA88

value: minor salivary glands

value: primary Sjogren's syndrome

value: Female


title: BRA87


title: Untreated mouse - replicate 3

value: tumor

tag: genotype

value: control


title: Untreated mouse - replicate 2


title: BRA84


title: Untreated mouse - replicate 1


title: 8-10wk_Jej_IELymph_WT 1087942

city: Tarrytown

first: Wei Keat

last: Lim

address: 777 Old Saw Mill River Rd

institute: Regeneron Pharmaceuticals

description:
8-10wk_Jej_IELymph_WT
1087942
dge_umi_1087942.txt

data_processing:
FASTQ files were aligned and quantified using Omicsoft ArrayStudio
Genome_build: GRCm38
Supplementary_files_format_and_content: tab-delimited text file include read count for each sample

source_name: small intestine

extract_protocol:
Total RNA was purified using MagMAX™-96 Total RNA Isolation Kit (Ambion by Life Technologies) according to manufacturer’s specifications. Genomic DNA was removed using RNase-Free DNase Set (Qiagen).
Strand-specific RNA-seq libraries were prepared using KAPA stranded mRNA-Seq Kit (KAPA Biosystems).

tag: strain

value: small intestine

value: WT


title: 8-10wk_Ileum_IELymph_KO 1087943

description:
8-10wk_Ileum_IELymph_KO
1087943
dge_umi_1087943.txt


title: 8-10wk_Ileum_IELymph_WT 1087944

description:
8-10wk_Ileum_IELymph_WT
1087944
dge_umi_1087944.txt


title: 8-10wk_Duo_IELymph_WT 1087940

description:
8-10wk_Duo_IELymph_WT
1087940
dge_umi_1087940.txt


title: 8-10wk_Jej_IELymph_KO 1087941

description:
8-10wk_Jej_IELymph_KO
1087941
dge_umi_1087941.txt


title: 10wk_Jej_IELymph_WT 1105598

description:
10wk_Jej_IELymph_WT
1105598
Counts_10264.txt

source_name: jejunum

value: jejunum


title: BRA83


title: 8-10wk_Duo_IELymph_KO 1087939

description:
8-10wk_Duo_IELymph_KO
1087939
dge_umi_1087939.txt


title: Normal_67_8-18-15_P3

first: Cameron

last: Baker

state: NY

address: 601 Elmwood Ave

institute: University of Rochester

data_processing:
DATA FORMATTING (Illumina -> FastQ) & DEMULTIPLEXING - bcltofastq-1.8.4
CLEANING - Trimmomatic-0.32 "SLIDINGWINDOW:4:20 TRAILING:13 LEADING:13 ILLUMINACLIP:adapters.fasta:2:30:10 MINLEN:15"
MAPPING - STAR_2.4.2a "--runMode alignReads --genomeDir ${GENOME} --readFilesIn ${SAMPLE} --outSAMtype BAM SortedByCoordinate --outSAMstrandField intronMotif --outFilterIntronMotifs RemoveNoncanonical"
DIFFERENTIAL EXP. - cufflinks-2.0.2 (cuffdiff) "--library-type fr-firststrand --FDR 0.05 -u -b GENOME"
Genome_build: GRCh38.p2 + Gencode-23 Annotation
Supplementary_files_format_and_content: A breakdown of gene counts by sample and by condition

source_name: ND-MSCs

extract_protocol:
Total RNA was extracted from MSCs using a QIAshredder homogenizer and the RNeasy plus Mini Kit (Qiagen, Valencia, CA, USA) following manufacturer’s protocol.  RNA quality was assessed by Nanodrop 1000 (ThermoFisher Scientific).
RNA integrity was determined on an Agilent Bioanalyzer (Agilent Technologies. Santa Clara, CA, USA).  Approximately 100 ng total RNA was utilized per sample.  Polyadenylated RNA was enriched, fragmented, and converted to cDNA with the Illumina TruSeqTM sample preparation kit (Illumina, San Diego, CA, USA).  Sequencing of the cDNA (RNA-Seq) was performed to a depth of more than 20 million reads (100-nt reads per sample) with the Illumina HiSeq2500v4.

