title: HFLF4, WGBS

city: Research Triangle Park

first: Paul

last: Wade

state: NC

address: 111 TW Alexander Drive

department: Laboratory of Molecular Carcinogenesis

institute: NIEHS

data_processing:
Each raw dataset was filtered to remove any read pairs with average base quality score <20.  Cutadapt (parameters: --adapter=AGATCGGAAGAGC -O 5) was used to trim adapters from BSP-seq libraries; adapter trimming was deemed unnecessary for the RNA-seq and WGBS libraries.  A minimum fragment length of 30nt (post-trimming) was required.
RNA-seq reads were mapped against the mm10 reference genome via TopHat v2.0.4 (parameters: --b2-sensitive --library-type fr-firststrand -g 10 --mate-inner-dist 40 --mate-std-dev 50).
RNA-seq read counts per gene per sample were collected using HTSeq-Count.
Differentially expressed genes were determined using DESeq2 v1.2.10 , with threholds p-value <0.01, adjusted p-value < 0.25, and fold change > 1.2.
RNA-seq coverage tracks (per genomic strand) were generated with bedtools2 v2.19.0 genomeCoverageBed, then convert to bigWig format with UCSC command-line tool bedGraphToBigWig.
BSP-seq reads were mapped via Bismark v0.7.8 (parameters: -I 0 -X 1000 --non_bs_mm --chunkmbs 1024 --non_directional) against a masked version of the mm10 reference genome where are nucleotides in non-query regions were replaced with Ns.
BSP-seq alignments were post-processed to clip redundant mapped bases due to overlapping mates from the same read pair.
Percent methylation at each CpG site in the query regions of the BSP-seq data was calculated as methylated mapped C bases divided by total (methylated+unmethylated) mapped C bases.
BSP-seq coverage tracks were generated with bedtools2 v2.19.0 genomeCoverageBed, then convert to bigWig format with UCSC command-line tool bedGraphToBigWig.
WGBS reads were mapped against the mm10 reference genome via Bismark v0.14.0 (parameters:  -I 0 -X 10000 --non_bs_mm --sam --old_flag -n 2 -l 50 -e 70 --chunkmbs 1024), then deduplicated with deduplicate_bismark v0.14.0 (parameters: --paired).
WGBS alignments were post-processed to separate hits according to source genome strand, to clip redundant mapped bases due to overlapping mates from the same read pair, and to clip 5' and/or 3' read cycles with methylation bias as identified with bismark_methylation_extractor using the --mbias_only option.
WGBS coverage tracks (per genomic strand) were generated with bedtools2 v2.19.0 genomeCoverageBed, then convert to bigWig format with UCSC command-line tool bedGraphToBigWig.
WGBS percent methylation was calculated (per cytosine in CpG, per genomic strand) as methylated mapped C bases divided by total (methylated+unmethylated) mapped C bases.
Differentially methylated regions were identified by merging CpG sites with differential methylation according to the Rao Scott Likelihood Ratio Test (p-value 0.05) within 5kb, with minimum weighted coverage of 10 in at least one cohort.  DMRs were then filtered to require at least 2 CpG sites, region FDR <0.01, and methylation difference of least 30% or 5-fold.
Genome_build: mm10
Supplementary_files_format_and_content: RNAseq mapped read depth by strand in bigWig format.
Supplementary_files_format_and_content: Tab-delimited text file with read counts per gene, per sample.
Supplementary_files_format_and_content: Tab-delimited text files with DESeq2 values (fold change, p-value, adjusted p-value) and DEG status according to selected thresholds.
Supplementary_files_format_and_content: BSPseq mapped read depth in bigWig format.
Supplementary_files_format_and_content: Tab-delimited text file with percent methylation at each CpG site in the BSP-seq query regions.
Supplementary_files_format_and_content: WGBS mapped read depth by strand in bigWig format.
Supplementary_files_format_and_content: WGBS percent methylation per CpG site in bigWig format; C on plus strand have positive values, C on minus strand have negative values;
Supplementary_files_format_and_content: WGBS DMRs for high fat vs low fat diet conditions.

source_name: colonic epithelium

extract_protocol:
The entire colon was removed from mouse and colonic epithelium was isolated using PBS with 5 mM EDTA. Genomic DNA and total RNA were isolated using Qiagen AllPrep DNA/RNA/miRNA Universal Kit according to the manufacturer’s instructions.
Whole-genome bisulfite sequencing libraries were prepared as follows: genomic DNA was sonicated to an average size of 200 bp using Covaris S220. DNA fragments were end-repaired, adenylated, and ligated to Illumina-compatible adaptors using BIOO NEXTflex Bisulfite-Seq Kit. Bisulfite conversion was performed using EZ DNA Methylation-Lightning™ Kit (Zymo Research Corporation) according to the manufacturer’s instructions. Then PCR was performed to enrich bisulfite converted and adaptor-ligated fragments.  RNA sequencing libraries were prepared using the TruSeq Stranded mRNA Sample Prep Kit (Illumina, #RS-122-2103). Bisulfite PCR sequencing libraries were prepared as follows: Genomic DNA was bisulfite converted using EZ DNA Methylation-Lightning™ Kit (Zymo Research Corporation) prior to PCR amplification. Amplicons from a single sample were pooled and individually indexed using TruSeq™ RNA Sample Preparation kit (Illumina) to create a multiplex library.

treatment_protocol: Six-week old male C57BL/6 mice were placed on three different dietary regimens as follows: 1) low-fat diet for 20 weeks; 2) high-fat diet for 20 weeks; 3) high-fat diet for an initial 15 weeks then switched to low-fat diet for another 5 weeks.

tag: Sex

value: male

tag: age

value: six-week old

value: colon

tag: diet

value: HF diet then switched to LF diet


title: HFLF5, WGBS

status: Public on Dec 19 2017

type: SRA

middle: A

country: USA

library_source: genomic

molecule: genomic DNA

organism: Mus musculus

tag: strain

tag: tissue


title: scBS-O-bst-2r

city: Hangzhou

first: Hongshan

last: Guo

state: Zhejiang Province

address: No.1369, Wenyixi Road

department: School of Medicine, Zhejiang University

country: China

institute: Liangzhu Laboratory

data_processing:
Illumina CASAVA version 1.8 were used to the basecalling.
All bisulfite sequencing reads were first trimmed to remove adaptors and low quality bases using trim_galore (RefXXX) (parameters: --quality 20 --phred33 –length 50 --paired).
Next, reads passed quality control were mapped to human reference genome (version: hg19) using bismark (version: 0.7.6) (RefXXX) with paired-end alignment mode (parameters: --non-directional --fastq). To rescue more sequencing reads, unmapped reads were realigned to the same reference genome in single-end alignment mode (RefXXX).
Genome_build: hg19
Supplementary_files_format_and_content: For bisulfite sequencing samples, the processed files include the DNA methylation levels of cytosines in CpG, CHH and CHG context, in bed format.

organism: Homo sapiens

source_name: blastocyst

extract_protocol:
single cell or small amounts of cells were seeded into the lysis buffer using the mouth pipette, and DNAs were released after proteinase treatment at 50C and then bisulfite converted.
After purification, DNAs were complemented with the biotinated random primer (5’-biotin-CTACACGACGCTCTTCCGATCTNNNNNNNNN-3’) and 50 units of klenow polymerase (3’ to 5’exo-, New England Biolabs). This random priming was repeated 5 times in total. The second strands were synthesized using another random primer (5’-AGACGTGTGCTCTTCCGATCTNNNNNNNNN-3’) and the final libraries were generated after 8-12 cycles PCR amplification with the Illumina universal PCR primer and Illumina indexed primer.

tag: cell type

value: blastocyst

tag: gender

tag: bulk or single cell

value: bulk cells


title: scBS-O-bst-14


title: scBS-O-bst-1


title: HFLF3, WGBS


title: HFLF2, WGBS


title: scBS-O-ICM-5s4

source_name: ICM

value: single cell


title: Diploid_F121-9_A5

city: Tallahassee

first: David

middle: M

last: Gilbert

state: FL

address: 319 Stadium Drive

department: Biology

institute: Florida State University

description:
processed data file:
singlecell_normalized_smoothed.txt
singlecell_binarized.txt

data_processing:
Library strategy: replication-profiling
Reads were parsed into single-cell specific reads using the unique barcodes. Parsed reads are mapped on mm10 using bowtie2. F121-9 diploid cells are also parsed, between cas and 129 genome.
Coverage data in 50 kb bins are calculated from mapped reads using samtools and bedtools.
S-phase cell coverage was normalzied using G1/G2 cell coverage, outliers bins were removed and data smoothed using median filter (span=15) as explained in supplementary methods (singlecell_normalized_smoothed.txt).
Normalized smooth data was binarized to reflect replicated vs. un-replicated bins as explained in supplementary methods (singlecell_bianrized.txt).
Binaraized data from F121-9 diploid cells were further parsed into cas and 129 homologue specific binary singnal based on the cas and 129 homolouge read coverage as descirbed in supplementary methods.
Genome_build: mm10
Supplementary_files_format_and_content: There are two proceesed data files. The first one is the normalized and smoothed single cell data (singlecell_normalized_smoothed.txt) and the other is the binarized data (singlecell_binarized.txt). In the binarized file 1 indicates a replicated bin and 0 indicates the bin has not replicated. The first 2 columns are CHR and POS. The rest of the columns are the single cells. For diploid cells, each cell has 2 columns in the binarized file representing the cas and 129 homologue.

source_name: mouse ESC

growth_protocol: F121-9 (diploid) and H129-2 (haploid) mouse embryonic cells were cultured in N2B27+2i+LIF media.

extract_protocol:
Single cells from G1 or S-phase were sorted using AriaII FACS sorter based on DNA content after DAPI staining. Next, we performed whole genome single-cell sequencing as described in Baslan et al. 2015. Briefly, the cells were lysed and amplified using the Sigma SeqPlex kit (SEQXE-50RXN). The WGA products were purified and the WGA universal adaptor sequences were removed as per the kit protocol, leaving NN overhangs.
Uniquely barcoded illumina adaptors with NN overhangs were ligated to purified amplfied DNA with NN overhangs. Upto 96 uniquely barcoded cells were pooled together and re-amplified. Samples were then quantified using the Bioanalyzer and qPCR and sequenced on Hiseq 2500 sequencer using 50 bp single-end read format.

