title: N2 + vector (replicate 3)

city: Quechee

first: Michael

last: Steinbaugh

state: VT

address: PO Box 1520

institute: Acid Genomics

description: poly(A)-enriched RNA

data_processing:
Align reads to C. elegans genome with STAR aligner
Import raw data into RStudio/Bioconductor
Quantification of mapped reads with featureCounts (Subread)
Normalization and differential expression with voom and limma
Genome_build: WBcel235 (Feb 2014)
Supplementary_files_format_and_content: comma separated values (log2CPM)

organism: Caenorhabditis elegans

source_name: whole animal

growth_protocol: Strains were bleach synchronized, L1 arrested, and harvested at day 1 adulthood.

extract_protocol:
Worms were snap frozen in liquid nitrogen. RNA was extracted with phenol/choloroform (TRIzol; Life Technologies), column purified (RNA Clean & Concentrator; Zymo Research), and DNase treated.
RNA libraries were prepared with poly(A) enrichment and sequencing using standard Illumina protocols (50 bp single end).

treatment_protocol: Strains were grown at 25°C. Feeding RNAi was started at egg stage.

tag: RNAi

value: L4440 vector

tag: replicate

value: biological replicate 3

value: day 1 adult


title: glp-1(bn18ts) + vector (replicate 3)

status: Public on Jul 21 2015

type: SRA

middle: J

country: USA

description: poly(A)-enriched RNA

library_source: transcriptomic

molecule: total RNA

tag: strain

tag: age


title: glp-1(bn18ts) + vector (replicate 2)

description: poly(A)-enriched RNA

value: biological replicate 2


title: glp-1(bn18ts) + skn-1 RNAi (replicate 3)

description: poly(A)-enriched RNA

value: skn-1 RNAi


title: glp-1(bn18ts) + skn-1 RNAi (replicate 2)

description: poly(A)-enriched RNA


title: N2 + skn-1 RNAi (replicate 2)

description: poly(A)-enriched RNA


title: N2 + vector (replicate 2)

description: poly(A)-enriched RNA


title: glp-1(bn18ts) + vector (replicate 1)

description: poly(A)-enriched RNA

value: biological replicate 1


title: N2 + vector (replicate 1)

description: poly(A)-enriched RNA


title: HiC_replicate2_mESC

city: Stockholm

first: Ilgar

last: Abdullayev

address: Nobels väg 3

department: Cell and Molecular Biology

country: Sweden

institute: Karolinska Institutet

description:
Hi-C biological replicate 2
HiC_promoter-enhancer.gff.gz

library_source: genomic

data_processing:
Mapping of reads. Paired-end sequences were aligned to the mouse genome (build mm9) through the tool HiCUP (Babraham Bioinformatics). We then used custom scripts to pair the independently mapped sequence ends and we indexed each sequence pair to their corresponding MboI restriction fragment.
Calling of interactions. We called significant interactions for all promoter containing restriction fragments. To this end, aligned pairs of which at least one mate mapping on a promoter were selected. Promoter regions were defined as 1000 bases downstream and 3000 bases upstream of transcription start site. The extension allowed mappings involving the directly surrounding fragment of the promoter-anchored fragment to be incorporated into analyses, as restriction cut efficiency was only 71%. Nonetheless, in 77% of interactions detected in first HiCap replicate and 92% of interactions detected in the second HiCap replicate, all reads mapped to sequence capture probes. We collected all paired sequences with one end originating from a promoter region and the other end at least 1000 bp away from the promoter region. Next we counted the occurrence of interactions to all MboI restriction fragments in the genome from each captured promoter region. Read pairs with the exact same mapping positions were discarded (to remove any potential effect from PCR duplicates). The same procedure was applied to the negative control regions to obtain read pairs for interactions that were later used as background interaction probabilities. We binned all negative control interactions distances (bin size of 1kb) and calculated the average and standard deviation of the number of interactions found per fragment for negative control regions (discarding fragments with zero interactions from the calculations). These background probabilities of interactions were then used to assess whether each promoter-anchored interaction was significant in each biological replicate independently, using a Z-test. We adjusted the P-values, to account for the multiple tests performed, using the Benjamini-Hochberg procedure and we required a significant interaction to have adjusted P-values below 0.2 in both biological replicates, resulting in an effective adjusted P-value threshold of 0.04 since interactions were required to be present in both biological replicates. Additionally, we required at least 4 supporting read pairs in each biological replicate. Promoter-promoter interactions were called similarly, but requiring that both ends of the paired reads aligned within the annotated promoter regions.
Using significant promoter-enhancer interactions (read threshold 3) we generated a GFF files (for biological replicates separately and for replicated interactions between them) for visualization in Genome Browser.
Genome_build: mm9
Supplementary_files_format_and_content: GFF

molecule: genomic DNA

organism: Mus musculus

source_name: Embryonic stem cells

growth_protocol: Mouse  embryonic stem cells (line R1) were obtained from Janet Rossant’s lab (Toronto, Canada). Cells were maintained on 0.1% gelatin-coated dishes in Dulbecco modified Eagle medium (DMEM) supplemented with 10% fetal calf serum (FCS), 0.1 mM non- essential amino acids, 0.3 mg/ml L-glutamine, 1 mM pyruvate (Invitrogen), 1000 U/ml murine LIF (Chemicon International ESGRO), and were kept in a 5% CO2 atmosphere at 37 °C. The medium of undifferentiated cells was changed daily.

extract_protocol:
Cells were cross-linked with 1% formaldehyde for 10 minutes, lysed and nuclei were isolated. Isolated nuclei were digested with 4-cutter FastDigest MboI (Thermo Scientific, 1µl/µg DNA) for 4 hours at 37 °C. The ends of digested material were filled with biotinylated dATP, dGTP, dCTP and dTTP using Klenow fragment (Fermentas, 0.1 U per 1 µg DNA).  Klenow was deactivated using 0.01 M EDTA at incubating 75 °C for 15 minutes. Then the material was diluted to 3.5 ng/µl and ligated using T4 DNA Ligase (Promega). The crosslinking was reversed by adding Proteinase K and incubating overnight at 65 °C. The proteins were removed and DNA was purified using phenol-chloroform followed by ethanol precipitation. Biotinylated but unligated ends were removed using T4 DNA polymerase by incubating at 12 °C for 15 minutes. The material was fragmented to 300-600 bases by sonication. The fragment ends were repaired and A-tailed. Then the biotinylated fragments were bound to streptavidin beads and unbound fragments were washed away. Sequencing adapters were then ligated to the fragments bound to beads. The material was amplified 6-9 cycles while bound to beads to obtain sufficient amount for sequence capture. Original biotinylated material was removed, supernatant was hybridized to sequence capture probe set according to manufacturer’s instructions (Roche Nimblegen Inc.). Hybridized material was washed according to manufacturer’s instructions and amplified with PCR for 3-6 cycles. Hybridization of the probes to the Hi-C material was done exactly according to the manufacturer’s instructions (Roche Nimblegen Inc).
Libraries were prepared for sequencing using Illumina TruSeq protocol

tag: cell line


title: MOLP8_KD_2

city: Boston

first: Salomon

last: Manier

state: Massachusetts

address: 77 Ave Louis Pasteur

department: Medical Oncology

institute: DFCI

data_processing:
We used Bcbio_nextgen (https://github.com/chapmanb/bcbio-nextgen/) to process the RNA-seq data
Cutadapt was used to trim adapters
Trimmed reads were aligned to Human reference genome (GRCh37) with tophat2
Read counts for each gene was calculated by HT-seq
Genome_build: GRCh37
Supplementary_files_format_and_content: RPKM files

organism: Homo sapiens

source_name: Multiple Myeloma cell line

growth_protocol: Cells were grown in RPMI 10% FBS containg

extract_protocol:
Total RNA was extracted using RNeasy Mini kit (QIAGEN).
NEBNext RNA library prep kit

treatment_protocol: Puromycin 1ug/mL for selection

tag: condition

value: LIN28B KO cells


title: HiC_replicate1_mESC

description:
Hi-C biological replicate 1
HiC_promoter-enhancer.gff.gz


title: scRNASeq: R1 SSEA1+ Cell84

first: avinash

last: waghray

state: MA

address: 185 Cambridge Street, CPZN Room 4254A

department: Center for Regenerative Medicine

institute: Massachussets General Hospital

description: single cell mRNA-Seq

data_processing:
Single Cell RNASeq: Fastq files were mapped to the genome using Tophat: tophat -o -p 4
Single Cell RNASeq: Output ".bam" files were process to get counts: cuffquant -o cell2_cuffquant -p 4
Single Cell RNASeq: Output ".cxb" files were processed to get FPKM values: cuffnorm -o cuffnorm_allLibs -p 4
Genome_build: mm9

molecule: polyA RNA

source_name: SSEA1+ wildtype mESCs

growth_protocol: R1 mESCs were cultured in mESC media containing serum and LIF without feeders

extract_protocol:
The cDNA synthesis was done following the manufacturers instruction using the C1 Single-Cell Auto Prep System (Fluidigm). Amount of cDNA synthesized was quantified using the Quant-iT™ PicoGreen® dsDNA Assay Kit (Life Technologies).
Sequencing libraries were prepared using the Nextera XT DNA Library Prep Kit (Illumina). About 24 libraries were mixed together. The concentration of the mixed libraries was assayed using Agilent Bioanalyzer.  The libraries were sequenced using 1*100bp on a HiSeq 2000/2500 platform at the genomics SRF at Mount Sinai and NYU genomics core.

