title: Nitric oxide shock (InSPI2)

city: Liverpool

first: Jay

last: Hinton

address: Crown Street

department: Institute of Integrative Biology

institute: University of Liverpool

data_processing:
Reads were de-multiplexed and sequence reads were then mapped on the S. Typhimurium 4/74 reference genome using Segemehl with accuracy set to 100%. To increase mapping quality, unmapped reads were sequentially truncated by one nucleotide from the end of the read and were mapped again. This process was iterated until a minimal read length of 20 nucleotides or until a read mapped into a single location on the chromosome.
Genome_build: ASM18873v1, RefSeq Genome Accession: PRJNA56087 ID: 56087. Salmonella enterica subsp. enterica serovar Typhimurium str. 4/74. Richardson EJ et al., "Genome sequences of Salmonella enterica serovar typhimurium, Choleraesuis, Dublin, and Gallinarum strains of well- defined virulence in food-producing animals.", J Bacteriol, 2011 Apr 8;193(12):3162-3.
Supplementary_files_format_and_content: .gr files are provided showing uniquely mapped sequence reads (normalization). Ready to load into Integrated Genome Browser (IGB). The file consists of two columns showing nucleotide position on the chromosome and number of reads mapped at each location. "Plus" and "Minus" refer to the strands of the Salmonella chromosome. Technical replicates are re-seqeuenced cDNA libraries. Biological replicates are designated as "biorep".

organism: Salmonella enterica subsp. enterica serovar Typhimurium str. ST4/74

source_name: Total RNA from bacteria

growth_protocol: Cells were grown overnight in 5 ml Lennox (L-) broth (10 g/l tryptone, 5 g/l yeast extract, 5 g/l NaCl) and diluted the next morning (1:1,000) in 250 ml flasks in 25 ml L-broth at and grown 37°C and 220 rpm. A New Brunswick Innova 3400 water bath was used to grow all agitated bacterial cultures prior to RNA isolation. Bacteria were grown to early exponential growth phase (EEP; OD600 0.1), mid exponential growth phase (MEP; OD600 0.3), late exponential growth phase (LEP; OD600 1.0), early stationary phase (ESP, OD600 2.0) and late stationary phase (LSP, OD600 2.0 + 6h). Environmental shocks in L-broth were performed on MEP-grown bacteria as follows: Osmotic shock (NaCl shock), addition of NaCl to a final concentration of 0.3 M and continued growth for 10 min; iron limitation (LowFe2+ shock), addition of 2,2’-dipyridyl to a final concentration of 0.2 mM and continued growth for 10 min; cold shock, flasks were transferred to a second water bath incubator maintained at 15°C for 15 min at 220 rpm; mild acidic stress (pH5.8 shock) and strong acidic shock (pH3 shock), cells were pelleted for 5 min at 3230 x g, resuspended in pre-warmed (37°C) L-broth (adjusted to pH5.8 or pH3 with HCl) and grown for 10 min; anaerobic shock, 15ml culture were transferred into a pre-warmed (37°C) 15 ml centrifuge tube, screwed tight and incubated without agitation for 30 min; bile salt stress (Bile shock), addition of ox bile (sodium choleate) to a final concentration of 3% (w/v) and continued growth for 10 min. For growth at low temperature (25°C) an overnight culture of 5 ml L-broth grown at 37°C was diluted 1:1,000 in a 250 ml flask containing 25 ml L-broth and incubated in a water bath incubator at 25°C and 220 rpm and RNA was isolated at OD600 0.3. For temperature shifts (Temp10, Temp20), cells were grown at 25°C (water-bath, 220 rpm) until OD600 of 0.3 and then transferred to 37°C (water-bath, 220 rpm) and RNA was isolated after 10 and 20 min. For growth in anaerobic conditions (anaerobic growth), a 50 ml centrifuge tube was filled with L-broth and inoculated with 50 µl (1:1,000) of an overnight culture grown in 5 ml L-broth, screwed tight, incubated without agitation at 37°C and RNA was isolated from cells grown until OD600 0.3. For aerobic shock, 25ml of cells grown anaerobically as described above until OD600 0.3 were transferred to a 250 ml baffled flask, incubated in a water bath incubator at 37°C and 250 rpm, and RNA was isolated after 15 min. For growth in phosphate carbon nitrogen (PCN) minimal medium, cells were grown over night in 5 ml L-broth and the next morning 1 ml culture was washed twice with, and then diluted 1:1,000 in 250 ml flasks in 25 ml in either SPI2-inducing PCN (InSPI2; pH5.8, 0.4 mM Pi), SPI2-non-inducing PCN (NonSPI2; pH7.4, 25 mM Pi) or SPI2-inducing PCN (LowMg2+; pH5.8, 0.4 mM Pi) containing low levels (10 µM) of magnesium sulfate. RNA was isolated at OD600 of 0.3. The shocks conducted in PCN (InSPI2) were conducted at OD600 0.3: addition of peroxide (Peroxide shock (InSPI2)) to a final concentration of 1 mM for 12 min5; addition of nitric oxide (Nitric oxide shock (InSPI2)) donor Spermine NONOate to a final concentration of 250 µM for 20 min.

extract_protocol:
Total RNA was isolated using TRIzol (Invitrogen) and digested with DNase I
cDNA libraries were constructed by vertis Biotechnologie AG (Freising) using an in-house protocol. Total RNA (DNase I digested) was fragmented by ultrasound (4 pulses of 30s at 4°C). The to construct dRNA-seq libraries, these RNA samples were subsequently digested with Terminator Exonuclease (TEX). 3′ ends were subjected to poly(A)-tailing using poly(A) polymerase, pyrophosphate groups were removed from the 5′ terminus using tobacco acid pyrophosphatase (TAP), and an RNA adapter was ligated to the 5′ end of the RNA. First-strand synthesis was performed using an oligo(dT) adapter and M-MLV-RNaseH-reverse transcriptase, following PCR amplification of cDNA using high-fidelity DNA polymerase to ∼20–30 ng/μL. The cDNAs were purified using the Agencourt AMPure XP kit (Beckman Coulter Genomics) and analyzed by capillary electrophoresis.

tag: growth conditions

value: Growth in PCN medium to OD600 0.3 (pH 5.8, 0.4 mM Pi):then addition of 250 µM Spermine NONOate for 20 min


title: InSPI2 LowMg2+

status: Public on Dec 18 2013

type: SRA

country: United Kingdom

library_source: transcriptomic

molecule: total RNA

value: Growth in PCN medium with 10 µM MgCl2 to OD600 0.3 (pH 5.8, 0.4 mM Pi)

tag: strain


title: Peroxide shock (InSPI2)

value: PCN to OD600 0.3, then addition of H2O2 to final concentration of 1 mM H2O2 for 12 min


title: NonSPI2

value: Growth in PCN medium to OD600 0.3 (pH 7.4, 25 mM Pi)


title: Oxygen shock

value: Static growth in Lennox broth to OD600 0.3 in a completely filled and closed 50 ml Falcon tube; then 15 min aerobic growth (baffled flask, 250 rpm)


title: pH5.8 shock

value: Growth in Lennox broth to OD600 0.3; then cells were harvested by centrifugation, resuspended in fresh Lennox pH5.8 and grown for additional 10 min


title: inSPI2 Biol. Replicate 2

value: Growth in PCN medium to OD600 0.3 (pH 5.8, 0.4 mM Pi)


title: InSPI2 Biol. Replicate 1


title: inSPI2 (dRNA-seq) from Biol. Replicate 2

description: dRNA-seq


title: Anaerobic growth

value: Static growth in Lennox broth to OD600 0.3 in a completely filled and closed 50 ml Falcon tube


title: Cold shock (15°C)

value: Growth in Lennox broth to OD600 0.3, then transfer for 10 min from 37°C to 15°C


title: Pool (dRNA-seq)

description: dRNA-seq

value: All 22 conditions pooled


title: NaCl shock

value: Growth in Lennox broth to OD600 0.3; then addition of NaCl to a final concentration of 0.3 M for 10 min


title: pH3 shock

value: Growth in Lennox broth to OD600 0.3 then cells were harvested by centrifugation, resuspended in fresh Lennox pH3.0 and grown for additional 10 min


title: Anaerobic shock

value: Growth in Lennox broth to OD600 0.3 (50 ml), then filled into 50 ml closed Falcon tube and incubated without agitation for 30 min at 37°C


title: Pool (RNA-seq)


title: Bile shock

value: Growth in Lennox broth to OD600 0.3; then addition of bile to a final concentration of 3% for 10 min


title: Temp20

value: Growth in Lennox broth to OD600 0.3 at 25°C, then transfer for 20 min to 37°C


title: ESP Biol. Replicate 1 (Tech. Replicate2)

value: Growth in Lennox broth to OD600 2.0


title: LSP Biol. Replicate 2

value: Growth in Lennox broth to OD600 2.0 + 6 h


title: ESP Biol. Replicate 2


title: LSP Biol. Replicate 1


title: ESP Biol. Replicate 1 (Tech. Replicate 1)


title: ESP (dRNA-seq)

description: dRNA-seq


title: LowFe2+ shock

value: Growth in Lennox broth to OD600 0.3;  then addition of 2,2’-dipyridyl to a final concentration of 0.2 mM for 10 min


title: SB431542 SMAD2 ChIP

city: Toronto

first: Tobias

middle: Andreas

last: Beyer

state: ONT

address: 600 University Ave

department: Lunenfeld-Tannenbaum Research Institute

country: Canada

institute: Mount Sinai Hospital

description: ChIP DNA

library_source: genomic

data_processing:
Basecall was performed using GERALD
Alignent to Hh19 was performed using ELAND
Peaks were called using CisGenome. Note that Input DNA, IgG control was used for background substraction for TEAD4 ChIP. In the case of SMAD2, SB431542 treated cells were used as an additional negative control.
Genome_build: Hg19, build 37
Supplementary_files_format_and_content: BED files were generated using CisGenome and coordinates represent called peaks

molecule: genomic DNA

organism: Homo sapiens

growth_protocol: WA09 grown on Matrigel/MEF conditioned DMEM/F12 20% KO-serum

extract_protocol:
Cells were fixed for 10min with 1% Formaldehyde, nuclei were extracted (hypotonic lysis), DNA sheared by sonication
Libraries were prepared according to Illumina's instructions accompanying the DNA Sample Kit (Part# 0801-0303).

