title: RNAseq-Neuron-CHD8-2


title: RNAseq-Neuron-CACNA1C-3

status: Public on Nov 01 2018

type: SRA

city: Toronto

first: Stephen

middle: W

last: Scherer

state: Ontario

address: 686 Bay Street

department: Genetics and Genomic Biology

country: Canada

institute: The Hospital for Sick Children

library_source: transcriptomic

data_processing:
Data quality was assessed using FastQC v.0.11.2
Trimmed reads were screened for presence of rRNA and mtRNA sequences using FastQ-Screen v.0.4.3
RSeQC package v.2.3.7 was used to assess read distribution, positional read duplication and confirm strandedness of alignments
Raw trimmed reads were aligned to the reference genome hg19 using Tophat v.2.0.11
Tophat alignments were processed to extract raw read counts for genes using htseq-count v.0.6.1p2
Raw gene counts were loaded and sample-normalized using DESeq v.1.18.0
Two-condition differential expression was done with the edgeR R package, v.3.8.6
The method used for normalizing the data was TMM, implemented by the calcNormFactors(y) function
The test for differential expression was done using the quasi-likelihood F-test functionality in edgeR
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text files include raw counts for each sample

molecule: polyA RNA

organism: Homo sapiens

source_name: glutamatergic NEUROG2-induced neurons

growth_protocol: All iPSC lines were maintained on matrigel coating, with complete media change every day in mTeSR (StemCellTechnologies). Neurons were generated by 7-day overexpression of NEUROG2 followed by 21-day maturation in Neurobasal media (Gibco), 1x B27 (Gibco), 1x glutamax (Gibco), 1x pen/strep (Gibco), laminin (10 μg/ml, Sigma), BDNF (10 ng/μl, Peprotech) and GDNF (10 ng/μl, Peprotech)

extract_protocol:
Total RNA was extracted using RNeasy mini kit (Qiagen)
RNA libraries were prepared using NEBNext Ultra RNA Library Preparation kit for Illumina

tag: tissue

value: glutamatergic NEUROG2-induced neurons

tag: genotype/variation

tag: passages

tag: days of differentiation


title: RNAseq-Neuron-CHD8-3


title: RNAseq-Neuron-CACNA1C-2


title: RNAseq-Neuron-ATRX-4

value: ATRX


title: RNAseq-Neuron-ASTN2-3


title: RNAseq-Neuron-ATRX-3


title: RNAseq-Neuron-AFF2-5


title: RNAseq-Neuron-AFF2-3


title: RNAseq-Neuron-TENM1-3


title: RNAseq-Neuron-control-1

value: control


title: RNAseq-Neuron-ATRX-2


title: RNAseq-Neuron-DLGAP2-2


title: RNAseq-Neuron-ASTN2-2


title: RNAseq-Neuron-TENM1-2


title: RNAseq-Neuron-AFF2-4


title: RNAseq-Neuron-AFF2-2


title: RNAseq-Neuron-ANOS1-1


title: RNAseq-Neuron-TENM1-1


title: RNAseq-Neuron-KCNQ2-2


title: RNAseq-Neuron-KCNQ2-3


title: RNAseq-Neuron-CHD8-1


title: RNAseq-Neuron-ATRX-1


title: RNAseq-Neuron-ASTN2-1


title: RNAseq-Neuron-CACNA1C-1


title: RNAseq-Neuron-KCNQ2-1


title: RNAseq-iPSC-CACNA1C-1

source_name: induced pluripotent stem cells (iPSCs)

value: induced pluripotent stem cells (iPSCs)


title: RNAseq-iPSC-control-8


title: RNAseq-Neuron-control-4


title: RNAseq-Neuron-SCN2A-1


title: RNAseq-iPSC-CACNA1C-2


title: RNAseq-Neuron-control-3


title: RNAseq-Neuron-control-2


title: RNAseq-iPSC-control-7


title: RNAseq-iPSC-control-6


title: RNAseq-Neuron-AFF2-1


title: RNAseq-iPSC-ATRX-4


title: RNAseq-iPSC-ATRX-3


title: RNAseq-iPSC-ATRX-2


title: RNAseq-Neuron-DLGAP2-1


title: RNAseq-iPSC-ASTN2-4


title: RNAseq-iPSC-SCN2A-2


title: RNAseq-iPSC-SCN2A-1


title: RNAseq-iPSC-AFF2-2


title: RNAseq-iPSC-ASTN2-3


title: RNAseq-iPSC-ASTN2-1


title: RNAseq-iPSC-SCN2A-3


title: RNAseq-iPSC-ATRX-1


title: RNAseq-iPSC-SCN2A-4


title: RNAseq-iPSC-AFF2-1


title: RNAseq-iPSC-ASTN2-2


title: RNAseq-iPSC-CHD8-3


title: RNAseq-iPSC-CHD8-1


title: RNAseq-iPSC-KCNQ2-4


title: RNAseq-iPSC-KCNQ2-3


title: RNAseq-iPSC-KCNQ2-2


title: RNAseq-iPSC-KCNQ2-1


title: RNAseq-iPSC-TENM1-2


title: RNAseq-iPSC-TENM1-1


title: RNAseq-iPSC-ANOS1-3


title: RNAseq-iPSC-ANOS1-4


title: RNAseq-iPSC-control-5


title: RNAseq-iPSC-DLGAP2-4


title: RNAseq-iPSC-CHD8-2


title: RNAseq-iPSC-DLGAP2-3


title: RNAseq-iPSC-CHD8-4


title: RNAseq-iPSC-DLGAP2-1


title: RNAseq-iPSC-ANOS1-1


title: RNAseq-iPSC-control-4


title: RNAseq-iPSC-ANOS1-2


title: RNAseq-iPSC-control-1


title: RNAseq-iPSC-control-2


title: RNAseq-iPSC-DLGAP2-2


title: PDX line HGC_3_con_1

city: Daejeon

first: Seon-Kyu

last: Kim

address: 125 Gwahak-ro, Yuseong-gu, Daejeon 305-806, Korea

department: Personalized Genomic Medicine Research Center

country: South Korea

institute: Korea Research Institutue of Bioscience & Biotechnology

data_processing:
Base calling was performed by Illumina Genome Studio(V2010.1).
Reference genome sequence data from Homo sapiens were obtained from the University of California Santa Cruz Genome Browser Gateway (assembly ID: hg19). Reference genome index was built by using bowtie2-build component of Bowtie2 (ver. 2.0, http://bowtie-bio.sourceforge.net/bowtie2) and SAMtools (ver. 0.1.18, http://samtools.sourceforge.net/).
Tophat2 was applied to tissue samples for mapping reads to reference genome. Read count data were estimated by Cufflinks software and the reads count per
million
 fragments
mapped (CPM) of each sample was estimated.
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text format with log2 transformed CPM values of genes

molecule: total RNA

source_name: gastric cancer PDX line

extract_protocol:
Total RNA was isolated by RNeasy Mini Kit (Qiagen, CA, USA), according to the manufacturer's protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light.
Sequencing library was prepared using TruSeq RNA Sample Preparation kit v2 (Illumina, CA, USA) according to the manufacturer’s protocols. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads, fragmented, and converted into cDNAs. Then, adapters were ligated and the fragments were amplified on a PCR.

tag: normal/tumor

value: tumor

tag: patholical subtype

value: diffuse type cancer


title: PDX line HGC_18_con


title: PDX line HGC_20_con_2


title: PDX line HGC_20_con_1


title: PDX line HGC_3_con_2


title: RNAseq-iPSC-control-3


title: surrounding normal 04502067N

source_name: surrounding normal

value: normal


title: surrounding normal 04504700N


title: surrounding normal 04351995N


title: surrounding normal 04501325N


title: surrounding normal 04503493N


title: surrounding normal 04501327N


title: surrounding normal 04002179N


title: Control tomato fruit Tomato-CTRL_7D_01

data_processing:
Base calling was performed by Illumina Genome Studio(V2010.1).
Reference genome sequence data for Solanum lycopersicum (tomato) were obtained from the National Center for Biotechnology Information (NCBI) genome database (assembly ID: SL2.50).
STAR was applied to tissue samples for mapping and to quantify reads to the reference genome (ver. 2.5).To estimate gene expression levels, counts per million (CPM) mapped reads values were calculated for each sample. The CPM data were normalised using quantile normalisation in the R language environment (version 3.2.5).
Genome_build: SL2.50
Supplementary_files_format_and_content: tab-delimited text format with log2 transformed CPM values of genes

organism: Solanum lycopersicum

source_name: tomato fruit

extract_protocol:
Total RNA was isolated using an RNeasy Mini Kit (Qiagen, CA, USA) according to the manufacturer’s protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light.
The sequencing library was prepared using a TruSeq RNA Sample Preparation kit v2 (Illumina, CA, USA) according to the manufacturer’s protocol. In brief, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads, fragmented and converted into cDNA. After the ligation of adapters, the fragments were amplified by PCR.

tag: sound treatment

value: No

tag: sound frequency


title: Control tomato fruit Tomato-CTRL_7D_02


title: mRNA-seq Col Rep2

city: Beijing

first: Xuncheng

last: Wang

address: 5 Yiheyuan Road

country: China

institute: Peiking University

description: polyA RNA isolated

data_processing:
We mapped Col RNA-seq reads to the TAIR10 genome using TopHat with a maximum of two allowed mismatches. Only uniquely mapped reads were retained for subsequent analyses. Ler RNA-seq reads were mapped to the  Ler reference genomes from The 1001 Genomes Project. For increased reliability, only genes that were highly conserved between Col and  Ler were analyzed. We used BLAT to align the genomic sequences of TAIR10 genes to the Ler genomes. Genes with >80% nucleotide identity in >80% of genic regions and no loss of TAIR10 splice sites were retained for further analysis.
Genome_build: TAIR10
Supplementary_files_format_and_content: tab-delimited text files include RPKM values for mRNA seq samples

organism: Arabidopsis thaliana

source_name: The first leaf

growth_protocol: Arabidopsis Col and  Ler ecotypes were used in this study. Plants were grown on Murashige and Skoog plates containing 1% sucrose at 22ºC under 100 µmol m–2 s–1 white light and 8 h light/16 h dark. Experiments were performed using 14-day-old seedlings

extract_protocol:
n/a
Total RNA was extracted from shoots of 14-day-old Arabidopsis seedling using the Rneasy plant mini kit (Qiagen). mRNAs were extracted from the total RNAs by Dynabeads oligo(dT) (Invitrogen Dynal). First- and second-strand cDNAs were obtained using random hexamer primers and SuperScript II reverse transcriptase (Invitrogen).

tag: age

value: 14 day old

tag: ecotype

value: Col


title: mRNA-seq Col Rep1

description: polyA RNA isolated


title: Control tomato fruit Tomato-CTRL_6H_02


title: mRNA-seq Ler Rep2

description: polyA RNA isolated

value: Ler


title: Control tomato fruit Tomato-CTRL_5D_01


title: Control tomato fruit Tomato-CTRL_6H_01


title: Control tomato fruit Tomato-CTRL_2D_02


title: Control tomato fruit Tomato-CTRL_5D_02


title: surrounding normal 04501978N


title: Sound wave treated tomato fruit Tomato-1KHZ_7D_01

source_name: Sound wave treated tomato fruit

value: Yes


title: Sound wave treated tomato fruit Tomato-1KHZ_5D_02


title: surrounding normal 04500663N


title: Sound wave treated tomato fruit Tomato-1KHZ_5D_01


title: Sound wave treated tomato fruit Tomato-1KHZ_6H_01


title: HCT116_JIB-04

city: Seoul

first: Hyein

last: Cho

address: 50, Yonsei-ro, Seodaemun-gu

department: Department of systems biology

institute: Yonsei university

data_processing:
Illumina HiSeq 4000 reads were trimmed and clipped for quality control in Trimmomatic 0.32.
Read quality was checked for each sample using FastQC v0.10.0
High-quality reads was aligned to the reference genome(hg19) using TopHat version 2.0.13 and bowtie2 2.2.3
After the read mapping, Cufflinks version 2.2.1 was used for transcript assembly. Expression profile was calculated for each sample and transcript/gene as FPKM (Fragment per Kilobase of transcript per Million mapped reads).
Genome_build: hg19
Supplementary_files_format_and_content: gtf files were generated by Cufflinks version 2.2.1

extract_protocol:
Total RNA was extracted from HCT116 with treatment of DMSO and JIB-04 using TRI-reagent LS (MRC). Illumina TruSeq RNA Sample Prep Kit v2 (Cat#RS-122-2001) was used with 1 ug of total RNA for the construction of sequencing libraries.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: HCT116 was treated with DMSO and 2µM of JIB-04 for 24hr.