treatment_protocol: SSEA1+DAPI- mESCs were sorted and collected

tag: cell type

value: embryonic stem cells

tag: cell line used

tag: cell population


title: scRNASeq: R1 SSEA1+ Cell80

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell85

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell87

description: single cell mRNA-Seq


title: N2 + skn-1 RNAi (replicate 3)

description: poly(A)-enriched RNA


title: FL_LSK_K27ac_100_Rep2

city: Iowa City

first: Kai

last: Tan

state: IA

address: 3292 CBRB, 285 Newton Road

department: Internal Medicine

institute: The University of Iowa

data_processing:
Raw sequencing reads were mapped to the human genome (hg19) or mouse genome (mm9) using Bowtie2 (v2.2.2) with default parameter setting. Only uniquly mapped reads were used for analysis
ChIP-seq peaks were identified by two peak caller, MACS (p-value < 10-5) and SPP (z-score > 4) with default parameter setting.
To generate the wig files, the human or mouse genome was divided into 100 bp bins, and the number of uniquely mapped reads were counted in each bin. We normalized the tag counts in each bin according to the total number of uniquely mapped reads. Input reads were processed in the same way and their normalized signals were subtracted from the ChIP-seq tracks.
Normalized wig files were converted to binary bigwig files
Genome_build: hg19 and mm9
Supplementary_files_format_and_content: bigwig files

source_name: Mouse Embryonic day 14.5 Fetal Liver

extract_protocol:
Cells were cross-linked for 5 min with 1% formaldehyde at room temperature prior to quencing with 125mM glycin. Cross-linked cells were sonicated using Covaris S2 sonicator for 14 min with 5% duty, Intensity 3 and Bursts 200. The sonicated lysate was centrifuged at a speed of 14000×g for 10 min under 4°C. The cleared chromatin (10000 cells per 100 µl) in the supernatant was transferred to a new low-bind Eppendorf tube for subsequent microfluidic ChIP.
[Isolation protocol] FLs were dissected from E14.5 embryos. Single cell suspensions were prepared by dissociating mechanically and expelling the cells through 40 μm Nylon filter, followed by red blood cell lysis (ACK Lysing Buffer, Lonza). To remove non-specific binding, anti-mouse CD16/CD32 (Fc Block, Biolegend) were added into single cell suspensions and incubated 10 min at 4°C. Next, Cells were stained with a cocktail of antibodies against several surface markers, including lineage markers (Ly-6G/Ly-6C, CD45R/B220, CD3ε, TER-119, CD4, CD8a, and CD19), CD117 (c-Kit), and Ly-6A/E (Sca-1). Cells were first subjected to yield sort for Lineage-Sca-1+c-Kit+ (LSK) and collected into 500µL 1×IMDM+20% FBS in a 12×75-mm polystyrene tube. Collected cells were then performed purity sort using the same gate strategy and sorted into 0.8 mL 1×IMDM+50% FBS in a 1.5 mL DNA LoBind tube.
The ChIPed and input DNA was constructed into libraries by using the ThruPLEX FD Kit (Rubicon Genomics, Ann Arbor, MI, USA). During the amplification step, 11cycles was needed to get enough library from input DNA without over-amplification. 12~13 cycles is needed for ChIPed DNA extracted from 10000 cells. 14~15 cycles is normally required for ChIPed DNA from 1000 or less cells.

value: B6129SF1 crossed with C57BL/6

value: Fetal Liver, Lineage-Sca1+c-Kit+ (LSK)

tag: chip antibody

value: H3K27ac (ab4729, Abcam, Cambridge, MA, USA)


title: FL_LSK_K27ac_100_Rep1


title: scRNASeq: R1 SSEA1+ Cell78

description: single cell mRNA-Seq


title: glp-1(bn18ts) + skn-1 RNAi (replicate 1)

description: poly(A)-enriched RNA


title: N2 + skn-1 RNAi (replicate 1)

description: poly(A)-enriched RNA


title: scRNASeq: R1 SSEA1+ Cell73

description: single cell mRNA-Seq


title: FL_LSK_K4me3_100_Rep2

value: H3K4me3 (07-473, Millipore,Billerica, MA, USA)


title: scRNASeq: R1 SSEA1+ Cell74

description: single cell mRNA-Seq


title: FL_LSK_K4me3_100_Rep1


title: scRNASeq: R1 SSEA1+ Cell69

description: single cell mRNA-Seq


title: FL_LSK_Input

extract_protocol:
[Isolation protocol] FLs were dissected from E14.5 embryos. Single cell suspensions were prepared by dissociating mechanically and expelling the cells through 40 μm Nylon filter, followed by red blood cell lysis (ACK Lysing Buffer, Lonza). To remove non-specific binding, anti-mouse CD16/CD32 (Fc Block, Biolegend) were added into single cell suspensions and incubated 10 min at 4°C. Next, Cells were stained with a cocktail of antibodies against several surface markers, including lineage markers (Ly-6G/Ly-6C, CD45R/B220, CD3ε, TER-119, CD4, CD8a, and CD19), CD117 (c-Kit), and Ly-6A/E (Sca-1). Cells were first subjected to yield sort for Lineage-Sca-1+c-Kit+ (LSK) and collected into 500µL 1×IMDM+20% FBS in a 12×75-mm polystyrene tube. Collected cells were then performed purity sort using the same gate strategy and sorted into 0.8 mL 1×IMDM+50% FBS in a 1.5 mL DNA LoBind tube.
Cells were cross-linked for 5 min with 1% formaldehyde at room temperature prior to quencing with 125mM glycin. Cross-linked cells were sonicated using Covaris S2 sonicator for 14 min with 5% duty, Intensity 3 and Bursts 200. The sonicated lysate was centrifuged at a speed of 14000×g for 10 min under 4°C. The cleared chromatin (10000 cells per 100 µl) in the supernatant was transferred to a new low-bind Eppendorf tube for subsequent microfluidic ChIP.
The ChIPed and input DNA was constructed into libraries by using the ThruPLEX FD Kit (Rubicon Genomics, Ann Arbor, MI, USA). During the amplification step, 11cycles was needed to get enough library from input DNA without over-amplification. 12~13 cycles is needed for ChIPed DNA extracted from 10000 cells. 14~15 cycles is normally required for ChIPed DNA from 1000 or less cells.

value: None (input)


title: SW480/pRTR +DOX  miRNA-Seq

city: Munich

first: Sabine

last: Huenten

address: Thalkirchner Strasse 36

country: Germany

description: small RNA sequencing data

data_processing:
Libraries were sequenced on an Illumina HiScan (HiSeq Control Software v. 1.4; CASAVA 1.8)
Fastq files were processed with an in-house pipeline consisting of adapter trimming, read alignment, read counting and normalization. Adapters were trimmed by computing a suffix-prefix alignment of each read against the Illumina 3’ adapter sequence.
Trimmed reads were then aligned to the reference genome (hg19) using bowtie 0.12.7 allowing for up to 2 mismatches.
All best matches were retained and multi-mapping reads were equally divided among all mapping sites.
To compute miRNA read counts all reads mapping to annotated mature miRNA positions (according to mirbase v16) were considered. At their 3’ end, a tolerance of +/- 3 bp was allowed, but no tolerance at their 5’ end.
Normalization was performed by fitting a robust linear model to the quantile-quantile plot of log miRNA counts and taking the offset as normalization factor.
Genome_build: miRBase 16
Supplementary_files_format_and_content: miRNA read counts, txt-format

source_name: Colorectal cancer cells

growth_protocol: SW480 cells and their derivatives were cultured in DMEM grwoth medium containig 10% FBS at 37°C and 5%CO2.

extract_protocol:
Total RNA was isolated using the Trizol reagent (Life Technologies) following the manufacturer’s protocol. The small RNA fraction  (representing lengths of about 18 to 25 nt) was gel-purified.
In short, an adenylated adapter was ligated to the 3’ end of the small RNA by a truncated T4 RNA Ligase 2, followed by the ligation of the 5’ adapter by T4 RNA Ligase 1 (NEB). After reverse-transcription with a specific primer, the cDNA was amplified by PCR. The correct PCR product was gel-purified, eluted in elution buffer, precipitated and solved in water. The quality of the libraries was assessed by qPCR and Bioanalyzer measurements.

treatment_protocol: SW480 cells were treated with DOX (100 ng/ml) for 16 hours to induce ectopic expression of p53.

tag: vector

value: pRTR

tag: treatment

value: 16 hours doxycyclin


title: FL_LSK_K27ac_600_Rep2

value: H3K27ac (Abcam, catalog# ab4729, lot# GR183919-1)


title: scRNASeq: R1 SSEA1+ Cell68

description: single cell mRNA-Seq


title: FL_LSK_K27ac_600_Rep1


title: FL_LSK_K27ac_1K_Rep2


title: scRNASeq: R1 SSEA1+ Cell66

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell64

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell63

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell62

description: single cell mRNA-Seq


title: FL_LSK_K27ac_10K_Rep1


title: FL_LSK_K4me3_600_Rep2

value: H3K4me3 (Millipore, catalog# 07-473, lot# 2289139)


title: FL_LSK_K27ac_1K_Rep1


title: FL_LSK_K27ac_10K_Rep2


title: scRNASeq: R1 SSEA1+ Cell71

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell70

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell61

description: single cell mRNA-Seq


title: MOLP8_KD_3


title: scRNASeq: R1 SSEA1+ Cell59

description: single cell mRNA-Seq


title: FL_LSK_K4me3_1K_Rep2


title: scRNASeq: R1 SSEA1+ Cell57

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell56

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell55

description: single cell mRNA-Seq


title: FL_LSK_K4me3_10K_Rep2


title: FL_LSK_K4me3_600_Rep1


title: scRNASeq: R1 SSEA1+ Cell53

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell72

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell52

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell49

description: single cell mRNA-Seq


title: Tbx3 +/N RNASeq

description: Tbx3 heterozygous mESCs

data_processing:
RNASeq: Fastq files were mapped to the genome using Tophat: tophat -o -p 4
RNASeq: Tophat output files were processed through Cufflinks (cufflinks -p 4 -L -o) and Cuffdiff (cuffdiff -o -L) programs to conduct differential gene expression analysis.
RNASeq: Homer package was used to generate the bedGraph files using the commands: makeTagDirectory and makeUCSCfile.
Genome_build: mm9
Supplementary_files_format_and_content: bed file with peaks; bedGraph files with read counts