treatment_protocol: cells were treated for 4h with DMSO or 10uM SB431542

tag: cell type

value: Human embryonic stem cells

tag: cell line

value: Grown on matrigel/MEF conditioned DMEM/F12, 20% KO serum

tag: treatment

value: 4h SB431542 treated

tag: chip antibody

value: SMAD2 (Cell Signaling)


title: LEP

value: Growth in Lennox broth to OD600 1.0


title: DMSO SMAD2 ChIP

description: ChIP DNA

value: 4h DMSO treated


title: SB431542 TEAD4 ChIP

description: ChIP DNA

value: TEAD4 (aviva)


title: MEP Tech. Replicate 3

value: Growth in Lennox broth to OD600 0.3


title: DMSO IgG ChIP

description: ChIP DNA

value: normal rabbit IgG


title: SB431542 IgG ChIP

description: ChIP DNA


title: MEP Tech. Replicate 1


title: child patient T4 (microcephaly), mutation CLP1 R140H

city: New York

first: Miguel

last: Brown

state: New York

address: 1230 York Ave Box 186

country: USA

institute: The Rockefeller University

description:
barcoded small RNA-seq
BAB3401

data_processing:
Samples are demultiplexed by assigning by 5 nt barcodes and adapters and barcodes are removed from fastq files converted to fasta using perl scripts.
Fasta file is collapsed into a non-redundant fasta file in which the read count is contained within the read header and mapped against an in-house tRNA reference database derived from GtRNAdb, http://gtrna.ucsc.edu.  BWA v0.5.9 used, with parameters aln -n 2 -t 16 -i 0 -d 0 to align reads to the reference.
Multi-mapping reads are first assigned to hits with the lowest number of errors, then the count is split equally between the number of locations mapped.
Genome_build: hg19
Supplementary_files_format_and_content: tab separated file summarizing reads attributed to an internal reference of tRNAs.  First column is the read, second is the count, last column a comma-separated list of mapped annotation

source_name: mutation CLP1 R140H

growth_protocol: Human fibroblasts were cultured at 37°C, 95% humidity and 5% CO2 in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% fetal bovine serum, 3 mM glutamine, 100 U/ml penicillin and 100 μg/ml streptomycin sulfate (all reagents from Sigma). Cells were split and/or harvested using 0.05% Trypsin–EDTA.

extract_protocol:
Total RNA for sequencing was isolated from patient (BAB3401 and 3402) or parental (BAB3845 and 3846) fibroblasts using the TRIzol Reagent (Invitrogen) according to the manufacturer’s instructions
For each sample 300 ng of total RNA were hydrolyzed in a 15 μL buffer of 10 mM Na2CO3 and 10 mM NaHCO3 at ~pH 9.7, for 5 minutes at 90 °C.  The hydrolyzed RNA was dephosphorylated with 10 U of calf intestinal phosphatase (NEB) in a 50 μL reaction of 100 mM NaCl, 50 mM Tris-HCl pH 7.9 at 25 °C, 10 mM MgCl2, 1 mM DTT, 3 mM Na2CO3 and 3 mM NaHCO3, at 37 °C for 1 h. The resulting RNA was re-phosphorylated with 10 U of T4 polynucleotide kinase (NEB) in a 20 µl reaction of 70 mM Tris-HCl pH 7.6 at 25 °C, 10 mM MgCl2, 5 mM DTT and 1 mM ATP, at 37 °C for 1 h. Fragments of 19-24 nts were converted into barcoded small RNA cDNA libraries and submitted for Illumina sequencing

value: primary fibroblasts

tag: patient description

value: child patient T4 (microcephaly)


title: SB431542 Input DNA

description: Total chromosomal DNA

value: input DNA


title: healthy parent T2,  wild-type CLP1

description:
barcoded small RNA-seq
BAB3845

source_name: wild type CLP1

value: healthy parent T2


title: Input_TRb_T3

city: Boston

first: Preeti

last: Ramados

address: 3 Blackfan Cir

institute: Beth Israel Deaconess Medical Center

data_processing:
ChIP-seq reads were aligned to mouse genome (mm9) using Bowtie
Duplicated reads were removed using Samtools.
Reads were sorted by Samtools
peaks were called using MACS version 2 with default parameters.
Genome_build: mm9
Supplementary_files_format_and_content: text file containing information of peaks called by MACS2

organism: Mus musculus

source_name: liver

growth_protocol: 9-10 week old heterozygouse BirA expressing mice were housed in individual cages, fed a PTU diet, administered either Ad-GFP or Ad-TRb virus and then treated with either saline or T3

extract_protocol:
Chromatin was extracted from mouse liver after crosslinking with both disuccinimidyl-glutarate and formaldehyde by first extracting liver nuclei and shearing chromatin by Covaris sonication. Chromatin was precipitated using streptavidin agarose to capture biotinylated TRb1.
Libraries were prepared using the using the NEBNext ChIP-Seq Library Prep Master Mix Set for Illumina according to the manufacturer's protocol (New England Biolabs).

treatment_protocol: Mice were fed PTU diet for 3 weeks, followed by adenoviral injections through the tail vein. Mice were then injected intraperitoneally with saline or T3 for 4 days and then euthanized and tissues were collected

tag: tissue

value: liver

tag: agent

value: adenovirus expressing GFP and biotinylated TRb1


title: DMSO Input DNA

description: Total chromosomal DNA


title: MEP Tech. Replicate 2


title: LSP (dRNA-seq)

description: dRNA-seq

value: Growth in Lennox broth to OD600 2.0 + 6 h


title: 25°C

value: Growth in Lennox broth to OD600 0.3 at 25°C


title: Temp10

value: Growth in Lennox broth to OD600 0.3 at 25°C, then transfer for 10 min to 37°C


title: child patient T3 (microcephaly), mutation CLP1 R140H

description:
barcoded small RNA-seq
BAB3402

value: child patient T3 (microcephaly)


title: TRb_PTU_ChIP-seq


title: healthy parent T1, wild-type CLP1

description:
barcoded small RNA-seq
BAB3846

value: healthy parent T1


title: TRb_T3_ChIP-seq


title: Total_DRB_HS_(Nuc4_20110223_4)

city: Seattle

first: Jorja

last: Henikoff

state: WA

address: 1100 Fairview AV N, A1-162

department: Basic Sciences

institute: Fred Hutchinson Cancer Research Center

description: MNase-protected DNA fragments in total nuclei after 10 minutes of DRB treatment and 15 minutes of head shock at 37 degrees C

data_processing: 1. We used Novoalign to map paired-end 25bp reads to release r5.30 of the D.melanogaster genomic sequence obtained from FlyBase. If a read was mapped to multiple locations, one location was picked at random. 2. For each base pair in the genome, we counted the number of paired-end fragments aligned over it. 3. We normalized base pair counts by dividing by the total number of counts for all base pairs (supplementary .bed file) and then multiplying by the total number of base pairs in the genome (supplementary file .bedgraph file) 4. We broke down aligned paired-end fragments into sub-groups by insert size length and repeated steps 2. and 3. for the paired-end fragments in each sub-group.

organism: Drosophila melanogaster

source_name: total nuclei

extract_protocol: Salt extraction was done as described in S Henikoff, JG Henikoff, A Sakai, GB Loeb, K Ahmad, Genome-wide profiling of salt fractions maps physical properties of chromatin. Genome Research, March 2009, 19:460-469, PMID 19088306 and supplementary file Salt_protocol.rtf. A modified Illumina Solexa library protocol was used as described in supplementary file Solexa_library_protocol_GEO.pdf.

value: S2 cells

value: DRB 10min and heat shock for 15min at 37C


title: GFP_PTU_ChIP-seq

value: adenovirus expressing only GFP


title: MEP (dRNA-seq)

description: dRNA-seq


title: Total_HS_(Nuc2_20110223_2)

description: MNase-protected DNA fragments in total nuclei after 15 minutes of heat shock at 37 degrees centigrade

value: heat shock for 15min at 37C


title: input DNA_Cre_preadipocytes

status: Public on Dec 17 2013

city: Bethesda

first: Kai

last: Ge

state: MD

address: 50 South Dr Rm 4154

department: NIDDK

institute: NIH

data_processing:
Base-calling and alignment (genome build mm9) performed by Illumina Analysis Pipeline.
Conversion to BED format by bedtools v2.16.
Peak-calling by SICER v1.1. For MyoD and MLL4, Window size 50bps, Gap size 50bps, FDR<1e-3. For H3K4me1, H3K4me3, and H3K27ac, Window size 200bps, Gap size 200bps, FDR<1e-3.
Genome_build: MGSCv37
Supplementary_files_format_and_content: Wig files of identified enriched regions generated by SICER v1.1.