value: colon

tag: cell type

value: colorectal carcinoma

tag: morphology

value: epithelial


title: Sound wave treated tomato fruit Tomato-1KHZ_2D_01


title: mRNA-seq Ler Rep1

description: polyA RNA isolated


title: RNAseq_cKO_2

city: London

first: Takayuki

last: Hirota

address: 1 Midland Road

country: United Kingdom

institute: The Francis Crick Institute

description: KO-2 TPM

data_processing:
The basecalling is done automatically by the sequencer with the illumina software RTA. Conversion to fastq was done with the illumina software bcl2fastq version 2.
RNA-seq: abundance was calculated by running kallisto (Bray et al, Nat Biotech, 2016) using the mouse transcriptome index (GRCm38), with the parameter "-b 150 -l 200 -t 4 -s 20 --single". Normalisation was performed using kallisto to generate transcript-level TPM values which were later aggregated to gene-level TPM values using sleuth (Pimentel et al, Nat Methods, 2017). Differential expression analysis was performed using sleuth. All chromosome and gene Biotype annotations were extracted from Ensembl.
ChIP-seq: alignment was performed by running hisat2 (Kim et al, Nat Methods, 2015) using mouse genome index (GRCm38), with the parameter "-p 6 -t -q --add-chrname -3 0 -5 9 --dta-cufflinks --no-spliced-alignment". Mapping files containing uniquely mapped reads were converted into bam format and sorted using samtools (Li et al, Bioinformatics, 2009). Duplicated reads were removed using picard (http://broadinstitute.github.io/picard). Bigwig file of H3K9me3 occupancy fold-change relative to Setdb1 cKO of wildtype cells was generated by comparing bam files using bamCompare in deeptools2 (Ramirez et al, Nucleic Acids Res, 2016) with the parameter "-bs 100 -bl mm10.blacklist.bed --normalizeTo1x 2150570000 --centerReads --pseudocount 1 --ratio reciprocal_ratio".
Genome_build: GRCm38
Supplementary_files_format_and_content: excel spreadsheet include TPM values and sleuth output values
Supplementary_files_format_and_content: bigwig file showing H3K9me3 occupancy fold-change relative to Setdb1 cKO of wildtype cells

organism: Mus musculus

extract_protocol:
RNA-seq: total RNA was extracted from 500 pachytene cells using RNAqueous-Micro Total RNA Isolation Kit (ThermoFisher, AM1931) and eluted in 10 µl of elution solution. ChIP-seq: wildtype (3268 cells) and Setdb1 cKO (5203 cells) pachytene cells were used for library prep described below.
RNA-seq: cDNA was amplified from 1 µl of total RNA by using Smart-seq2 protocol (S. Picelli et al., Nat Methods. 10, 1096-8. 2013; 15 amplification cycles). 10 ng of cDNA was sheared using Covaris E220. Libraries of ~300 bp were generated using Ovation Ultralow DR kit (NuGEN, 0330) with 14 PCR cycles. ChIP-seq: Ultra-low-input native ChIP-seq library was prepared by following a published protocol (J. Brind'Amour et al., Nat. Commun. 6, 6033. 2015). 5% of the samples after micrococcal nuclease digestion were taken as input. 6.25 µl of diluted H3K9me3 antibody (1:100; Active Motif, 39161) per reaction was used for ChIP. NEBNext Adapter for Illumina was used as adapters and adapter-ligated DNAs were amplified by 13 PCR cycles using NEBNext Index primers (New England Biolabs, included in E7335 and E7500). The libraries were size-selected (200-500 bp) using E-Gel (ThermoFisher).

treatment_protocol: wildtype and Setdb1 cKO

tag: strain

tag: Sex

value: male

value: Setdb1 cKO

value: testis

value: pachytene spermatocytes


title: RNAseq_cKO_1

description: KO-1 TPM


title: RNAseq_WT_2

description: WT-2 TPM

value: wildtype


title: HCT116_DMSO


title: Abx_4wk_RNA_Seq_Vancomycin_3

city: New York

first: Eduardo

middle: Jose

last: Contijoch

state: NY

address: 1 Gustave L Levy Pl

department: Genetics and Genomic Sciences

country: USA

institute: Icahn School of Medicine at Mount Sinai

data_processing:
Transcript expression values were obtained by mapping to the Mus musculus mm10 genome (http://genome.ucsc.edu/) using HISAT and StringTie.
FPKM was exported with the ballgown R package.
Genome_build: mm10
Supplementary_files_format_and_content: The processed data file format is the *e_.ctab file format, which is generated by StringTie and Tablemaker for use with the Ballgown package for RNA Seq data analysis. The file contains exon-level expression measurements. One row per exon. Columns are e_id (numeric exon id), chr, strand, start, end (genomic location of the exon), and the following expression measurements for each sample:
• rcount: reads overlapping the exon
• ucount: uniquely mapped reads overlapping the exon
• mrcount: multi-map-corrected number of reads overlapping the exon
• cov average per-base read coverage
• cov_sd: standard deviation of per-base read coverage
• mcov: multi-map-corrected average per-base read coverage
• mcov_sd: standard deviation of multi-map-corrected per-base coverage

extract_protocol:
10-30mg of tissue from the proximal colon was placed into an RNAlater (Qiagen). RNA was extracted with an RNeasy Kit (Qiagen) using 1mm zirconia/silica beads (BioSpec).
mRNA Illumina libraries were generated by the NYU Genome Technology Center and sequenced to a depth of 27.6 ±  5 million (mean ±  std) 50nt paired-end reads/sample (Illumina HiSeq).

treatment_protocol: Antibiotic treatments were given to 4 week old mice for 4 weeks prior to sacrifice

value: 4 weeks

tag: sample group

value: Vancomycin

value: Colon


title: surrounding normal 04503847N

value: normal


title: Abx_4wk_RNA_Seq_PolymyxinB_3

value: Polymyxin B


title: Abx_4wk_RNA_Seq_PolymyxinB_1


title: Abx_4wk_RNA_Seq_Vancomycin_1


title: Abx_4wk_RNA_Seq_Germ_Free_4

value: Germ Free


title: Sound wave treated tomato fruit Tomato-1KHZ_7D_02


title: Abx_4wk_RNA_Seq_Vancomycin_2


title: Sound wave treated tomato fruit Tomato-1KHZ_6H_02


title: Abx_4wk_RNA_Seq_Germ_Free_2


title: Abx_4wk_RNA_Seq_Control_1

value: Control


title: Sound wave treated tomato fruit Tomato-1KHZ_2D_02


title: Abx_4wk_RNA_Seq_Control_4


title: Abx_4wk_RNA_Seq_PolymyxinB_2


title: Abx_4wk_RNA_Seq_Clindamycin_1

value: Clindamycin


title: RNAseq_WT_1

description: WT-1 TPM


title: Abx_4wk_RNA_Seq_Control_3


title: Abx_4wk_RNA_Seq_Ciprofloxacin_1

value: Ciprofloxacin


title: SC_3

city: Stockholm

first: Julian

last: Walfridsson

country: Sweden

data_processing:
Samples were demulitplexed using the configureBclToFastq.pl script from Illumina
Gene level counts were generated by the featureCounts program version 1.5.1
Supplementary_files_format_and_content: Table of gene raw counts

growth_protocol: THP-1 cells were propagated in RPMI + 10% FBS and 1% Penecilin/Streptomycin antibiotic

extract_protocol:
RNA extraction was done by using Qiagen micro RNAeasy extraction kit.
TotalScriptTM RNA-seq kit (Epicentre, Madison, WI) was used to prepare strand specific RNA libraries according to the manufacturer’s instructions.

treatment_protocol: THP-1 cells transduced with lentiviral shRNA virus agaist CHD4 and SC control and cells were harvested 72h after transduction

tag: cell line

value: childhood acute myeloid leukemia (AML) cell line

tag: transduced with

value: negative control vectors


title: Control tomato fruit Tomato-CTRL_2D_01

value: No


title: SC_2


title: Abx_4wk_RNA_Seq_Ciprofloxacin_2

tag: tissue


title: Abx_4wk_RNA_Seq_Clindamycin_2


title: Abx_4wk_RNA_Seq_Ampicillin_3

value: Ampicillin


title: Abx_4wk_RNA_Seq_Ciprofloxacin_3


title: Abx_4wk_RNA_Seq_Germ_Free_1


title: Abx_4wk_RNA_Seq_Ampicillin_2


title: SC_1


title: Abx_4wk_RNA_Seq_Control_2


title: Abx_4wk_RNA_Seq_Control_5


title: Abx_4wk_RNA_Seq_Germ_Free_3


title: CHD4_72h_2

value: shRNA targeting CHD4


title: Abx_4wk_RNA_Seq_Ampicillin_1


title: CHD4_72h_3


title: CHD4_72h_1


title: Kras WT, 1

first: Alberto

last: Ambesi-Impiombato

address: 1130 St. Nicholas Avenue

department: ICG

institute: Columbia University

description: ALL tumor Kras wild type, replicate 1

data_processing:
We use RTA (Illumina) for base calling and bcl2fastq (version 1.8.4) for converting BCL to fastq format, coupled with adaptor trimming
We map the reads to a reference genome using Tophat [1] (version 2.0.4) with 4 mismatches (--read-mismatches = 4) and 10 maximum multiple hits (--max-multihits = 10)
We estimate the relative abundance (aka expression level) of genes and splice isoforms using cufflinks (version 2.0.2) with default settings.
Genome_build: mm9
Supplementary_files_format_and_content: tab-delimited text files include FPKM values for each Sample

source_name: spleen

extract_protocol:
We use poly-A pull-down to enrich mRNAs from total RNA samples (200ng-1ug per sample, RIN>8 required)
We prepared libraries were using Illumina TruSeq RNA prep kit
We multiplex samples in each lane, which yields targeted number paired-end 100bp reads for each sample, as a fraction of 180 million reads for the whole lane

value: LSL-K-ras G12D

value: Leukemia

tag: genotype

value: wild type (Kras wt/LSL-Kras G12D)


title: Kras G12D, 3

description: ALL tumor Kras G12D, replicate 3

value: Kras wt/Kras G12D


title: T5_20uM_6h_mRNA

city: Fujisawa

first: Yusuke

last: Nakayama

state: Kanagawa

address: 26-1, Muraoka-Higashi 2-chome

department: Pharmaceutical Research Division

country: Japan

institute: Takeda Pharmaceutical Company Limited

data_processing:
Illumina mRNA-Seq reads were aligned to hg19 (GRCh37) reference genome assembly using the GSNAP aligner. Aligned libraries had mate-pair information fixed, were removed of potential PCR duplicates.
Cufflinks was used to quantify gene expression FPKM values.
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text files include FPKM values

source_name: osteosarcoma

growth_protocol: The human osteosarcoma cancer cell line U2OS was maintained in McCoy's 5a (Life Technologies, Carlsbad, CA, USA). The media were supplemented with 10% FBS (Life Technologies), penicillin (10,000 U/mL; Life Technologies) and streptomycin (10,000 μg/mL; Life Technologies). Cells were seeded and subcultured in 100 mm diameter dishes every 3–4 d. All cell lines were from American Type Culture Collection (Manassas, VA, USA).

extract_protocol:
Total RNA was extracted using an RNeasy Miniprep Kit (Qiagen).
Libraries were prepared according to Illumina's instructions. Libraries were sequenced using HiSeq 2000 following the manufacturer's protocols.

treatment_protocol: U2OS cells were seeded into 100 mm diameter dishes and incubated overnight in culture medium. Cells were treated with CPT, T4 or T5 for 6 h.

value: osteosarcoma


title: Kras WT, 2

description: ALL tumor Kras wild type, replicate 2


title: T5_5uM_6h_mRNA


title: T5_10uM_6h_mRNA


title: Abx_4wk_RNA_Seq_Clindamycin_3

value: 4 weeks

value: Colon


title: Kras G12D, 2

description: ALL tumor Kras G12D, replicate 2


title: Kras G12D, 1

description: ALL tumor Kras G12D, replicate 1


title: T4_20uM_6h_mRNA


title: T5_0.5uM_6h_mRNA


title: gd-Sox13hi_H3K27me3-ChIPseq

city: Worcester

first: OK HYUN

last: CHO

state: MA

address: 368 Plantation Street

department: Pathology

institute: University of Massachusetts Medical School

library_source: genomic

data_processing:
Sequence reads were obtained and mapped to a mouse reference genome (mm9) using the Illumina HiSeq 2000 Pipeline.
All reads mapping with two or fewer mismatches were retained, applied to a Cisgenome 2.0 integrated software system (Hongkai et, 2008) and converted to browser extensible data (BED) files for viewing the data in the UCSC or Cisgenome browser.
The parameters for ChIPseq was Read Extension Length E=150bp, Bin Size B=50bp, Half Window Size W=3, Max Gap=50bp, Min Peak Length=100bp, Win Stat Cutoff C>=3 in One Sample Peak Calling. Following this, peak enrichment regions that fell below the false discovery rate (FDR<0.05) and within 100kb of the transcription start site or the transcription end site were considered for further analysis.
Genome_build: mm9
Supplementary_files_format_and_content: BED files are tab-delimited files with one line for each genomic region

molecule: genomic DNA

source_name: mouse thymocytes

growth_protocol: Cells were sorted by FACS according to established markers

extract_protocol:
1 million cells for SOX13 ChIPseq and 0.25 milion cells for H3K4me3 and H3K27me3 were sorted (gd+, CD24+, CFPhi or CFPlo/-), crosslinked with 1% formaldehyde, sonicated, and then subjected to chromatin immunoprecipitation with anti-SOX13, anti-H3K4me3 and anti-H3K27me3 antibodies. 300-500 bp DNA fragments were obtained after reverse-cross linking.
ChIP DNA fragments were processed for ChIPseq with Illumina adapters and Illumina primers (Primer1.1 and Primer2.1). After adapter ligation, DNAs were PCR-amplified for 17 cycles and library fragments of 300-500 bp were extracted from an agarose gel.