source_name: mESCs

extract_protocol:
For ChIP cells were fixed with 11% formaldehyde in mESC media for 10 minutes on a rotating platform. The fixation was stopped by addition of 125nM of Glycine for 5 minutes on a rotating platform. Cells were scraped, quick-frozen and stored at -80°C. ChIP was done by pulling down the bfTbx3 protein using Dynabeads conjugated to streptavidin (SA) in Tbx3N/N+NBirA+bfTbx3 cells. Pull down in Tbx3N/N+NBirA cells was used as negative control.  For mRNA-Seq sample preparation, the total RNA was isolated using Trizol reagent following the manufacturer’s instructions. Quality and quantity of total RNA was assayed using Nanodrop and Agilent Bioanalyzer.
For ChIPSeq, DNA library preparation was done using the Illumina ChIP-seq sample prep kit. The libraries were run on HiSeq 2000 machine. For mRNA-seq, libraries were prepared using the TrueSeq protocol from Illumina. The concentration of the libraries was assayed using Agilent Bioanalyzer and sequenced either using 1*26bp or 1*100bp on an Illumina Genome analyzer II or HiSeq 2000 platform

tag: genotype


title: Tbx3 N/N RNASeq

description: Tbx3 null mESCs


title: scRNASeq: R1 SSEA1+ Cell67

description: single cell mRNA-Seq


title: Tbx3 +/+ RNASeq

description: Tbx3 wildtype mESCs


title: Subject 3 Infecting Strain-During Natural Infection

first: Ryan

last: McClure

address: 650 Albany St.

institute: Boston University

description:
Various organisms, sample from human female genital tract, mainly human and N. gonorrhoeae.
Isolated from human female genital tract

data_processing:
fastq files output from Illumina machine were examined by Rockhopper with default parameters (McClure, et. al. Nucleic Acids Res, 2013, 41(14)).
Alignment was to the NCCP11945 Neisseria gonorrhoeae genome (Accession # NC_011035)
Genome_build: ASM2010v1
Supplementary_files_format_and_content: Table_S1_Expression_All_Genes_Seperated.txt reports RPKMs

organism: Neisseria gonorrhoeae

source_name: Lavage from female subject

growth_protocol: Isolated from human female genital tract or grown in CDM

extract_protocol:
TRIzol according to manufacturer's instructions, both prokaryotic and eukaryotic rRNA was depleted from all samples
BioChain’s High Yield Directional mRNA Sample Prep Kit

tag: infected host

value: female human

tag: host identifier

value: Subject 3

tag: protocol

value: N. gonorrhoeae isolated from human female genital tract


title: scRNASeq: R1 SSEA1+ Cell30

description: single cell mRNA-Seq


title: Subject 3 Infecting Strain-During Growth in CDM

description: Isolated after growth in CDM

source_name: Infecting N. gonorrhoeae strain

value: N. gonorrhoeae grown in CDM


title: Subject 2 Infecting Strain-During Natural Infection

value: Subject 2


title: GM12878_K27ac_direct_100_Rep1

growth_protocol: GM12878 cells were grown in RPMI 1640 medium (Gibco) supplemented with 15% Fetal Bovine Serum (FBS) (Gibco), penicillin (Invitrogen), streptomycin (Invitrogen). Cultures were seeded at a concentration of between 200,000 and 500,000 viable cells per mL. Medium was changed every 2-3 days depending on cell density.

extract_protocol:
The procedure was different for preparing sonicated chromatin from 100 or 600 cells directly. Cells were counted with a hematocytometer and 100/600 cells were transferred to a 1.5 ml LoBind Eppendorf tube containing 10 µl 10% FBS in PBS. Cells were then cross-linked for 5 min at room temperature by adding 0.625 µl 16% formaldehyde to yield a final concentration of 1%. Cross-linking was quenched by adding 1.25 µl 2.5 M glycine for 5 min at room temperature. The cross-linked sample was then diluted using 120 µl Covaris sonication buffer (to give a total volume of 130 µl) and sonicated with a Covaris E220 sonicator for 8 min with 5% duty, 105 peak incident power and 200 cycles per burst in a Covaris microtube (520045, Covaris). The sonicated lysate was centrifuged at 14000×g for 10 min at 4°C. Sonicated chromatin in the supernatant was transferred to a new 1.5 ml LoBind Eppendorf tube for MOWChIP-Seq.
The ChIPed and input DNA was constructed into libraries by using the ThruPLEX FD Kit (Rubicon Genomics, Ann Arbor, MI, USA). During the amplification step, 11cycles was needed to get enough library from input DNA without over-amplification. 12~13 cycles is needed for ChIPed DNA extracted from 10000 cells. 14~15 cycles is normally required for ChIPed DNA from 1000 or less cells.

value: B-lymphocyte


title: FL_LSK_K4me3_1K_Rep1


title: scRNASeq: R1 SSEA1+ Cell29

description: single cell mRNA-Seq


title: GM12878_K27ac_direct_100_Rep2


title: Subject 2 Infecting Strain-During Growth in CDM_B

description: Isolated after growth in CDM


title: GM12878_K27ac_direct_600_Rep1


title: GM12878_K27ac_direct_600_Rep2


title: scRNASeq: R1 SSEA1+ Cell23

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell24

description: single cell mRNA-Seq


title: Subject 2 Infecting Strain-During Growth in CDM_A

description: Isolated after growth in CDM


title: GM12878_K4me3_direct_100_Rep1


title: Subject 4 Infecting Strain-During Natural Infection

value: Subject 4


title: Subject 1 Infecting Strain-During Growth in CDM

description: Isolated after growth in CDM

value: Subject 1


title: GM12878_K4me3_direct_600_Rep2


title: SW480/pRTR-p53-VSV +DOX  miRNA-Seq

description: small RNA sequencing data


title: GM12878_K4me3_direct_100_Rep2


title: Subject 1 Infecting Strain-During Natural Infection


title: FL_LSK_K4me3_10K_Rep1

value: B6129SF1 crossed with C57BL/6


title: scRNASeq: R1 SSEA1+ Cell20

description: single cell mRNA-Seq

value: embryonic stem cells


title: GM12878_Input

extract_protocol:
Cells were cross-linked for 5 min with 1% formaldehyde at room temperature prior to quencing with 125mM glycin. Cross-linked cells were sonicated using Covaris S2 sonicator for 14 min with 5% duty, Intensity 3 and Bursts 200. The sonicated lysate was centrifuged at a speed of 14000×g for 10 min under 4°C. The cleared chromatin (10000 cells per 100 µl) in the supernatant was transferred to a new low-bind Eppendorf tube for subsequent microfluidic ChIP.
The ChIPed and input DNA was constructed into libraries by using the ThruPLEX FD Kit (Rubicon Genomics, Ann Arbor, MI, USA). During the amplification step, 11cycles was needed to get enough library from input DNA without over-amplification. 12~13 cycles is needed for ChIPed DNA extracted from 10000 cells. 14~15 cycles is normally required for ChIPed DNA from 1000 or less cells.


title: scRNASeq: R1 SSEA1+ Cell18

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell32

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell19

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell31

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell16

description: single cell mRNA-Seq


title: GM12878_K27ac_100_Rep2


title: scRNASeq: R1 SSEA1+ Cell13

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell10

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell11

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell15

description: single cell mRNA-Seq


title: GM12878_K27ac_600_Rep1


title: GM12878_K27ac_100_Rep1


title: GM12878_K27ac_600_Rep2


title: scRNASeq: R1 SSEA1+ Cell6

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell5

description: single cell mRNA-Seq


title: GM12878_K4me3_direct_600_Rep1


title: GM12878_K27ac_10K_Rep1


title: GM12878_K27ac_10K_Rep2


title: scRNASeq: R1 SSEA1+ Cell4

description: single cell mRNA-Seq


title: GM12878_K27ac_1K_Rep1


title: scRNASeq: R1 SSEA1+ Pool

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell1

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell2

description: single cell mRNA-Seq


title: scRNASeq: R1 SSEA1+ Cell3

description: single cell mRNA-Seq


title: GM12878_K4me3_100_Rep2


title: GM12878_K4me3_600_Rep2


title: GM12878_K4me3_600_Rep1


title: Nkx2-5-ChIP

city: New Orleans

first: Yiping

last: Chen

state: LA

address: 6400 Freret

department: CMB

institute: Tulane University

description: antibody: anti-Nkx2-5 (SantaCruze. Cat. N-19, Lot. SC-8697, 1:1 mixed  Lot C0113 and Lot 12514

data_processing:
Standard mapping using bowtie for illumina inserted in the Galaxy main instance
Peaks calling using MACS/MACS2 with default setting in Galaxy main/Cistrome instance
mm9
bedgraph files are generated by MACS
Bedgraph was converted to bigwig using Bedgraph to bigwig tool in Galaxy main instance
Genome_build: mm9

source_name: ChIP-Sequencing on Shox2-HA E12.5 heart (contain proximal part of pulmonary vein and R/LSVC, part of ventricle was dissected away)

growth_protocol: fresh dissected tissue

extract_protocol:
ChIP, following manufracture protocol provided by Active Motif ChIP-IT high sensitivity protocol
Illumina sequencing libraries were prepared from the ChIP and Input DNAs by the standard consecutive enzymatic steps of end-polishing, dA-addition, and adaptor ligation. After a final PCR amplification step, the resulting DNA libraries were quantified and sequenced