source_name: mouse brown preadipocytes, MLL4 KO, input

growth_protocol: E18.5 mouse embryo-derived MLL3-/-;MLL4flox/flox brown preadipocytes were immortalized by SV40T. Cells were infected with retroviral plasmid expressing MyoD, followed by infection with adenoviral Cre to delete the MLL4 gene. Cells were changed to myogenic medium (2% horse serum) when 70% confluent.

extract_protocol:
Lysates were clarified from sonicated nuclei, and protein-DNA complexes were isolated with antibody (MyoD: Santa Cruz Biotechnology, sc-760 (lot: H2107); H3K4me1: abcam, ab8895 (lot: GR61280-1); H3K4me3: Millipore, 17-614 (lot: 2109590); H3K27ac: abcam, ab4729 (lot: GR81163-1); homemade MLL4).
Libraries were prepared according to Illumina's instructions accompanying the DNA Sample Kit.

treatment_protocol: 2% horse serum.

tag: strain/background

tag: genotype

tag: age

value: E18.5 embryos

value: immortalized brown preadipocytes


title: input DNA_GFP_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, WT, input

value: MyoD-induced immortalized brown preadipocytes


title: DMSO TEAD4 ChIP

description: ChIP DNA

value: Human embryonic stem cells

value: Grown on matrigel/MEF conditioned DMEM/F12, 20% KO serum

value: 4h DMSO treated

value: TEAD4 (aviva)


title: input DNA_Cre_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, MLL4 KO, input


title: Total_DRB_(Nuc3_20110223_3)

description: MNase-protected DNA fragments in total nuclei after 10 minutes of DRB treatment

value: DRB 10min


title: EEP

value: Growth in Lennox broth to OD600 0.1


title: input DNA_GFP_preadipocytes

source_name: mouse brown preadipocytes, WT, input


title: Input_TRb_PTU

value: liver

value: adenovirus expressing GFP and biotinylated TRb1


title: H3K4me3_ChIPSeq_Cre_preadipocytes

source_name: mouse brown preadipocytes, MLL4 KO, H3K4me3 ChIP


title: H3K4me3_ChIPSeq_Cre_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, MLL4 KO, H3K4me3 ChIP


title: H3K27ac_ChIPSeq_GFP_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, WT, H3K27ac ChIP


title: H3K27ac_ChIPSeq_GFP_preadipocytes

source_name: mouse brown preadipocytes, WT, H3K27ac ChIP


title: H3K4me3_ChIPSeq_GFP_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, WT, H3K4me3 ChIP


title: H3K27ac_ChIPSeq_Cre_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, MLL4 KO, H3K27ac ChIP


title: Input_GFP_PTU


title: H3K4me1_ChIPSeq_Cre_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, MLL4 KO, H3K4me1 ChIP


title: H3K4me1_ChIPSeq_Cre_preadipocytes

source_name: mouse brown preadipocytes, MLL4 KO, H3K4me1 ChIP


title: H3K4me1_ChIPSeq_GFP_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, WT, H3K4me1 ChIP


title: H3K4me1_ChIPSeq_GFP_preadipocytes

source_name: mouse brown preadipocytes, WT, H3K4me1 ChIP


title: MLL4_ChIPSeq_Cre_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, MLL4 KO, MLL4 ChIP


title: MyoD_ChIPSeq_Cre_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, MLL4 KO, MyoD ChIP

value: MyoD


title: MLL4_ChIPSeq_GFP_preadipocytes

source_name: mouse brown preadipocytes, WT, MLL4 ChIP


title: MLL4_ChIPSeq_GFP_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, WT, MLL4 ChIP


title: MyoD_ChIPSeq_GFP_preadipocytes

source_name: mouse brown preadipocytes, WT, MyoD ChIP


title: MyoD_ChIPSeq_GFP_D5 myocytes

source_name: MyoD-induced mouse brown preadipocytes, WT, MyoD ChIP


title: MyoD_ChIPSeq_Cre_preadipocytes

source_name: mouse brown preadipocytes, MLL4 KO, MyoD ChIP


title: H3K27ac_ChIPSeq_Cre_preadipocytes

source_name: mouse brown preadipocytes, MLL4 KO, H3K27ac ChIP


title: RNA_Cre_D5 myocytes

description: mRNA

data_processing:
Base-calling and alignment (genome build mm9) performed by Illumina Analysis Pipeline.
Conversion to BED format by bedtools v2.16.
Count reads and calculate RPKM on exonic regions for each gene by SICER v1.1.
Genome_build: MGSCv37
Supplementary_files_format_and_content: Tab-delimited text file (gene, read count, RPKM) of RNA-Seq reads generated by SICER v1.1.

source_name: MyoD-induced mouse brown preadipocytes, MLL4 KO

extract_protocol:
RNA was extracted using Trizol reagent.
Libraries were prepared according to Illumina's instructions accompanying the DNA Sample Kit.


title: RNA_Cre_preadipocytes

description: mRNA

source_name: mouse brown preadipocytes, MLL4 KO


title: RNA_GFP_D5 myocytes

description: mRNA

source_name: MyoD-induced mouse brown preadipocytes, WT


title: Input DNA_C/EBPbeta_GFP

data_processing:
Base-calling and alignment (genome build mm9) performed by Illumina Analysis Pipeline.
Conversion to BED format by bedtools v2.16.
Peak-calling by SICER v1.1. For C/EBPbeta and MLL4, Window size 50bps, Gap size 50bps, FDR<1e-3. For H3K4me1 and H3K27ac, Window size 200bps, Gap size 200bps, FDR <1e-3.
Genome_build: MGSCv37
Supplementary_files_format_and_content: Wig files of identified enriched regions generated by SICER v1.1.

source_name: mouse brown preadipocytes, WT, C/EBPbeta GFP, input

growth_protocol: E18.5 mouse embryo-derived MLL3-/-;MLL4flox/flox brown preadipocytes were immortalized by SV40T. Cells were infected with retroviral plasmid expressing C/EBPbeta, followed by infection with adenoviral Cre to delete the MLL4 gene.

extract_protocol:
Lysates were clarified from sonicated nuclei, and protein-DNA complexes were isolated with antibody (C/EBPb: Santa Cruz Biotechnology, sc-150X (lot: L2910); H3K4me1: abcam, ab8895 (lot: GR61280-1); H3K27ac: abcam, ab4729 (lot: GR81163-1); homemade MLL4).
Libraries were prepared according to Illumina's instructions accompanying the DNA Sample Kit.

tag: genotype/variation

tag: overexpression

value: C/EBPbeta GFP


title: Input DNA_C/EBPbeta_Cre

source_name: mouse brown preadipocytes, MLL4 KO, C/EBPbeta Cre, input

value: C/EBPbeta Cre


title: RNA_GFP_preadipocytes

description: mRNA

source_name: mouse brown preadipocytes, WT


title: H3K4me1_ChIPSeq_C/EBPbeta_Cre

source_name: mouse brown preadipocytes, MLL4 KO, C/EBPbeta Cre, H3K4me1 ChIP


title: H3K27ac_ChIPSeq_C/EBPbeta_Cre

source_name: mouse brown preadipocytes, MLL4 KO, C/EBPbeta Cre, H3K27ac ChIP


title: H3K27ac_ChIPSeq_C/EBPbeta_GFP

source_name: mouse brown preadipocytes, WT, C/EBPbeta GFP, H3K27ac ChIP


title: H3K4me1_ChIPSeq_C/EBPbeta_GFP

source_name: mouse brown preadipocytes, WT, C/EBPbeta GFP, H3K4me1 ChIP


title: C/EBPbeta_ChIPSeq_Vec_Cre

source_name: mouse brown preadipocytes, MLL4 KO, Vec Cre, C/EBPbeta ChIP

value: Vec Cre

value: C/EBPbeta


title: C/EBPbeta_ChIPSeq_C/EBPbeta_Cre

source_name: mouse brown preadipocytes, MLL4 KO, C/EBPbeta Cre, C/EBPbeta ChIP


title: C/EBPbeta_ChIPSeq_C/EBPbeta_GFP

source_name: mouse brown preadipocytes, WT, C/EBPbeta GFP, C/EBPbeta ChIP


title: C/EBPbeta_ChIPSeq_Vec_GFP

source_name: mouse brown preadipocytes, WT, Vec GFP, C/EBPbeta ChIP

value: Vec GFP


title: input DNA_D0_MLL4 KO

data_processing:
Base-calling and alignment (genome build mm9) performed by Illumina Analysis Pipeline.
Conversion to BED format by bedtools v2.16.
Peak-calling by SICER v1.1 (Window size 200bps, Gap size 200bps, FDR<1e-3).
Genome_build: MGSCv37
Supplementary_files_format_and_content: Wig files of identified enriched regions generated by SICER v1.1.

source_name: mouse brown preadipocytes, MLL4 KO, input

growth_protocol: E18.5 mouse embryo-derived MLL3-/-;MLL4flox/flox brown preadipocytes were immortalized by SV40T. Cells were then infected with adenoviral Cre to delete the MLL4 gene. Cells were seeded at a density of 5x10^5 / 10cm culture dish. Two days after confluence (day 0), cells were induced with adipogenic cocktail.

extract_protocol:
Lysates were clarified from sonicated nuclei, and histone-DNA complexes were isolated with antibody (H3K4me1: abcam, ab8895 (lot: GR61280-1); H3K4me2: abcam, ab7766 (lot: GR102810-1); H3K4me3: Millipore, 17-614 (lot: 2109590); H3K27ac: abcam, ab4729 (lot: GR81163-1)).
Libraries were prepared according to Illumina's instructions accompanying the DNA Sample Kit.