value: TCRbeta KO.Sox13 ECFP KI/+

value: sorted gd T thymocytes

tag: index

value: GATCAG

tag: chip antibody

value: anti-H3K27me3 (Abcam, ab6002)


title: gd-Sox13lo_H3K4me3-ChIPseq

value: ACAGTG

value: anti-H3K4me3 (Millipore, 17-614)


title: gd-Sox13lo_H3K27me3-ChIPseq

value: GCCAAT


title: T4_5uM_6h_mRNA


title: T4_2uM_6h_mRNA


title: T4_10uM_6h_mRNA


title: gd-Sox13hi_H3K4me3-ChIPseq

value: ACTTGA


title: Sox13hi and Sox13lo Input

value: ATCACG


title: T4_0.5uM_6h_mRNA


title: Kras WT, 3

description: ALL tumor Kras wild type, replicate 3


title: CPT_20uM_6h_mRNA


title: CPT_10uM_6h_mRNA


title: CPT_2uM_6h_mRNA


title: Sox13tg+.Sox13 Input

data_processing:
Sequence reads were obtained and mapped to a mouse reference genome (mm9) using the Illumina HiSeq 2000 Pipeline.
All reads mapping with two or fewer mismatches were retained, applied to a Cisgenome 2.0 integrated software system (Hongkai et, 2008) and converted to browser extensible data (BED) files for viewing the data in the UCSC or Cisgenome browser.
The parameters for TCF1 ChIPseq was Read Extension Length E=150bp, Bin Size B=50bp, Half Window Size W=3, Max Gap=50bp, Min Peak Length=100bp, Win Stat Cutoff C>=3 in One Sample Peak Calling. Following this, peak enrichment regions that fell below the false discovery rate (FDR<0.05) and within 100kb of the transcription start site or the transcription end site were considered for further analysis.
Genome_build: mm9
Supplementary_files_format_and_content: BED files are tab-delimited files with one line for each genomic region

extract_protocol:
1 million cells for TCF1 ChIPseq were sorted (gd+, CD24+ and CFPlo/-), crosslinked with 1% formaldehyde, sonicated, and then subjected to chromatin immunoprecipitation with anti-TCF1 antibody. 300-500 bp DNA fragments were obtained after reverse-cross linking.
The TCF1 ChIP DNA fragments were processed for ChIPseq with Illumina adapters and Illumina primers (Primer1.1 and Primer2.1). After adapter ligation, DNAs were PCR-amplified for 17 cycles and library fragments of 300-500 bp were extracted from an agarose gel.

value: TCRbeta KO.Sox13tg+.Sox13 ECFP KI/+


title: CPT_5uM_6h_mRNA


title: T5_2uM_6h_mRNA


title: DMSO_6h_mRNA


title: gd-Sox13lo_TCF1-ChIPseq

extract_protocol:
1 million cells for TCF1 ChIPseq were sorted (gd+, CD24+ and CFPhi or CFPlo/-), crosslinked with 1% formaldehyde, sonicated, and then subjected to chromatin immunoprecipitation with anti-TCF1 antibody. 300-500 bp DNA fragments were obtained after reverse-cross linking. 1 million cells of DP were isolated from C57BL/6 thymocytes.
The TCF1 ChIP DNA fragments were processed for ChIPseq with Illumina adapters and Illumina primers (Primer1.1 and Primer2.1). After adapter ligation, DNAs were PCR-amplified for 17 cycles and library fragments of 300-500 bp were extracted from an agarose gel.

value: anti-TCF1 (SantaCruz, sc-13025)


title: DP_TCF1-ChIPseq

value: wild type

value: sorted CD4 CD8 double-positive  thymocytes


title: gd-Sox13hi_TCF1-ChIPseq


title: T5_20uM_6h

data_processing:
Library strategy: 3'-seq
Adaptor and low-quality sequences were trimmed from raw sequence reads using by PRINSEQ.
Trimmed sequence reads were aligned to hg19 (GRCh37) reference genome using the Bowtie2 with one mismatch allowed in a seed alignment during multiseed alignment.
Peaks of 3’Seq were identified from uniquely mapped reads using by MACS software.
Peak coordination between control and treatment samples was arranged by MAnorm. Peaks with less than 50 reads in all samples were discarded
Genome_build: hg19
Supplementary_files_format_and_content: bedGraph files were generated using MAnorm

extract_protocol:
Total RNA was extracted using an RNeasy Miniprep Kit (Qiagen).
Poly(A) mRNA was purified using Oligotex -dT30<Super> mRNA Purification Kit (Takara Bio., Japan, Shiga). Poly(A) mRNA was fragmented at 70°C for 5 min using RNA fragmentation buffer (Life Technologies) and first strand cDNA was synthesised using SuperScript Double-Stranded cDNA Synthesis Kit (Life Technologies) and P7-t25-vn oligo-dT primer. Subsequently, second strand cDNA was synthesised and then end-repaired, at 30°C for 20 min, using NEBNext End Repair Module (New England Biolabs, Ipswich, MA, USA). cDNA was purified using MinElute Reaction Cleanup Kit (Qiagen) and 100 pmol annealed P5-splinkerette ligated with cDNA for 2 h at 16°C. Ligated cDNA was purified and size-selected (~220 bp), using NucleoMag NGS Clean-up and Size Select Kit (Takara Bio). Samples were amplified with P5 and P7 primers using Phusion Hot Start Flex 2X Master Mix (New England Biolabs). After purification, the library was sequenced on the Illumina HiSeq 2000.


title: Input


title: T5_10uM_6h


title: DP_ATACseq

data_processing:
Library strategy: ATAC-seq
Sequence reads were obtained and mapped to a mouse reference genome (mm9) using the Illumina HiSeq 2000 Pipeline.
All reads mapping with two or fewer mismatches were retained, applied to a Cisgenome 2.0 integrated software system (Hongkai et, 2008) and converted to browser extensible data (BED) files for viewing the data in the UCSC or Cisgenome browser.
The parameter for ATACseq used in Cisgenome was Window Size W=100bp in One Sample Peak Calling.
Genome_build: mm9
Supplementary_files_format_and_content: BED files are tab-delimited files with one line for each genomic region

extract_protocol:
40 thousand CD24+CFPhi (SOX13hi) or CD24+CFPlo/- (SOX13lo) from gd+ T cells were sorted from thymocytes of SOX13 reporter mice or Sox13 transgenic SOX13 reporter mice or DP cells were isolated from C57BL/6 thymocytes.
For ATAC-Seq, harvested nuclei were subjected to the transposition reaction with Illumina transposase in 1x TD buffer and library fragments were amplified with indexing primers from Nextera kit.

value: double-positive thymocytes

value: GTAGAGGA


title: gd-Sox13tg_Sox13lo_ATACseq

source_name: mouse gd T cells

value: ACCACTGT


title: gd-Sox13tg_Sox13hi_ATACseq


title: gd-Sox13tg_Sox13lo_TCF1-ChIPseq


title: gd-Sox13hi_SOX13-ChIPseq

value: CAGATC

value: anti-Sox13 (Abcam, ab96776)


title: T5_2uM_6h

value: osteosarcoma


title: T4_20uM_6h


title: T5_5uM_6h


title: T5_0.5uM_6h


title: T4_5uM_6h


title: T4_10uM_6h


title: T4_2uM_6h


title: T4_0.5uM_6h


title: CPT_5uM_6h


title: CPT_10uM_6h


title: CPT_0.5uM_6h_mRNA


title: CPT_20uM_6h


title: CPT_2uM_6h


title: DMSO_6h


title: CPT_0.5uM_6h


title: BeWo IN-5

city: Shanghai

first: Jiuru

last: zhao

address: Hengshan Road 910#

department: Pathology and Bio-Bank

institute: International Peace Maternity and Child Health Hospital Affiliated to Shanghai Jiao Tong University School of Medicine

data_processing:
Base calling performed using Illumina Real Time Analysis (RTA).
Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to HG38 whole genome with Hisat2 (version:2.0.4).
Fragments Per Kilobase of exon per Megabase (FPKM) were calculated using edgeR-DESeq2.
Genome_build: HG38
Supplementary_files_format_and_content: FPKM and count values for each Sample

source_name: choriocarcinoma cells

growth_protocol: BeWo, JAR and JEG-3 cells were maintained in Dulbecco's modified Eagle's medium (DMEM, Invitrogen, NY, USA) in T25 flasks supplemented with 10% fetal bovine serum (FBS, Invitrogen) at 37°C.

extract_protocol:
Total RNA was extracted with the RNeasy Mini Kit (Qiagen, Hilden, Germany).RNA integrity was analyzed by an Agilent Bioanalyzer 2100 (Agilent technologies, Santa Clara, CA, US). Qualified total RNA was further purified by RNAClean XP Kit (Beckman Coulter, Kraemer Boulevard Brea, CA, USA) and RNase-Free DNase Set (Qiagen).
Libraries were prepared according to the Whole Transcriptome Sequencing Protocol (ShanghaiBio Corporation, Shanghai, China). Steps briefly included the followings: mRNA purification with RNA Purification Beads, mRNA fragmentation, synthesis of the first strand cDNA, synthesis of the second strand cDNA, end repair, 3' end adenylation, adapters ligation, PCR amplification,library quality control.Libraries were sequenced on the HiSeq X Ten (Illumina, San Diego, CA, USA) following the manufacturer's protocols.

treatment_protocol: Cells were plated in 24-well plates the day before transfection and grown to 70-80% conﬂuence. Cells were then transfected with 150 nM hsa-miR-371a-5p, hsa-miR-518a-3p or control inhibitor by using Lipofectamine 3000 (Invitrogen) according to the manufacturer’s instructions.At 36 h post transfection, cells were washed three times with PBS and harvested.

value: BeWo

value: choriocarcinoma cells

tag: transfected with

value: hsa-miR-518a-3p inhibitor


title: JEG-3 CK-5

value: control inhibitor


title: JAR IN-5

value: JAR

value: hsa-hsa-miR-518a-3p inhibitor


title: JEG-3 IN-5


title: gd-Sox13lo_ATACseq

value: sorted gd T thymocytes

value: TCRbeta KO.Sox13 ECFP KI/+

value: TAGGCATG


title: BeWo CK-5


title: gd-Sox13hi_ATACseq

value: CGTACTAG


title: JEG-3 CK-3


title: JEG-3 IN-3

value: hsa-miR-371a-5p inhibitor


title: JAR CK-3


title: BeWo CK-3


title: JAR CK-5


title: JAR IN-3


title: carrot leaf

city: State College

first: Michael

middle: J

last: Axtell

state: PA

address: University Park

department: Department of Biology

institute: Penn State University

data_processing:
The 3' adapter was trimmed with cutadapt (--discard-untrimmed -m 15).
The low quality reads were removed with FASTX-Toolkit (-q 20 -p 85 -Q 33 -v).
FastQC was used to verify the quality of the libraries before and after the pre-processing.
The abundance of the unique sequences was obtained with a customized Perl script
Genome_build: Cacao: v1.1 (http://www.cacaogenomedb.org/Tcacao_genome_v1.1); Spinach: v1 (http://www.spinachbase.org/cgi-bin/spinach/tool/download.cgi); Carrot: v2.0 (Phytozome v12)
Supplementary_files_format_and_content: Tab-delimited text files contain two columns: the first column is the sequence of the unique, non-redundant sRNA read, the second column is its total raw abundance

organism: Daucus carota

source_name: whole leaf

extract_protocol:
A pool of leaves or roots was flash-frozen in liquid nitrogen and stored at -80 degrees C. Total RNA was extracted from frozen tissue using Trizol for spinach and carrot or Purelink (ThermoFisher) for cacao.
The libraries were prepared with NEBNext® Small RNA Library Prep Set for Illumina® and sequenced on an Illumina Hiseq2500 platform by the Pennsylvania State University Genomics Core Facility