tag: tissue

value: heart

tag: developmental stage


title: Input


title: GM12878_K4me3_10K_Rep2


title: HA-Shox2-ChIP

description: antibody: anti-HA(Abcam, Cat.Ab9110, Lot.  GR146572-6)


title: GM12878_K4me3_1K_Rep1


title: GM12878_K4me3_1K_Rep2


title: GM12878_K27ac_1K_Rep2


title: Tbx3 N/N-BirA-bfTbx3 ChIPSeq

description: Tbx3 null mESCs expressing Biotin Ligase BirA and Flag-Biotin-Tbx3

data_processing:
ChIPSeq: Fastq files were mapped to the genome using Bowtie (v1.0): bowtie -p 4 -n 2 -l 100 --best -m 1
ChIPSeq: The mapped output file was processed through MACS analysis (v1.4) software to determine peaks: macs14 -t  -c -g mm -w -S -n
ChIPSeq: Homer software was used for annotation of the peaks: annotatePeaks.pl mm9
ChIPSeq: bigWig files: generated from the online Galaxy program at https://usegalaxy.org/
Genome_build: mm9
Supplementary_files_format_and_content: bed file with peaks; bedGraph files with read counts


title: GM12878_K4me3_10K_Rep1


title: Tbx3 N/N-BirA ChIPSeq

description: Tbx3 null mESCs expressing Biotin Ligase BirA


title: shTbx3 RNASeq

description: Wildtype mESCs with shTbx3


title: shLuc RNASeq

description: Wildtype mESCs with shLuciferase


title: GM12878_K4me3_100_Rep1


title: BY4741

city: PARIS

first: Simon

last: Lebaron

address: 4 avenue de l'observatoire

country: France

institute: Université Paris Descartes

description:
S.cerevisiae BY4741 (ASY079)
Cells were grown in minimum media and directly corss-linked in the cutlutre media using the Megatron approach at 30°C

data_processing:
Fastx_clipper -a data.fastq -l10 -c -v. Use to eliminate adapter sequence from the reads.
Tmapall -F Saccharomyces_cerevisiae.EF2.59.1.0.fa -r Trimeddata.fastq -v -g 0 -y -u -o 1 stage1 ma1 map2 map3 map4. Map reads to Saccharomyces cerevisiae S288C genome using Tmap
pyReadCounters.py -f input.novo generated sgr files. Custom program used to generate hit tables and plots of read density. From the pyCRAC software package (sandergranneman.bio.ed.ac.uk/Granneman_Lab/pyCRAC_software.html).
Genome_build: SGD S288C
Supplementary_files_format_and_content: SGR files (.sgr) Tab-delimited graph format. Sequence graph files that show base coordinate scores. These files are generated by CNAT (the Affymetrix Chromosome Copy Number Analysis Tool software). The format of .sgr text files is: chromosome identification, then two columns of numbers separated by a single space or a tab. The first number is the base position; the second number is the score

organism: Saccharomyces cerevisiae BY4741

source_name: yeast cells

growth_protocol: Cells were grown in YMM, gulcose media without tryptophane

extract_protocol:
Lysate were clarified and a two-step IP was performed with one in denaturing condition (6M guanidinium),
RNA.Rrp5 complexes were seperated by SDS-PAGE, transferred to a nitrocelluose membrane and extracted. Protein was removed by Prrteinase K digestion and RNAs purified by phenol:chloroform extraction.  Extracted RNAs were converted to cDNA and PCR amplified. PCR products between ~150 and 250 bp were gel extracted and submitted forTorrent Sequencing.

treatment_protocol: After cross-link cells were centrifuged and frozen at -80°C

tag: protein-tag

value: Control no tag

value: MATalpha; ura3-52; leu2-3,112; his3-delta-200; lys2-delta-201; GAL2;

tag: uv-crosslink

value: megatron


title: H3K27Ac_EV_ChIPSeq

status: Public on Jul 20 2015

city: Cambridge

first: Evangelia

last: Diamanti

address: Wellcome Trust / MRC Building, Hills Road

department: Haematology

country: United Kingdom

institute: University of Cambridge

data_processing:
ChIP-seq reads were aligned to mm10 using bowtie2 (version 2.0.6) with options -k 2 -N 1.
bigWig density profiles were created with in-house script incorporating UCSC's wigToBigWig utility.
Peaks were called using MACS2 (version 2.0.10).
Genome_build: GRCm38 (mm10)
Supplementary_files_format_and_content: Density profiles (bigWig) and peaks (bed).

source_name: X18.1.1 AML cell line, empty vector, H3K27Ac ChIP

growth_protocol: Cells were maintained in high-glucose RPMI 1640 supplemented with 10% fetal calf serum, 1% penicillin/streptomycin, 300μM asparagine, 2mM L-glutamine and 50µM beta-mercaptoethanol. Cells were partially adherent requiring trypsin treatment for passage, and were maintained between 3-10 x10^5 cells/ml.

extract_protocol:
Lysates were clarified from sonicated nuclei and histone-DNA complexes were isolated with antibody.
Library construction was performed using the Illumina TruSeq DNA Sample Kit (Cat. No. IP-202-1012), with quantification performed with the Kapa SYBRFAST Universal qPCR kit (Cat. No. KK4824), both according to manufacturer's instructions.

treatment_protocol: 100nM OHT for 2 hours.

value: AML cell line

tag: transfection

value: empty vector

value: H3K27Ac (Abcam ab4729)


title: IgG_EV_ChIPSeq

source_name: X18.1.1 AML cell line, empty vector, IgG ChIP

tag: cell line

value: Rabbit IgG (Sigma I5006)


title: IgG_PuER_ChIPSeq

source_name: X18.1.1 AML cell line, PuER, IgG ChIP

value: PuER


title: Rpf2-HTTP

value: MATalpha; ura3-52; leu2-3,112; his3-delta-200; lys2-delta-201; GAL2; RPF2-HTP-URA3


title: H3K27Ac_PuER_ChIPSeq

source_name: X18.1.1 AML cell line, PuER, H3K27Ac ChIP


title: 12 days post-fertilization (dpf) embryo sample (MH_0016)

city: Woods Hole

first: Neelakanteswar

last: Aluru

address: 45 Water Street

department: Biology

institute: Woods Hole Oceanographic Institution

data_processing:
Data was analyzed using CLC Genomics workbench (Version 4.7.2.; Qiagen Inc.). All the analysis was done in color space format. The analysis work flow involved adaptor trimming, counting different unique small RNA sequences and mapping them to zebrafish, medaka, puffer fish precursor microRNA sequences obtained from miRBase version 21.
Expression values (counts) were for mature microRNAs were obtained
All precursor microRNAs from killifish were summarized and provided as a fasta file
Precusor microRNAs obtained from sequence analysis were mined from the draft genome (unpublished) and genome coordinates were extracted. They are provided in the bed file.
Genome_build: miRBase version 21
Supplementary_files_format_and_content: Four files were expression values, one fasta file with all precursor sequences and one bed file with genome coordinates of all precursor sequences. A total of 6 processed files are provided.

organism: Fundulus heteroclitus

source_name: New Bedford Harbor (NBH), Massachusetts

extract_protocol:
Total RNA from the different stages of embryos was isolated using STAT60 method (Tel-Test, Inc., Friendswood, Texas) and quantified using Nanodrop spectrophotometer. Quality of the total RNA was checked by running the samples on a Agilent Small RNA kit using 2100 Bioanalyzer. All the samples had RNA integrity number of >9.8.
Small RNA library construction and microRNA sequencing were performed by the Genomic Services Lab at the HudsonAlpha Institute for Biotechnology in Huntsville, AL, USA. Small RNA libraries were prepared using the small RNA expression kit (SREK) protocol (Applied Biosystems, Foster City, CA). Sequencing was done on a SOLiD V3 system (Applied Biosystems).

treatment_protocol: Gametes from Adult killfiish from NBH and SC populations were in vitro fertilized to obtain embryos. Embryos were raised in full strength sea water at 22oC and sampled daily upto 15 days post-fertilzation.

value: 12 dpf embryos

tag: strain

value: New Bedford Harbor

tag: generation


title: RC3H1_PARCLIP

city: Berlin

first: Markus

last: Landthaler

address: Robert-Rössle-Straße 10

department: Berlin Institute for Medical Systems Biology

institute: Max-Delbrück-Center for Molecular Medicine

description: binding sites

data_processing: Adapters were removed with FAR 1.81 (the felxible adapter remover: http://sourceforge.net/projects/theflexibleadap/) aligned to hg18 and a set of RefSeq pre-mRNA sequences with BWA 0.5.8c. Unique alignments were converted to a pileup and read clusters scored for characteristic conversions and read variability with a custom script. After stringent-false positive filtering (using antisense clusters as a decoy database) remaining clusters were output as bed files. See Lebedeva et al. 2011 Mol Cell 43, 340–352 for details.

source_name: HEK293 cell culture

growth_protocol: Flp-In 293 T-REx cells (Invitrogen) were grown in D-MEM high glucose with 10% (v/v) fetal bovine serum, 1% (v/v) 2 mM L-glutamine, 1% (v/v) 10,000 U/ml penicillin 10,000 µg/ml streptomycin.

extract_protocol: PAR-CLIP cDNA and small RNA cDNA preparation were prepared as described in Hafner et al. 2010 Cell 141, 129–141.