treatment_protocol: 0.02mM insulin, 1nM T3, 0.125mM indomethacin, 2mg/ml dexamethasone, 0.5mM IBMX treatment for two days after confluence.

value: E18.5 embryos


title: H3K27ac_ChIPSeq_D2_WT

source_name: mouse brown preadipocytes, WT, H3K27ac ChIP

value: immortalized brown preadipocytes


title: H3K27ac_ChIPSeq_D2_MLL4 KO

source_name: mouse brown preadipocytes, MLL4 KO, H3K27ac ChIP


title: input DNA_D0_WT

source_name: mouse brown preadipocytes, WT, input


title: input DNA_D2_WT


title: input DNA_D2_MLL4 KO


title: H3K4me3_ChIPSeq_GFP_preadipocytes

source_name: mouse brown preadipocytes, WT, H3K4me3 ChIP


title: H3K27ac_ChIPSeq_D0_WT


title: H3K4me3_ChIPSeq_D0_MLL4 KO

source_name: mouse brown preadipocytes, MLL4 KO, H3K4me3 ChIP


title: H3K4me3_ChIPSeq_D2_MLL4 KO


title: MLL4_ChIPSeq_C/EBPbeta_Cre

source_name: mouse brown preadipocytes, MLL4 KO, C/EBPbeta Cre, MLL4 ChIP


title: MLL4_ChIPSeq_C/EBPbeta_GFP

source_name: mouse brown preadipocytes, WT, C/EBPbeta GFP, MLL4 ChIP


title: H3K4me2_ChIPSeq_D2_MLL4 KO

source_name: mouse brown preadipocytes, MLL4 KO, H3K4me2 ChIP


title: H3K4me3_ChIPSeq_D2_WT


title: H3K4me2_ChIPSeq_D2_WT

source_name: mouse brown preadipocytes, WT, H3K4me2 ChIP


title: H3K4me3_ChIPSeq_D0_WT


title: H3K4me2_ChIPSeq_D0_WT


title: H3K4me1_ChIPSeq_D2_MLL4 KO

source_name: mouse brown preadipocytes, MLL4 KO, H3K4me1 ChIP


title: MLL4_ChIPSeq_Cre_preadipocytes

source_name: mouse brown preadipocytes, MLL4 KO, MLL4 ChIP


title: H3K4me2_ChIPSeq_D0_MLL4 KO


title: H3K4me1_ChIPSeq_D0_MLL4 KO


title: Pol_II_ChIPSeq_D0_WT

data_processing:
Base-calling and alignment (genome build mm9) performed by Illumina Analysis Pipeline.
Conversion to BED format by bedtools v2.16.
Peak-calling by SICER v1.1 (Window size 50bps, Gap size 50bps, FDR<1e-3).
Genome_build: MGSCv37
Supplementary_files_format_and_content: Wig files of identified enriched regions generated by SICER v1.1.

source_name: mouse brown preadipocytes, WT, Pol II ChIP

extract_protocol:
Lysates were clarified from sonicated nuclei, and TF bound-DNA complexes were isolated with antibody (C/EBPa: Santa Cruz Biotechnology, sc-61X (lot: G1112); C/EBPb: Santa Cruz Biotechnology, sc-150X (lot: L2910); PPARg: Santa Cruz Biotechnology, sc-7196X (lot: H1512); Pol II: Millipore, 17-672 (lot: 2015592)).
Libraries were prepared according to Illumina's instructions accompanying the DNA Sample Kit.

value: Pol II


title: H3K4me1_ChIPSeq_D0_WT

source_name: mouse brown preadipocytes, WT, H3K4me1 ChIP


title: H3K4me1_ChIPSeq_D2_WT


title: PPARgamma_ChIPSeq_D2_WT

source_name: mouse brown preadipocytes, WT, PPARgamma ChIP

value: PPARgamma


title: Pol_II_ChIPSeq_D2_KO

source_name: mouse brown preadipocytes, MLL4 KO, Pol II ChIP


title: Pol_II_ChIPSeq_D2_WT


title: Pol_II_ChIPSeq_D0_KO


title: PPARgamma_ChIPSeq_D0_WT


title: H3K27ac_ChIPSeq_D0_MLL4 KO


title: C/EBPbeta_ChIPSeq_D2_WT

source_name: mouse brown preadipocytes, WT, C/EBPbeta ChIP


title: C/EBPbeta_ChIPSeq_D0_WT


title: C/EBPalpha_ChIPSeq_D2_WT

source_name: mouse brown preadipocytes, WT, C/EBPalpha ChIP

value: C/EBPalpha


title: C/EBPalpha_ChIPSeq_D0_WT


title: RNA_D2_MLL4 KO

description: mRNA

data_processing:
Base-calling and alignment (genome build mm9) performed by Illumina Analysis Pipeline.
Conversion to BED format by bedtools v2.16.
Count reads and calculate RPKM on exonic regions for each gene by SICER v1.1.
Genome_build: MGSCv37
Supplementary_files_format_and_content: Tab-delimited text files (gene, read count, RPKM) of RNA-Seq reads generated by SICER v1.1.

source_name: mouse brown preadipocytes, MLL4 KO


title: X-M+D+

city: Singapore

first: Weiling

last: Zheng

address: Science Drive 4

country: Singapore

institute: National University of Singapore

data_processing:
The SOLiD-generated RNA-Seq reads was in 27 bp length and an initial filtering process was taken to remove any non-desirable contamination sequences. The reads were mapped to the zebrafish RefSeq mRNA database allowing maxium mismatches.
The expression levels of mapped transcripts were normalized into transcript per million (TPM) to faciliate comparison among different samples.
Genome_build: danRer7
Supplementary_files_format_and_content: The mapped transcripts were listed with GI and RefSeq ID together with expression levels in TPM.

organism: Danio rerio

source_name: liver tumor

extract_protocol:
Total RNA was extracted using TRIzol Reagent (Invitrogen, USA) and treated with DNase I to remove genomic DNA contamination.
Library construction was conducted by Mission Biotech (Taiwan) following standard ABI SOLiD protocol.

treatment_protocol: Transgenic zebrafish and their wildtype siblings were treated starting from 3.5 mpf. Doxycycline treatment was conducted in 6-L tanks with around 25 adult and water was changed every other day.

value: Tg(fabp10:TA; TRE:Myc; krt4:GFP)

value: doxycycline


title: X-M-D+

source_name: control liver

value: wildtype sibling


title: X-M+D-


title: RNA_D0_MLL4 KO

description: mRNA


title: X-M-D-


title: RNA_D0_WT

description: mRNA

source_name: mouse brown preadipocytes, WT


title: MLL4_ChIPSeq_D2_MLL4 KO

growth_protocol: E18.5 mouse embryo-derived MLL3-/-;MLL4flox/flox brown preadipocytes were immortalized by SV40T. Cells were then infected with adenoviral Cre to delete the MLL4 gene. Cells were seeded at a density of 5x10^5 / 10cm culture dish. Two days after confluence (day 0), cells were induced with adipogenic cocktail. The cells were replenished with medium containing insulin and T3 every two days.

extract_protocol:
Lysates were clarified from sonicated nuclei, and MLL4-DNA complexes were isolated with homemade MLL4 antibody.
Libraries were prepared according to Illumina's instructions accompanying the DNA Sample Kit.

treatment_protocol: 0.02mM insulin, 1nM T3, 0.125mM indomethacin, 2mg/ml dexamethasone, 0.5mM IBMX treatment for two days after confluence. Every two days, cells were replenished with medium containing insulin and T3.


title: input DNA_D7_MLL4 WT

source_name: mouse brown preadipocytes, WT, input


title: MLL4_ChIPSeq_D7_WT

source_name: mouse brown preadipocytes, WT, MLL4 ChIP


title: MLL4_ChIPSeq_D2_WT


title: MLL4_ChIPSeq_D0_WT


title: MLL4_ChIPSeq_D7_MLL4 KO


title: input DNA_D7_MLL4 KO

source_name: mouse brown preadipocytes, MLL4 KO, input


title: MLL4_ChIPSeq_D0_MLL4 KO


title: X+M-D-

value: Tg(fabp10:TA; TRE:xmrk; krt4:GFP)


title: SNIK-in_rep1

city: Viçosa

first: Elizabeth

middle: Pacheco Batista

last: Fontes

state: MG

address: Av. PH. Rolfs, s/n

department: Biochemistry

country: Brazil

institute: Federal University of Viçosa

description:
Sample name: GHY-11
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

data_processing:
RTA SCS.2.6, GERALD.1.5.1 - Parameters of the quality filter:  1- Maximum 1 base below a quality of 5 on the first 30 bases, 2- A minimum average quality of 10,  3- No “N” allowed, 4- Not more than 35 identical bases (low information reads).  This pipeline filtered the raw data file using the parameters  quality. Then it counted each read originating the table file  "Profiles_with_differential_expressions.csv". Therefore the data is  discrete.
Genome_build: International Tomato Annotation Group (ITAG) – release 2.3 – cDNA data file
Supplementary_files_format_and_content: csv
The reads from the file "Profiles_with_differential_expressions.csv" was mapped using Bowtie 0.12.7 (default parameters) to the ITAG 2.3 cDNA dataset file. A parser create from myself interpreted the result of Bowtie. Thus, it created the table (map_itag23.csv) correlating the ITAG 2.3 cDNA ID with reads, their position and the strand sense in the cDNA sequence.If there was more than one read mapped in cDNA sequence it was used the nearest position to 5' end. That's because some specification from the used GEX protocol.