tag: cultivar

value: Burpee wt

tag: growing conditions

value: control conditions

tag: developmental stage

value: 5-weeks-old plants


title: carrot root

source_name: whole root

value: 6-weeks-old plants


title: SS5

city: Lanzhou

first: y

middle: zun

last: qiang

state: Gansu Province

address: No. 1 Yingmen village, Anning District

institute: College of Animal Science and Technology

data_processing:
Fastq format raw reads (raw data) were handled through in-house perl scripts. Clean reads (clean data) were gained by removing adapters, ploy-N and low quality reads from raw reads (raw data). Meanwhile, Q20, Q30 and GC content of the clean data were evaluated. The paired-end clean reads were mapped to the pig genome sequence assembly (Sscrofa 10.2) with Tophat (v2.0.9) software.
CNCI, CPC, PFAM and phyloCSF, were used to obtain the candidate lncRNA. Firstly, transcripts without coding potential were achieved using any of the four tools with earlier described instructions. Next, those without coding potential shared by four tools were screened as the candidate lncRNAs for subsequent research.
The genes expression level of both lncRNAs and protein-coding in each sample was calculated by FPKM (fragments per kb for a million reads) evaluated using Cuffdiff (v2.1.1)
To explore transcripts conservation, the Phast (v1.3) software was widely used for phylogenetic analysis and thus phastCons expression.
Gene Ontology (GO) enrichment analysis of differentially expressed genes or lncRNA target genes were implemented by the GOseq R package. KOBAS software was performed to test the statistical enrichment of differential expression genes or lncRNA target genes in KEGG pathways.
Coding genes 10k/100k upstream and downstream of lncRNA were treated as the cis target gene. Then, the trans role of lncRNA is to identify using the expression level.
Genome_build: Sus scrofa 10.2
Supplementary_files_format_and_content: Tab-delimited text file includes FPKM values for each Sample

organism: Sus scrofa

source_name: Spleen

extract_protocol:
Spleen were removed, flash frozen and  total RNA was extracted from each sample using TRIzol reagent (Invitrogen, Carlsbad, CA, USA).
RNA libraries were prepared for sequencing using standard Illumina protocols

tag: breed

value: Y x L

tag: age

value: 7-day old

tag: infection

value: Clostridium perfringens type C

tag: group

value: SS

value: spleen


title: cacao leaf

organism: Theobroma cacao

source_name: immature green leaf stage, tip of the leaves

value: Scavina 6 wt

value: tree


title: spinach leaf 1

organism: Spinacia oleracea

source_name: tip of the leaves

value: sp75 wt


title: SS4


title: SS2


title: SR5

value: SR


title: SS3


title: SR4


title: SR3


title: SR1


title: SC5

value: SC


title: BeWo IN-3

value: BeWo

tag: cell type

value: choriocarcinoma cells


title: SC1


title: SC2


title: SC4


title: d7_HiC_rep2

status: Public on Oct 31 2018

city: Cambridge

first: John

middle: Edward

last: Froberg

address: 7 Divinity Avenue

department: Stem Cell & Regenerative Biology

institute: Harvard University

data_processing:
RNA-seq: RNA-seq reads were aligned to the cas (Xa) and mus (Xi) genomes allele-specifically using a previously published pipeline (Kung et al., Molecular Cell 2015)(GSE58242). Following alignment, gene expression levels for each gene were defined using HOMER. Differential expression and fold changes between conditions were calculated using DESeq2. We plotted the cumulative distributions of fold changes for autosomal and X-linked genes and evaluated the significance of any differences between the distributions of the fold changes using the Kolmogorov-Smirnov (KS) test. To examine allele-specific expression from the Xa and the Xi, we summed together allelic reads across both biological replicates and filtered for genes with at least 12 allelic reads in both wild-type and Dxz4∆/∆:FirreXi∆/+and fpm > 0 in all replicates. We also used RNA-seq done in pure hybrid mus or cas fibroblasts to identify and eliminate genes that have incorrect SNP information. We defined escapee genes in a particular condition as genes where at least 10% of allelic reads came from the Xi in either replicate of that condition. We plotted the distribution of expression levels from the Xi (Xi/(Xi+Xa) read counts) for all genes passing our filtered for each replicate. We evaluated the significance in differences of the mean expression level from the Xi using the Wilcoxon Signed Rank Test with Bonferroni correction for multiple hypothesis testing.
ATAC-seq: Attack seq alignment to mm9 was performed exactly as ChIP-seq alignment was performed in (Minajigi et al., Science 2015) (GSE67516). Peaks were called using macs2 with default parameters. Biallelic peaks were identified as peaks with at least 10 alleleic reads in a sample and an Xi:Xa ratio greater than 1/3. Xi-specific peaks were defined as peaks with at least 10 allelic reads and a Xi:Xa ratio less than 1/3. To test whether Xi-specific peaks in wild-type are “restored” (that is: acquire appreciable accessibility on the Xi) in either the Dxz4 or Firre deletion, we plot the wild-type Xa reads on the x-axis and the deletion Xi reads on the y-axis and identify peaks where the deletion Xi/wild-type Xa ratio is greater than ½ (these are peaks where the deletion accessibility level reaches at least half the wild-type accessibility ratio). We also examine the biallelic peaks and plot the wild-type Xi reads on the x-axis and the deletion Xi reads on the y-axis to determine whether the accessibility on the Xi changes for the peaks that are bi-allelic in wild-type.
Hi-C: Hi-C alignment to mm9 was performed according to the method of (Minajigi et al., Science 2015)(GSE67516) The allele-specific Hi-C reads were filtered for quality and uniqueness with HOMER. Custom scripts were used to convert HOMER tag directories into the format accecpted by Juicebox; contact maps were generated using the Juicer tools ‘pre’ command. All Hi-C contact maps visualized in this study are KR-normalized contact maps generated by Juicebox.
Hi-C^2: Reads of each pair were individually mapped to the mus and cas reference genomes using novoalign and merged into Hi-C summary files and filtered using HOMER as previously described (Minajigi et al., Science 2015). For the chrX:70,370,161-71,832,975 captures, 3-4% of mapped and paired reads fell within the target region (0.05% expected based on size of capture region versus genome) and for the chrX:71,832,976-73,511,687 captures, 1-2% of mapped and paired reads fell within the target region (0.06% expected based on size of capture region versus genome). To avoid computational complexities arising from normalization of sparse, non-enriched regions in the Hi-C contact map, only Hi-C interactions falling within the capture region were analyzed further. For each capture, a custom script was used to pull out the filtered Hi-C interactions falling within the target region from the HOMER tag directories. Hi-C contact maps of the capture regions were then generated from these HOMER tags using the ‘pre’ command of Juicer tools. The resulting Hi-C contact maps in .hic format were visualized and normalized with the ‘Coverage (Sqrt)’ option in Juicebox.
4C: 4C analysis was performed using the previously published pipeline in (Chu et al., NSMB 2017) (GSE69887).
Genome_build: mm9
Supplementary_files_format_and_content: bedGraph files display fragment counts per million reads passing filter for 4C experiments. bigWig files display fpm-normalized ATAC-seq coverage. .hic files can be used to display and generate Hi-C contact maps using the Juicebox toolkit. For bedGraph and bigWig files, "comp" tracks are generated using all unique reads, "mus" tracks are generated using mus-specific reads, "cas" tracks are generated using cas-specific reads and "reps" tracks are generated using non-unique reads (reads with multiple alignments are randomly assigned to one position). genetable*.xlsx files are generated from homer and contain fragment count information for each gene in each experiment.

source_name: mESC

extract_protocol: We used the in situ Hi-C method of (Rao et al. Cell 2014) to prepare all libraries, using 5-10 million cells. Importantly, we sequenced 20-40 million reads per library. This is a lower sequencing depth than many published Hi-Cs, however since the megadomains are large and prominent feature of the organization of the Xi, this depth is appropriate for detecting the megadomains efficiently and economically.

tag: strain

value: CAST/Ei x 129/Sv/Jae

value: mESC (Tsix-stop)

value: WT

tag: time


title: spinach leaf 2

value: control conditions

value: 3-weeks-old plants


title: d10rep2_WT_cntrl_HiC_rep3


title: SC3

value: Y x L


title: d3_HiC_rep1


title: d3_HiC_rep2


title: SS1

value: 7-day old


title: Xist+Pfib_TgHiC

source_name: fibroblast

value: male immortalized fibroblast

value: Xist Tg


title: d7_HiC_rep1


title: d10rep1_WT_cntrl_HiC_rep2


title: ∆Dxz:∆Firre_HiC_rep1


title: WT_cntrl_HiC_rep1


title: d10TST_DXZ4_Cap_rep2

data_processing:
Library strategy: HiC^2
RNA-seq: RNA-seq reads were aligned to the cas (Xa) and mus (Xi) genomes allele-specifically using a previously published pipeline (Kung et al., Molecular Cell 2015)(GSE58242). Following alignment, gene expression levels for each gene were defined using HOMER. Differential expression and fold changes between conditions were calculated using DESeq2. We plotted the cumulative distributions of fold changes for autosomal and X-linked genes and evaluated the significance of any differences between the distributions of the fold changes using the Kolmogorov-Smirnov (KS) test. To examine allele-specific expression from the Xa and the Xi, we summed together allelic reads across both biological replicates and filtered for genes with at least 12 allelic reads in both wild-type and Dxz4∆/∆:FirreXi∆/+and fpm > 0 in all replicates. We also used RNA-seq done in pure hybrid mus or cas fibroblasts to identify and eliminate genes that have incorrect SNP information. We defined escapee genes in a particular condition as genes where at least 10% of allelic reads came from the Xi in either replicate of that condition. We plotted the distribution of expression levels from the Xi (Xi/(Xi+Xa) read counts) for all genes passing our filtered for each replicate. We evaluated the significance in differences of the mean expression level from the Xi using the Wilcoxon Signed Rank Test with Bonferroni correction for multiple hypothesis testing.
ATAC-seq: Attack seq alignment to mm9 was performed exactly as ChIP-seq alignment was performed in (Minajigi et al., Science 2015) (GSE67516). Peaks were called using macs2 with default parameters. Biallelic peaks were identified as peaks with at least 10 alleleic reads in a sample and an Xi:Xa ratio greater than 1/3. Xi-specific peaks were defined as peaks with at least 10 allelic reads and a Xi:Xa ratio less than 1/3. To test whether Xi-specific peaks in wild-type are “restored” (that is: acquire appreciable accessibility on the Xi) in either the Dxz4 or Firre deletion, we plot the wild-type Xa reads on the x-axis and the deletion Xi reads on the y-axis and identify peaks where the deletion Xi/wild-type Xa ratio is greater than ½ (these are peaks where the deletion accessibility level reaches at least half the wild-type accessibility ratio). We also examine the biallelic peaks and plot the wild-type Xi reads on the x-axis and the deletion Xi reads on the y-axis to determine whether the accessibility on the Xi changes for the peaks that are bi-allelic in wild-type.
Hi-C: Hi-C alignment to mm9 was performed according to the method of (Minajigi et al., Science 2015)(GSE67516) The allele-specific Hi-C reads were filtered for quality and uniqueness with HOMER. Custom scripts were used to convert HOMER tag directories into the format accecpted by Juicebox; contact maps were generated using the Juicer tools ‘pre’ command. All Hi-C contact maps visualized in this study are KR-normalized contact maps generated by Juicebox.
Hi-C^2: Reads of each pair were individually mapped to the mus and cas reference genomes using novoalign and merged into Hi-C summary files and filtered using HOMER as previously described (Minajigi et al., Science 2015). For the chrX:70,370,161-71,832,975 captures, 3-4% of mapped and paired reads fell within the target region (0.05% expected based on size of capture region versus genome) and for the chrX:71,832,976-73,511,687 captures, 1-2% of mapped and paired reads fell within the target region (0.06% expected based on size of capture region versus genome). To avoid computational complexities arising from normalization of sparse, non-enriched regions in the Hi-C contact map, only Hi-C interactions falling within the capture region were analyzed further. For each capture, a custom script was used to pull out the filtered Hi-C interactions falling within the target region from the HOMER tag directories. Hi-C contact maps of the capture regions were then generated from these HOMER tags using the ‘pre’ command of Juicer tools. The resulting Hi-C contact maps in .hic format were visualized and normalized with the ‘Coverage (Sqrt)’ option in Juicebox.
4C: 4C analysis was performed using the previously published pipeline in (Chu et al., NSMB 2017) (GSE69887).
Genome_build: mm9
Supplementary_files_format_and_content: bedGraph files display fragment counts per million reads passing filter for 4C experiments. bigWig files display fpm-normalized ATAC-seq coverage. .hic files can be used to display and generate Hi-C contact maps using the Juicebox toolkit. For bedGraph and bigWig files, "comp" tracks are generated using all unique reads, "mus" tracks are generated using mus-specific reads, "cas" tracks are generated using cas-specific reads and "reps" tracks are generated using non-unique reads (reads with multiple alignments are randomly assigned to one position). genetable*.xlsx files are generated from homer and contain fragment count information for each gene in each experiment.