treatment_protocol: Stably transfected and inducible RC3H1 expressing cells were labeled with 100 µM 4-thiouridine (4SU) or 6-thioguanosine (6SG) for 12 h. After labeling the cells, PAR-CLIP was performed as described in (Hafner et al. 2010 Cell 141, 129–141) . Briefly, UV-irradiated cells were lysed in NP-40 lysis buffer (50 mM HEPES-KOH at pH 7.4, 150 mM KCl, 2 mM EDTA, 0.5% (v/v) NP40, 0.5 mM DTT, complete EDTA-free protease inhibitor cocktail). Immunoprecipitation was carried out with protein G magnetic beads (Invitrogen) coupled to anti-FLAG M2 antibody (SIGMA) from extracts of FLAG/HA-RC3H1 expressing and 4SU labeled HEK 293 cells

tag: antibody

value: FLAG

tag: culture medium

value: DMEM


title: 3'-Seq mouse SKMuscle Rep2

city: Fukuoka

first: Yasuyuki

last: Ohkawa

address: 3-1-1 Maidashi, Higashi-ku, Fukuoka

department: Medical Institute of Bioregulation, Medical Institute of Bioregulation

country: Japan

institute: Kyushu University

description: Protocol: 3'-seq

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
Quantification of each gene was performed by counting the number of reads that were mapped around the 3′-UTR region and then normalizing the number as reads per million (RPM) per region. In the case of novel histone H3 variant genes, the region within 3 kb from the end of a coding sequence was defined as the putative 3'-UTR.
genome build: mm9
processed data files format and content: tab-delimited text files include RPKM values for each Sample
processed data file: 3primeSeq_RPMTable_rep2.txt.gz

source_name: skeletal muscle

extract_protocol:
Sample preparations for 3′-seq was performed as previously reported (Lianoglou et al., Genes & Development, 2013) using total RNA extracted from 8 week-old C57BL/6 male mouse tissue, including testis, liver, brain, and skeletal muscle.
3'-seq libraries were prepared for sequencing using previously reported protocol(Lianoglou et al., Genes & Development, 2013).

tag: gender

value: male

tag: age

value: 8 weeks

value: skeletal muscle


title: 1-15 dpf pooled embryo sample (MH_0014)

value: 1-15dpf pooled embryos


title: 3'-Seq mouse SKMuscle

description: Protocol: 3'-seq

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
Quantification of each gene was performed by counting the number of reads that were mapped around the 3′-UTR region and then normalizing the number as reads per million (RPM) per region. In the case of novel histone H3 variant genes, the region within 3 kb from the end of a coding sequence was defined as the putative 3'-UTR.
genome build: mm9
processed data files format and content: tab-delimited text files include RPKM values for each Sample
processed data file: 3primeSeq_RPMTable_rep1.txt.gz


title: 3'-Seq mouse Testis Rep2

description: Protocol: 3'-seq

source_name: testis

value: testis


title: CEBPA_PuER_ChIPSeq

source_name: X18.1.1 AML cell line, PuER, CEBPA ChIP

tag: cell type

tag: chip antibody

value: CEBPA (Santa Cruz sc61x)


title: 3'-Seq mouse Brain

description: Protocol: 3'-seq

source_name: brain

value: brain


title: Pu.1_PuER_ChIPSeq

source_name: X18.1.1 AML cell line, PuER, Pu.1 ChIP

value: AML cell line

value: Pu.1 (Santa Cruz sc352x)


title: 3'-Seq mouse Liver Rep2

description: Protocol: 3'-seq

source_name: liver

value: liver


title: CEBPA_EV_ChIPSeq

source_name: X18.1.1 AML cell line, empty vector, CEBPA ChIP

value: empty vector


title: 3'-Seq mouse Testis

description: Protocol: 3'-seq


title: leaf

city: Kunming

first: Yun

last: Zheng

state: Yunnan

address: 452 Fengyuan Road

country: China

institute: Yunnan Agricultural University

data_processing:
Reads with low scored nucleotids < 15 were removed.
3' adapters were removed and the small RNA sequences were extracted from the raw reads.
5' barcodes GT were removded.
The reads with at least 18nt were maintained in the final results.
The unique sequences and their counts were calculated from the extracted sequences.
Genome_build: The obtained unique sequences were aligned to the genome of Chinese sacred lotus, GenBank Assembly ID: GCA_000365185.1.
Supplementary_files_format_and_content: unique sequence and count

organism: Nelumbo nucifera

source_name: pooled leaf tissue

growth_protocol: Chinese sacred lotus (Nelumbo nucifera Gaertn.) were grown in normal condition.

extract_protocol:
Total RNA was isolated from selected tissues using TRIzol reagent with the manufacture's protocol.
Small RNA libraries were prepared by following the Illumina's protocol.

value: leaf


title: 3'-Seq mouse Brain Rep2

description: Protocol: 3'-seq


title: Pu.1_EV_ChIPSeq

source_name: X18.1.1 AML cell line, empty vector, Pu.1 ChIP


title: 12 days post-fertilization (dpf) embryo sample (MH_0015)

source_name: Scorton Creek (SC), Massachusetts

value: Scorton creek


title: 3'-Seq mouse Liver

description: Protocol: 3'-seq


title: 1-15 dpf pooled embryo sample (MH_0013)


title: 3'-Seq C2C12-G

description: Protocol: 3'-seq

source_name: C2C12 cells_Growth

growth_protocol: Cells  were grown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 20% fetal bovine serum. Undifferentiated cells were harvested at 60–70% confluence.

treatment_protocol: Differentiated cells were transferred to DMEM containing 2% horse serum upon reaching confluence and harvested 48 h later.

value: myoblast

tag: culture status

value: growth (G)


title: InputDNA C2C12-H3mm13-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm13 gene under a doxycycline (Dox)-inducible promoter.

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm13-D-GFP_sub.bw

source_name: C2C12 cells_H3mm13_Differentiated

extract_protocol:
Cultured cells were cross-linked in 0.5% formaldehyde and suspended in ChIP buffer (5 mM PIPES, 200 mM KCl, 1 mM CaCl2, 1.5 mM MgCl2, 5% sucrose, 0.5% NP-40, and protease inhibitor cocktail; Nacalai Tesque). Samples were sonicated for 5 s three times, and digested with micrococcal nuclease (1 ul; New England Biolabs, Ipswich, MA) at 37°C for 40 min. The digested samples were centrifuged at 15,000 × g for 10 min. Supernatant containing 4–8 ug DNA was incubated with a rat monoclonal antibody against GFP (1A5, 2 ug, Bio Academia) pre-bound to magnetic beads at 4°C overnight with rotation. The immune complexes were eluted from the beads using 1% SDS in TE, followed by washing with ChIP buffer and TE buffer (both twice). Cross-links were reversed, and DNA was purified using a Qiaquick PCR purification kit (Qiagen, Valencia, CA).
ChIP libraries were prepared for sequencing using standard Illumina protocols.

value: none (input)

value: differentiation (D)


title: D51_MS04T51

city: Kyoto

first: Yukihiro

last: Yabuta

state: Kyoto

address: Yoshida-Konoe-cho, Sakyo-ku

department: Anatomy and Cell Biology

institute: Kyoto University, Graduate school of medicine

description:
SC3seq amplified from single cell dissocaited from embryonic genital ridge
processed data file: expression_cynomolgus.txt

data_processing:
All the reads were surveyed and the adaptor or the poly-A sequences were trimmed by cutadapt-1.3 with options "-c -m 30 -a CTCGAGGGCGCGCCGGATCCATATACGCCTTGGCCGTACAGCAG -g CTCGAGGGCGCGCCGGATCCATATACGCCTTGGCCGTACAGCAG -a AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA". The trimmed reads with less than 30 bp were discarded.
Untrimmed and trimmed reads of 30 bp or longer were mapped onto the genome and the ERCC spike-in RNA sequences with tophat-1.4.1/bowtie1.0.1 with the “—no-coverage-search” option.
Mapped reads on the genome and the ERCC were separated, and the reads on the genome were converted into the expression levels by cufflinks-2.2.0 using the “—compatible-hits-norm”, “—no-length-correction” and “—library-type fr-secondstrand” options and reference gene annotations with extended TTSs. We also set the cufflinks option “—max-mle-iterations” to 50,000, because default iterations (5,000) resulted in “FAILED” when estimating the expression levels of some genes. For the reference gene annotations used in cufflinks, we extended the TTSs of the reference genes up to 10 kb downstream to correctly estimate the expression levels of genes whose transcripts are longer than the reference toward the 3 prime.
Genome_build: mm10
Genome_build: hg19
Genome_build: Macaca_fascicularis_5.0
Supplementary_files_format_and_content: tab-delimited text files include RPM values for each Sample.

organism: Macaca fascicularis

source_name: cyPGC

growth_protocol:
hiPSCs were maintained under a feeder-free condition [StemFitTM (Ajinomoto, Tokyo, Japan) medium on recombinant LAMININ511 (rLN511E8) (iMatrix-511, Nippi, Tokyo, Japan)-coated cell culture plates] (Nakagawa et al., 2014).  The iMeLCs were induced by plating 1.0-2.0 × 10^5 hiPSCs maintained in StemFitTM onto a well of a human plasma fibronectin (Millipore, FC010)-coated 12-well plate in GK15 medium [GMEM (Life Technologies) with 15% KSR, 0.1 mM NEAA, 2 mM L-glutamine, 1 mM sodium pyruvate and 0.1 mM 2-mercaptoethanol] containing 50 ng/ml of Activin A, 3 µM of CHIR99021 and 10 µM of a ROCK inhibitor (Y-27632; Wako Pure Chemical Industries).  The hPGCLCs were induced by plating 3.0 × 10^3 iMeLCs or iPSCs into a well of a low-cell-binding V-bottom 96-well plate (Thermo, 81100574) in GK15 supplemented with 1000 U/ml of LIF (Millipore, #LIF1005), 200 ng/ml of BMP4, 100 ng/ml of SCF (R&D Systems, 455-MC), 50 ng/ml of EGF (R&D Systems, 236-EG), and 10 µM of the ROCK inhibitor.  In some experiments, PD173074 (StemGent, #04-0008) or LDN193189 (StemGent, #04-0074) were added for iMeLCs or hPGCLC induction, respectively.  In other experiments, WNT3A (R&D Systems, 5036-WN) was used in place of CHIR99021, and BMP2 (R&D Systems, 355-BM), BMP7 (R&D Systems, 354-BP), or BMP8A (R&D Systems, 1073-BP) was used in place of BMP4.
mESCs were cultured in a 2i+LIF, feeder-free culture condition. mEpiLCs and mPGCLCs (d2, d4, and d6) were induced as described previously (Hayashi et al., 2011).
cyESCs (CMK9) were cultured with conventional hESC medium [DMEM/F12 (Life Technologies) supplemented with 20% (vol/vol) of KSR (Life Technologies), 1 mM of sodium pyruvate (Life Technologies), 2 mM of GlutaMax (Life Technologies), 0.1 mM of nonessential amino acids (Life Technologies), 0.1 mM of 2-mercaptoethanol (Sigma-Aldrich), 1000 U/mL of ESGRO mouse LIF (Millipore), 4 ng/ml of recombinant human bFGF (Wako Pure Chemical Industries)] on mouse embryonic feeders (MEFs).