organism: Solanum lycopersicum

source_name: T474D-overexpressing line infected by ToYSV repetition 1

growth_protocol: Wild type and transformed plants were grown in a greenhouse under natural conditions of light, 70% relative humidity and approximately equal day and night lengths

extract_protocol:
Total RNA was extracted from the leaves of the mock and infected inoculated plants using TRIzol (Invitrogen). Quality control was verified using 1.5% agarose gels eletrophoresis.
Protocol Illumina GEX-NIaIII: Poly-A transcripts purification and cDNA preparation were performed using oligo-dT magnetic beads. The samples were digested by NlaIII  with 4-base cutter enzyme and GEX NlaIII adpter 1 was ligated. Subsequent samples were digested with restriction enzyme MmeI to create 17 bp tag and the GEX adapter 2 has been connected. Reverse transcription and PCR amplification to generate the DNA colonies Template lybrary. Gel purification. Dilution at 10nM.

treatment_protocol: The transgenic (35S::NIK1-4 and 35S::T474D) and wild-type lines (20 plants for each line) were infected at the six-leaf stage with either tugstein particle or ToYSV-[MG-Bi2] by biolistic delivery using  2 μg of the tandemly repeated viral DNA-A and DNA-B and a microprojectile bombardment model PDS-1000/He accelerator (BIORAD) at 900 psi.

value: Moneymaker

tag: toysv infection

value: infected

value: systemic leaves

value: 40 days post germination(10DPI)


title: X+M-D+

value: liver


title: NIK-in_rep2

description:
Sample name: GHY-8
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: NIK-overexpressing line infected by ToYSV repetition 2

value: NIK-overexpression


title: NIK-ni_rep2

description:
Sample name: GHY-6
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: NIK-overexpressing, mock-inoculated line repetition 2

value: mock


title: SNIK-in_rep2

description:
Sample name: GHY-12
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: T474D-overexpressing line infected by ToYSV repetition 2


title: NIK-in_rep1

description:
Sample name: GHY-7
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: NIK-overexpressing line infected by ToYSV repetition 1


title: SNIK-ni_rep2

description:
Sample name: GHY-10
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: T474D-overexpressing, mock-inoculated line repetition 2


title: NIK-ni_rep1

description:
Sample name: GHY-5
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: NIK-overexpressing, mock-inoculated line repetition 1


title: WT-in_rep2

description:
Sample name: GHY-4
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: Wild-type infected by ToYSV repetition 2

value: wild type


title: WT-ni_rep1

description:
Sample name: GHY-1
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: Mock-inoculated wild-type line repetition 1


title: WT-ni_rep2

description:
Sample name: GHY-2
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: Mock-inoculated wild-type line repetition 2


title: RNA_D2_WT

description: mRNA

value: E18.5 embryos


title: U-2932_ChIPSeq_input

status: Public on Dec 16 2013

city: Stanford

first: Jennifer

middle: Marion

last: Hardee

state: California

address: 300 Pasteur Dr., M-344

institute: Stanford University

description: Sample 18

data_processing:
Base calls performed using Illumina ELAND
ChIP-Seq reads were aligned to hg19 using BowTie v0.12.5, parameters "-p 8 -S -q -v 2 -m 1 --best --strata encodeHg19Male" (or encodeHg19Female).
The SPP peak caller v1.10.1 was used with a relaxed peak calling threshold (FDR = 0.9) to obtain a large number of peaks (maximum of 300,000) that span true signal as well as noise (false identifications).
Used the Irreproducible Discovery Rate (IDR) framework in order to identify high confidence and reliable regions of enrichments (peaks) in the ChIP-seq datasets. Specifically, we followed the ENCODE uniform processing pipeline as outlined at http://anshul.kundaje.net/projects/idr. The number of peaks with IDR scores better than 0.02 (2%) was used as the cross-replicate peak rank threshold.
Overlapping or abutting high confidence STAT3 peaks were merged into broader “binding regions” to facilitate comparison between cell lines (output file: ChIPSeq_STAT3BindingRegions.txt).  The ChIP-Seq data for each line was then rescored to determine how many fragments mapped to each binding region.  Binding regions that occurred in only one cell line were eliminated from further analysis.
Replicates were normalized using DESeq: The effective library size of each sample was estimated based on the pooled count data. First, a reference sample was defined in which the reference count of each binding region is its geometric mean over all samples. Second, for each sample, a vector was calculated as the ratios of the read counts over the reference counts for all the binding regions. Third, the median of these ratios across all the binding regions was defined as the “size factor” of each sample. Lastly, each sample was normalized by dividing the real counts by its size factor.
Applied the negative binomial model in DESeq to assess the significance levels of differential STAT3 binding.  The dispersion parameter in the model is estimated from the data by examining the relationship between the mean and variance of read counts across all the BRs. To contrast two conditions, we used the parameterized negative binomial model for each gene and obtained the p-values. To correct for multiple comparison, we adjusted the p-values with the Benjamini-Hochberg procedure which controls false discovery rate.  We compared 24 GCB replicates versus 11 ABC replicates.  Cell line OCI-Ly19 was excluded from the analysis: RNA-Seq data showed that its gene expression clustered in between the subtypes, probably due to its EBV+ status.
STAT3 binding regions (BRs) were associated with genes that they might regulate via the Genomic Regions Enrichment of Annotations Tool v2.0.2 using its default settings (http://great.stanford.edu).  To determine whether a BR and a given gene are linked, GREAT first determines a putative regulatory domain for every gene.  This consists of a basal regulatory domain (BRD) from 5 kb upstream to 1 kb downstream, plus an extended domain calculated by elongating the BRD both upstream and downstream for 1000 kb or until reaching another gene’s BRD, whichever occurs first.  Once this set of extended regulatory domains is established, GREAT associates the list of ChIP-Seq STAT3 binding regions with all of the genes whose regulatory domains they overlap.
Genome_build: hg19
Supplementary_files_format_and_content: *ChIPSeq_STAT3_IDRpeaks.bed: BED files were generated using the IDR pipeline (http://anshul.kundaje.net/projects/idr).  Files are in the UCSC-supported ENCODE narrowPeak format (http://genome.ucsc.edu/FAQ/FAQformat.html#format12).  NOTE:  BED column 4 reports ranks, as the IDR analysis pipeline uses rank as an important measurement of peak significance.
Supplementary_files_format_and_content: ChIPSeq_STAT3BindingRegions.txt: File was generated by a custom script. "IDRpeaks.bed" files for all 9 cell lines were concatenated.  Any overlapping or abutting regions were merged together to form one larger "binding region" (BR). Regions that occurred in only one cell line were discarded.  Headers are "chr/start/end/numCellLines", where "numCellLines" is "number of cell lines in which this peak is found".  Linked as supplementary file on Series record.
Supplementary_files_format_and_content: ChIPSeq_ReadCountsByReplicate.txt: Abundance measurements.  The total fragment count for 10,337 STAT3 binding regions in each of the 35 replicates, after normalization.  Linked as supplementary file on Series record.
Supplementary_files_format_and_content: ChIPSeq_StatisticalResults.txt: Mean fragment count for 10,337 STAT3 binding regions in each subtype (ABC, GCB) after normalization; calculated fold change; p-value and FDR for differential gene expression between the two subtypes.  Linked as supplementary file on Series record.
Supplementary_files_format_and_content: ChIPSeq_AssociatedGenes.txt: Location-based association between 10,337 STAT3 binding regions and annotated RefSeq genes (analyzed via GREAT).  In many cases, STAT3 BRs fall in regions where the regulatory domains of two genes overlap; consequently, GREAT associates these BRs with both genes.  For purposes of downstream comparison, we treated these multiple associations as separate table entries, to allow the greatest sensitivity in detecting associations with gene expression data.  Linked as supplementary file on Series record.

source_name: B cells

growth_protocol: Cell lines OCI-Ly7, OCI-Ly19, SU-DHL2, SU-DHL4, SU-DHL6, SU-DHL10, and U-2932 were cultured in suspension in RPMI 1640, supplemented with 15% heat-inactivated FBS.  Cell lines OCI-Ly3 and OCI-Ly10 were cultured in suspension in IMDM, supplemented with 15% heat-inactivated FBS and 55 uM beta-mercaptoethanol.

extract_protocol:
Crosslinked cell pellets were dounce homogenized to collect nuclei.  Nuclear lysate was sonicated, then immunoprecipitated.  Antibody-protein-DNA complexes were collected using Protein A agarose beads.
Libraries were prepared according to Illumina's instructions using non-Illumina enzymes and kits.  Briefly, DNA was end-repaired using a combination of T4 DNA polymerase, E. coli DNA Pol I large fragment (Klenow polymerase) and T4 polynucleotide kinase (End-It Repair Kit, Epicenter-Illumina). The blunt ends were treated with Klenow fragment (32 to 52 exo minus) and dATP to yield a protruding 3- 'A' base for ligation of Illumina's adapters. DNA was then gel purified and size selected for 150-300 bp fragments to exclude unligated adapters, PCR amplified with Illumina primers using Phusion high-fidelity DNA polymerase for 15 cycles, and size selected again from an agarose gel for 150-300 bp fragments. The purified DNA was captured on an Illumina flow cell for cluster generation. Libraries were sequenced on the Genome Analyzer IIx following the manufacturer's protocols.