extract_protocol: HYbrid Capture Hi-C (Hi-C2) probes were designed and hybridization to in-situ Hi-C libraries carried out as described previously (Sanborn et al., PNAS 2015). Probe sets were designed to enrich interactions in two regions of interest: chrX:70,370,161-71,832,975 and chrX:71,832,976-73,511,687 (mm9). Briefly, 120 bp probes were designed around the MboI restriction sites of the regions of interest as previously described 6 and custom synthesized pools of single stranded oligodeoxynucleotides ordered from CustomArray, Inc. (Bothell, WA). Single stranded DNA oligos were amplified and biotinylated in a MAXIScript T7 transcription reaction (Ambion). The resulting biotinylated RNA probes were hybridized to 250-300 ng of in situ Hi-C libraries for 24 hours at 65C. DNA hybridized to the RNA probes was pulled down by streptavidin beads (Dynabeads MyOne Streptavidin C1, Life Technologies), washed, and eluted as described (Sanborn et al., 2015). The resulting DNA was desalted using a 1X SPRI cleanup and amplified with Illumina primers for 18 cycles to prepare for sequencing.


title: FirreXi∆/+_D1_HiC_rep1

value: FirreXi{delta}/+


title: d3TST_DXZ4_Cap_rep2


title: d0TST_DXZ4_Cap_rep2


title: d7TST_MeCP2_Cap_rep2


title: d10TST_MeCP2_Cap_rep2


title: WT_Xyfib_TgHiC

extract_protocol: We previously developed a modified 4C protocol (Chu et al., NSMB 2017)  to examine chromatin conformation from repetitive viewpoints. Our protocol has several advantages over existing 4C profiles: 1.) It sequences the genomic region amplified by the 4C primers, ensuring that on-target priming events can be identified and filtered from numerous off-target priming events 2.) Sequencing the viewpoint allows every read to be assigned to a particular allele if the viewpoint is near a variant, 3.) We use a random barcode to identify PCR duplicates, which previously has not been possible in 4C experiments. We performed our modified 4C using the protocol and analysis pipeline previously described for viewpoints within PAR-TERRA repeats (Chu et al., 2017). We used it for several viewpoints within Firre and Dxz4. Some viewpoints were in the core tandem repeats. For these viewpoints, we use the read outside the viewpoint for allelic determination. Others were in unique regions near the tandem repeats; for these we could use known variants to assign every read to the Xa or the Xi. We performed our analysis in two fibroblast lines, one where the mus X is inactive (mus Xi cas Xa), the other where the cas X is inactive (mus Xa cas Xi).


title: XPDXZ4.4fib_TgHiC_2days

value: Xist+Dxz4 Tg (+dox 2 days)


title: d0_HiC_rep2


title: d0TST_MeCP2_Cap_rep2


title: d0_HiC_rep1


title: d10TST_DXZ4_Cap_rep1


title: d3TST_MeCP2_Cap_rep2


title: d7TST_DXZ4_Cap_rep1


title: FirreXi∆/+_E9_HiC


title: d0TST_DXZ4_Cap_rep1


title: d7TST_MeCP2_Cap_rep1


title: d3TST_MeCP2_Cap_rep1


title: ∆∆Dxz4_HiC_rep1


title: d10TST_MeCP2_Cap_rep1


title: SR2

value: Clostridium perfringens type C

value: spleen


title: d0TST_MeCP2_Cap_rep1


title: rel_2 RNA-Seq

city: Bad Nauheim

first: Carsten

last: Kuenne

address: Ludwigstrasse 43

department: Bioinformatics

country: Germany

institute: Max Planck Institute for Heart and Lung Research

data_processing:
Raw reads were assessed for quality, adapter content and duplication rates with FastQC version 0.11.2.
Reaper version 13-100 was employed to trim reads after a quality drop below a mean of Q20 in a window of 10 nucleotides. Only reads between 30 and 150 nucleotides were cleared for further analyses.
Trimmed and filtered reads were aligned versus the Ensembl mouse genome version mm10 (GRCm38) using STAR 2.4.0a with the parameter “--outFilterMismatchNoverLmax 0.1” to increase the maximum ratio of mismatches to mapped length to 10%.
The number of reads aligning to genes was counted with featureCounts 1.4.5-p1 tool from the Subread package. Only reads mapping at least partially inside exons were admitted and aggregated per gene. Reads overlapping multiple genes or aligning to multiple regions were excluded.
Raw counts were normalized using DESeq2.
Genome_build: mm10
Supplementary_files_format_and_content: matrix.txt contains DESeq2 normalized count values for all genes overlapped by at least one read.

source_name: Murine ES cells

growth_protocol: Murine embryonic stem cells (mES-D3) were purchased from ATCC® and were adapted in culture without feeder layer. mES were cultured in ground state medium (GS); spontaneous differentiation medium (DM); and mesendodermal medium achieved adding 250 μM Diethylenetriamine/nitric oxide adduct (DETA/NO-SIGMA-ALDRICH®) as nitric oxide exogenous source (NO).

extract_protocol:
Total RNA for transcriptome analysis was isolated with miRNeasy Micro Kit (Qiagen) from one six mm2 dishes per sample. The integrity of RNA was checked on Bioanalyzer 2100 (Agilent), and 5μg of RNA with RIN >9 were used for ribosomal depletion using the Ribo-Minus Eukaryote Kit v2 (Invitrogen). Following modifications to the standard RNA-seq Library protocol was performed
Next generation sequencing was performed on Ion Torrent Proton sequencing platform (Thermo Fisher) using the Ion Total RNA-Seq Kit v2 (Thermo Fisher) with minor modifications. Total RNA for transcriptome analysis was isolated with miRNeasy Micro Kit (Qiagen) from one six mm 2 dishes per sample. The integrity of RNA was checked on Bioanalyzer 2100 (Agilent), and 5μg of RNA with RIN >9 were used for ribosomal  depletion using the Ribo-Minus Eukaryote Kit v2 (Invitrogen). Following modifications to the standard RNA-seq Library protocol were performed: fragmented RNA was concentrated to 3μl with SpeedVac (Eppendorf) for 10-15min, and all 3μl were used for further steps. The number of amplification cycles was reduced to 8-12 cycles resulting in lower PCR duplication levels without any influence to quality/contribution of obtained reads. To maximize data, recovery libraries were size selected using the LabChipXT system (Perkin Elmer) with an isolation window between 180-270bp (corresponding to 60-150bp insert size). Obtained RNA libraries were quantified on Qubit 2.0 and diluted to 100 pM and used in a final concentration of 10 pM for template preparation on Ion OneTouch2 instrument (Thermo Fisher). For each run on the PI Ion Torrent V2 Chip, 2 RNA libraries were pooled in equimolar ratios to obtain between 37-63M raw reads per sample.

treatment_protocol: 24 h treatment in GS; DM; and NO. GS cultures were perfomed in NDiff N2B27 media (Stem Cells, Inc.; scs-sf-nb-02) in the presence of the following three inhibitors (2i/L): 1 μM PD0325901 MEK inhibitor (SIGMA-ALDRICH®), 3 μM CHIR99021 GSK-3 inhibitor XVI (Millipore) and 20 ng/mL LIF (Millipore). DM cultures were performed in DMEM with pyroxidine/HCl (SIGMA-ALDRICH®), supplemented with 1 g/L glucose, 4 mmol/L glutamine, 0.1 mmol/L 2-mercaptoethanol (ROTH) and 10% FBS Pre-tested for ES cells (PAA). NO cultures were performed in DMEM with pyroxidine/HCl (SIGMA-ALDRICH®), supplemented with 1 g/L glucose, 4 mmol/L glutamine, 0.1 mmol/L 2-mercaptoethanol (ROTH), 10% FBS Pre-tested for ES cells (PAA) and 250 μM Diethylenetriamine/nitric oxide adduct (DETA/NO-SIGMA-ALDRICH®).

tag: medium

value: DM = Spontaneous differentiation medium

tag: cell passages


title: rel_3 RNA-Seq


title: det_2 RNA-Seq

value: NO = Mesendodermal medium


title: rel_1 RNA-Seq


title: ctrl_1 RNA-Seq

value: GS = Ground state


title: det_1 RNA-Seq


title: zeb1_2 ChIP-Seq

description: zeb1_2 ChIP-Seq ChIP-Seq

data_processing:
The quality of raw reads was assessed using FastQC version 0.11.2.
Reads were trimmed for a minimum average quality of Q20 in a window of 20 nucleotides using Reaper 13.274 from the EBI Kraken package. Only reads between 20 and 150 nucleotides were cleared for further analysis.
To normalize all samples to the same sequencing depth, 30 million reads per sample were randomly selected for further analysis. These were mapped versus the mm10 (GRCm38) version of the mouse genome with STAR 2.4.2a 54 using only unique alignments to exclude reads with unclear placing (--outFilterMismatchNoverLmax 0.1 --alignIntronMin 2 --alignIntronMax 1 --alignEndsType EndToEnd --outFilterMultimapNmax 1).
The reads were deduplicated using Picard 1.136 to avoid PCR artifacts leading to multiple copies of the same original fragment.
The ENCODE peak caller PeakRanger 1.18 58 was employed in ccat-mode to accommodate for broad peaks. Significant peaks were deemed to show at least 20 treatment reads, a minimum enrichment of treatment versus input reads of 2-fold, and a maximum FDR of 0.05.
Peaks overlapping ENCODE blacklisted regions (known misassemblies, satellite repeats) were excluded.
Only those peaks that were present in at least two replicates (overlap >= 1 nucleotide) were permitted for further analysis.
To be able to compare peaks in different samples to assess reproducibility, the resulting three lists of significant peaks (one per treatment replicate) were overlapped and unified to represent identical regions. Input and treatment read coverage were recomputed for the unified peaks for each sample and normalized to the same depth using factor normalization. For each peak, input reads were subtracted from treatment reads to correct for mapping irregularities.
The background corrected counts were then submitted to DESeq for further normalization considering differences of sequencing depth between samples and outlier correction.
Unified peaks were annotated with Homer 4.7 based on data from RefSeq mm10. Peaks were determined to overlap a promoter if their center was located less than 5kb up- or downstream from the TSS of the respective gene.
Genome_build: mm10
Supplementary_files_format_and_content: peaks.txt contains averaged values of unified peaks per sample (treatment reads, input reads, and enrichment).

growth_protocol: Murine embryonic stem cells (mES-D3) were purchased from ATCC® and were adapted in culture without feeder layer. mES were cultured in ground state medium (GS).

extract_protocol:
mES cultured in GS underwent cross-linking with 1% formaldehyde (Applichem) and quenching with 10X Glycine (Millipore) as well as nuclear extraction. Then, chromatin solution was sheared by Bioruptor® Plus (Diagenode) to obtain about 200bp fragments for Sequencing. Immunoprecipitation protocol was performed after overnight incubation at 4°C with 8 μg of Zeb1 (H-102 from Santa Cruz) antibody with Magna-ChIP™ A/G (Millipore) kit according to manufacturer's instruction. DNA fragments were recovered and analysed by Sequencing.
ChIP samples were processed for sequencing on the Ion Torrent platform using a modified DNA Library protocol based on the Ion Xpress Plus Fragment Library Kit (Thermo Fisher). 1-10ng dsDNA were used as starting material. After end repair of DNA fragments, Ion Torrent specific and barcoded DNA, Adapters were ligated and covalently bound by nick translation, followed by amplification with 18 cycles using the components of the Ion Xpress Plus Fragment Library Kit. The final SPRI bead cleanup was performed as double size selection with 0.7x DNA/Bead ratio followed by 0.8x DNA/bead ratio. QC of obtained libraries was done on Bioanalyzer 2100 (Agilent) and quantitation was measured on Qubit 2.0 with HS DNA Assay. Libraries were diluted to a final concentration of 10 pM and used in equimolar ratios for template preparation on Ion Touch 2 instrument. Libraries were pooled on PI Ion Torrent V2 Chips to obtain a minimum amount of 20M raw reads per sample.

treatment_protocol: GS cultures were perfomed in NDiff N2B27 media (Stem Cells, Inc.; scs-sf-nb-02) in the presence of the following three inhibitors (2i/L): 1 μM PD0325901 MEK inhibitor (SIGMA-ALDRICH®), 3 μM CHIR99021 GSK-3 inhibitor XVI (Millipore) and 20 ng/mL LIF (Millipore).

tag: experiment

value: ChIP-Seq Zeb1

value: Zeb1 (SantaCruz; clone H-102; #SC25388)


title: zeb1_3 ChIP-Seq

description: zeb1_3 ChIP-Seq ChIP-Seq


title: zeb1_1 ChIP-Seq

description: zeb1_1 ChIP-Seq ChIP-Seq


title: d7TST_DXZ4_Cap_rep2

value: CAST/Ei x 129/Sv/Jae

value: mESC (Tsix-stop)

tag: genotype


title: ctrl_3 RNA-Seq


title: d3TST_DXZ4_Cap_rep1

value: WT


title: non-treated cardiomyocytes rep3

city: Tokyo

first: Seitaro

last: Nomura

state: Select a State or Province

address: 7-3-1, Hongo, Bunkyo-ku

department: Department of Cardiovascular Medicine

institute: The University of Tokyo

data_processing:
Reads were mapped to the rat genome (rn5) using Bowtie (version 1.1.1) with the parameters ‘-S -m 1 -l 36 -n 2 mm9’.
RPKM was calculated with reads mapped to the genome using DEGseq (version 1.8.0).
Genome_build: rn5
Supplementary_files_format_and_content: file includes RPKM values for each sample

organism: Rattus norvegicus

source_name: cardiomyocytes

growth_protocol: Primary neonatal rat cardiomyocytes were prepared from the ventricles of 1-day-old Wistar rats. The isolated and dispersed cardiac cells were incubated for 80 minutes to remove non-cardiomyocytes. The unattached viable cells, which were rich in cardiomyocytes, were cultured on gelatin-coated dishes at 37°C in DMEM media supplemented with 10% FCS for 24 hours.