value: hybrid cas/129

value: ESC

tag: cell number

value: Single cell

tag: cell cycle stage

value: S-phase

tag: ploidy

value: diploid


title: HFLF1, WGBS


title: HF5, WGBS

value: 60% fat diet (HF)


title: scBS-M-MII-2

source_name: metaphase II oocyte

value: metaphase II oocyte

value: female


title: scBS-M-MII-1


title: scBS-K-MII-3


title: HF4, WGBS


title: HF2, WGBS


title: scBS-K-MII-2


title: scBS-K-MII-1


title: scBS-O-bst-7


title: scBS-K-GV-3

source_name: GV oocyte

value: GV oocyte


title: scBS-K-GV-4


title: HF1, WGBS


title: HF3, WGBS


title: LF3, WGBS

value: 10% fat diet (LF)


title: scBS-K-GV-2


title: scBS-J-MII-5


title: LF2, WGBS

value: male


title: LF4, WGBS

value: six-week old


title: scBS-H-PN4-2


title: scBS-K-GV-1


title: scBS-hSp9

source_name: sperm

value: sperm


title: scBS-M-MII-3


title: LF1, WGBS

value: colon


title: LF5, WGBS


title: scBS-hSp8


title: HFLF5, BSPseq

value: HF diet then switched to LF diet


title: HFLF2, BSPseq


title: HFLF4, BSPseq


title: HFLF3, BSPseq


title: scBS-H-PN4-1


title: scBS-H-PN3-2


title: HF4, BSPseq


title: HF5, BSPseq


title: HF3, BSPseq


title: HFLF1, BSPseq


title: scBS-H-PN2-1


title: scBS-H-PN2-2


title: scBS-H-PN3-1


title: scBS-F-GV1


title: scBS-E-PN9-1


title: scBS-H-PN1-2


title: LF1, BSPseq


title: LF5, BSPseq


title: scBS-H-PN1-1


title: HF1, BSPseq


title: scBS-G-MII-13


title: LF4, BSPseq


title: LF2, BSPseq


title: LF3, BSPseq


title: Dpse_25

city: Woodbury

first: Philippe

last: Batut

state: NY

address: 500 Sunnyside Blvd.

institute: CSHL

library_source: transcriptomic

data_processing:
Sequences corresponding to the library identification barcode (first 6 bases of read 1) and the reverse-transcription primer (first 15 bases of read 2) were trimmed prior to mapping.
Trimmed reads were mapped with STAR, with parameters as follows (--outSAMattributes All --outFilterScoreMinOverLread 0.85 --outFilterMatchNminOverLread 0.85 —outFilterMultimapNmax 50 --outFilterIntronMotifs None --seedSearchStartLmax 30 —outSAMunmapped Within --outFilterType BySJout --outFilterMismatchNmax 10 —clip5pNbases 6 15). All uniquely mapping reads were kept. As a rescue strategy for multiply mapping reads, if all alignments for those reads started within an annotated transposon and overlapped the same gene annotation, the alignment starting in the closest transposon insertion was selected. All non-rescued multi-mappers were discarded.
PCR duplicates, defined as reads sharing the same alignment coordinates (start, end and splice sites), were removed from the individual datasets. To avoid over-collapsing, we took advantage of the fact that the long random sequence (15-mer) of our reverse-transcription primer often primes with mismatches. We used this sequence as a pseudo-random barcode allowing us to distinguish between true duplicates (same barcode) and independent identical inserts.
Custom scripts were used to extract the 5'-most position of each RAMPAGE read, which corresponds to the TSS used for the transcription of the original RNA molecule.
All collapsed datasets in the time series were  combined prior to peak calling. The density of cDNA 5' ends across the genome was determined from this combined dataset, as well as the density of coverage by second (i.e., downstream) sequencing reads. Peaks were called by a sliding window algorithm that assesses the significance of local signal enrichment given a null distribution. Downstream read coverage in the same window was used to correct for local transcript abundance, by subtracting from the raw signal a pseudocount proportional to this coverage. After FDR correction, significant windows in close proximity to each other were merged into peaks, and those were trimmed at the edges down to the first base with signal. (Parameters: window width 15 bases, null distribution negative binomial with k=0.5, background weight 0.5, FDR 0.1, merging range 150 bases).
Individual peaks were connected to annotated genes based on cDNA structure information. For each peak, if we could find at least 2 inserts having their 5' in the peak and overlapping an annotated exon of a gene, the peak was functionally linked to that gene. If a peak could potentially be linked to several genes, ties were broken by removing all links that were 5-fold weaker than the strongest one. For quantification, the signal for each peak and each timepoint was derived from the uncollapsed datasets, and normalized to dataset size (defined as the total number of reads attributed to any genic TSS). Expression valuesin the matrix files are thus in reads per milion (RPM). Expression values for genes are the sum of expression values for all TSCs attributed to the gene (in RPM).
Gene expression matrices were upsampled 5-fold, subjected to Gaussian smoothing (width parameter=10), and converted to Z-scores using the GTEM package (see Goltsev et al., BMC Bioinformatics 2009). The time series was globally aligned to the D. melanogaster replicate 1 series using the MAlign tool in GTEM.
Genome_build: dpse r2.9 (FlyBase)
Supplementary_files_format_and_content: Signal density tracks (bigWig) were generated after collapsing PCR duplicates, and represent the density of RAMPAGE read 5' ends (i.e., the 5' mapping position) over each base across the genome.
Supplementary_files_format_and_content: Peak calls (i.e., TSCs) for the combined time series datasets are annotated in BED6 file format. Scores correspond to the total number of collapsed read 5' ends supporting the peak.
Supplementary_files_format_and_content: TSC expression and Gene expression matrices combine expression values for individual features, normalized by the total number of uniquely mapped reads per time point (in reads per million, RPM).
Supplementary_files_format_and_content: The aligned gene expression matrix represents expression values as Z-scores of the original RPM values, after upsampling, smoothing and global alignment of the time series.

molecule: total RNA

organism: Drosophila pseudoobscura

source_name: Whole embryos (staged)

growth_protocol: Stocks were maintained on standard cornmeal medium. Embryo collections were performed in population cages. 2- to 7-day-old flies were left to acclimatize to the cage for at least 48h and regularly fed with grape juice-agar plates generously loaded with fresh yeast paste. After two 2-hour pre-lays, embryos were collected in 1-hour windows and aged appropriately (29 time points, 0-29h). Embryos were washed with deionized water, dechorionated for 90 sec with 50% bleach, rinsed abundantly with water, and snap-frozen in liquid nitrogen.

extract_protocol:
Total RNA was extracted from embryos using a Beadbeater (Biospec, Cat. #607) with 1.0 mm zirconia beads (Biospec, #11079110zx) and the RNAdvance Tissue kit (Agencourt #A32649) according to the manufacturer’s instructions, including DNaseI treatment. We systematically checked on a Bioanalyzer RNA Nano chip (Agilent) that the RNA was of very high quality.
Libraries were prepared as described in Batut et al., Genome Research 2012. In brief, 5’-monophosphate transcripts were depleted by TEX digest (Epicentre #TER51020). For every time series, each sample was labeled with a different sequence barcode during reverse-transcription, and all samples for the series were then pooled and processed together as a single library. The 5'-complete cDNA selection strategy relies on the combination of two orthogonal enrichment methods: reverse-transcriptase template-switching, and cap-trapping. The template-switching approach is based on the ability of reverse-transcriptase to add linker sequences to the ends of 5'-complete cDNAs – preferentially if they are made from capped transcripts. Cap-trapping relies on the biotinylation of capped RNA molecules and specific pulldown of their associated 5'-complete cDNAs. Quality control and library quantification were carried out on a Bioanalyzer DNA High Sensitivity chip. Each library was sequenced on one lane of an Illumina HiSeq 2000.
reference: Batut, P., Dobin, A., Plessy, C., Carninci, P. & Gingeras, T.R. High-fidelity promoter profiling reveals widespread alternative promoter usage and transposon-driven developmental gene expression. Genome Res (2012).
reference: Batut, P. & Gingeras, T.R. RAMPAGE: Promoter Activity Profiling by Paired-End Sequencing of 5'-Complete cDNAs. Curr Protoc Mol Biol 104, 25B 11 1-25B 11 16 (2013).

value: WT (reference genome strain)

tag: ucsd stock #

tag: Stage

value: 24-25 hours after egg laying


title: scBS-E-PN9-2

value: single cell


title: scBS-E-PN1-1


title: scBS-E-PN1-2


title: scBS-E-PN8-2


title: scBS-E-PN8-1


title: Dpse_29

value: 28-29 hours after egg laying


title: scBS-E-PN12-2


title: scBS-D-PN7-2


title: Dpse_24

value: 23-24 hours after egg laying


title: scBS-E-PN12-1


title: Dpse_28

value: 27-28 hours after egg laying


title: HF2, BSPseq


title: scBS-E-PN11-1


title: scBS-F-GV2


title: scBS-E-MII-20


title: Dpse_21

value: 20-21 hours after egg laying


title: scBS-E-PN11-2


title: Dpse_27

value: 26-27 hours after egg laying


title: scBS-4C-8-3

source_name: 4-cell embryo#8


title: Dpse_26

value: 25-26 hours after egg laying


title: Dpse_23

value: 22-23 hours after egg laying


title: scBS-E-MII-19

value: metaphase II oocyte

value: female


title: scBS-D-PN7-1


title: scBS-4C-8-1


title: scBS-4C-7-3

source_name: 4-cell embryo#7


title: Dpse_22

value: 21-22 hours after egg laying


title: scBS-4C-8-2


title: scBS-4C-8-4


title: Dpse_20

value: 19-20 hours after egg laying


title: Dpse_16

value: 15-16 hours after egg laying


title: Dpse_17

value: 16-17 hours after egg laying


title: scBS-4C-7-2


title: scBS-D-GV-2

value: GV oocyte


title: Dpse_14

value: WT (reference genome strain)

value: 13-14 hours after egg laying


title: scBS-4C-7-1

value: single cell


title: Dpse_13

value: 12-13 hours after egg laying


title: scBS-4C-6-4

source_name: 4-cell embryo#6


title: Dpse_12

value: 11-12 hours after egg laying


title: scBS-4C-6-2


title: Dpse_19

value: 18-19 hours after egg laying


title: Dpse_11

value: 10-11 hours after egg laying


title: scBS-4C-6-1


title: Dpse_18

value: 17-18 hours after egg laying


title: scBS-4C-7-4


title: scBS-4C-5-1

source_name: 4-cell embryo#5


title: Dpse_10

value: 9-10 hours after egg laying


title: scBS-4C-5-3


title: scBS-4C-2-4

source_name: 4-cell embryo#2


title: Dpse_08

value: 7-8 hours after egg laying


title: scBS-4C-2-3


title: Dpse_09

value: 8-9 hours after egg laying


title: scBS-4C-5-4


title: scBS-2C-6-2

source_name: 2-cell embryo#6


title: Dpse_06

value: 5-6 hours after egg laying


title: scBS-2C-8-1

source_name: 2-cell embryo#8


title: Dpse_04

value: 3-4 hours after egg laying


title: Dpse_03

value: 2-3 hours after egg laying


title: Diploid_F121-9_A7

description:
Removed at quality control steps
processed data file:
NA

value: hybrid cas/129

value: ESC

value: Single cell

value: S-phase

value: diploid


title: Dpse_15

value: WT (reference genome strain)