treatment_protocol: Cells were suspended in their growing media at 1e6 per mL and crosslinked with formaldehyde at a final concentration of 1% for 10 minutes at room temperature, followed by quenching with glycine in PBS at a final concentration of 125 mM for 5 minutes.

tag: disease state

value: diffuse large B cell lymphoma (DLBCL)

tag: dlbcl subtype

value: ABC


title: SU-DHL6_ChIPSeq_input

description: Sample 17

value: GCB


title: SU-DHL4_ChIPSeq_input

description: Sample 16


title: SNIK-ni_rep1

description:
Sample name: GHY-9
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: T474D-overexpressing, mock-inoculated line repetition 1


title: OCI-Ly3_ChIPSeq_input

description: Sample 12


title: SU-DHL6_ChIPSeq

description: Sample 8

value: STAT3 (Santa Cruz, sc-482X)


title: SU-DHL10_ChIPSeq_input

description: Sample 14


title: SU-DHL4_ChIPSeq

description: Sample 7


title: SU-DHL10_ChIPSeq

description: Sample 5


title: OCI-Ly19_ChIPSeq_input

description:
Sample 11
Isolated from an EBV+ patient.   Based on RNA expression profiling, clusters in between GCB and ABC subtypes.

value: GCB+EBV


title: SU-DHL4_RNASeq

description: Sample 7

data_processing:
Base calls performed using Illumina ELAND
RNA-Seq reads were aligned to hg19 using BowTie v0.9.9.3, with parameters "--best -k 2 --unfa".  The top two best mappings were kept, tolerating two or fewer mismatched bases per read. Then a custom script was used to select the better of these two unique mappings.
Filtered out reads that mapped to human ribosomal RNAs
Filtered reads were intersected with the RefSeq transcriptome
Replicates were normalized using DESeq: The effective library size of each sample was estimated based on the pooled count data. First, a reference sample was defined in which the reference count of each transcript is its geometric mean over all samples. Second, for each sample, a vector was calculated as the ratios of the read counts over the reference counts for all the transcripts. Third, the median of these ratios across all the transcripts was defined as the “size factor” of each sample. Lastly, each sample was normalized by dividing the real counts by its size factor.
Collapsed the replicates by summing the read counts of two replicates for each cell line, because of the high degree of similarity between RNA-Seq replicates
Applied the negative binomial model in DESeq to assess the significance levels of differential gene expression.  The dispersion parameter in the model is estimated from the data by examining the relationship between the mean and variance of read counts across all the transcripts.  To contrast two conditions, we used the parameterized negative binomial model for each gene and obtained the p-values. To correct for multiple comparison, we adjusted the p-values with the Benjamini-Hochberg procedure which controls false discovery rate.
Genome_build: hg19
Supplementary_files_format_and_content: mRNA_ReadCountsByLine.txt: Abundance measurements.  The total fragment count for 22,156 RefSeq genes in each of the 8 cell lines, after normalization.  Linked as supplementary file on Series record.
Supplementary_files_format_and_content: mRNA_StatisticalResults.txt: Mean fragment count for 22,156 RefSeq genes in each subtype (ABC, GCB) after normalization; calculated fold change; p-value and FDR for differential gene expression between the two subtypes.  Linked as supplementary file on Series record.

molecule: polyA RNA

extract_protocol:
mRNA was isolated from the lysate of 1e6 cells using the Dynabeads mRNA DIRECT kit, which enriches for poly-A transcripts.  The isolated mRNA was fragmented chemically and double-stranded cDNA was synthesized using random hexamers.
Libraries were prepared according to Illumina's instructions using non-Illumina enzymes and kits.  Briefly, DNA was end-repaired using a combination of T4 DNA polymerase, E. coli DNA Pol I large fragment (Klenow polymerase) and T4 polynucleotide kinase (End-It Repair Kit, Epicenter-Illumina). The blunt ends were treated with Klenow fragment (32 to 52 exo minus) and dATP to yield a protruding 3- 'A' base for ligation of Illumina's adapters. DNA was then gel purified and size selected for 150-300 bp fragments to exclude unligated adapters, PCR amplified with Illumina primers using Phusion high-fidelity DNA polymerase for 15 cycles, and size selected again from an agarose gel for 150-300 bp fragments. The purified DNA was captured on an Illumina flow cell for cluster generation. Libraries were sequenced on the Genome Analyzer IIx following the manufacturer's protocols.


title: OCI-Ly10_ChIPSeq

description: Sample 1


title: OCI-Ly19_ChIPSeq

description:
Sample 2
Isolated from an EBV+ patient.   Based on RNA expression profiling, clusters in between GCB and ABC subtypes.


title: OCI-Ly3_ChIPSeq

description: Sample 3


title: SU-DHL10_RNASeq

description: Sample 5


title: OCI-Ly7_RNASeq

description: Sample 4


title: U-2932_ChIPSeq

description: Sample 9


title: SU-DHL2_ChIPSeq_input

description: Sample 15


title: SU-DHL2_RNASeq

description: Sample 6


title: WT-in_rep1

description:
Sample name: GHY-3
Main site of tomato project : http://solgenomics.net/organism/Solanum_lycopersicum/genome
cDNA file: http://solgenomics.net/organism/Solanum_lycopersicum/genome#itag23_annotation_release

source_name: Wild-type infected by ToYSV repetition 1


title: SU-DHL6_RNASeq

description: Sample 8


title: OCI-Ly19_RNASeq

description:
Sample 2
NOT INCLUDED in final analysis. Isolated from an EBV+ patient.  Based on RNA-Seq gene expression data, OCI-Ly19 clusters in between GCB and ABC subtypes.


title: OCI-Ly10_RNASeq

description: Sample 1


title: RBP7 (Tb927.10.12100) over-expressor minus dox rep 2

city: Edinburgh

first: Alasdair

last: Ivens

address: Kings Buildings

institute: Centre for Immunity, Infection and Evolution

data_processing:
The quality of raw sequence data was assessed using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ).   No additional processing of the primary data was required.
Paired end sequences were aligned to the Tbb genome (obtained from ftp.sanger.ac.uk/pub4/pathogens/Trypanosoma/brucei/Latest_Whole_Genome_Sequence/Tb927_WGS_24_08_2012/chromosomes/ ) using bowtie2 (parameters: --very-sensitive-local; version: 2.0.2), piped through samtools (parameters: -bhS; version: 0.1.18), and stored in indexed BAM format.
The annotated Tbb genome was viewed using Artemis software (http://www.sanger.ac.uk/resources/software/artemis/ ; http://ukpmc.ac.uk/abstract/MED/11120685), and coding segment (CDS) region coordinates extracted prior to conversion to bedtools bedfile format.  Bedtools (paramters: multicov -bams ; version: bedtools 2.15.0) was used to generate coverages for each CDS for each sample replicate.  RPKM-like values were calculated by dividing coverage by CDS size.
Statistical analyses of the sample groups were undertaken in the R environment (www.R-project.org) using Bioconductor (www.bioconductor.org) packages.  Differential expression was explored using linear models and empirical Bayes methods, using the limma package (Smyth, G. K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 3, No. 1, Article 3. (Online, Tech Report PDF)).  RPKM-like values were offset by 1, logged, and quantile normalised prior to group-wise comparison.  Data were filtered to remove loci whose mean RPKM-like values across all samples were below the 10% quantile.
Genome_build: ftp.sanger.ac.uk/pub4/pathogens/Trypanosoma/brucei/Latest_Whole_Genome_Sequence/Tb927_WGS_24_08_2012/chromosomes/
Supplementary_files_format_and_content: Annotated, normalised RPKM values (log2)

organism: Trypanosoma brucei brucei

growth_protocol: RBP7 (Tb927.10.12100) RNAi  and over-expressor lines were grown in mice.

extract_protocol:
RNA was isolated from AnTat1.1 cells grown in mice with or without doxycycline and from RBP7 RNAi or over-expressor lines grown in mice with or without doxycycline.  The method used for RNA extraction was RNAeasy (Qiagen).
Library construction and sequencing was carried out by BGI-Hong Kong using the Illumina® TruSeq™ RNA Sample Preparation Kit.

treatment_protocol: RBP7 over-expressor and RNAi lines were grown in mice with or without doxycycline.

tag: Stage

value: Pleomorphic slender

tag: days after infection


title: OCI-Ly7_ChIPSeq_input

description: Sample 13


title: OCI-Ly10_ChIPSeq_input

description: Sample 10


title: RBP7 (Tb927.10.12100) over-expressor plus dox rep 2

tag: strain


title: RBP7 (Tb927.10.12100) over-expressor plus dox rep 1


title: AnTat minus dox rep 2

source_name: AnTat minus dox rep 2


title: Treated biological replicate 3

city: Padova

first: Davide

last: Risso

address: Via C. Battisti, 241

country: Italy

institute: University of Padova

data_processing:
Illumina Casava1.7 software used for basecalling.
Reads were mapped to a custom reference, defined as the union of the Zv9 reference zebrafish genome downloaded from Ensembl v. 67 and the ERCC spike-in sequences, using TopHat (v. 2.0.4, supplying the Ensembl GTF annotation through the -G option)
Gene-level read counts were generated using the htseq-count python script in the "union" mode and Ensembl (v. 67) gene annotation
Genome_build: Zv9
Supplementary_files_format_and_content: tab-delimited text files contain gene-level read counts for each sample

source_name: Olfactory sensory neuron

growth_protocol: OMP-Gal4;UAS-GCaMP1.6 transgenic zebrafish embryos were collected upon fertilization and raised in embryo media at 28oC.