tag: individual

tag: cell type

value: ND-MSCs


title: PARPi treated mouse - replicate 1

value: no

value: yes


title: BRA82


title: BRA80


title: 10wk_Jej_IELymph_KO 1105593

description:
10wk_Jej_IELymph_KO
1105593
Counts_10264.txt


title: 10wk_Jej_IELymph_WT 1105596

description:
10wk_Jej_IELymph_WT
1105596
Counts_10264.txt


title: Normal_53_9-3-15_P4

tag: disease state


title: 10wk_Jej_IELymph_WT 1105597

description:
10wk_Jej_IELymph_WT
1105597
Counts_10264.txt

tag: tissue


title: AML_Pt8_P4

source_name: AML-MSCs

value: AML

value: AML-MSCs


title: Normal_53_8-15-15_P4


title: 10wk_Jej_IELymph_WT 1105595

description:
10wk_Jej_IELymph_WT
1105595
Counts_10264.txt


title: 10wk_Jej_IELymph_KO 1105594

description:
10wk_Jej_IELymph_KO
1105594
Counts_10264.txt


title: BRA79

tag: diagnosis


title: AML_Pt2_P4


title: 10wk_Ileum_IELymph_WT 1105588

description:
10wk_Ileum_IELymph_WT
1105588
Counts_10264.txt

source_name: ileum

value: ileum


title: 10wk_Ileum_IELymph_WT 1105590

description:
10wk_Ileum_IELymph_WT
1105590
Counts_10264.txt


title: 10wk_Jej_IELymph_KO 1105592

description:
10wk_Jej_IELymph_KO
1105592
Counts_10264.txt


title: BRA78

tag: gender


title: 10wk_Ileum_IELymph_WT 1105589

description:
10wk_Ileum_IELymph_WT
1105589
Counts_10264.txt


title: 10wk_Ileum_IELymph_WT 1105587

description:
10wk_Ileum_IELymph_WT
1105587
Counts_10264.txt


title: BRA81


title: AML_Pt1_P4


title: BRA76


title: 10wk_Ileum_IELymph_KO 1105586

description:
10wk_Ileum_IELymph_KO
1105586
Counts_10264.txt


title: 10wk_Duo_IELymph_WT 1105582

description:
10wk_Duo_IELymph_WT
1105582
Counts_10264.txt

source_name: duodenum

value: duodenum


title: 10wk_Ileum_IELymph_KO 1105585

description:
10wk_Ileum_IELymph_KO
1105585
Counts_10264.txt


title: MDA-MB-468 - c19ROW39

city: Shenzhen

first: Wenfei

last: Jin

state: Guangdong

address: 1088 Xueyuan Rd #faculty research building 1

department: Department of Biology

institute: Southern University of Science and Technology

data_processing:
Basecalling was performed with CASAVA v1.7 from Illumina.
Each column was demultiplexed to single cells using a script provided by Fluidigm (mRNASeqHT_demultiplex.pl).
Reads were filtered and trimmed using Trim Galore version 0.6.1.
Reads from each cell were mapped to human reference genome (hg19) or mouse GRCm38  by STAR version 2.5.2b.
Gene expression level was quantified by htseq-count version 0.11.2.
Genome_build: hg19 for human; GRCm38 for mouse
Supplementary_files_format_and_content: Counts matrix are tab-delimited files containing raw counts of each cell. Each column represents a sample/cell and each row represents a gene.

extract_protocol:
Single cell RNA libraries were prepared by Fluidigm C1 Single-Cell Autoprep System.
We started scPolyA-seq library preparation by cell lysis. Then we added primers containing polyT and cell barcode for labeling the 3’ end of transcripts. Full-length cDNA was synthesized by template-switching reverse transcription, amplification and tagmentation with Tn5 transposases. Nextera XT DNA Library Preparation Kit (Ilumina) was applied to construct scPolyA-seq library. DNA fragments at the 3’ end of the cDNA were captured by targeted PCR, and sequencing indexes were added for amplification. The quality of library was examined by Qubit 3.0 Fluorometer and Agilent 2100 Bioanalyzer. Libraries separated by columns were pooled together and sequenced on Illumina HiSeq2500 to obtain 150-bp paired-end reads.