extract_protocol:
Total RNA was extracted from hiPSCs, iMeLCs, and hPGCLCs or mESCs, mEpiLCs, and mPGCLCs by using an RNeasy Micro Kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions.  Synthesis and amplification of cDNAs using 1 ng of purified total RNA, and construction of cDNA libraries for RNA sequencing (ABI SOLiD 5500XL system; Life Technologies) were performed as described in (Nakamura et al., 2015).
For isolating single cells of cyESCs for the SC3-seq analysis [Nakamura et.al., Nuceic Acids Res. (2015)], cells were first detached as clumps by the CTK solution [0.25% of Trypsin (Life Technologies), 0.1 mg/mL of Collagenase Ⅳ (Life Technologies), 1 mM of CaCl2 (Nacalai Tesque)], were incubated in 0.25% of trypsin/PBS (Sigma-Aldrich) for around 10 min at 37℃, and were then dispersed into single cells in 1% (vol/vol) KSR/PBS. Genital ridges were dissected out and were dissociated into single cells by incubating with 0.25% trypsin/PBS for around 10 min at 37℃ followed by repeated pipetting. The resulting single cells were dispersed in 0.1 mg/ml of PVA/PBS (Sigma-Aldrich) and were processed for the SC3-seq analysis (Nakamura et al., 2015).
cDNA synthesis and amplification from isolated RNAs/single cells were perfomed essentially as reported in [Kurimoto, K.et.al., Nucleic Acids Research, 34(5), e42.]. Library constructions for SOLiD System were performed as reported in [Nakamura et.al., Nuceic Acids Res. (2015)].

value: cyPGC

value: Embrionic day 51


title: d4_ko1

description:
SC3seq amiplified from 1 ng total RNA extracted from cells sorted with BTAG
processed data file: expression_human.txt

source_name: d4 BTAG+ cells

value: d4 BTAG+ cells


title: d4_ko2


title: D51_MS04T44


title: d4_het


title: flower

source_name: pooled flower tissue

value: flower


title: d4_wt2

description:
SC3seq amiplified from 1 ng total RNA extracted from cells sorted with AG
processed data file: expression_human.txt

source_name: d4 AG+ cells

value: d4 AG+ cells


title: d4_wt1


title: InputDNA C2C12-H3mm16-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm16 gene under a doxycycline (Dox)-inducible promoter.

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm16-D-GFP_sub.bw

source_name: C2C12 cells_H3mm16_Differentiated


title: D51_MS04T32


title: D51_MS04T12


title: d2_ko1

source_name: d2 BTAG+ cells

value: d2 BTAG+ cells


title: d2_ko2


title: D51_MS04T25


title: InputDNA C2C12-H3mm7-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm7 gene under a doxycycline (Dox)-inducible promoter.

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm7-D-GFP_sub.bw

source_name: C2C12 cells_H3mm7_Differentiated


title: d2_het


title: InputDNA C2C12-H3mm12-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm12 gene under a doxycycline (Dox)-inducible promoter.

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm12-D-GFP_sub.bw

source_name: C2C12 cells_H3mm12_Differentiated


title: D50_MS04T17

value: Embrionic day 50


title: D51_MS04T05


title: d2_wt2

source_name: d2 AG+ cells

value: d2 AG+ cells


title: 3'-Seq C2C12-D

description: Protocol: 3'-seq

source_name: C2C12 cells_Differentiated


title: InputDNA C2C12-H3.2-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3.2 gene under a doxycycline (Dox)-inducible promoter.

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)

source_name: C2C12 cells_H3.2_Differentiated


title: InputDNA C2C12-H3t-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3t gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3t_Differentiated


title: D50_MS04T16


title: d2_wt1


title: D51_MS04T45


title: iPSC_ko2

description:
SC3seq amiplified from 1 ng total RNA extracted from cells
processed data file: expression_human.txt

source_name: hiPSC

value: hiPSC


title: D50_MS04T14


title: InputDNA C2C12-H3.1-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3.1 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3.1_Differentiated


title: D50_MS04T13


title: D50_MS04T15


title: InputDNA C2C12-H3mm13-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm13-G-GFP_sub.bw

source_name: C2C12 cells_H3mm13_Growth


title: InputDNA C2C12-H3mm16-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm16-G-GFP_sub.bw

source_name: C2C12 cells_H3mm16_Growth


title: iPSC_ko1


title: D43_MS04T10

value: Embrionic day 43


title: InputDNA C2C12-H3mm11-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm11 gene under a doxycycline (Dox)-inducible promoter.

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm11-D-GFP_sub.bw

source_name: C2C12 cells_H3mm11_Differentiated


title: iPSC_wt2


title: InputDNA C2C12-H3.3-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3.3 gene under a doxycycline (Dox)-inducible promoter.

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3v3-D-GFP_sub.bw

source_name: C2C12 cells_H3.3_Differentiated


title: InputDNA C2C12-H3mm12-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm12-G-GFP_sub.bw

source_name: C2C12 cells_H3mm12_Growth


title: iPSC_wt1


title: D43_MS04T07

source_name: cyPGC


title: InputDNA C2C12-H3mm11-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm11-G-GFP_sub.bw

source_name: C2C12 cells_H3mm11_Growth


title: D43_MS04T08


title: InputDNA C2C12-H3mm7-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm7-G-GFP_sub.bw

source_name: C2C12 cells_H3mm7_Growth


title: 585A1_surface_d6#2

description:
SC3seq amiplified from 1 ng total RNA extracted from cells sorted with EpCAM and CD49f
processed data file: expression_human.txt

source_name: d6 CSM+ cells

value: d6 CSM+ cells


title: D43_MS04T06


title: 585A1_iMeLC#2

source_name: iMeLC

value: iMeLC


title: InputDNA C2C12-H3.2-G

source_name: C2C12 cells_H3.2_Growth


title: InputDNA C2C12-H3.3-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped to the mouse genome (mm9) with STAR alignment software (Dobin et al., 2013) and the parameter “--outFilterMultimapNmax 1 --alignIntronMax 1” (no multi-hit reads, no splice prediction) to treat poly-A containing reads.
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3v3-G-GFP_sub.bw

source_name: C2C12 cells_H3.3_Growth


title: D43_MS04T04


title: 585A1_iMeLC#1


title: D43_MS04T03


title: InputDNA C2C12-H3t-G

source_name: C2C12 cells_H3t_Growth


title: 585A1_hiPSC#2


title: iPSC_het


title: D43_MS04T02


title: CMK9_MS05T75

description:
SC3seq amplified from single cell of cyESC
processed data file: expression_cynomolgus.txt

source_name: cyESC

value: cyESC


title: CMK9_MS05T74


title: 585A1_hiPSC#1


title: CMK9_MS05T73


title: d6BTAG+*1

source_name: d6 BTAG+ cells

value: d6 BTAG+ cells


title: d6BTAG+*2


title: 585A1_surface_d6#1


title: ChIP GFP C2C12-H3mm11-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm11-D-GFP_sub.bw

value: myoblast

value: rat monoclonal antibody against GFP (1A5, 2 ug, Bio Academia)


title: d8BTAG+#2

source_name: d8 BTAG+ cells

value: d8 BTAG+ cells


title: ChIP GFP C2C12-H3mm16-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm16-D-GFP_sub.bw

source_name: C2C12 cells_H3mm16_Differentiated

value: differentiation (D)


title: ChIP GFP C2C12-H3mm12-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm12-D-GFP_sub.bw

source_name: C2C12 cells_H3mm12_Differentiated


title: InputDNA C2C12-H3.1-G

source_name: C2C12 cells_H3.1_Growth

value: none (input)

value: growth (G)


title: hiPSC*2

source_name: hiPSC


title: hiPSC*1


title: ChIP GFP C2C12-H3mm7-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm7-D-GFP_sub.bw

source_name: C2C12 cells_H3mm7_Differentiated


title: ChIP GFP C2C12-H3.3-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3v3-D-GFP_sub.bw

source_name: C2C12 cells_H3.3_Differentiated


title: CMK9_MS05T72

data_processing:
All the reads were surveyed and the adaptor or the poly-A sequences were trimmed by cutadapt-1.3 with options "-c -m 30 -a CTCGAGGGCGCGCCGGATCCATATACGCCTTGGCCGTACAGCAG -g CTCGAGGGCGCGCCGGATCCATATACGCCTTGGCCGTACAGCAG -a AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA". The trimmed reads with less than 30 bp were discarded.
Untrimmed and trimmed reads of 30 bp or longer were mapped onto the genome and the ERCC spike-in RNA sequences with tophat-1.4.1/bowtie1.0.1 with the “—no-coverage-search” option.
Mapped reads on the genome and the ERCC were separated, and the reads on the genome were converted into the expression levels by cufflinks-2.2.0 using the “—compatible-hits-norm”, “—no-length-correction” and “—library-type fr-secondstrand” options and reference gene annotations with extended TTSs. We also set the cufflinks option “—max-mle-iterations” to 50,000, because default iterations (5,000) resulted in “FAILED” when estimating the expression levels of some genes. For the reference gene annotations used in cufflinks, we extended the TTSs of the reference genes up to 10 kb downstream to correctly estimate the expression levels of genes whose transcripts are longer than the reference toward the 3 prime.
Genome_build: mm10
Genome_build: hg19
Genome_build: Macaca_fascicularis_5.0
Supplementary_files_format_and_content: tab-delimited text files include RPM values for each Sample.