value: 14-15 hours after egg laying


title: Dpse_02

value: 1-2 hours after egg laying


title: scBS-2C-11-2

source_name: 2-cell embryo#11

value: single cell


title: Dpse_01

value: 0-1 hour after egg laying


title: Dana_22

data_processing:
Sequences corresponding to the library identification barcode (first 6 bases of read 1) and the reverse-transcription primer (first 15 bases of read 2) were trimmed prior to mapping.
Trimmed reads were mapped with STAR, with parameters as follows (--outSAMattributes All --outFilterScoreMinOverLread 0.85 --outFilterMatchNminOverLread 0.85 —outFilterMultimapNmax 50 --outFilterIntronMotifs None --seedSearchStartLmax 30 —outSAMunmapped Within --outFilterType BySJout --outFilterMismatchNmax 10 —clip5pNbases 6 15). All uniquely mapping reads were kept. As a rescue strategy for multiply mapping reads, if all alignments for those reads started within an annotated transposon and overlapped the same gene annotation, the alignment starting in the closest transposon insertion was selected. All non-rescued multi-mappers were discarded.
PCR duplicates, defined as reads sharing the same alignment coordinates (start, end and splice sites), were removed from the individual datasets. To avoid over-collapsing, we took advantage of the fact that the long random sequence (15-mer) of our reverse-transcription primer often primes with mismatches. We used this sequence as a pseudo-random barcode allowing us to distinguish between true duplicates (same barcode) and independent identical inserts.
Custom scripts were used to extract the 5'-most position of each RAMPAGE read, which corresponds to the TSS used for the transcription of the original RNA molecule.
All collapsed datasets in the time series were  combined prior to peak calling. The density of cDNA 5' ends across the genome was determined from this combined dataset, as well as the density of coverage by second (i.e., downstream) sequencing reads. Peaks were called by a sliding window algorithm that assesses the significance of local signal enrichment given a null distribution. Downstream read coverage in the same window was used to correct for local transcript abundance, by subtracting from the raw signal a pseudocount proportional to this coverage. After FDR correction, significant windows in close proximity to each other were merged into peaks, and those were trimmed at the edges down to the first base with signal. (Parameters: window width 15 bases, null distribution negative binomial with k=0.5, background weight 0.5, FDR 0.1, merging range 150 bases).
Individual peaks were connected to annotated genes based on cDNA structure information. For each peak, if we could find at least 2 inserts having their 5' in the peak and overlapping an annotated exon of a gene, the peak was functionally linked to that gene. If a peak could potentially be linked to several genes, ties were broken by removing all links that were 5-fold weaker than the strongest one. For quantification, the signal for each peak and each timepoint was derived from the uncollapsed datasets, and normalized to dataset size (defined as the total number of reads attributed to any genic TSS). Expression valuesin the matrix files are thus in reads per milion (RPM). Expression values for genes are the sum of expression values for all TSCs attributed to the gene (in RPM).
Gene expression matrices were upsampled 5-fold, subjected to Gaussian smoothing (width parameter=10), and converted to Z-scores using the GTEM package (see Goltsev et al., BMC Bioinformatics 2009). The time series was globally aligned to the D. melanogaster replicate 1 series using the MAlign tool in GTEM.
Genome_build: dana r1.3 (FlyBase)
Supplementary_files_format_and_content: Signal density tracks (bigWig) were generated after collapsing PCR duplicates, and represent the density of RAMPAGE read 5' ends (i.e., the 5' mapping position) over each base across the genome.
Supplementary_files_format_and_content: Peak calls (i.e., TSCs) for the combined time series datasets are annotated in BED6 file format. Scores correspond to the total number of collapsed read 5' ends supporting the peak.
Supplementary_files_format_and_content: TSC expression and Gene expression matrices combine expression values for individual features, normalized by the total number of uniquely mapped reads per time point (in reads per million, RPM).
Supplementary_files_format_and_content: The aligned gene expression matrix represents expression values as Z-scores of the original RPM values, after upsampling, smoothing and global alignment of the time series.

organism: Drosophila ananassae

growth_protocol: Stocks were maintained on standard cornmeal medium. Embryo collections were performed in population cages. 2- to 7-day-old flies were left to acclimatize to the cage for at least 48h and regularly fed with grape juice-agar plates generously loaded with fresh yeast paste. After two 2-hour pre-lays, embryos were collected in 1-hour windows and aged appropriately (22 time points, 0-22h). Embryos were washed with deionized water, dechorionated for 90 sec with 50% bleach, rinsed abundantly with water, and snap-frozen in liquid nitrogen.

extract_protocol:
Total RNA was extracted from embryos using a Beadbeater (Biospec, Cat. #607) with 1.0 mm zirconia beads (Biospec, #11079110zx) and the RNAdvance Tissue kit (Agencourt #A32649) according to the manufacturer’s instructions, including DNaseI treatment. We systematically checked on a Bioanalyzer RNA Nano chip (Agilent) that the RNA was of very high quality.
Libraries were prepared as described in Batut et al., Genome Research 2012. In brief, 5’-monophosphate transcripts were depleted by TEX digest (Epicentre #TER51020). For every time series, each sample was labeled with a different sequence barcode during reverse-transcription, and all samples for the series were then pooled and processed together as a single library. The 5'-complete cDNA selection strategy relies on the combination of two orthogonal enrichment methods: reverse-transcriptase template-switching, and cap-trapping. The template-switching approach is based on the ability of reverse-transcriptase to add linker sequences to the ends of 5'-complete cDNAs – preferentially if they are made from capped transcripts. Cap-trapping relies on the biotinylation of capped RNA molecules and specific pulldown of their associated 5'-complete cDNAs. Quality control and library quantification were carried out on a Bioanalyzer DNA High Sensitivity chip. Each library was sequenced on one lane of an Illumina HiSeq 2000.
Batut, P., Dobin, A., Plessy, C., Carninci, P. & Gingeras, T.R. High-fidelity promoter profiling reveals widespread alternative promoter usage and transposon-driven developmental gene expression. Genome Res (2012).
Batut, P. & Gingeras, T.R. RAMPAGE: Promoter Activity Profiling by Paired-End Sequencing of 5'-Complete cDNAs. Curr Protoc Mol Biol 104, 25B 11 1-25B 11 16 (2013).

value: In(3R)A (reference genome strain)

value: 21-22 hours after egg laying


title: Dana_20

value: 19-20 hours after egg laying


title: scBS-A-MII-4

description: single cell

extract_protocol:
single cell or small amounts of cells were seeded into the lysis buffer using the mouth pipette, and DNAs were released after proteinase treatment at 50C and then bisulfite converted.
After column based purification, DNAs were complemented with the biotinated random primer (5’-biotin-CTACACGACGCTCTTCCGATCTNNNNNNNNN-3’) and 50 units of klenow polymerase (3’ to 5’exo-, New England Biolabs). This random priming was repeated 5 times in total. The second strands were synthesized using another random primer (5’-AGACGTGTGCTCTTCCGATCTNNNNNNNNN-3’) and the final libraries were generated after 8-12 cycles PCR amplification with the Illumina universal PCR primer and Illumina indexed primer.

value: oocyte

value: female


title: Dana_19

value: 18-19 hours after egg laying


title: Dana_21

value: 20-21 hours after egg laying


title: scBS-A-MII-3

description: single cell


title: scBS-4C-2-1


title: Dpse_05

value: 4-5 hours after egg laying


title: scBS-A-MII-2

description: single cell


title: Dana_15


title: Dana_16

value: 15-16 hours after egg laying


title: Dana_17

value: 16-17 hours after egg laying


title: Dana_18

value: 17-18 hours after egg laying


title: Dana_14

value: 13-14 hours after egg laying


title: Dana_12

value: 11-12 hours after egg laying


title: Dpse_07

value: WT (reference genome strain)

value: 6-7 hours after egg laying


title: Dana_11

value: 10-11 hours after egg laying


title: Dana_09

value: 8-9 hours after egg laying


title: Dana_10

value: In(3R)A (reference genome strain)

value: 9-10 hours after egg laying


title: Dana_06

value: 5-6 hours after egg laying


title: Dana_07


title: Dana_08

value: 7-8 hours after egg laying


title: Mo_GMCSF_IL4_72to144h_rep2

city: Bonn

first: Joachim

last: Schultze

state: NRW

address: Carl-Troll-Strasse 31

department: Genomics and Immunoregulation

country: Germany

institute: LIMES (Life and Medical Sciences Center Genomics and Immunoregulation)

data_processing:
Sequencing reads were retrieved as FASTQ files and then demultiplexed using CASAVA software suite version 1.8.2
Reads were aligned against the human genome version hg19 using TopHat version v2.1.0 (Kim et al., 2013); all default options were used
BAM files were sorted according to the mapping position and then imported into Partek® Genomics Suite® software, version 6.6 Copyright©; 2017 (PGS)
Quantification of mRNA was performed against the hg19 RefSeq Transcripts database version 2015-08-04 to obtain read counts for each individual RefSeq gene; 20,359 genes were finally retrieved
The obtained read count table was normalized using the R package DESeq2 (Love et al., 2014) and were then imported back into PGS
Normalized read counts were batch corrected to remove the unwanted variation introduced by donor
Then, genes were reduced to those with a mean normalized read count of 10 in at least one of the investigated groups, leading to 12,794 genes
All normalized count values smaller than 1 were set to 1 to avoid spurious Fold-Changes later on
Genome_build: hg19
Supplementary_files_format_and_content: TAB-delimited text file containing normalized abundance measurements for a filtered list of genes (see processing steps)

growth_protocol: CD14+ monocytes were cultured in RPMI1640 medium supplemented with 10% FCS, 1% Penicillin-Streptomycin, 1% Sodiumpyruvate and 1% Glutamax (all from Gibco) for three days