title: 10wk_Ileum_IELymph_KO 1105583

description:
10wk_Ileum_IELymph_KO
1105583
Counts_10264.txt


title: BRA75


title: 10wk_Jej_IELymph_KO 1105591

description:
10wk_Jej_IELymph_KO
1105591
Counts_10264.txt


title: MDA-MB-468 - c19ROW38


title: MDA-MB-468 - c19ROW40


title: BRA73


title: BRA74


title: 10wk_Duo_IELymph_WT 1105580

description:
10wk_Duo_IELymph_WT
1105580
Counts_10264.txt


title: MDA-MB-468 - c19ROW37


title: BRA72


title: 10wk_Duo_IELymph_KO 1105578

description:
10wk_Duo_IELymph_KO
1105578
Counts_10264.txt


title: 10wk_Duo_IELymph_KO 1105577

description:
10wk_Duo_IELymph_KO
1105577
Counts_10264.txt


title: BRA71


title: 7wk_Ileum_IECs_WT 1003491

description:
7wk_Ileum_IECs_WT
1003491
Counts_8482.txt


title: 10wk_Duo_IELymph_KO 1105576

description:
10wk_Duo_IELymph_KO
1105576
Counts_10264.txt


title: 7wk_Ileum_IECs_KO 1003485

description:
7wk_Ileum_IECs_KO
1003485
Counts_8482.txt


title: 7wk_Ileum_IECs_WT 1003488

description:
7wk_Ileum_IECs_WT
1003488
Counts_8482.txt


title: MDA-MB-468 - c19ROW36


title: MDA-MB-468 - c19ROW33


title: BRA20


title: 7wk_Ileum_IECs_KO 1003484

description:
7wk_Ileum_IECs_KO
1003484
Counts_8482.txt


title: MDA-MB-468 - c19ROW30


title: 10wk_Duo_IELymph_WT 1105581

description:
10wk_Duo_IELymph_WT
1105581
Counts_10264.txt


title: BRA19


title: MDA-MB-468 - c19ROW29


title: 10wk_Duo_IELymph_WT 1105579

description:
10wk_Duo_IELymph_WT
1105579
Counts_10264.txt


title: MDA-MB-468 - c19ROW27


title: MDA-MB-468 - c19ROW26


title: BRA18


title: MDA-MB-468 - c19ROW25


title: BRA70


title: BRA14


title: 7wk_Jej_IECs_WT 1003477

description:
7wk_Jej_IECs_WT
1003477
Counts_8482.txt


title: 7wk_Ileum_IECs_KO 1003481

description:
7wk_Ileum_IECs_KO
1003481
Counts_8482.txt


title: BRA11


title: 7wk_Jej_IECs_WT 1003476

description:
7wk_Jej_IECs_WT
1003476
Counts_8482.txt


title: BRA15


title: 7wk_Jej_IECs_WT 1003480

description:
7wk_Jej_IECs_WT
1003480
Counts_8482.txt


title: 7wk_Jej_IECs_KO 1003475

description:
7wk_Jej_IECs_KO
1003475
Counts_8482.txt


title: BRA13


title: 7wk_Jej_IECs_KO 1003473

description:
7wk_Jej_IECs_KO
1003473
Counts_8482.txt


title: YNG_WT_SI 964952

description:
YNG_WT_SI
964952
Counts_7964.txt


title: 7wk_Duo_IECs_WT 1003465

description:
7wk_Duo_IECs_WT
1003465
Counts_8482.txt


title: 7wk_Duo_IECs_WT 1003468

description:
7wk_Duo_IECs_WT
1003468
Counts_8482.txt


title: MDA-MB-468 - c19ROW35


title: MDA-MB-468 - c19ROW23


title: 7wk_Duo_IECs_KO 1003459

description:
7wk_Duo_IECs_KO
1003459
Counts_8482.txt


title: MDA-MB-468 - c19ROW22


title: MDA-MB-468 - c19ROW20


title: 7wk_Jej_IECs_KO 1003474

description:
7wk_Jej_IECs_KO
1003474
Counts_8482.txt


title: BRA16


title: YNG_WT_SI 964950

description:
YNG_WT_SI
964950
Counts_7964.txt


title: YNG_WT_SI 964949

description:
YNG_WT_SI
964949
Counts_7964.txt


title: BRA64


title: 7wk_Duo_IECs_KO 1003464

description:
7wk_Duo_IECs_KO
1003464
Counts_8482.txt


title: MDA-MB-468 - c19ROW19


title: YNG_WT_SI 964951

description:
YNG_WT_SI
964951
Counts_7964.txt


title: YNG_WT_SI 964948

description:
YNG_WT_SI
964948
Counts_7964.txt


title: 7wk_Duo_IECs_WT 1003466

description:
7wk_Duo_IECs_WT
1003466
Counts_8482.txt


title: BRA41


title: YNG_WT_SI 964947

description:
YNG_WT_SI
964947
Counts_7964.txt


title: MDA-MB-468 - c19ROW18


title: MDA-MB-468 - c19ROW16


title: YNG_Btnl2-KO_SI 964945

description:
YNG_Btnl2-KO_SI
964945
Counts_7964.txt


title: MDA-MB-468 - c19ROW17


title: BRA36

value: Healthy volunteer


title: YNG_Btnl2-KO_SI 964944

description:
YNG_Btnl2-KO_SI
964944
Counts_7964.txt


title: BRA37


title: YNG_Btnl2-KO_SI 964942

description:
YNG_Btnl2-KO_SI
964942
Counts_7964.txt


title: MDA-MB-468 - c19ROW15


title: YNG_Btnl2-KO_SI 964943

description:
YNG_Btnl2-KO_SI
964943
Counts_7964.txt


title: YNG_WT_SI 964946

description:
YNG_WT_SI
964946
Counts_7964.txt