extract_protocol:
RNA from cardiomyocytes was extracted using a RNeasy Mini Kit (Qiagen, Hilden, Germany) was used according to the manufacturer's protocol.
RNA sequencing libraries were generated with a TruSeq RNA Library Preparation Kit (Illumina, San Diego, CA, USA) according to the manufacture's protocol.

treatment_protocol: Cardiomyocytes were starved (0.1% FCS) for 6 hours and subsequently treated with vehicle or TAZ-K (10 µM) for 24 hours.

value: Primary neonatal rat cardiomyocytes

value: Wistar


title: ctrl_1 ChIP-Seq

description: ctrl_1 ChIP-Seq ChIP-Seq

value: ChIP-Seq Input


title: TAZ-K treated cardiomyocytes rep1


title: non-treated cardiomyocytes rep2


title: TAZ-K treated cardiomyocytes rep3


title: non-treated cardiomyocytes rep1


title: TAZ-K treated cardiomyocytes rep2


title: HFD_0h_LPS_rep3

city: Amsterdam

first: Menno

last: de Winther

address: Meibergdreef 9

department: Medical Biochemistry

country: Netherlands

institute: Academic Medical Center University of Amsterdam

data_processing:
Bases were called using Illumina CASAVA 1.8.2
Reads were aligned to the mouse genome mm10 by STAR 2.5.2b
BAM files were indexed and filitered on MAPQ > 15 with SAM Tools 1.3.1
Raw tag counts per gene were counted using HOMER2’s analyzeRepeats.pl script
Genome_build: mm10
Supplementary_files_format_and_content: matrix of read counts per gene

source_name: Peritoneal macrophages

extract_protocol:
RNA was extracted uisng the Qiagen RNAeasy mini kit
Libraries were constructed using the NuGen Ovation Universal RNA-seq kit

tag: tissue

value: Peritoneal macrophages

tag: diet

value: high fat

tag: Sex

value: Female


title: HFD_24h_LPS_rep1


title: HFD_0h_LPS_rep1


title: Chow_24h_LPS_rep3

value: chow


title: HFD_0h_LPS_rep2


title: HFD_24h_LPS_rep3


title: Chow_24h_LPS_rep2


title: det_3 RNA-Seq


title: Chow_24h_LPS_rep1


title: Chow_0h_LPS_rep2


title: Chow_0h_LPS_rep3


title: Chow_0h_LPS_rep1


title: ctrl_2 RNA-Seq


title: HFD_24h_LPS_rep2


title: HFD_4_heart

data_processing:
Raw reads were assessed for quality, adapter content and duplication rates with FastQC version 0.11.2.
Trimmomatic version 0.33 was employed to trim reads after a quality drop below a mean of Q20 in a window of 4 nucleotides. Only reads above 20 nucleotides were cleared for further analyses.
Trimmed and filtered reads were aligned versus the Ensembl mouse genome version mm10 (GRCm38) using STAR 2.4.2a with the parameter “--outFilterMismatchNoverLmax 0.1” to increase the maximum ratio of mismatches to mapped length to 10%.
The number of reads aligning to genes was counted with featureCounts 1.4.5-p1 tool from the Subread package. Only reads mapping at least partially inside exons were admitted and aggregated per gene. Reads overlapping multiple genes or aligning to multiple regions were excluded.
Raw counts were normalized using DESeq2.
Genome_build: mm10
Supplementary_files_format_and_content: matrix.txt contains DESeq2 normalized count values for all genes overlapped by at least one read. Normalized reads were rounded to full integer.

source_name: Murine heart

extract_protocol:
RNA was isolated from mice heart samples (4 wt, 4 HFD and 4 HFD + AA6) using the miRNeasy micro Kit (Qiagen) combined with on-column DNase digestion (DNase-Free DNase Set, Qiagen) to avoid contamination by genomic DNA.
For next generation sequencing (NGS) RNA was isolated from mice heart samples (4 wt, 4 HFD and 4 HFD + AA6) using the miRNeasy micro Kit (Qiagen) combined with on-column DNase digestion (DNase-Free DNase Set, Qiagen) to avoid contamination by genomic DNA. RNA and libraries integrity were verified with a BioAnalyzer 2100 (Agilent) or LabChip Gx Touch 24 (Perkin Elmer). 1 µg total RNA was used as input for Truseq Stranded mRNA Library preparation following the low sample protocol (Illumina). Sequencing was performed on the NextSeq500 instrument (Illumina) using v2 chemistry.

value: heart

value: high fat diet

tag: aa6 administration

value: no


title: CTR_1_heart

value: control


title: CTR_2_heart


title: CTR_3_heart


title: CTR_4_heart


title: HFD-AA6_3_heart

value: yes


title: HFD_1_heart


title: HFD_3_heart


title: HFD_2_heart


title: HFD-AA6_2_heart


title: HFD_3_muscle

data_processing:
Raw reads were assessed for quality, adapter content and duplication rates with FastQC version 0.11.2.
Trimmomatic version 0.33 was employed to trim reads after a quality drop below a mean of Q20 in a window of 4 nucleotides. Only reads above 20 nucleotides were cleared for further analyses.
Trimmed and filtered reads were aligned versus the Ensembl mouse genome version mm10 (GRCm38) using STAR 2.4.2a with the parameter “--outFilterMismatchNoverLmax 0.1” to increase the maximum ratio of mismatches to mapped length to 10%.
The number of reads aligning to genes was counted with featureCounts 1.4.5-p1 tool from the Subread package. Only reads mapping at least partially inside exons were admitted and aggregated per gene. Reads overlapping multiple genes or aligning to multiple regions were excluded.
Raw counts were normalized using DESeq2.
Genome_build: mm10
Supplementary_files_format_and_content: matrix.txt contains DESeq2 normalized count values for all genes overlapped by at least one read. Normalized counts were rounded to full integer.

source_name: Murine skeletal muscle

extract_protocol:
RNA was isolated from mice skeletal muscle (3 wt, 3 HFD and 3 HFD + AA6) using the miRNeasy micro Kit (Qiagen) combined with on-column DNase digestion (DNase-Free DNase Set, Qiagen) to avoid contamination by genomic DNA.
For next generation sequencing (NGS) RNA was isolated from mice skeletal muscle (3 control, 3 HFD and 3 HFD + AA6) using the miRNeasy micro Kit (Qiagen) combined with on-column DNase digestion (DNase-Free DNase Set, Qiagen) to avoid contamination by genomic DNA. RNA and libraries integrity were verified with a BioAnalyzer 2100 (Agilent) or LabChip Gx Touch 24 (Perkin Elmer). 1 µg total RNA was used as input for Truseq Stranded mRNA Library preparation following the low sample protocol (Illumina). Sequencing was performed on the NextSeq500 instrument (Illumina) using v2 chemistry.

value: skeletal muscle


title: HFD_2_muscle


title: HFD-AA6_4_heart


title: HFD-AA6_1_heart


title: CTR_1_muscle


title: HFD_1_muscle


title: HFD-AA6_2_muscle


title: CTR_3_muscle


title: HFD-AA6_3_muscle


title: HFD-AA6_1_muscle


title: SKOV3_8day_ssiCSC_2_RNA-seq

first: Yoonjung

last: Choi

address: 291 Daehak-ro, Yuseong-gu

institute: KAIST

data_processing:
Prepared libraries were sequenced on a HiSeq2500 with single-end method (50-bp reads).
The sequenced reads were aligned to the human genome (version: Hg19) using the STAR aligner (v.2.4.0)
The number of mapped reads was further analyzed using HOMER and DESeq
Genome_build: Hg19
Supplementary_files_format_and_content: RNA-seq : tab-delimited text files include RPKM values for each Sample

growth_protocol: Cancer cells (1 × 106) were seeded on poly(2,4,6,8-tetravinyl-2,4,6,8-tetramethyl cyclotetrasiloxane) (pV4D4)-coated plates and cultured in RPMI-1640, Dulbecco’s Modified Eagle Medium (DMEM) or Minimal Essential Medium (MEM), as appropriate, containing 10% (v/v) serum replacement (SR; Gibco), 1% (v/v) penicillin/streptomycin (P/S; Gibco), and L-glutamine at 37°C in a humidified 5% CO2 atmosphere.  For optimum spheroid growth, culture medium was refreshed every 2–3 days.

extract_protocol:
DNase-treated mRNA was purified using Magnetic mRNA Isolation Kit (NEB), and subjected to library preparation using NEXTflex™ Rapid Directional mRNA-Seq Kit (BIOO) following the manufacturer’s instructions.
mRNA-seq libraries were made using NEXTflexTM Rapid RNA-Seq kit (cat. 5138) from isolated mRNA.

value: ovarian cancer cell lines


title: SKOV3_8day_ssiCSC_1_RNA-seq


title: SKOV3_0day_2_RNA-seq


title: HT1197_Pano_B

city: Salt Lake City

first: Sumati

last: Gupta

state: Utah

address: 2000 Circle of Hope

department: Medicine

institute: Huntsman Cancer Institute

data_processing:
Fastq sequences were aligned with Novoalign (v. 2.8) against the hg38 genome with splice junctions.
Alignments to splice junctions were converted to genomic coordinates with USeq SamTranscriptomeParser (v.8.8.8).
Alignments were counted over annotation using Subread featureCounts (v. 1.5.1) and Ensembl annotation (release 87). Genes with 10 or fewer counts in any sample were removed.
FPKM values were calculated from the counts using a custom script based on the reported gene length from featureCounts and the total number of counts per sample.
Genome_build: hg38
Supplementary_files_format_and_content: Raw alignment counts and converted FPKM values from the counts

source_name: HT1197_treated with panobinostat

growth_protocol: Human bladder carcinoma lines HT1197 from ATCC, were cultured at 37 degrees Celsius and 5% CO2 in DMEM media supplemented with 10% fetal bovine serum (FBS), 100 units/ml of penicillin, 100 ug/ml streptomycin and 0.2 mg/ml normocin.

extract_protocol:
RNA was extracted using an RNeasy kit (Qiagen, Valencia, CA, USA).
The molarity of adapter-modified molecules was defined by quantitative PCR using the Kapa Biosystems Kapa Library Quant Kit (cat#KK4824). Individual libraries were normalized to 10 nM and equal volumes were pooled in preparation for Illumina sequence analysis.

treatment_protocol: HT1197 cells were seeded in triplicate at a density of 1 X 10^6 in 10 cm dishes and treated the next day with vehicle (1% DMSO) or 2X cell line IC50 for Panobinostat and incubated for 48 hours.

tag: condition

value: treated

tag: cell line

value: bladder carcinoma


title: HT1197_Pano_C


title: HT1197_Pano_A


title: CTR_2_muscle


title: HT1197_C

value: untreated


title: SKOV3_0day_1_RNA-seq


title: HT1197_B


title: ND-CMSC_7

data_processing:
Raw reads were assessed for quality, adapter content and duplication rates with FastQC version 0.11.2.
Trimmomatic version 0.33 was employed to trim reads after a quality drop below a mean of Q20 in a window of 4 nucleotides. Only reads above 20 nucleotides were cleared for further analyses.
Trimmed and filtered reads were aligned versus the Ensembl human genome version hg19 (GRCh37) using STAR 2.4.2a with the parameter “--outFilterMismatchNoverLmax 0.1” to increase the maximum ratio of mismatches to mapped length to 10%.
The number of reads aligning to genes was counted with featureCounts 1.4.5-p1 tool from the Subread package. Only reads mapping at least partially inside exons were admitted and aggregated per gene. Reads overlapping multiple genes or aligning to multiple regions were excluded.
Raw counts were normalized using DESeq2.
Genome_build: hg19
Supplementary_files_format_and_content: matrix.txt contains DESeq2 normalized count values for all genes overlapped by at least one read. Normalized counts were rounded to full integer.