extract_protocol:
Total RNA was extracted using the miRNeasy Mini Isolation Kit (Qiagen), ribosomal RNA integrity was checked via a RNA assay on a Tapestation 2200 (Agilent)
TruSeq RNA Library Prep Kit v2 (Illumina) was used to generate libraries according to manufacturer‘s protocol. A DNA1000 assay for Tapestation 2200 (Agilent) was used to determine library fragment size and a qPCR quantification with a Library Quantification Kit for Illumina NGS libraries (Kapa Biosystems) on a Roche LightCycler480 was performed for quantification. Libraries were clustered to a TruSeq SR v3 flowcell and sequenced on a HiSeq1500 with 76bp+7ix reads

treatment_protocol: CD14+ monocytes were differentiated into (1) Mo-GMCSF[IL4 (0h)] cells by the addition of 800 IU/ml rhGM-CSF for 72 hours, (2) Mo-GMCSF[IL4 (0-72h)] or Mo-GMCSF[IL4 (0-144h)] cells by the addition of 800 IU/ml rhGM-CSF and 500 IU/ml rhIL4 for 72 or 144 hours, respectively, and (3) Mo-GMCSF[IL4 (12-144h)], Mo-GMCSF[IL4 (24-144h)], Mo-GMCSF[IL4 (48-144h)] or Mo-GMCSF[IL4 (72-144h)] cells by the addition of 800 IU/ml rhGM-CSF for the first 12, 24, 48 or 72 hours, respectively, and then 800 IU/ml rhGM-CSF and 500 IU/ml rhIL4 for the remaining hours until a final total duration of 144 hours

value: Mo-GMCSF[IL4 (72-144h)] cell

tag: donor

value: blood


title: Dana_05


title: Dana_04

value: 3-4 hours after egg laying


title: Mo_GMCSF_IL4_48to144h_rep3

value: Mo-GMCSF[IL4 (48-144h)] cell


title: Mo_GMCSF_IL4_48to144h_rep2


title: Mo_GMCSF_IL4_72to144h_rep1


title: Mo_GMCSF_IL4_48to144h_rep1


title: Mo_GMCSF_IL4_24to144h_rep3

value: Mo-GMCSF[IL4 (24-144h)] cell


title: Dana_03

value: 2-3 hours after egg laying


title: Dana_01

value: 0-1 hour after egg laying


title: Dana_02

value: 1-2 hours after egg laying


title: Dana_13

value: 12-13 hours after egg laying


title: Mo_GMCSF_IL4_12to144h_rep2

value: Mo-GMCSF[IL4 (12-144h)] cell


title: Mo_GMCSF_IL4_12to144h_rep3


title: Mo_GMCSF_IL4_12to144h_rep1


title: Mo_GMCSF_IL4_24to144h_rep2


title: Mo_GMCSF_IL4_0to72h_rep3

value: Mo-GMCSF[IL4 (0-72h)] cell


title: Mo_GMCSF_IL4_72to144h_rep3


title: Mo_GMCSF_IL4_0to72h_rep1


title: Mo_GMCSF_IL4_0to144h_rep2

value: Mo-GMCSF[IL4 (0-144h)] cell


title: Mo_GMCSF_IL4_0to144h_rep1


title: Mo_GMCSF_IL4_0to72h_rep2


title: Mo_GMCSF_IL4_0h_rep3

value: Mo-GMCSF[IL4 (0h)] cell


title: LFD_male_HNF4a_ChIPSeq_replicate2_input

data_processing:
ChIP-seq read pairs were filtered to retain only those with mean base quality score >20.
Filtered reads were mapped to mm9 via Bowtie (v0.12.8) with parameters -m 1 -X 2000 --chunkmbs 1024.
Duplicate read pairs were removed via MarkDuplicates.jar from the Picard tools suite v1.110.
For histone modification ChIPseq data, uniquely-mapped non-duplicate reads were downsampled to 10 million prior to peak-calling with SICER. SICER parameters were window size 200, gap size 200, FDR 0.001 for H3K27ac and window size 200, gap size 400, and FDR 0.001 for H3K4me1.
For NHF4a ChIPseq data, uniquely-mapped non-duplicate reads were downsampled to 20 million, then peak calls were made by HOMER at default parameters.
For all ChIP-seq data, mapped read depth files were generated by BEDtools genomeCoverageBed then by UCSC utility bedGraphToBigWig, after read pairs were converted to a single fragment by filling in region between read ends with Ns. Mapped depths are normalized to 10M for histone modification ChIP-seq data and 20M for HNF4a ChIP-seq data.
RNA-seq read pairs were filtered to retain only those with mean base quality score >20.
Filtered read pairs were mapped to mm9 via STAR v2.5 with the following paramters: --outMultimapperOrder Random --outSAMattrIHstart 0 --outFilterType BySJout --alignSJoverhangMin 8 --limitBAMsortRAM 55000000000.
For each sample, counts per gene were extracted by subread featureCounts v1.5.0-p1 with parameters -s2 -Sfr -p.
Genome_build: mm9
Supplementary_files_format_and_content: ChIP-seq normalized mapped read depth in bigWig format.
Supplementary_files_format_and_content: ChIP-seq peak calls in BED format.
Supplementary_files_format_and_content: RNA-seq raw counts per gene per sample in tab-delimited text file.

source_name: colon epithelium

extract_protocol: Chip-seq libraries were prepared by Bioo NEXTflex Rapid DNA-seq Kit (cat# 514402).

value: colon epithelium

value: male

tag: chip antibody

value: low fat diet


title: Mo_GMCSF_IL4_0h_rep2


title: scrambledRNA_rep2b

data_processing:
Sequencing reads were retrieved as FASTQ files and then demultiplexed using CASAVA software suite version 1.8.2
Reads were aligned against the human genome version hg19 using TopHat version v2.0.13 (Kim et al., 2013); all default options were used
BAM files were sorted according to the mapping position and then imported into Partek® Genomics Suite® software, version 6.6 Copyright©; 2017 (PGS)
Quantification of mRNA was performed against the hg19 RefSeq Transcripts database version 2015-08-04 to obtain read counts for each individual RefSeq gene; 19,384 genes were finally retrieved
The obtained read count table was normalized using the R package DESeq2 (Love et al., 2014) and were then imported back into PGS
Genes were reduced to those with a mean normalized read count of 10 in at least one of the investigated groups, leading to 12,816 genes
All normalized count values smaller than 1 were set to 1 to avoid spurious Fold-Changes later on
Genome_build: hg19
Supplementary_files_format_and_content: TAB-delimited text file containing normalized abundance measurements for a filtered list of genes (see processing steps) for the three different datasets

source_name: scrambledRNA

growth_protocol: CD14+ monocytes were cultured in RPMI1640 medium supplemented with 10% FCS, 1% Penicillin-Streptomycin, 1% Sodiumpyruvate and 1% Glutamax (all from Gibco) for three days.

treatment_protocol: CD14+ monocytes were differentiated into Mo-GMCSF[IL4 (0-72h)] by the addition of 800 IU/ml rhGM-CSF and 500 IU/ml rhIL4 incubated for 3 days. For the last 24 hours, whether siRNAs targeting NCOR2 or scrambled RNAs were added to the activation program.

value: monocyte-derived Mo-GMCSF[IL4 (0-72h)] cell

tag: genotype

value: scrambled RNA

tag: replicate type

value: technical replicate


title: LFD_male_HNF4a_ChIPSeq_replicate1_input

tag: Sex


title: HFD_male_HNF4a_ChIPSeq_replicate2_input

value: high fat diet


title: HFD_male_HNF4a_ChIPSeq_replicate1_input


title: scrambledRNA_rep2a

value: blood

value: biological replicate


title: Mo_GMCSF_IL4_0h_rep1


title: Mo_GMCSF_IL4_24to144h_rep1

value: Mo-GMCSF[IL4 (24-144h)] cell


title: LFD_male_HNF4a_ChIPSeq_replicate1

value: HNF4a (Abcam, ab41898)


title: aNCOR2_rep2b

value: siRNA knockdown of NCOR2


title: LFD_male_HNF4a_ChIPSeq_replicate2


title: scrambledRNA_rep1


title: aNCOR2_rep2a


title: HFD_male_HNF4a_ChIPSeq_replicate1


title: HFD_male_HNF4a_ChIPSeq_replicate2


title: aNCOR2_rep1


title: HF-rep2-batch2

data_processing:
RNA-seq read pairs were filtered to retain only those with mean base quality score >20.
Adapter sequence was trimmed from the end of reads by CutAdapt v1.2.1 with parameters -O 5 -q 0.
Filtered, adapter-trimmed read pairs were mapped to mm10 via STAR v2.5 with the following paramters: --outMultimapperOrder Random --outSAMattrIHstart 0 --outFilterType BySJout --alignSJoverhangMin 8 --limitBAMsortRAM 55000000000.
For each sample, counts per gene were extracted by subread featureCounts v1.5.0-p1 with parameters -s2 -Sfr -p.
Genome_build: mm10
Supplementary_files_format_and_content: RNA-seq raw counts per gene per sample in tab-delimited text file.

source_name: colonic epithelium

extract_protocol:
The entire colon was removed from mouse and colonic epithelium was isolated using PBS with 5 mM EDTA. Total RNA was isolated using Qiagen AllPrep DNA/RNA/miRNA Universal Kit according to the manufacturer’s instructions.
RNA sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero H/M/R Gold (Illumina, #RS-122-2301), following the manufacturer’s instructions.

treatment_protocol: Six-week old male C57BL/6 mice were placed on three different dietary regimens as follows: 1) low-fat diet for 43 weeks; 2) high-fat diet for 43 weeks; 3) high-fat diet for an initial 15 weeks then switched to low-fat diet for another 28 weeks.