title: CMK9_MS05T69


title: d6BTAG+#2


title: CMK9_MS05T70


title: ChIP GFP C2C12-H3mm13-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm13-D-GFP_sub.bw

source_name: C2C12 cells_H3mm13_Differentiated


title: CMK9_MS05T68


title: ChIP GFP C2C12-H3t-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)

source_name: C2C12 cells_H3t_Differentiated


title: ChIP GFP C2C12-H3.2-D

source_name: C2C12 cells_H3.2_Differentiated


title: ChIP GFP C2C12-H3.1-D

source_name: C2C12 cells_H3.1_Differentiated


title: d8BTAG+#1


title: CMK9_MS05T71


title: ChIP GFP C2C12-H3mm16-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm16-G-GFP_sub.bw

source_name: C2C12 cells H3mm16_Growth


title: d2BTAG+#2

source_name: d2 BTAG+ cells


title: d4BTAG+#1

source_name: d4 BTAG+ cells

value: d4 BTAG+ cells


title: d6BTAG+#1


title: ChIP GFP C2C12-H3mm13-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm13-G-GFP_sub.bw

source_name: C2C12 cells H3mm13_Growth


title: ChIP GFP C2C12-H3mm12-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm12-G-GFP_sub.bw

source_name: C2C12 cells H3mm12_Growth


title: ChIP GFP C2C12-H3mm11-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm11-G-GFP_sub.bw

source_name: C2C12 cells H3mm11_Growth


title: d2BTAG+#1


title: myb_wr3

city: Durham

first: Louisa

middle: M

last: Liberman

state: NC

address: 130 Science Dr. BOX 90338

institute: Duke

description: myb36 whole root biological rep3

data_processing:
mapping with tophat2: tophat2 -N 1 -i10 -p8 --segment-mismatches 3 --min-segment-intron 10 --library-type fr-secondstrand --transcriptome-index
script used: "RNAseqPipelineAnnotated.sh"
sorting by name with samtools: samtools sort -n accepted_hits.bam accepted_hits_sort
converting to sam files: samtools view accepted_hits.bam > accepted_hits_sort.sam
used cufflinks, cuffmerg and cuffdiff to acquire FPKMs for genes
counting with HTSeq: python -m HTSeq.script.count - r name -t exon -I gene_id -m intersection-strict
remove the last 5 summarizing records from the files: awk NR<=33602
convert all the XY formatted files to a single matrix with format XYYYY using script "filestoR.py"
Genome_build: TAIR10

organism: Arabidopsis thaliana

source_name: Whole Root Arabidopsis

growth_protocol: Seeds were sterilized with 3% sodium hypochlorite and 0.1% Tween for 7 minutes and rinsed 5 times in sterile water. Seeds were stratified and imbibed 48 hours at 4°C and then plated on sterile mesh, 1xMS, 1% agar, 1% sucrose plant growth media and sealed with Parafilm. Plates were grown under long day conditions for 6 days.

extract_protocol:
RNA was extracted using the Qiagen Rneasy kit or Rneasy micro kit for sorted cells
Script-seq v2 RNA-seq library prep kit (Epicentre) was used to generate strand-specific RNAseq libraries

treatment_protocol: Whole Roots (wr) were harvested and frozen in liquid nitrogen or harvested for protoplasting, sorted by FACS for the endodermal cell population (en) and then frozen on dry ice

tag: ecotype

tag: genotype/variation

value: mutant (myb36-1)

value: 6 Days Post Exposure to Light

value: whole root


title: myb_wr2

description: myb36 whole root biological rep2

tag: tissue


title: iMeLC#2

source_name: iMeLC


title: col_wr3

description: columbia whole root biological rep3

value: wild type


title: hiPSC#2

value: hiPSC


title: ChIP GFP C2C12-H3mm7-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3mm7-G-GFP_sub.bw

source_name: C2C12 cells H3mm7_Growth


title: ChIP GFP C2C12-H3.2-G

source_name: C2C12 cells_H3.2_Growth


title: ChIP GFP C2C12-H3.3-G

data_processing:
Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)
processed data file: w1000s100_H3v3-G-GFP_sub.bw

source_name: C2C12 cells_H3.3_Growth


title: hiPSC#1

source_name: hiPSC


title: ChIP GFP C2C12-H3t-G

source_name: C2C12 cells_H3t_Growth


title: d4BTAG+#2


title: myb_en3

description: myb36 endodermis biological rep3

source_name: Sorted Endodermis Arabidopsis

value: sorted endodermis (FACS)


title: SU25.23

city: Davis

first: Dario

last: Cantu

state: CA

address: One Shields Ave

department: Viticulture & Enology

institute: University of California, Davis

description:
Sample name: SU25.23_GAGTGG
Column header name in processed data file: SU25-23_GAGTGG
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 5DPI

data_processing:
raw data files were adapter and quality trimmed with Sickle v 1.2.1 (Q>20) and Scythe v0.991 (prior 0.4) programs. Respectively.
Bowtie2 (v. 2.2.3) with options (-q --end-to-end --sensitive --no-unal -p 20) was run with the custom built bowtie2 index (bowtie2-build) from concatenated transcripts from the V. vinifera cv. PN40024 (transcriptome version V1 obtained from CRIBI - http://genomes.cribi.unipd.it/grape/) and the E. necator C-strain reference genomes
Ambiguously mapped reads were excluded from further analysis using the sam2counts.py script (v0.9.1; -q30 option)
Genome_build: e.necator.transcripts.fasta and v.vinifera.transcripts.fasta are linked as supplementary files on the Series record.
Supplementary_files_format_and_content: processed(sam2counts.py -q30) tab-delimited file of raw bowtie2 counts from quality filtered (sickle Q>20/scythe prior 0.4) data; contains 97 columns (one gene identifier, 96 samples) and 36505 rows with one header row, 29971 rows referencing grapevine genes, and 6533 rows representing E. necator genes

organism: Vitis vinifera

source_name: whole plant

growth_protocol: green cuttings were prepared in June 2013 and established in the greenhouse. After four months, three plants of each accession were transferred to two Conviron PGR15 growth chambers in the UC Davis Controlled Environment Facility. The growing conditions in both chambers were identical and set to conditions that favor E. necator infections (23°C during the day, 15°C at night, 16-hour photoperiod, 60% humidity).

extract_protocol:
Leaves from each plant were collected at two time points (1 day and 5 days after inoculation) and immediately frozen in liquid nitrogen. RNA was extracted using a CTAB extraction protocol followed by a cleanup step with the Qiagen RNeasy Plant Mini Kit. High quality RNA samples were obtained from all accessions, time points (1 and 5 days post inoculation), and treatments (healthy and PM infected).
cDNA libraries were sequenced in single-end mode with 50 cycles at the DNA Technology core at the UC Davis Genome Center using an Illumina HiSeq2500 sequencer.
A total of 8 HiSeq2500 lanes were sequenced with each individual lane loaded with a 12 libraries comprising all replicates (3 biological replicates) of each infection time point (1 and 5 dpi) and treatment (powdery mildew infected and healthy controls) of a specific genotype

treatment_protocol: A suspension of E. necator (strain C-strain) conidia was prepared. Conidia were collected from detached leaf cultures, suspended in 0.001% Tween 20 solution, and adjusted to a concentration of 5 x 105 conidia/mL. In one chamber, E. necator conidia were applied to grapevine leaves using a portable paint sprayer. Grapevines in the other chamber were mock inoculated with 0.001% Tween solution only.

value: sativa

tag: cultivar

value: Sochal

tag: timepoint

value: 5 DPI

tag: infection

value: Mock Innoculated

tag: resistant to powdery mildew

value: yes

value: whole plant


title: col_wr1

description: columbia whole root biological rep1


title: SU324.25

description:
Sample name: SU324.25_ACTGAT
Column header name in processed data file: SU324-25_ACTGAT
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 1DPI

value: 1 DPI


title: mRNA C2C12-H3mm16-D

data_processing:
Illumina RTA 1.17 software used for basecalling.
Sequenced reads were mapped onto the mouse genome (mm9) using Tophat (version 2.0.8) (Trapnell et al., 2012) with the software's default parameter.
Gene expression levels (FPKM; Fragments per kilobase of exon per million mapped sequence reads) were estimated using the cuffdiff program in Cufflinks (version 2.0.1) (Trapnell et al., 2012) using mapped reads and the software’s default parameters.
genome build: mm9
processed data files format and content: tab-delimited text file include FPKM values for each Sample
processed data file: mRNASeq_FPKMTable.txt.gz

source_name: C2C12 cells_H3mm16_Differentiated

extract_protocol:
Total RNA was isolated and reversed-transcribed with Takara Prime Script Reverse Transcriptase and an oligo dT primer.
RNA libraries were prepared for sequencing using standard Illumina protocols.