source_name: Human primary CMSC

growth_protocol: Primary human cardiac mesenchymal cells (CMSCs) were obtained from the auricles of non-diabetic (ND) and diabetic (D) donors. Cells were isolated and cultured in IMDM supplemented with 20% Hyclone serum, 1% Pen/Strep, 1% Glutamine and 10ng/ml bFGF

extract_protocol:
RNA was isolated from 14 independent human cell lines (7 ND- and 7-D-) using the miRNeasy micro Kit (Qiagen) combined with on-column DNase digestion (DNase-Free DNase Set, Qiagen) to avoid contamination by genomic DNA.
For next generation sequencing (NGS) RNA was isolated from 14 independent human cell lines (7 ND- and 7-D-) using the miRNeasy micro Kit (Qiagen) combined with on-column DNase digestion (DNase-Free DNase Set, Qiagen) to avoid contamination by genomic DNA. RNA and libraries integrity were verified with a BioAnalyzer 2100 (Agilent) or LabChip Gx Touch 24 (Perkin Elmer). 1 µg of total RNA was used as input for SMARTer Stranded Total RNA Sample Prep Kit - HI Mammalian (Clontech). Sequencing was performed on the NextSeq500 instrument (Illumina) using v2 chemistry.

tag: disesase state

value: ND = non-diabetic

tag: passages

value: Human cardiac mesenchymal cells


title: HT1197_A


title: ND-CMSC_5


title: ND-CMSC_4


title: ND-CMSC_1


title: D-CMSC_3

value: D = diabetic


title: D-CMSC_2


title: D-CMSC_1


title: ND-CMSC_3


title: D-CMSC_6


title: D-CMSC_7


title: ND-CMSC_6


title: C6_3

city: Parkville

first: Belinda

last: Phipson

state: VIC

address: 1G Royal Parade

country: Australia

institute: WEHI

data_processing:
Fastq files were generated using the bcl to fastQ converter 2.17.
The raw reads were mapped to the human genome (hg19) using the STAR aligner version 2.4.0h1 in the two pass mapping mode
The mapped reads were quantified at the gene level using featureCounts version 1.4.6 using GENCODE Release 19 comprehensive annotation
Genome_build: hg19
Supplementary_files_format_and_content: tab delimited text file with Gene symbol and Gene length in the first two columns, followed by 3 columns containing counts for each sample

source_name: Day 25 kidney organoid derived epithelium

growth_protocol: Human iPSCs were cultured in a differentiation medium (8 uM CHIR99021 in APEL medium) for 4 days, followed by FGF9 (200 ng/mL) and Heparin (1 ug/mL) for 3days. Then, cells were dissociated into single cells and spun down at 400xg for 2min to form a pellet and then transferred onto a Transwell 0.4mm pore polyester membrane. Pellets were treated with 5 uM CHIR99021 in APEL for 1 h, and then cultured with FGF9 (200ng/mL) and heparin (1ug/mL) for 5 days, followed by another 12 days in APEL basal medium. iPSC-derived kidney organoids were dissociated by incubation with TrypLE select enzyme (Thermo Fisher Scientific) for 10 minutes at 37°C, with gentle pipetting every 2 minutes to aid dissociation. The epithelial fraction of the organoids was isolated by sorting for EPCAM+ cells using MACS.

extract_protocol:
RNA were extracted using QIAGEN RNeasy micro kit.
RNA libraries were prepared for sequencing using standard Illumina protocols

tag: clone

value: human iPSC line RG_0019.0149.C6

value: Epithelium from hiPSCs-derived kidney organoid (25 days differentiation)


title: D-CMSC_4


title: C6_1


title: ND-CMSC_2


title: THP1 TRIPZ-shRUVBL2 DOX-1

first: Owen

last: Williams

address: 30 Guilford Street

department: Cancer section

institute: UCL GOS ICH

data_processing:
Analysis performed with the BaseSpace® RNA Express app consisting of the following steps:
Alignment: Reads for each sample are aligned against the corresponding genome using the Spliced Transcripts Alignment to a Reference (STAR) software
Post-Alignment: After alignment, the BAM files are sorted, indexed, and bedGraph coverage files are created using bedtools
Read Counting: Gene expression is estimated at the gene level by counting the number of aligned reads that overlap each gene present in the annotation. The counting strategy is similar to htseq-count in the ‘union’ mode
Global Expression: The raw read counts are used as input for differential expression analysis using R and DESeq2
Pairwise Differential Expression: A new R script for the differential analysis is executed. This script loads the counts for all samples in this comparison and performs a pairwise differential expression analysis between them using DESeq2
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text file including average count values for each sample and statistical analysis.

growth_protocol: THP1 cells (monocyte cell line) (ATCC , Manassas, VA, USA) were maintained in culture in RPMI 1640 medium containing 10% fetal bovine serum, 100 units/ml penicillin and 100 ug/ml streptomycin at 37°C with 5% CO2.

extract_protocol:
Total RNA was extracted with RNeasy Plus Mini Kit according to manufacturers instructions
Indexed RNA libraries were prepared for sequencing using standard Illumina TruSeq RNA v2 protocols

treatment_protocol: TRIPZ-shRUVBL2 transduced THP1 cells were treated with either medium only or 1 μg/ml Doxycycline for 4 days

value: monocyte

tag: agent

value: doxycycline


title: THP1 TRIPZ-shRUVBL2 NO DOX-2

tag: cell type


title: THP1 TRIPZ-shRUVBL2 DOX-3


title: THP1 TRIPZ-shRUVBL2 DOX-2


title: THP1 TRIPZ-shRUVBL2 NO DOX-5


title: THP1 TRIPZ-shRUVBL2 NO DOX-1


title: THP1 TRIPZ-shRUVBL2 DOX-4


title: THP1 TRIPZ-shRUVBL2 NO DOX-3


title: C6_2


title: THP1 TRIPZ-shRUVBL2 NO DOX-4


title: LTL_S3

data_processing:
Fastq files were generated using the bcl to fastQ converter 2.17.
To obtain the processed counts file, counts_hg19.txt, the raw reads were mapped to the human genome (hg19) using the STAR aligner version 2.4.0h1 in the two pass mapping mode.
The mapped reads were quantified at the gene level using featureCounts version 1.4.6 using GENCODE Release 19 comprehensive annotation.
To obtain the processed counts file, counts_hg38.txt, first transcript level counts were estimated using Salmon v0.8.2, using the ENSEMBL GRCh38 version of the human transcriptome.
Transcript level counts were converted to gene level counts using the Bioconductor R package tximport v1.3.13.
Genome_build: hg19, hg38
Supplementary_files_format_and_content: File counts_hg19.txt is a tab delimited text file with Gene symbol and Gene length in the first two columns, followed by 3 columns containing counts for each sample.
Supplementary_files_format_and_content: File counts_hg38.txt is a tab delimited text file with ensemble gene id and the averaged gene length across all 3 samples in the first two columns, followed by 3 columns containing counts for each sample.

source_name: Day 25 kidney organoid derived proximal tubules

growth_protocol: Human iPSCs were cultured in a differentiation medium (8 uM CHIR99021 in APEL medium) for 4 days, followed by FGF9 (200 ng/mL) and Heparin (1 ug/mL) for 3days. Then, cells were dissociated into single cells and spun down at 400xg for 2min to form a pellet and then transferred onto a Transwell 0.4mm pore polyester membrane. Pellets were treated with 5 uM CHIR99021 in APEL for 1 h, and then cultured with FGF9 (200ng/mL) and heparin (1ug/mL) for 5 days, followed by another 12 days in APEL basal medium. iPSC-derived kidney organoids were dissociated by incubation with TrypLE select enzyme (Thermo Fisher Scientific) for 10 minutes at 37°C, with gentle pipetting every 2 minutes to aid dissociation. Proximal tubules were isolated by sorting for LTL+ cells using MACS.

extract_protocol:
RNA were extracted using QIAGEN RNeasy micro kit.
TruSeq stranded total RNA with RiboZero rRNA depletion

value: human iPSC line CRL1502 (clone C32)

value: Proximal tubules from hiPSCs-derived kidney organoid (25 days differentiation)


title: LTL_S2


title: D-CMSC_5


title: THP1 TRIPZ-shRUVBL2 DOX-5


title: d7_vial3_S12

description: hiPSCs-derived kidney organoid (7 days differentiation)

data_processing:
Fastq files were generated using the bcl to fastQ converter 2.17.
The raw reads were mapped to the human genome (hg19) using the STAR aligner version 2.4.0h1 in the two pass mapping mode
The mapped reads were quantified at the gene level using featureCounts version 1.4.6 using GENCODE Release 19 comprehensive annotation
Genome_build: hg19
Supplementary_files_format_and_content: tab delimited text file with Gene symbol and Gene length in the first two columns, followed by 12 columns containing counts for each sample

source_name: Day 7 kidney organoids

growth_protocol: Human iPSCs were cultured in a differentiation medium (8 uM CHIR99021 in APEL medium) for 4 days, followed by FGF9 (200 ng/mL) and Heparin (1 ug/mL) for 3days. Then, cells were dissociated into single cells and spun down at 400g for 2min to form a pellet and then transferred onto a Transwell 0.4mm pore polyester membrane. Pellets were treated with 5 uM CHIR99021 in APEL for 1 h, and then cultured with FGF9 (200ng/mL) and heparin (1ug/mL) for 5 days, followed by another 6 days in APEL basal medium.

tag: vial

value: vial 3


title: d18_vial3_S11

description: hiPSCs-derived kidney organoid (18 days differentiation)

source_name: Day 18 kidney organoids


title: LTL_S1


title: d18_vial2_S6

value: vial 2


title: d7_vial1_S4

value: vial 1


title: d18_vial1_S3


title: d18_vial2_S7


title: d7_vial2_S8


title: d0_vial1_S1

description: hiPSCs (0 days differentiation)

source_name: Day 0 human induced pluripotent stem cells


title: d0_vial3_S9

description: hiPSCs (0 days differentiation)


title: d7_batch4_S8

data_processing:
Fastq files were generated using the bcl to fastQ converter 2.17.
The raw reads were mapped to the human genome (hg19) using the STAR aligner version 2.4.0h1 in the two pass mapping mode
The mapped reads were quantified at the gene level using featureCounts version 1.4.6 using GENCODE Release 19 comprehensive annotation
Genome_build: hg19
Supplementary_files_format_and_content: tab delimited text file with Gene symbol and Gene length in the first two columns, followed by 10 columns containing counts for each sample

tag: batch


title: d0_vial2_S5

description: hiPSCs (0 days differentiation)


title: d7_batch5_S10


title: d18_vial1_S2


title: d18_batch4_S2


title: d18_batch5_S3


title: d18_batch4_S1


title: d7_batch4_S6


title: d18_batch5_S4


title: d18_batch5_S5


title: d18_vial3_S10


title: d18_batch3_vial3_S5

value: hiPSCs-derived kidney organoid (18 days differentiation)


title: d18_batch3_vial3_S6


title: d18_batch3_vial1_S1


title: d18_batch3_vial2_S4


title: d18_batch3_vial2_S3


title: d18_batch3_vial1_S2


title: d18_batch2_S4


title: d7_batch5_S9


title: d18_batch2_S3


title: d18_batch2_S1


title: d18_batch2_S2


title: C32_D4_3_S6

description:
Late primitive streak stage
RawCounts.txt

data_processing:
Fastq files were generated using the bcl to fastQ converter 2.17.
The raw reads were mapped to the human genome (hg19) using the STAR aligner version 2.4.0h1 in the two pass mapping mode
The mapped reads were quantified at the gene level using featureCounts version 1.4.6 using GENCODE Release 19 comprehensive annotation
Genome_build: hg19
Supplementary_files_format_and_content: tab delimited text file with Gene symbol and Gene length in the first two columns, followed by 6 columns containing counts for each sample

source_name: Day 4 differentiated cells

growth_protocol: Human iPSCs were cultured in a differentiation medium (8 uM CHIR99021 in APEL medium) for 4 days.