value: colon

value: 60% fat diet (HF)


title: HF-rep1-batch2


title: HFLF-rep5-batch2

value: HF diet then switched to LF diet


title: Dere_23

data_processing:
Sequences corresponding to the library identification barcode (first 6 bases of read 1) and the reverse-transcription primer (first 15 bases of read 2) were trimmed prior to mapping.
Trimmed reads were mapped with STAR, with parameters as follows (--outSAMattributes All --outFilterScoreMinOverLread 0.85 --outFilterMatchNminOverLread 0.85 —outFilterMultimapNmax 50 --outFilterIntronMotifs None --seedSearchStartLmax 30 —outSAMunmapped Within --outFilterType BySJout --outFilterMismatchNmax 10 —clip5pNbases 6 15). All uniquely mapping reads were kept. As a rescue strategy for multiply mapping reads, if all alignments for those reads started within an annotated transposon and overlapped the same gene annotation, the alignment starting in the closest transposon insertion was selected. All non-rescued multi-mappers were discarded.
PCR duplicates, defined as reads sharing the same alignment coordinates (start, end and splice sites), were removed from the individual datasets. To avoid over-collapsing, we took advantage of the fact that the long random sequence (15-mer) of our reverse-transcription primer often primes with mismatches. We used this sequence as a pseudo-random barcode allowing us to distinguish between true duplicates (same barcode) and independent identical inserts.
Custom scripts were used to extract the 5'-most position of each RAMPAGE read, which corresponds to the TSS used for the transcription of the original RNA molecule.
All collapsed datasets in the time series were  combined prior to peak calling. The density of cDNA 5' ends across the genome was determined from this combined dataset, as well as the density of coverage by second (i.e., downstream) sequencing reads. Peaks were called by a sliding window algorithm that assesses the significance of local signal enrichment given a null distribution. Downstream read coverage in the same window was used to correct for local transcript abundance, by subtracting from the raw signal a pseudocount proportional to this coverage. After FDR correction, significant windows in close proximity to each other were merged into peaks, and those were trimmed at the edges down to the first base with signal. (Parameters: window width 15 bases, null distribution negative binomial with k=0.5, background weight 0.5, FDR 0.1, merging range 150 bases).
Individual peaks were connected to annotated genes based on cDNA structure information. For each peak, if we could find at least 2 inserts having their 5' in the peak and overlapping an annotated exon of a gene, the peak was functionally linked to that gene. If a peak could potentially be linked to several genes, ties were broken by removing all links that were 5-fold weaker than the strongest one. For quantification, the signal for each peak and each timepoint was derived from the uncollapsed datasets, and normalized to dataset size (defined as the total number of reads attributed to any genic TSS). Expression valuesin the matrix files are thus in reads per milion (RPM). Expression values for genes are the sum of expression values for all TSCs attributed to the gene (in RPM).
Gene expression matrices were upsampled 5-fold, subjected to Gaussian smoothing (width parameter=10), and converted to Z-scores using the GTEM package (see Goltsev et al., BMC Bioinformatics 2009). The time series was globally aligned to the D. melanogaster replicate 1 series using the MAlign tool in GTEM.
Genome_build: dere r1.3 (FlyBase)
Supplementary_files_format_and_content: Signal density tracks (bigWig) were generated after collapsing PCR duplicates, and represent the density of RAMPAGE read 5' ends (i.e., the 5' mapping position) over each base across the genome.
Supplementary_files_format_and_content: Peak calls (i.e., TSCs) for the combined time series datasets are annotated in BED6 file format. Scores correspond to the total number of collapsed read 5' ends supporting the peak.
Supplementary_files_format_and_content: TSC expression and Gene expression matrices combine expression values for individual features, normalized by the total number of uniquely mapped reads per time point (in reads per million, RPM).
Supplementary_files_format_and_content: The aligned gene expression matrix represents expression values as Z-scores of the original RPM values, after upsampling, smoothing and global alignment of the time series.

organism: Drosophila erecta

growth_protocol: Stocks were maintained on standard cornmeal medium. Embryo collections were performed in population cages. 2- to 7-day-old flies were left to acclimatize to the cage for at least 48h and regularly fed with grape juice-agar plates generously loaded with fresh yeast paste. After two 2-hour pre-lays, embryos were collected in 1-hour windows and aged appropriately (23 time points, 0-23h). Embryos were washed with deionized water, dechorionated for 90 sec with 50% bleach, rinsed abundantly with water, and snap-frozen in liquid nitrogen.

value: WT (reference genome strain)

value: 22-23 hours after egg laying


title: Dere_22

value: 21-22 hours after egg laying


title: Dere_21

value: 20-21 hours after egg laying


title: HFLF-rep3-batch2


title: scBS-2C-6-1

value: single cell


title: Dere_20

value: 19-20 hours after egg laying


title: HFLF-rep4-batch2


title: Dere_18

value: 17-18 hours after egg laying


title: HFLF-rep1-batch2


title: Dere_19

value: 18-19 hours after egg laying


title: HFLF-rep2-batch2


title: LF-rep4-batch2

value: 10% fat diet (LF)


title: Dere_17

value: 16-17 hours after egg laying


title: LF-rep3-batch2


title: LF-rep2-batch2


title: Dere_15

value: 14-15 hours after egg laying


title: HF-rep3-batch2


title: Dere_16

value: 15-16 hours after egg laying


title: HF-rep3-batch1


title: HF-rep2-batch1


title: Dere_14

value: 13-14 hours after egg laying


title: Dere_11

value: 10-11 hours after egg laying


title: Dere_13

value: 12-13 hours after egg laying


title: HF-rep1-batch1

value: colon

value: 60% fat diet (HF)


title: Dere_09

value: WT (reference genome strain)

value: 8-9 hours after egg laying


title: HFLF-rep4-batch1

value: HF diet then switched to LF diet


title: LF-rep1-batch2


title: Dere_10

value: 9-10 hours after egg laying


title: HFLF-rep3-batch1


title: HFLF-rep2-batch1


title: Dere_07

value: 6-7 hours after egg laying


title: Dere_06

value: 5-6 hours after egg laying


title: Dere_05

value: 4-5 hours after egg laying


title: Dere_03

value: 2-3 hours after egg laying


title: LF-rep3-batch1

value: 10% fat diet (LF)


title: LF-rep2-batch1


title: Dere_12

value: 11-12 hours after egg laying


title: LF-rep4-batch1


title: Dere_02

value: 1-2 hours after egg laying


title: Dere_01

value: 0-1 hour after egg laying


title: Dere_08

value: 7-8 hours after egg laying


title: LFDHFB_male_H3K27ac_ChIPSeq_replicate1_input

treatment_protocol: epithelium was isolated from mice on the low fat diet and high diet, fecal samples were collected freshly

value: colon epithelium

value: male

value: low fat diet-high fat bacterai


title: LFDLFB_male_H3K27ac_ChIPSeq_replicate2_input

value: low fat diet- low fat bacteria


title: LFDHFB_male_H3K27ac_ChIPSeq_replicate2_input


title: LFDLFB_male_H3K27ac_ChIPSeq_replicate1

value: H3K27ac (Abcam, ab4729)


title: LFDLFB_male_H3K27ac_ChIPSeq_replicate3


title: LFDLFB_male_H3K27ac_ChIPSeq_replicate3_input


title: LFDHFB_male_H3K27ac_ChIPSeq_replicate3_input


title: LFDLFB_male_H3K27ac_ChIPSeq_replicate1_input


title: LFDLFB_male_H3K27ac_ChIPSeq_replicate2


title: LFDHFB_male_H3K27ac_ChIPSeq_replicate3


title: HFLF-rep1-batch1

value: colon


title: HFDLFB_male_H3K27ac_ChIPSeq_replicate3_input

value: high fat diet-low fat bacteria


title: HFDLFB_male_H3K27ac_ChIPSeq_replicate1_input


title: Dere_04

value: WT (reference genome strain)

value: 3-4 hours after egg laying


title: HFDHFB_male_H3K27ac_ChIPSeq_replicate1_input

value: high fat diet-high fat bacteria


title: HFDHFB_male_H3K27ac_ChIPSeq_replicate2_input


title: HFDLFB_male_H3K27ac_ChIPSeq_replicate2_input


title: HFDLFB_male_H3K27ac_ChIPSeq_replicate3


title: LF-rep1-batch1


title: LFD_female_ChIPSeq_replicate3_input

value: female

value: low fat diet


title: HFDHFB_male_H3K27ac_ChIPSeq_replicate1


title: LFD_female_ChIPSeq_replicate2_input


title: LFD_female_ChIPSeq_replicate1_input


title: HFD_female_ChIPSeq_replicate3_input

value: high fat diet


title: LFDHFB_male_H3K27ac_ChIPSeq_replicate2


title: LFDHFB_male_H3K27ac_ChIPSeq_replicate1


title: scBS-A-MII-1

description: single cell

value: oocyte


title: LFD_female_H3K27ac_ChIPSeq_replicate3


title: LFD_female_H3K4me1_ChIPSeq_replicate1

value: H3K4me1 (Abcam, ab8895)


title: LFD_female_H3K4me1_ChIPSeq_replicate3


title: HFD_female_ChIPSeq_replicate1_input


title: HFD_female_ChIPSeq_replicate2_input


title: LFD_female_H3K27ac_ChIPSeq_replicate1


title: HFD_female_H3K4me1_ChIPSeq_replicate3


title: HFD_female_H3K27ac_ChIPSeq_replicate3


title: HFD_female_H3K27ac_ChIPSeq_replicate1


title: LFD_male_H3K27ac_ChIPSeq_replicate2_input


title: HFD_female_H3K4me1_ChIPSeq_replicate2


title: HFD_female_H3K4me1_ChIPSeq_replicate1


title: HFD_female_H3K27ac_ChIPSeq_replicate2


title: HFDLFB_male_H3K27ac_ChIPSeq_replicate2


title: HFDLFB_male_H3K27ac_ChIPSeq_replicate1


title: LFD_female_H3K4me1_ChIPSeq_replicate2


title: HFDHFB_male_H3K27ac_ChIPSeq_replicate2


title: LFD_male_H3K27ac_ChIPSeq_replicate1_input


title: HFD_male_H3K27ac_ChIPSeq_replicate3_input


title: HFD_male_H3K27ac_ChIPSeq_replicate2_input


title: HFD_male_H3K27ac_ChIPSeq_replicate1_input


title: LFD_male_H3K27ac_ChIPSeq_replicate3


title: LFD_male_H3K27ac_ChIPSeq_replicate2


title: LFD_male_H3K27ac_ChIPSeq_replicate1


title: HFD_male_H3K27ac_ChIPSeq_replicate3


title: HFD_male_H3K27ac_ChIPSeq_replicate2


title: HFD_male_H3K27ac_ChIPSeq_replicate1


title: LFD_male_H3K4me1_ChIPSeq_replicate3_input


title: LFD_male_H3K27ac_ChIPSeq_replicate3_input


title: HFD_male_H3K4me1_ChIPSeq_replicate3_input


title: HFD_male_H3K4me1_ChIPSeq_replicate2_input


title: LFDLFB_male_RNAseq_replicate3


title: HFD_male_H3K4me1_ChIPSeq_replicate3


title: LFD_male_H3K4me1_ChIPSeq_replicate2_input


title: LFDLFB_male_RNAseq_replicate1


title: LFD_male_H3K4me1_ChIPSeq_replicate3


title: LFDHFB_male_RNAseq_replicate3


title: LFDHFB_male_RNAseq_replicate2


title: LFD_male_H3K4me1_ChIPSeq_replicate2


title: HFD_male_H3K4me1_ChIPSeq_replicate2


title: LFD_female_H3K27ac_ChIPSeq_replicate2


title: LFDHFB_male_RNAseq_replicate1


title: BEC vIRF3 replicate 1

city: Los Angeles

first: Fan

last: Li

state: CA

address: 675 Charles E Young Drive South

department: Pediatrics

institute: University of California Los Angeles

description:
BEC-vIRF3-1
PolyA RNA

data_processing:
FASTQ files were generated using bcl2fastq v2.17
Reads were aligned to the hg19 genome using Tophat v2.0.14 with parameters '--max-mismatches 2 --max-multihits 10 --library-type fr-firststrand'
Gene-level counts were obtained using HTSeq v0.6.1p1 with parameters '-s reverse -m union'.
Genome_build: hg19
Supplementary_files_format_and_content: counts

source_name: blood endothelial cells

extract_protocol:
Total RNAs were isolated using TRIzol® reagent (Sigma).
RNA-seq libraries were prepared using the Illumina TruSeq Stranded mRNA Library Prep Kit following manufacturer's protocol.