extract_protocol:
Total RNA was harvested using Trizol reagent & DNase treated. Poly(A)+ RNA was enriched from total RNA using oligo(dT)25 magnetic beads (Life Technologies, cat#61006).
The libraries were prepared using PrepX SPIA RNA-Seq (cat#400030) and ILM DNA Library kits (cat#400044) according to the manufacturer’s (IntegenX, Inc.) protocols.

treatment_protocol: At 16-20 hours post fertilization (hpf), embryos were treated with 100 µM gallein or DMSO (control). Fresh embryo media with the appropriate drug treatment was replaced every 24 hours.  Heads of 5  days post fertilization embryos were dissected and dissociated with trypsin and collagenase and sorted for GFP fluorescence; cells were collected in 1ml of Trizol and stored at -80oC

tag: tansgenic line

value: OMP-Gal4 transgenic zebrafish

tag: cell sorting

value: GFP (+)

value: 100 µM gallein


title: AnTat minus dox rep 1

source_name: AnTat minus dox rep 1


title: Treated biological replicate 2


title: AnTat plus dox rep 2

source_name: AnTat plus dox rep 2


title: RBP7 (Tb927.10.12100) RNAi plus dox rep 2


title: Control biological replicate 2

value: DMSO


title: Control biological replicate 1


title: AnTat plus dox rep 3

source_name: AnTat plus dox rep 3


title: Treated biological replicate 1


title: RBP7 (Tb927.10.12100) RNAi plus dox rep 1

data_processing:
The quality of raw sequence data was assessed using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ).   No additional processing of the primary data was required.
Paired end sequences were aligned to the Tbb genome (obtained from ftp.sanger.ac.uk/pub4/pathogens/Trypanosoma/brucei/Latest_Whole_Genome_Sequence/Tb927_WGS_24_08_2012/chromosomes/ ) using bowtie2 (parameters: --very-sensitive-local; version: 2.0.2), piped through samtools (parameters: -bhS; version: 0.1.18), and stored in indexed BAM format.
The annotated Tbb genome was viewed using Artemis software (http://www.sanger.ac.uk/resources/software/artemis/ ; http://ukpmc.ac.uk/abstract/MED/11120685), and coding segment (CDS) region coordinates extracted prior to conversion to bedtools bedfile format.  Bedtools (paramters: multicov -bams ; version: bedtools 2.15.0) was used to generate coverages for each CDS for each sample replicate.  RPKM-like values were calculated by dividing coverage by CDS size.
Statistical analyses of the three sample groups were undertaken in the R environment (www.R-project.org) using Bioconductor (www.bioconductor.org) packages.  Differential expression was explored using linear models and empirical Bayes methods, using the limma package (Smyth, G. K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 3, No. 1, Article 3. (Online, Tech Report PDF)).  RPKM-like values were offset by 1, logged, and quantile normalised prior to group-wise comparison.  Data were filtered to remove loci whose normalised mean RPKM-like values were below the 10% quantile for all samples (8780 retained, 898 discarded).
master_set.txt
genome build: ftp.sanger.ac.uk/pub4/pathogens/Trypanosoma/brucei/Latest_Whole_Genome_Sequence/Tb927_WGS_24_08_2012/chromosomes/
processed data files format and content: Annotated, normalised RPKM values

growth_protocol: RBP7 RNAi lines grown in mice.

extract_protocol:
RNA was isolated from AnTat1.1 cells grown in mice with doxycycline and from RBP7 RNAi lines grown in mice with or without doxycycline. The method used for RNA extraction was RNAeasy (Qiagen).
Library construction and sequencing was carried out by BGI-Hong Kong using the Illumina® TruSeq™ RNA Sample Preparation Kit.

treatment_protocol: RNAi lines were grown in mice with or without doxycycline.

tag: treatment

value: PlusDox


title: RBP7 (Tb927.10.12100) RNAi minus dox rep 2


title: Control biological replicate 3


title: HG stimulated tubular epithelial cells

city: Kanazawa

first: Yasunori

last: Iwata

state: Ishikawa

country: Japan

institute: Kanazawa University

description: Sample 3

data_processing:
For each of the samples, the PGMTM raw reads were aligned against the human refseq genes (http://www.ncbi.nlm.nih.gov/refseq/ Nov. 2012) using BWA 0.6.2 which uses the 25_1 mapping parameter.
We generated unique gene counts by excluding reads that mapped to contigs of more than one gene.
Reads mapping to several contigs within an isogroup were only counted once.
Genome_build: RefSeq Release 56
Supplementary_files_format_and_content: The processed data was normalized transcripts per million. Text file includes normalized numbers of read tags for each group (mesangium cell and HK-II, HG and mannitol) and gene identifiers.

source_name: HK-II

growth_protocol: Normal human mesangial cells (Lonza, Basel, Switzerland) were cultured in mesangial culture kit (Lonza). Human immortalized TECs, HK-2 (ATCC, Manassas, VA) was cultured in 10% FBS DMEM (Life technologies, Tokyo) with 100 µg/ml streptomycin and 100 U/ml penicillin. All the cells were grown in a humidified atmosphere (5% CO2/95% air) at 37°C and were seeded onto six-well cell culture cluster (Corning Incorporated, Corning, NY).

extract_protocol:
RNA was isolated using mRNA Isolation kit (Sigma-Aldolich, St louis, MO)
Gene expression analysis was performed by SAGE method and NGS. NGS data from the PGMTM was generated from 1μg of total RNA isolated from cell line. SAGE libraries were constructed using the SOLiD SAGETM kit from Life Technologies (Life Technologies) according to manufacturer’s protocol. DNA was recovered from the agarose gel using PureLink Gel Extraction kit (Life Technologies).

treatment_protocol: The cells were stimulated with 30 mM glucose (Wako, Tokyo) for 24 hours for hyperglycemic stimulation. For osmotic control, the cells were cultured with 30 mM mannitol (Wako) for 24 hours.

tag: cell type

value: tubular epithelial cells

value: high glucose


title: Mannitol control of mesangial cells

description: Sample 2

source_name: mesangial cells

value: mesangial cells

value: control


title: OCI-Ly3_RNASeq

description: Sample 3

tag: cell line


title: Mannitol control of tubular epithelial cells

description: Sample 4


title: HG stimulated mesangial cells

description: Sample 1


title: RBP7 (Tb927.10.12100) RNAi minus dox rep 1

value: MinusDox


title: AnTat plus dox rep 1

source_name: AnTat plus dox rep 1

value: AnTat


title: 4P (GFI_225) polysomal RNA, monomorphic S427

description: Polysomal RNA

data_processing:
Adapter sequences and short or poor quality reads were trimmed from the data using Trimmomatic.
An alignment index for SMALT (v0.6.4) was created with a word length of 11 from the most recent GeneDB trypanosome contigs (version: 13/03/2012) (http://www.genedb.org/Homepage/Tbruceibrucei927) with ORFs extended using the predicted UTR data from the Cross Laboratory, with a maximum of 2 mismatches per read and multiple mappings given a score of 0.
Pairwise comparisons of the relative expression of transcripts between life cycle stages were performed using the DESeq 1.11.2 package within R 2.15.1 using a binomial model and a blind variance stabilising transformation, this normalising for variation in raw read counts from individual samples.
Genome_build: GeneDB trypanosome contigs (version: 13/03/2012)
Supplementary_files_format_and_content: Tab-delimited  file includes mean expression values

source_name: Whole organism

extract_protocol:
RNAs were prepared from each life cycle stage harvested 3 days (slender), 4-5 days (intermediate) or 6-7 (stumpy) days after the initiation of infections with T. brucei strains AnTat.1.1 or EATRO 2340.  Parasites were harvested from mouse (female MF1) infections and maintained at 37oC prior to DEAE column purification, also at 37oC. For monomorphic bloodstream form mRNA analysis and for procyclic form analyses, T. brucei brucei Lister S427 was used.  For transfection of pleomorphic trypanosomes, T. brucei AnTat1.1 90:13 was used.  For the bloodstream monomorphic cell samples, cells were grown in 5 flasks of 50 ml culture volumes to a cell density of 1-2 x106 cells/ml. The cells were incubated with cycloheximide (100 µg/ml) for 10 minutes at 37°C, then pelleted by centrifugation for 10 minutes, pooled, and and washed twice in ice-cold PSG containing 100 µg/ml cycloheximide. For the stumpy cell sample, T. brucei AnTat1.1 cells were purified from the blood of four mice 6 days post-infection, cell density was determined and then the cells were incubated with cycloheximide (100 µg/ml) for 10 minutes at 37°C. After centrifugation for 10 minutes the cells were washed once with ice-cold PSG containing 100 µg/ml cycloheximide. Samples were then stored at -80°C . Next, 50% and 15% sucrose solutions (w/v; sucrose in polysome buffer) were sterilized through a syringe filter (0.22 µm; Sartorius Stedim Biotech) and completed with 100 µg/ml cycloheximide, 0.5 µl/ml RNase inhibitor (RNasin, Promega), protease inhibitor cocktail (1 tablet per 50 ml polysome buffer; Roche) and 0.1mM DTT. Gradients were poured using a Hoefer SG 50 Gradient Maker (Amersham Biosciences), magnetic stirrer and MasterFlex C/L peristaltic pump (Cole-Parmer) in to Polyallomer centrifuge tubes (14 x 95 mm; Beckman) and stored at briefly (<2h) at 4° until ultra-centrifugation and fractionation.  Cell samples were lysed (unthawed) through sonication for ~3-6 minutes in a water bath with sonication (Bandelin Sonorex) with brief periods of vortexing. 5 µl of sample was removed to confirm cell lysis by microscopic examination. Cell lysates were then centrifuged at 12 000 rpm for 4 minutes at 4°C and the supernatant transferred to a fresh eppendorf tube containing 1 µl of RNase inhibitor (RNasin). Cell lysate was then  layered on to the top of a 15-50% sucrose gradient and centrifuged in a pre-cooled Beckman L-60 Ultracentrifuge at 40 000 rpm for 2 hours at 4°C, using a SW40 rotor. Thereafter, the centrifuge tube was pierced with a Brandel Tube Piercer and Fluorinert FC-77 (Sigma-Aldrich) pumped through as the high-density chase solution with a Brandel Syringe Pump. The gradient was then separated in to fractions using a Foxy R1 fractionator (Teledyne Isco) (one fraction was taken for every 13 drops) and the optical density read at 254 nm throughout fractionation on a UA-6 Absorbance Detector (Teledyne Isco). PeakTrak software (Teledyne Isco, Inc.) was used to record the absorbance output.  RNA extraction was carried out using the Qiagen RNeasy kit. Following fractionation, 3.5 ml of Buffer RLT with -mercaptoethanol (10 l -mercaptoethanol per 1 ml RLT buffer) was added to each polysome fraction. After overnight storage at -80oC, 2.5 ml of 100% ethanol was added and mixed. RNA was then extracted from each fraction sample using a separate RNeasy column and according to the manufacturer’s instructions for the ‘RNA cleanup’ protocol, including on-column DNase treatment (RNase-Free DNase Set, Qiagen). RNA was eluted from each column with 30 or 40 l nuclease-free water and stored at -80C. RNA concentration was determined using a NanoDrop Spectrophotometer ND-1000 and for the Illumina digital tag sequencing experiment, 10% of each sample was examined on an RNA gel to confirm RNA integrity.
Total RNA from each life cycle stage of these two strains was polyA-enriched, converted to cDNA, fragmented using NlaIII and Solexa sequenced at MWG Eurofins Operon & The Genepool, University of Edinburgh.