tag: media

value: 4 days 8uM CHIR99021 in APEL medium

tag: day

tag: Stage

value: late primitive streak


title: ∆∆Dxz4_HiC_rep2

data_processing:
RNA-seq: RNA-seq reads were aligned to the cas (Xa) and mus (Xi) genomes allele-specifically using a previously published pipeline (Kung et al., Molecular Cell 2015)(GSE58242). Following alignment, gene expression levels for each gene were defined using HOMER. Differential expression and fold changes between conditions were calculated using DESeq2. We plotted the cumulative distributions of fold changes for autosomal and X-linked genes and evaluated the significance of any differences between the distributions of the fold changes using the Kolmogorov-Smirnov (KS) test. To examine allele-specific expression from the Xa and the Xi, we summed together allelic reads across both biological replicates and filtered for genes with at least 12 allelic reads in both wild-type and Dxz4∆/∆:FirreXi∆/+and fpm > 0 in all replicates. We also used RNA-seq done in pure hybrid mus or cas fibroblasts to identify and eliminate genes that have incorrect SNP information. We defined escapee genes in a particular condition as genes where at least 10% of allelic reads came from the Xi in either replicate of that condition. We plotted the distribution of expression levels from the Xi (Xi/(Xi+Xa) read counts) for all genes passing our filtered for each replicate. We evaluated the significance in differences of the mean expression level from the Xi using the Wilcoxon Signed Rank Test with Bonferroni correction for multiple hypothesis testing.
ATAC-seq: Attack seq alignment to mm9 was performed exactly as ChIP-seq alignment was performed in (Minajigi et al., Science 2015) (GSE67516). Peaks were called using macs2 with default parameters. Biallelic peaks were identified as peaks with at least 10 alleleic reads in a sample and an Xi:Xa ratio greater than 1/3. Xi-specific peaks were defined as peaks with at least 10 allelic reads and a Xi:Xa ratio less than 1/3. To test whether Xi-specific peaks in wild-type are “restored” (that is: acquire appreciable accessibility on the Xi) in either the Dxz4 or Firre deletion, we plot the wild-type Xa reads on the x-axis and the deletion Xi reads on the y-axis and identify peaks where the deletion Xi/wild-type Xa ratio is greater than ½ (these are peaks where the deletion accessibility level reaches at least half the wild-type accessibility ratio). We also examine the biallelic peaks and plot the wild-type Xi reads on the x-axis and the deletion Xi reads on the y-axis to determine whether the accessibility on the Xi changes for the peaks that are bi-allelic in wild-type.
Hi-C: Hi-C alignment to mm9 was performed according to the method of (Minajigi et al., Science 2015)(GSE67516) The allele-specific Hi-C reads were filtered for quality and uniqueness with HOMER. Custom scripts were used to convert HOMER tag directories into the format accecpted by Juicebox; contact maps were generated using the Juicer tools ‘pre’ command. All Hi-C contact maps visualized in this study are KR-normalized contact maps generated by Juicebox.
Hi-C^2: Reads of each pair were individually mapped to the mus and cas reference genomes using novoalign and merged into Hi-C summary files and filtered using HOMER as previously described (Minajigi et al., Science 2015). For the chrX:70,370,161-71,832,975 captures, 3-4% of mapped and paired reads fell within the target region (0.05% expected based on size of capture region versus genome) and for the chrX:71,832,976-73,511,687 captures, 1-2% of mapped and paired reads fell within the target region (0.06% expected based on size of capture region versus genome). To avoid computational complexities arising from normalization of sparse, non-enriched regions in the Hi-C contact map, only Hi-C interactions falling within the capture region were analyzed further. For each capture, a custom script was used to pull out the filtered Hi-C interactions falling within the target region from the HOMER tag directories. Hi-C contact maps of the capture regions were then generated from these HOMER tags using the ‘pre’ command of Juicer tools. The resulting Hi-C contact maps in .hic format were visualized and normalized with the ‘Coverage (Sqrt)’ option in Juicebox.
4C: 4C analysis was performed using the previously published pipeline in (Chu et al., NSMB 2017) (GSE69887).
Genome_build: mm9
Supplementary_files_format_and_content: bedGraph files display fragment counts per million reads passing filter for 4C experiments. bigWig files display fpm-normalized ATAC-seq coverage. .hic files can be used to display and generate Hi-C contact maps using the Juicebox toolkit. For bedGraph and bigWig files, "comp" tracks are generated using all unique reads, "mus" tracks are generated using mus-specific reads, "cas" tracks are generated using cas-specific reads and "reps" tracks are generated using non-unique reads (reads with multiple alignments are randomly assigned to one position). genetable*.xlsx files are generated from homer and contain fragment count information for each gene in each experiment.

tag: strain

value: CAST/Ei x 129/Sv/Jae

value: mESC (Tsix-stop)

tag: genotype


title: d7_batch4_S7


title: C32_D4_2_S5


title: C32_D4_1_S4


title: C32_D0_2_S2

description:
Undifferentiated stage
RawCounts.txt

source_name: Day 0 hiPSCs

value: MEF-conditioned human ES cell medium

value: undifferentiated


title: C32_D0_1_S1

description:
Undifferentiated stage
RawCounts.txt


title: FirreXi∆/+_D1_HiC_rep2

value: FirreXi{delta}/+


title: XPDXZ4.4fib_TgHiC_9days

value: male immortalized fibroblast

value: Xist+Dxz4 Tg (+dox 9 days)


title: C32_D0_3_S3

description:
Undifferentiated stage
RawCounts.txt


title: W5-3

city: Pretoria

first: Stanford

last: Kwenda

state: Gauteng

address: Lunnon Road, Hilcrest

department: Microbiology and Plant Pathology Forestry and Agricultural Biotechnology Institute (FABI)

country: South Africa

institute: University of Pretoria

data_processing:
Sequencing of the cDNA libraries was performed using the Illumina HiSeq 2000 platform.
Illumina Casava1.7 software used for basecalling.
Filtered reads were mapped to the Pantoea ananatis LMG 2665T draft genome sequence (ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF_000661975.1_Pantoea_ananatis_LMG_2665/GCF_000661975.1_Pantoea_ananatis_LMG_2665_genomic.fna.gz) using SOAP2 (Li et al 2009)
Gene expression levels and differential gene expression was determined using calculated RPKM values as described by Mortazavi et al 2008
Genome_build: ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF_000661975.1_Pantoea_ananatis_LMG_2665/GCF_000661975.1_Pantoea_ananatis_LMG_2665_genomic.fna.gz
Supplementary_files_format_and_content: text files include RPKM values for each sample

organism: Pantoea ananatis LMG 2665

source_name: P. ananatis LMG 2665T virulent natural isolate from pineapple

growth_protocol: lag (OD600=0.2) and log (OD600=05) phase in RM media.

extract_protocol:
Total RNA was isolated using the RNeasy Mini Kit (Qiagen, GmbH, D-40724 Hilden) following instructions from the manufacturer
RNA libraries were prepared for sequencing using standard Illumina protocols

tag: growth phase

value: log phase

value: eanI/eanR wild type


title: M5-3

source_name: P. ananatis LMG 2665T ∆(eanI, eanR), resistant to kanamycin

value: eanI/eanR mutant


title: M5-1


title: M5-2


title: W5-2


title: W5-1


title: M2-3

value: lag phase


title: W2-3


title: M2-2


title: M2-1


title: W2-1


title: W2-2


title: ∆Dxz:∆Firre_HiC_rep2

source_name: mESC


title: L. lactis TOMSC161_early stationary_11

status: Public on Oct 30 2018

city: Thiverval-Grignon

first: Helene

last: Velly

address: 1 avenue Lucien Bretignieres

country: France

institute: INRA

data_processing:
The quality of sequencing reads was checked with FastqC software (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The read length was 50 bp on average and the sequencing depth ranged from 11 to 17 million reads per sample.
The obtained reads were then mapped onto the sequenced genome of L. lactis TOMSC161 (Velly et al. 2014c) using Bowtie 0.12.9 mapping software (Langmead et al. 2009), allowing mapping the first 35 bases, one mismatch and 100 alignments per read.
Only uniquely mapped reads were used for data analysis. Differential expression analysis was performed by comparing the number of mapped reads for each gene in the three replicates from the two different conditions (early vs. late stationary phase). First, the count table was filtered to select only data corresponding to CDS features that exhibited an average of more than 50 mapped reads in average. Data were then normalized using R and the DESeq2 package (Anders and Huber 2010). Finally, differentially expressed genes were identified according to the false discovery rate of the adjusted Benjamini Hochberg p-value (Benjamini and Hochberg 1995) implemented within the DESeq2 package and using a cutoff of adjusted p-value < 0.05.
Genome_build: EMBL database accession numbers CBUJ010000001 to CBUJ010000062; http://www.ncbi.nlm.nih.gov/assembly/GCF_000493355.1
Supplementary_files_format_and_content:
data_Norm_A30_C30.csv; normalized data using DESeq2
Diff_All_genes_A30_C30.csv; differential expression analysis of all genes
genes_DE_A30_C30.csv; significant differentially expressed genes

organism: Lactococcus lactis subsp. lactis

source_name: Lactic acid bacterium_early stationary

growth_protocol: The culture medium was composed of 60 g.L-1 lactose (VWR; Leuven, Belgium) and 15 g.L-1 yeast extract (BD; Sparks, MD, USA). After adjusting the pH to 6.8 with a 30% KOH solution, the medium was introduced into a 5-L working volume bioreactor (Biostat® A plus, Sartorius-Stedim; Aubagne, France) and sterilized at 120°C for 20 min. The inoculation was done at a low initial concentration of approximately 100 CFU.mL-1. The fermentation was performed at 30°C, pH 6.2, and with an agitation speed of 200 rpm to permit homogenization. The pH was controlled by the automatic addition of 15 N KOH solution (Merck; Darmstadt, Germany) in the bioreactor.

extract_protocol:
25 mL of cultures were harvested at the early and late stationary phase. One volume of ice-cold K-Buffer (20 mM Tris-HCl pH 7.5; 5 mM MgCl2; 20 mM NaN3) was then immediately added to two volumes of each cell suspension and gently mixed. Pellets were collected by centrifugation (15,000 g, 5 min, 4°C), rapidly frozen in liquid nitrogen and stored at -80°C.
For the extraction of total RNA, the previous method described by Sperandio et al. (2005) was used. Ribosomal RNA was then depleted using the Ribo-Zero Magnetic Kit (Epicentre; Madison, WI, USA) according to the manufacturer’s instructions. Finally, RNA concentration was quantified at 260 nm using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies; Wilmington, DE, USA) and RNA integrity was assessed by gel electrophoresis using an RNA 6000 NANO chip with the 2100 Bioanalyzer (Agilent; Palo Alto, CA, USA) according to the manufacturer’s instructions.
RNA-Seq libraries were constructed on cBot (Illumina; San Diego, CA, USA) using TruSeq SR Cluster Kit v3-cBot-HS (Illumina) and a single-end sequencing was performed on Hiseq 1000 (Illumina) using TruSeq SBS Kit v3-HS (Illumina) according to the manufacturer’s instructions.

tag: run (fermentation) number

tag: harvesting time

value: early stationary phase


title: L. lactis TOMSC161_early stationary_4


title: L. lactis TOMSC161_late stationary_6

source_name: Lactic acid bacterium_late stationary

value: late stationary phase


title: L. lactis TOMSC161_early stationary_13


title: L. lactis TOMSC161_late stationary_15


title: L. lactis TOMSC161_late stationary_10


title: LNCaP Vehicle-4

city: Houston

first: Lukas

last: Simon

address: 1 Baylor Plaza

department: THINC

institute: Baylor College of Medicine

description: Sample_12-LNV-4.Aligned.sortedByCoord.out.bam

data_processing:
Sequenced reads were mapped to human reference genome (hg38) using STAR (2.5.2a) with default parameters.
Aligned reads were summarized into gene counts using the featureCounts (v1.5.0) command of the Subread package with default parameters in conjunction with the human gencode annotation file (hg38 release 85).
Genome_build: hg38
Supplementary_files_format_and_content: tab-delimited text file containing raw read counts for all samples

growth_protocol: LNCaP cells were cultured in regular growth medium (RPMI1640 + 10% FCS + 1%P/S + 1% Glutamine)

extract_protocol:
RNA was harvested using Trizol reagent.
The TruSeq stranded RNA sample prep kit was used for library generation according to Illumina's protocol.

treatment_protocol: For samples 1-8, cells were transfected with either Allstar control siRNA or XBP1-specific siRNA. After two days, the cells were treated with 30 nM thapsigargin for 3 hours. For samples 9-16, LNCaP cells were treated with either DMSO or 10 μM MKC8866 for 24 h before 3h induction with 30 nM thapsigargin.

value: LNCaP

value: Human prostate cancer cells

tag: passage

tag: treated with

value: DMSO (vehicle) for 24hrs


title: LNCaP MKC8866-4

description: Sample_16-LN86-4.Aligned.sortedByCoord.out.bam

tag: cell line

value: 10 μM MKC8866 for 24hrs


title: LNCaP Vehicle-3

description: Sample_11-LNV-3.Aligned.sortedByCoord.out.bam


title: LNCaP Vehicle-2

description: Sample_10-LNV-2.Aligned.sortedByCoord.out.bam


title: LNCaP siXBP1-4

description: Sample_8-LNX1-4.Aligned.sortedByCoord.out.bam

tag: transfected with

value: XBP1-specific siRNA


title: LNCaP Vehicle-1

description: Sample_9-LNV-1.Aligned.sortedByCoord.out.bam


title: LNCaP siXBP1-3

description: Sample_7-LNX1-3.Aligned.sortedByCoord.out.bam


title: LNCaP MKC8866-1

description: Sample_13-LN86-1.Aligned.sortedByCoord.out.bam


title: LNCaP siXBP1-2

description: Sample_6-LNX1-2.Aligned.sortedByCoord.out.bam


title: LNCaP MKC8866-3

description: Sample_15-LN86-3.Aligned.sortedByCoord.out.bam


title: LNCaP siXBP1-1

description: Sample_5-LNX1-1.Aligned.sortedByCoord.out.bam


title: LNCaP siCtrl-2

description: Sample_2-LNC-2.Aligned.sortedByCoord.out.bam

value: Allstar control siRNA


title: LNCaP siCtrl-4

description: Sample_4-LNC-4.Aligned.sortedByCoord.out.bam


title: LNCaP siCtrl-1

description: Sample_1-LNC-1.Aligned.sortedByCoord.out.bam

value: human prostate cancer cells