value: blood endothelial cells (BEC)

tag: genotype/variation

value: V5/vIRF3 overexpression


title: BEC vIRF3 replicate 2

description:
BEC-vIRF3-2
PolyA RNA


title: BEC vIRF3 replicate 3

description:
BEC-vIRF3-3
PolyA RNA


title: BEC vector control replicate 3

description:
BEC-vector-3
PolyA RNA

value: vector control


title: BEC vector control replicate 2

description:
BEC-vector-2
PolyA RNA


title: HFDLFB_male_RNAseq_replicate2

value: colon epithelium

value: male

tag: diet


title: HFDLFB_male_RNAseq_replicate1

tag: strain


title: BEC vector control replicate 1

description:
BEC-vector-1
PolyA RNA


title: LFDLFB_male_RNAseq_replicate2

tag: tissue

value: low fat diet- low fat bacteria


title: HFDHFB_male_RNAseq_replicate3


title: LFD_male_H3K4me1_ChIPSeq_replicate1


title: LFD_male_H3K4me1_ChIPSeq_replicate1_input


title: HFDHFB_male_RNAseq_replicate2


title: HFLF5, RNAseq

tag: age

value: six-week old

value: HF diet then switched to LF diet


title: HFD_male_H3K4me1_ChIPSeq_replicate1_input


title: HFDLFB_male_RNAseq_replicate3

value: high fat diet-low fat bacteria


title: HFD_male_H3K4me1_ChIPSeq_replicate1


title: HFLF1, RNAseq

value: colon


title: 2.5_hpf_Rad21_1

city: Dunedin

first: Michael

last: Meier

address: 1st Floor Hercus Building, Dunedin School of Medicine, Great King Street

department: Pathology

country: New Zealand

institute: University of Otago

data_processing:
After adapter and quality trimming, reads were aligned to the Zv9 genome assembly using bowtie2 (version 2.2.1.) with default settings. 85% of the raw reads could be aligned except for Rad21 ChIP samples from 2.5 hpf, which had a 40% mapping rate
Peak finding and downstream data analysis was performed using HOMER. Peaks were defined at a 0.1% estimated false discovery rate
Genome_build: Zv9
Supplementary_files_format_and_content: peak files in bed format from HOMER analysis,

organism: Danio rerio

source_name: whole embryos

extract_protocol:
Chromatin was prepared from two independent collections of pooled embryos (n=2000) for 2.5 hpf stage embryos and (n=1000) for 4.5 hpf and 10 hpf embryos.Briefly, embryos were dechorionated using a syringe with a 21G needle, fixed in 1% formaldehyde 10 minutes at room temperature. Fixation was stopped by adding glycine to a final concentration to 0.125 M and incubation on ice for 5 minutes. Fixed embryos were then washed three times in ice cold 1x PBS, snap frozen and stored at -80 °C until use. After cell lysis, chromatin was sheared to 200-500 base pairs using a S220 Focused-ultrasonicator (Covaris) with the following settings per cycle: peak power = 70, duty factor = 5, cycles of bursts = 200, time=30 s. Individual cycle numbers were optimized for each stage. Chromatin from pre-MZT embryos needed 6 cycles of sonication to reach the desired 200-500 bp range, whereas chromatin isolated from 4.5 hpf and 10 hpf stages required 10 cycles.  Cell debris was removed by centrifugation. To provide standardized input for each ChIP experiment, chromatin was diluted to A260=0.25. For each ChIP, 6 µg of Rad21 antibody per 10 µl Dynabeads and 100 µl chromatin was incubated overnight at 4 °C. After elution, ChIP DNA and input controls were purified and precipitated with ethanol.
The ThruPLEX® DNA-seq Kit (Rubicon Genomics, USA) was used to prepare the 2.5 hpf sample libraries for sequencing. 125-bp paired-end sequencing was performed to a depth of 20-50 million reads per library on an Illumina HiSeq 2500TM by New Zealand Genomics Limited, NZ. Libraries for the 4.5 hpf and 10 hpf samples were constructed and sequenced at the Beijing Genomics Institute (China), yielding 20 million 50 bp single-end reads per sample

value: AB/PS

value: whole embryos

value: 2.5 hpf

value: Rad21 (custom made by GenScript Corporation, USA)


title: HF2, RNAseq

value: 60% fat diet (HF)


title: HF3, RNAseq


title: 2.5_hpf_Rad21_2


title: HFLF2, RNAseq


title: HF1, RNAseq


title: 2.5_hpf_Input_2

value: no antibody input control


title: LF4, RNAseq

value: 10% fat diet (LF)


title: LF3, RNAseq


title: LF5, RNAseq


title: HFLF3, RNAseq


title: LF2, RNAseq


title: LF1, RNAseq


title: 2.5_hpf_Input_1


title: C29-Form-R2

city: Amherst

first: Begum

middle: D.

last: Topcuoglu

state: MA

address: 336 North Pleasant St., Apt:3B

department: Microbiology

institute: University of Massachusetts

description: Formate

data_processing:
Basecalls performed using Illumina CASAVA software
Sequenced reads were trimmed for adaptor sequence
Alligned to T. paralvinellae genome using STAR_2.5.1b
FeatureCounts (Liao et al., 2014) was used to assign aligned sequence reads to genomic features
Transcript per Million (TPM) were reported
Genome_build: NZ_CP006965.1 Refseq NCBI
Supplementary_files_format_and_content: tab-delimited text files include raw count or TPM values for each Sample

organism: Thermococcus paralvinellae

source_name: Hyperthermophilic archeaon

extract_protocol:
Cell pellets were resuspended in TRIzol (Invitrogen) and total RNA was extracted using a Direct-zol RNA extraction kit (Zymo). RNA quantity was determined with Qubit fluorometry. RNA integrity was checked by a bioanalyzer and a Nanodrop spectrometer. Genewiz sequencing facilities performed rRNA removal, library construction, multiplexing and sequence the RNA with HiSeq2500, 2×100 Paired-End.
RNA libraries were prepared for sequencing using standard Illumina protocols by Genewiz Sequencing Facilities.

tag: carbon source

value: Formate


title: C28-Form-R1

description: Formate


title: HFDHFB_male_RNAseq_replicate1

value: high fat diet-high fat bacteria


title: C25-TryH2-R2

description: Tryptone+Hydrogen

value: Tryptone and Hydrogen


title: C27-TryH2-R3

description: Tryptone+Hydrogen


title: C22-TryH2-R1

description: Tryptone+Hydrogen


title: C15-Try-R3

description: Tryptone

value: Tryptone


title: C14-Try-R2

description: Tryptone


title: C30-Form-R3

description: Formate


title: C9-MalH2-R2

description: Maltose+Hydrogen

value: Maltose and Hydrogen


title: C12-Mal-R3

description: Maltose

value: Maltose


title: C8-MalH2-R1

description: Maltose+Hydrogen


title: C4-Mal-R2

description: Maltose


title: LEC vIRF3 replicate 3

description: PolyA RNA

source_name: lymphatic endothelial cells

tag: cell type

value: lymphatic endothelial cells (LEC)

value: V5/vIRF3 overexpression


title: C3-Mal-R1

description: Maltose


title: LEC vIRF3 replicate 2

description: PolyA RNA


title: LEC vector control replicate 3

description: PolyA RNA

value: vector control


title: C10-MalH2-R3

description: Maltose+Hydrogen


title: LEC vIRF3 replicate 1

description: PolyA RNA


title: C13-Try-R1

description: Tryptone


title: HF4, RNAseq

value: male

value: six-week old

value: colon


title: LEC vector control replicate 1

description: PolyA RNA


title: LEC vector control replicate 2

description: PolyA RNA


title: HLF KO 3 RNAseq

status: Public on Dec 18 2017

city: Lund

first: Shamit

last: Soneji

address: Solvegatan 19

country: Sweden

institute: BMC

data_processing:
Reads aligned using Tophat
Reads quantitated using Rsubread package using the Reqseq gene annotations
Genome_build: mm9
Supplementary_files_format_and_content: Read counts per Refseq annotated gene

source_name: Hematopoietic Stem cells

growth_protocol: Freshly isolated HSC (Lin- Sca+ c-Kit+ CD34-Flt3-)

extract_protocol:
Total RNA was isolated from 3,000 sorted LSK CD34- Flt3- cells using the QIAshredder and RNeasy Mini Kit (QIAGEN)
RNA libraries were constructed by the UCLA Clinical Microarray Core, Los Angeles, using TruSeq kits (Illumina).

value: HLF KO

tag: celltype

value: HSC (Lin- Sca+ c-Kit+ CD34-Flt3-)

tag: cell number


title: 18-2-3

city: Newcastle upon Tyne

first: Dean

middle: Mark

last: Hallam

state: Tyne and Wear

address: International Centre for Life

department: Institute of Genetic Medicine

country: United Kingdom

institute: Newcastle University

data_processing:
The quality of sequencing reads was firstly checked with FastQC (Version 0.11.2)
Poly-N tails were trimmed off from reads with an in house Perl script.
Low quality bases (Q < 30) and standard Illumina (Illumina, Inc.  California, U.S.) paired-end sequencing adaptors on 3’ ends of reads were trimmed off using autoadapt (Version 0.2) and only those that were at least 20bp in length after trimming were kept
The high quality reads were then mapped to the human reference genome hg38 with STAR (Version 2.5.0c)
Reads mapped to genes were then counted with HTSeq-count (Version 0.6.1) [4] according to annotations from GENCODE (Version 24)
Differentially expressed genes were identified with Bionconductor (Version 3.2) package DESeq2 (Version 1.10.1)
Genome_build: human reference genome hg38
Supplementary_files_format_and_content: Differentially expressed genes, collective analysis of 3 biological replicates.