value: Lister S427

value: Slender


title: SP (GFI_229) polysomal RNA, stumpy AnTat1.1

description: Polysomal RNA

value: Stumpy


title: 4T (GFI_226) total RNA, monomorphic S427


title: ST (GFI_230) total RNA, stumpy AnTat1.1


title: Smc3 ChIP-seq, RAD21cv HEK293, TEV Treated

city: La Jolla

first: Jesse

middle: R

last: Dixon

state: CA

address: 10010 N. Torrey Pines Rd.

institute: Salk Institute for Biological Studies

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
smc3_TEV.nodup.bw: hg18

growth_protocol: Cells were grown in DMEM supplemented with 0.2mM L-glutamine, 100 U/mL penicillin, 100 mg/mL streptomycin, and 10% fetal calf serum at 37°C and 5% CO2

extract_protocol:
ChIP was performed as previously described in Wendt et al. Nature 2008
Libraries were constructed according to the Illumina protocol

treatment_protocol: A stably integrated transgene in the RAD21cv HEK293T cells was activated for 3 days with 2µg/mL of doxycycline.  Cells were then transfected with a plasmid expressing HRV protease using Lipofectamine 2000 (Invitrogen) for 24 hours before harvesting

value: HEK293T RAD21cv


title: Input ChIP-seq, RAD21cv HEK293, TEV Treated

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
input_TEV.nodup.bw: hg18


title: mRNA-seq, HEK293 siRNA CTCF, replicate one

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
CTCF1.pos.norm.bw: hg18
CTCF1.neg.norm.bw: hg18
CTCF_r1.rpkm: hg18

source_name: mRNA-seq, HEK293 siRNA CTCF

extract_protocol:
Total RNA was extract using Trizol (Invitrogen) according to manufacturer's instructions.  polyA RNA was isolated using Dynalbeads mRNA purification kit (Invitrogen) according to the manufacturer's instructions.
Strand Specific libraries were constructed according to Parkhomchuk et al. 2009, Nucleic Acids Res

treatment_protocol: HEK293T cells were transfected with CTCF siRNA oligos using Lipofectamine 2000 according to manufacterure's instructions.  Cells were harvested 48hrs later.


title: C_St total RNA, stumpy pleomorphic EATRO

value: EATRO 2340


title: INT (GFI_227) intermediate AnTat1.1

value: Intermediate


title: B_INT total RNA, intermediate pleomorphic EATRO


title: mRNA-seq, HEK293 siRNA Control, replicate one

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
CONTROL1.pos.norm.bw: hg18
CONTROL1.neg.norm.bw: hg18
CTRL_r1.rpkm: hg18

source_name: mRNA-seq, HEK293 siRNA Control

treatment_protocol: HEK293T cells were transfected with control siRNA oligos using Lipofectamine 2000 according to manufacterure's instructions.  Cells were harvested 48hrs later.


title: mRNA-seq, RAD21cv HEK293, HRV treated, replicate two

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
HRV2.pos.norm.bw: hg18
HRV2.neg.norm.bw: hg18
HRV_r2.rpkm: hg18

source_name: mRNA-seq, RAD21cv HEK293, HRV treated


title: mRNA-seq, RAD21cv HEK293, HRV treated, replicate one

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
HRV1.pos.norm.bw: hg18
HRV1.neg.norm.bw: hg18
HRV_r1.rpkm: hg18


title: SL (GFI_228) total RNA, slender AnTat1.1


title: A_SL total RNA, slender pleomorphic EATRO


title: mRNA-seq, HEK293 siRNA Control, replicate two

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
CONTROL2.pos.norm.bw: hg18
CONTROL2.neg.norm.bw: hg18
CTRL_r2.rpkm: hg18


title: mRNA-seq, RAD21cv HEK293, TEV treated, replicate one

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
TEV1.pos.norm.bw: hg18
TEV1.neg.norm.bw: hg18
TEV_r1.rpkm: hg18

source_name: mRNA-seq, RAD21cv HEK293, TEV treated

treatment_protocol: A stably integrated transgene in the RAD21cv HEK293T cells was activated for 3 days with 2µg/mL of doxycycline.  Cells were then transfected with a plasmid expressing TEV protease using Lipofectamine 2000 (Invitrogen) for 24 hours before harvesting


title: Hi-C, HEK293 siRNA Control, replicate two

data_processing:
Library strategy: Hi-C
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
CTRL_r2_cis.index.txt: hg18

source_name: Hi-C, HEK293 siRNA Control

extract_protocol:
Hi-C experiments were conducted using HindIII according to previous publication (Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289-93 (2009).).
Sequencing libraries were constructed according to previous publication (Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289-93 (2009).).


title: Hi-C, HEK293 siRNA CTCF, replicate two

data_processing:
Library strategy: Hi-C
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
CTCF_r2_cis.index.txt: hg18

source_name: Hi-C, HEK293 siRNA CTCF


title: Hi-C, HEK293 siRNA CTCF, replicate one

data_processing:
Library strategy: Hi-C
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
CTCF_r1_cis.index.txt: hg18


title: mRNA-seq, RAD21cv HEK293, TEV treated, replicate two

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
TEV2.pos.norm.bw: hg18
TEV2.neg.norm.bw: hg18
TEV_r2.rpkm: hg18


title: Hi-C, RAD21cv HEK293, HRV treated, replicate two

data_processing:
Library strategy: Hi-C
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
HRV_r2_cis.index.txt: hg18

source_name: Hi-C, RAD21cv HEK293, HRV treated


title: Hi-C, RAD21cv HEK293, TEV treated, replicate two

data_processing:
Library strategy: Hi-C
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
TEV_r2_cis.index.txt: hg18

source_name: Hi-C, RAD21cv HEK293, TEV treated


title: Hi-C, RAD21cv HEK293, HRV treated, replicate one

data_processing:
Library strategy: Hi-C
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
HRV_r1_cis.index.txt: hg18


title: mRNA-seq, HEK293 siRNA CTCF, replicate two

data_processing:
fastq:  Illumina's HiSeq Control Software
Hi-C reads were aligned as single end reads using BWA with default parameters.  Uniquely mapping reads were manually paired using in an in house pipeline.  PCR duplicate reads were removed using Picard MarkDuplicates.
RNA-seq data were mapped as paired-end reads using tophat with the following parameters: -g 1 -p 12 --solexa1.3-quals --library-type fr-firststrand --segment-length 25 --bowtie1
RNA-seq bigWig files were generated through an in house pipeline that includes performing trimmed mean of M (TMM) normalization (Robinson et al. Genome Biology 2010)
ChIP-seq data were mapping with bowtie using the following parameters: -v 3 -m 1 --best --strata -S --time -p 8.  Data was filtered for uniquely mapping reads.  PCR duplicates were removed using Picard MarkDuplicates
ChIP-seq bigWig files were generated through an in house pipeline
Genome_build: hg18
Supplementary_files_format_and_content: ChIP-seq and RNA-seq processed files are in bigWig format.  As the RNA-seq experiment was strand specific, bigWig files for both the positive and negative strands are included
Supplementary_files_format_and_content: Hi-C processed files are in a modified bed format.  Each row lists the chromosome and the start and end coordiates of two interacting bins as well as the normalized interaction frequency between these two bins
Supplementary_files_format_and_content: Processed mRNA-seq data include information for each gene and its count and rpkm values.  Each line includes chromosome, start position, end position, strand, gene name, read counts, and rpkm values
Genome Build:
CTCF2.pos.norm.bw: hg18
CTCF2.neg.norm.bw: hg18
CTCF_r2.rpkm: hg18