value: myoblast

tag: cell line

value: differentiation (D)


title: ChIP GFP C2C12-H3.1-G

source_name: C2C12 cells_H3.1_Growth

value: rat monoclonal antibody against GFP (1A5, 2 ug, Bio Academia)

value: growth (G)


title: myb_en2

description: myb36 endodermis biological rep2

value: mutant (myb36-1)


title: SU224.22

description:
Sample name: SU224.22_CGTACG
Column header name in processed data file: SU224-22_CGTACG
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 1DPI


title: myb_en1

description: myb36 endodermis biological rep1

value: 6 Days Post Exposure to Light


title: SU1b5.27

description:
Sample name: SU1b5.27_ATTCCT
Column header name in processed data file: SU1b5-27_ATTCCT
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 5DPI


title: mRNA C2C12-H3mm13-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm13 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3mm13_Differentiated


title: mRNA C2C12-H3mm12-D

source_name: C2C12 cells_H3mm12_Differentiated


title: mRNA C2C12-H3mm11-D

source_name: C2C12 cells_H3mm11_Differentiated


title: SU15.21

description:
Sample name: SU15.21_GTTTCG
Column header name in processed data file: SU15-21_GTTTCG
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 5DPI


title: col_en3

description: columbia endodermis biological rep3


title: col_en2

description: columbia endodermis biological rep2


title: iMeLC#1

value: iMeLC


title: myb_wr1

description: myb36 whole root biological rep1

value: whole root


title: SU124.20

description:
Sample name: SU124.20_GTGGCC
Column header name in processed data file: SU124-20_GTGGCC
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 1DPI


title: col_en1

description: columbia endodermis biological rep1

value: wild type


title: SI2b24.10

description:
Sample name: SI2b24.10_TAGCTT
Column header name in processed data file: SI2b24-10_TAGCTT
plants were placed in growth chambers innoculated with grapevine powdery mildew. Whole plant data was collected 1DPI

value: inoculated with Erysiphe necator c-strain


title: mRNA C2C12-H3.3-D

source_name: C2C12 cells_H3.3_Differentiated


title: col_wr2

description: columbia whole root biological rep2


title: mRNA C2C12-H3mm7-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm7 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3mm7_Differentiated


title: SI2a24.8

description:
Sample name: SI2a24.8_ACTTGA
Column header name in processed data file: SI2a24-8_ACTTGA
plants were placed in growth chambers innoculated with grapevine powdery mildew. Whole plant data was collected 1DPI

value: sativa


title: mRNA C2C12-H3.2-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3.2 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3.2_Differentiated


title: SI25.9

description:
Sample name: SI25.9_GATCAG
Column header name in processed data file: SI25-9_GATCAG
plants were placed in growth chambers innoculated with grapevine powdery mildew. Whole plant data was collected 5DPI

value: Sochal


title: mRNA C2C12-H3t-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3t gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3t_Differentiated


title: mRNA C2C12-H3.1-D

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3.1 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3.1_Differentiated


title: SI1a5.3

description:
Sample name: SI1a5.3_TTAGGC
Column header name in processed data file: SI1a5-3_TTAGGC
plants were placed in growth chambers innoculated with grapevine powdery mildew. Whole plant data was collected 5DPI

value: 5 DPI


title: mRNA C2C12-WT-D

description: C2C12 cells that non harbor the N-terminal or C-terminal -GFP-tagged H3 gene

source_name: C2C12 cells_WT_Differentiated


title: SI124.1

description:
Sample name: SI124.1_ATCACG
Column header name in processed data file: SI124-1_ATCACG
plants were placed in growth chambers innoculated with grapevine powdery mildew. Whole plant data was collected 1DPI


title: SI1b5.11

description:
Sample name: SI1b5.11_GGCTAC
Column header name in processed data file: SI1b5-11_GGCTAC
plants were placed in growth chambers innoculated with grapevine powdery mildew. Whole plant data was collected 5DPI


title: HiSeq_E16

city: Montreal

first: Juan Pablo

last: Lopez

state: Quebec

address: 6875 La Salle Blvd

department: Human Genetics

country: Canada

institute: McGill University

description: processed_data: ncRNA_Expression.txt

data_processing:
All sequencing data were processed using CASAVA 1.8+ and extracted from FASTQ files
Fastx_toolkit was used to trim the Illumina adapter sequences
Additional filtering based on defined cutoffs was applied in order to obtain high quality data. These filters included: 1) Phred quality (Q) score higher than 30, 2) reads between 15-40nt in length, 3) adapter detection based on perfect-10nt match, and 4) removal of reads without detected adapter
We used Bowtie to align reads to the human genome (GRCh37)
We used ncPRO-seq in combination with miRBase (V20) to match them to known miRNA sequences
We used the Rfam and NCBI's piRNA databases to map other small RNA sequences
All sequencing data was normalized with the Bioconductor - DESeq2 package, using a detection threshold of 1 count per miRNA (present at least once in each of the libraries tested)
Genome_build: Human genome (GRCh37)
Supplementary_files_format_and_content: Tab-delimited text files include small RNA count values for each sample

source_name: Liver

extract_protocol:
Peripheral blood samples were collected in PAXgene blood RNA tubes (PreAnalytix, Switzerland). PAXgene tubes were frozen using a sequential freezing process. This involves storing tubes at room temperature for 3h, transferring to 4°C overnight, followed by 6-8h at -20°C and then final storage at -80°C. Total RNA (including the miRNA fraction) was isolated from whole-blood using the PAXgene Blood miRNA Kit (Qiagen, Canada), according to manufacturer's instructions. Furthermore, total RNA was isolated from frozen brain, heart and liver tissues using the miRNeasy Mini Kit protocol (Qiagen, Canada) with no modifications. RNA and miRNA yield and quality were determined using the Nanodrop 1000 (Thermo Scientific, USA) and Agilent 2100 Bioanalizer (Agilent Technologies, USA).
All libraries were prepared using the Illumina TruSeq Small RNA protocol following the manufacturer's instructions with 12 cycles of PCR amplification after ligation of the 3' and 5' adapters.  Individual libraries were prepared using a unique index primer in order to allow for pooling of multiple samples prior to sequencing. Libraries were validated and quantified using an Agilent 2100 Bioanalyzer High Sensitivity DNA chip and qRT-PCR with the KAPA library quantification kit (Kapa Biosystems, USA). Sample C1 (control - human brain) was not sequenced. All additional samples (A1-A10), as well as sample AC (control - no purification method), were sequenced.
Purification Method: In order to compare three different small RNA library purification methods, we prepared 11 libraries starting with 1µg of good quality total RNA (RIN>8). All libraries were prepared using total RNA extracted from peripheral blood of a single individual. The RNA was split into 11 aliquots and each was used as a technical replicate. In addition, we used total RNA from commercially available human brain as a library preparation control. Libraries were purified as follows: 1) Purification by Novex TBE PAGE gel: 50µl of amplified cDNA from samples A1-A3 and C1 were loaded into a 6% Novex gel and run for 80 minutes at 130-135 V. After cleaning the gel with RNase free water, a band was manually cut to contain all fragments sized 145-160nt, corresponding to mature miRNAs and other regulatory small RNA molecules;  2) Purification by Pippin Prep automated gel system (Sage 3%): The Pippin Prep system (PPS) allows automatic selection of specified cDNA products. 25µl of amplified cDNA from samples A4-A7 were loaded into a Pippin Prep machine. Furthermore, in order to test variability between machines, samples A4 and A5 were loaded into PPS1, while samples A6 and A7 were loaded into PPS2. Size selection was automated for products between 125 and 180nt; 3) Purification by AMPure XP beads: Biotinylated magnetic AMPure beads allow for selection of specified cDNA products bound to streptavidin. 50µl of amplified cDNA from samples A8-A10 were mixed and purified two times with AMPure XP beads at a 1.8:1 ratio (beads:sample). This ratio allows for optimal selection of all products higher than 100nt.

value: Liver

tag: input amount (rna)

value: 1 ug

tag: purification method

value: AMPure XP beads

tag: rin value


title: LU35.19

description:
Sample name: LU35.19_GTGAAA
Column header name in processed data file: LU35-19_GTGAAA
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 5DPI

value: Late Vavilov

value: Mock Innoculated

value: yes

value: whole plant


title: mRNA C2C12-H3mm13-G

source_name: C2C12 cells_H3mm13_Growth

value: myoblast

value: growth (G)


title: HiSeq_E14

description: processed_data: ncRNA_Expression.txt


title: HiSeq_E15

description: processed_data: ncRNA_Expression.txt


title: mRNA C2C12-H3mm16-G

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm16 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3m16_Growth


title: HiSeq_E13

description: processed_data: ncRNA_Expression.txt


title: LU324.18

description:
Sample name: LU324.18_GTCCGC
Column header name in processed data file: LU324-18_GTCCGC
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 1DPI

value: 1 DPI


title: mRNA C2C12-H3mm11-G

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3mm11 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3mm11_Growth


title: HiSeq_E12

description: processed_data: ncRNA_Expression.txt

source_name: Heart

value: Heart


title: LU25.16

description:
Sample name: LU25.16_CCGTCC
Column header name in processed data file: LU25-16_CCGTCC
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 5DPI

source_name: whole plant


title: mRNA C2C12-H3mm7-G

source_name: C2C12 cells_H3mm7_Growth


title: HiSeq_E10

description: processed_data: ncRNA_Expression.txt


title: LU15.14

description:
Sample name: LU15.14_AGTTCC
Column header name in processed data file: LU15-14_AGTTCC
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 5DPI


title: mRNA C2C12-H3.3-G

description: Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3.3 gene under a doxycycline (Dox)-inducible promoter.

source_name: C2C12 cells_H3.3_Growth


title: LU124.13

description:
Sample name: LU124.13_AGTCAA
Column header name in processed data file: LU124-13_AGTCAA
plants were placed in growth chambers and mock-innoculated. Whole plant data was collected 1DPI


title: mRNA C2C12-H3.2-G

source_name: C2C12 cells_H3.2_Growth


title: HiSeq_E9

description: processed_data: ncRNA_Expression.txt


title: mRNA C2C12-H3t-G

source_name: C2C12 cells_H3t_Growth


title: HiSeq_E8

description: processed_data: ncRNA_Expression.txt

source_name: Brain

value: Brain


title: HiSeq_E7

description: processed_data: ncRNA_Expression.txt