source_name: High risk AMD donor

growth_protocol: iPSC derived from low and high risk donors were spontaneously differentiated into RPE over a 4 month period, patches of RPE were then enriched and plated into hanging cell culture inserts

extract_protocol:
Truseq v2 total RNA extraction method (Illumina)
cDNA was generated using SMART-Seq v4 Ultra Low Input RNA Kit (Clontech)
Sequencing libraries were generated using Nextera XT DNA Library Prep Kit (Illumina)

tag: diagnosis

value: age-related macular degeneration (AMD)

value: induced pluripotent stem cell-derived retinal pigmented epithelium cells (iPSC-RPE)

value: CFH +/+ ARMS2/HTRA1 -/-

tag: passage


title: HLF KO 2 RNAseq


title: 18-2-2


title: 18-2-1


title: 13-2-1

source_name: Low risk donor

value: healthy

value: CFH -/- ARMS2/HTRA1 -/-


title: 13-2-2


title: 13-2-3


title: WT 2 RNAseq

value: wild type


title: HLF KO 1 RNAseq


title: WT 3 RNAseq


title: WT 1 RNAseq


title: WT_H3K4me3_ChIPSeq.rep2

city: La Jolla

first: Bing

last: Ren

address: 9500 Gilman Dr., CMM-East, Admin Area/Rm 2071

institute: University of California, San Diego School of Medicine

data_processing:
ChIP-seq sequencing data was trimmed and aligned to mm9(July 2007, NCBI37) by bwa (version 0.7.13-r1126). Unmapped, multimapped and PCR duplicates were removed by Picard(2.11.0).
ChIP seq peaks were called for each replicate and pooled data using MACS2(2.1.0.20150731) with default parameters. Pooled peaks that were found in both replicates were defined as reproducible peaks for each factor.
ChIP Fold enrichment over input was calculated by macs2 bdgcmp. Normalized ChIP signal was generated by UCSC tool bedGraphToBigWig. Averaged ChIP-seq fold enrichment over input at each reproducible peak was calculated using bigWigAvgOverBed.
Distal regions are peaks whose center are ± 2kb away from GENCODE transcript TSS. Using two fold difference cut off, distal regions were classified as “decreased”,”unhcnaged” and “increased” by comparing the fold enrichment over input in DCD to that in WT. If the fold enrichment of a region in DCD is less than half of that in WT, the region was defined as decreased.
Heatmap and aggregate profile of input normalized CHIP-seq signal were generated by deepTools 2.5.1.
Genome_build: mm9
Supplementary_files_format_and_content: Signal tracks were generated by bamCoverage 2.5.3 with parameters "--normalizeUsingRPKM -e 300 -bs 25 --smoothLength 75" (deepTools)

source_name: embryonic stem cells

growth_protocol: Cells were cultured on MEF feeder cells in serum free media (DMEM 10013-cv supplemented with 15% KSR, 2 mM L-glutamine, 100 μM nonessential amino acids, 50 μM beta-mercaptoethanol, 1000 units ml⁻¹ leukemia inhibitory factor (LIF), 100 units ml⁻¹ penicillin, and 100 μg ml⁻¹ streptomycin.) at 37°C with 5%CO2.

extract_protocol: Crosslinked cells were processed by Covaris truChIP Chromatin Shearing kit and chromatin were sonicated to 300-500bp by Covaris M220. ChIP DNA and Input DNA were constucted into illumina Tru-seq libraries as previously described (Jian Yan et al., 2013), followed by size selection for 300-500bp.

tag: cell line

value: R1 ESC

value: wild-type

tag: antibody

tag: antibody catalog #

tag: antibody vendor

value: Millipore


title: HFLF4, RNAseq

value: HF diet then switched to LF diet


title: dCD_H3K27ac_ChIPSeq.rep2

tag: genotype

value: MLL3/4 double catalytic dead

value: Active Motif


title: WT_BRG1_ChIPSeq.rep2

value: Abcam


title: dCD_H3K4me2_ChIPSeq.rep1


title: dCD_DPF2_ChIPSeq.rep2


title: dCD_H3K4me3_ChIPSeq.rep1


title: WT_DPF2_ChIPSeq.rep2


title: dCD_BRG1_ChIPSeq.rep2


title: dCD_H3K4me2_ChIPSeq.rep2


title: WT_H3K27ac_ChIPSeq.rep2


title: dCD_Input.rep2


title: WT_H3K4me1_ChIPSeq.rep2


title: WT_Input.rep2


title: WT_BRG1_ChIPSeq.rep1


title: dCD_H3K4me1_ChIPSeq.rep1


title: WT_H3K27ac_ChIPSeq.rep1


title: WT_DPF2_ChIPSeq.rep1


title: dCD_H3K27ac_ChIPSeq.rep1


title: WT_H3K4me2_ChIPSeq.rep1


title: dCD_BRG1_ChIPSeq.rep1


title: WT_H3K4me3_ChIPSeq.rep1


title: WT_H3K4me1_ChIPSeq.rep1


title: mtr4 rrp41 RRP41Pi-Cat-_replicate 2 [ETS]

city: Strasbourg

first: Dominique

last: Gagliardi

address: 12, rue du General Zimmer

department: IBMP

country: France

institute: CNRS

data_processing:
After initial data processing by the MiSeq Control Software v 2.5. (Illumina), base calls were retrieved and further analysed by a suite of home made python scripts (v2.7) using biopython (v1.63) and regex (v2.4) libraries
Sequences with identical nucleotides in read 1 (insert) and the 1st to 15th cycle in read 2 (randomized bases in 3’ adapter) were deduplicated.
Next, the sequence ATCTCGCGCTTGTACGGC corresponding to  5' ETS rRNA was searched in reads 1.
The matching read 1 were extracted and annotated alongside with their corresponding read 2.  Reads 2 missing a delimiter sequence,  ‘GTCAG’ as in the direction of read 2, were discarded.
For the remaining reads 2, the randomized sequence and the delimiter present in the 3’ adapter were removed.
As the target sequences were often short, reads 2 often run into the 5’ PCR primer, the sequences of which were also removed. Reads 2 that were after these trimming operations shorter than 20 nt were excluded from further analysis
In order to determine the 3’ extremities of the target RNAs, reads 2 were mapped to the precursor sequence of the Arabidopsis thaliana 5' ETS rRNA.
3' end position 1 corresponds to the first nucleotide of ETS sequence that matchs the 5' PCR primer, i. e. ATCTCGCGCTTGTACGGC.
rRNA species that contain non-templated tails produce reads 2 that do not match the reference sequence. To identify such reads and map their 3’ end position, the sequences of the unmatched reads 2 were sucessively trimmed from their 3’ end.
After each trimming step of 1 nt, sequences were mapped to the reference genome, and the unmatched sequences were further trimmed until a maximum of 30 nt has been removed.
At each mapping step, non-templated nucleotides at the 3’ were extracted and analysed for their size and composition.
3’ modifications longer than 6, 10 and 15 nt were considered only if they contained at least one stretch of AAA or TTT, two stretches of AAA or TTT, or three stretches of AAA or TTT, respectively.
Genome_build: Arabidopsis thaliana rRNA repeat unit (Genbank X52322.1)
Supplementary_files_format_and_content: Processed data are provided for each genotype and biological replicate in one file. Each line corresponds to one individual reads.
Supplementary_files_format_and_content: For each read, we indicate the 3' end position, encoded sequence, modification sequence, modification size, biological replicate and genotype.
Supplementary_files_format_and_content: For 3' end position, position 1 corresponds to the first nucleotide of 5' ETS sequence that matchs the 5' PCR primer. The +1 position corresponds to P cleavage site.

organism: Arabidopsis thaliana

source_name: mtr4 rrp41 RRP41Pi-Cat-

growth_protocol: Arabidopsis thaliana plants (accession Col-0) were grown on soil with 16h light/8h darkness cycles.

extract_protocol:
RNA was extracted from rosette leaves of indicated genotypes using TRI Reagent® (MRC)
3' RACE-seq
Data were obtained either from single or multiple sequencing runs to obtain the desired depth for each sample.

value: mtr4 rrp41 RRP41Pi-Cat-

value: rosette leaves


title: dCD_DPF2_ChIPSeq.rep1


title: mtr4 rrp41 RRP41WT_replicate 2 [ETS]

source_name: mtr4 rrp41 RRP41WT

value: mtr4 rrp41 RRP41WT


title: dCD_H3K4me3_ChIPSeq.rep2


title: WT_Input.rep1


title: RRP44KD rrp6L2 rrp41 RRP41WT_replicate 2 [ETS]

source_name: RRP44KD rrp6L2 rrp41 RRP41WT

value: RRP44KD rrp6L2 rrp41 RRP41WT


title: mtr4_replicate 2 [ETS]


title: RRP44KD rrp6L2_replicate 2 [ETS]

source_name: RRP44KD rrp6L2

value: RRP44KD rrp6L2


title: RRP44KD rrp6L2 rrp41 RRP41Pi-Cat-_replicate 2 [ETS]

source_name: RRP44KD rrp6L2 rrp41 RRP41Pi-Cat-

value: RRP44KD rrp6L2 rrp41 RRP41Pi-Cat-


title: dCD_H3K4me1_ChIPSeq.rep2


title: rrp41 RRP41Pi-Cat-_replicate 2 [ETS]

source_name: rrp41 RRP41Pi-Cat-

value: rrp41 RRP41Pi-Cat-


title: rrp6L2 rrp41 RRP41Pi-Cat-_replicate 2 [ETS]

source_name: rrp6L2 rrp41 RRP41Pi-Cat-

value: rrp6L2 rrp41 RRP41Pi-Cat-


title: rrp6L2 rrp41 RRP41WT_replicate 2 [ETS]

source_name: rrp6L2 rrp41 RRP41WT

value: rrp6L2 rrp41 RRP41WT


title: rrp6L2_replicate 2 [ETS]


title: Col-0_replicate 2 [ETS]


title: rrp41 RRP41Pi-_replicate 2 [ETS]

source_name: rrp41 RRP41Pi-

value: rrp41 RRP41Pi-


title: RRP44KD rrp6L2 rrp41 RRP41WT_replicate 1 [ETS]


title: dCD_Input.rep1

value: R1 ESC


title: rrp6L2 rrp41 RRP41WT_replicate 1 [ETS]


title: rrp6L2_replicate 1 [ETS]


title: rrp41 RRP41WT_replicate 2 [ETS]

source_name: rrp41 RRP41WT

value: rrp41 RRP41WT


title: RRP44KD rrp6L2 rrp41 RRP41Pi-Cat-_replicate 1 [ETS]


title: RRP44KD rrp6L2_replicate 1 [ETS]


title: rrp41 RRP41Pi-Cat-_replicate 1 [ETS]


title: rrp6L2 rrp41 RRP41Pi-Cat-_replicate 1 [ETS]


title: Col-0_replicate 1 [ETS]


title: rrp41 RRP41WT_replicate 1 [ETS]


title: rrp41 RRP41Pi-_replicate 1 [ETS]


title: mtr4 rrp41 RRP41WT_replicate 2

data_processing:
After initial data processing by the MiSeq Control Software v 2.5. (Illumina), base calls were retrieved and further analysed by a suite of home made python scripts (v2.7) using biopython (v1.63) and regex (v2.4) libraries
Sequences with identical nucleotides in read 1 (insert) and the 1st to 15th cycle in read 2 (randomized bases in 3’ adapter) were deduplicated.
Next, the sequences TCTGCCTGGGTGTCACAA for 5.8S precursor rRNA and TTCTGGCCGAGGGCACGTCTG for 5.8S mature rRNA were searched in reads 1.
The matching read 1 were extracted and annotated alongside with their corresponding read 2.  Reads 2 missing a delimiter sequence,  ‘GTCAG’ as in the direction of read 2, were discarded.
For the remaining reads 2, the randomized sequence and the delimiter present in the 3’ adapter were removed.
As the target sequences were often short, reads 2 often run into the 5’ PCR primer, the sequences of which were also removed. Reads 2 that were after these trimming operations shorter than 20 nt were excluded from further analysis
In order to determine the 3’ extremities of the target RNAs, reads 2 were mapped to the precursor sequence of the Arabidopsis thaliana 5.8S rRNA.
3' end position 1 corresponds to the first nucleotide of 5.8S sequence that matchs the 5' PCR primer, i. e. TCTGCCTGGGTGTCACAAATC and TTCTGGCCGAGGGCACGTCTG for 5.8S precursor rRNA and 5.8S mature rRNA, respectively.
rRNA species that contain non-templated tails produce reads 2 that do not match the reference sequence. To identify such reads and map their 3’ end position, the sequences of the unmatched reads 2 were sucessively trimmed from their 3’ end.
After each trimming step of 1 nt, sequences were mapped to the reference genome, and the unmatched sequences were further trimmed until a maximum of 30 nt has been removed.
At each mapping step, non-templated nucleotides at the 3’ were extracted and analysed for their size and composition.
3’ modifications longer than 6, 10 and 15 nt were considered only if they contained at least one stretch of AAA or TTT, two stretches of AAA or TTT, or three stretches of AAA or TTT, respectively.
Final processing was performed with R software (v3.3.1). Reads mapping upstream position of the 5' PCR primer were discarded and position of 3' end extremities were corrected so that position 1 corresponds to the first nucleotide after the end of the 5.8S mature form.
Genome_build: Arabidopsis thaliana rRNA repeat unit (Genbank X52322.1)
Supplementary_files_format_and_content: Processed data are provided for each genotype and biological replicate in one file. Each line corresponds to one individual reads.
Supplementary_files_format_and_content: For each read, we indicate the 3' end position, encoded sequence, modification sequence,modification size, biological replicate and genotype.
Supplementary_files_format_and_content: For 3' end position, position 1 corresponds to the first nucleotide after the end of the 5.8S mature form.

tag: reference sequence

value: 5.8S  precursor rRNA


title: HF5, RNAseq

data_processing:
Each raw dataset was filtered to remove any read pairs with average base quality score <20.  Cutadapt (parameters: --adapter=AGATCGGAAGAGC -O 5) was used to trim adapters from BSP-seq libraries; adapter trimming was deemed unnecessary for the RNA-seq and WGBS libraries.  A minimum fragment length of 30nt (post-trimming) was required.
RNA-seq reads were mapped against the mm10 reference genome via TopHat v2.0.4 (parameters: --b2-sensitive --library-type fr-firststrand -g 10 --mate-inner-dist 40 --mate-std-dev 50).
RNA-seq read counts per gene per sample were collected using HTSeq-Count.
Differentially expressed genes were determined using DESeq2 v1.2.10 , with threholds p-value <0.01, adjusted p-value < 0.25, and fold change > 1.2.
RNA-seq coverage tracks (per genomic strand) were generated with bedtools2 v2.19.0 genomeCoverageBed, then convert to bigWig format with UCSC command-line tool bedGraphToBigWig.
BSP-seq reads were mapped via Bismark v0.7.8 (parameters: -I 0 -X 1000 --non_bs_mm --chunkmbs 1024 --non_directional) against a masked version of the mm10 reference genome where are nucleotides in non-query regions were replaced with Ns.
BSP-seq alignments were post-processed to clip redundant mapped bases due to overlapping mates from the same read pair.
Percent methylation at each CpG site in the query regions of the BSP-seq data was calculated as methylated mapped C bases divided by total (methylated+unmethylated) mapped C bases.
BSP-seq coverage tracks were generated with bedtools2 v2.19.0 genomeCoverageBed, then convert to bigWig format with UCSC command-line tool bedGraphToBigWig.
WGBS reads were mapped against the mm10 reference genome via Bismark v0.14.0 (parameters:  -I 0 -X 10000 --non_bs_mm --sam --old_flag -n 2 -l 50 -e 70 --chunkmbs 1024), then deduplicated with deduplicate_bismark v0.14.0 (parameters: --paired).
WGBS alignments were post-processed to separate hits according to source genome strand, to clip redundant mapped bases due to overlapping mates from the same read pair, and to clip 5' and/or 3' read cycles with methylation bias as identified with bismark_methylation_extractor using the --mbias_only option.
WGBS coverage tracks (per genomic strand) were generated with bedtools2 v2.19.0 genomeCoverageBed, then convert to bigWig format with UCSC command-line tool bedGraphToBigWig.
WGBS percent methylation was calculated (per cytosine in CpG, per genomic strand) as methylated mapped C bases divided by total (methylated+unmethylated) mapped C bases.
Differentially methylated regions were identified by merging CpG sites with differential methylation according to the Rao Scott Likelihood Ratio Test (p-value 0.05) within 5kb, with minimum weighted coverage of 10 in at least one cohort.  DMRs were then filtered to require at least 2 CpG sites, region FDR <0.01, and methylation difference of least 30% or 5-fold.
Genome_build: mm10
Supplementary_files_format_and_content: RNAseq mapped read depth by strand in bigWig format.
Supplementary_files_format_and_content: Tab-delimited text file with read counts per gene, per sample.
Supplementary_files_format_and_content: Tab-delimited text files with DESeq2 values (fold change, p-value, adjusted p-value) and DEG status according to selected thresholds.
Supplementary_files_format_and_content: BSPseq mapped read depth in bigWig format.
Supplementary_files_format_and_content: Tab-delimited text file with percent methylation at each CpG site in the BSP-seq query regions.
Supplementary_files_format_and_content: WGBS mapped read depth by strand in bigWig format.
Supplementary_files_format_and_content: WGBS percent methylation per CpG site in bigWig format; C on plus strand have positive values, C on minus strand have negative values;
Supplementary_files_format_and_content: WGBS DMRs for high fat vs low fat diet conditions.

source_name: colonic epithelium

tag: Sex

value: male

value: six-week old

value: colon

value: 60% fat diet (HF)


title: mtr4_replicate 2

tag: genotype/variation


title: mtr4 rrp41 RRP41Pi-Cat-_replicate 2

value: mtr4 rrp41 RRP41Pi-Cat-


title: RRP44KD rrp6L2 rrp41 RRP41WT_replicate 2

value: rosette leaves


title: mtr4 rrp41 RRP41Pi-Cat-_replicate 1 [ETS]


title: rrp6L2 rrp41 RRP41WT_replicate 2


title: rrp6L2_replicate 2


title: rrp6L2 rrp41 RRP41Pi-Cat-_replicate 2


title: rrp41 RRP41WT_replicate 2


title: Col-0_replicate 2


title: mtr4 rrp41 RRP41WT_replicate 1 [ETS]

value: mtr4 rrp41 RRP41WT


title: rrp41 RRP41Pi-Cat-_replicate 2


title: mtr4_replicate 1 [ETS]


title: mtr4 rrp41 RRP41Pi-Cat-_replicate 1


title: mtr4 rrp41 RRP41WT_replicate 1


title: mtr4_replicate 1


title: RRP44KD rrp6L2 rrp41 RRP41Pi-Cat-_replicate 1


title: RRP44KD rrp6L2 rrp41 RRP41WT_replicate 1

value: RRP44KD rrp6L2 rrp41 RRP41WT


title: rrp6L2 rrp41 RRP41Pi-Cat-_replicate 1


title: RRP44KD rrp6L2_replicate 1

value: RRP44KD rrp6L2


title: rrp6L2 rrp41 RRP41WT_replicate 1


title: RRP44KD rrp6L2 rrp41 RRP41Pi-Cat-_replicate 2

value: RRP44KD rrp6L2 rrp41 RRP41Pi-Cat-


title: RNASEQ_mDCs_ZBK6_48h_infected

city: Cambridge

first: Xu

middle: G

last: Yu

state: Massachusetts

address: 400 Technology sqr

institute: Ragon Institute of MGH, MIT and Harvard

data_processing:
FASTQ files were obtained by Illumina demultiplexing pipeline. STAR and RSEM were used to align to HG38 and to calculate the raw counts for genes, respectively.
Supplementary_files_format_and_content: raw counts & TPM
Genome_build: Genome_build: HG38

source_name: myeloid dendritic cells

extract_protocol:
myeloid dendritic cells were sorted by FACS ARIA sorter, and RNA was extracted using Picopure RNA extraction kit. Construction of sequencing libraries were adapted from the published protocol (Trombetta JJ et al. 2014).
Whole transcriptome amplification (WTA) and tagmentation-based library preparation was performed using SMART-seq2.

value: peripheral blood

tag: infection status

value: ZIKV infected

tag: environment

value: in vitro

tag: time point


title: RRP44KD rrp6L2_replicate 2

tag: tissue


title: RNASEQ_mDCs_ZBK6_24h_infected


title: rrp6L2_replicate 1


title: rrp41 RRP41Pi-Cat-_replicate 1

value: rrp41 RRP41Pi-Cat-


title: RNASEQ_mDCs_ZBK6_24h_uninfected

value: ZIKV uninfected


title: rrp41 RRP41WT_replicate 1

value: rrp41 RRP41WT


title: RNASEQ_mDCs_ZBK5_48h_infected


title: RNASEQ_mDCs_ZBK6_48h_uninfected


title: Col-0_replicate 1

value: 5.8S  precursor rRNA


title: RNASEQ_mDCs_ZBK5_24h_infected


title: rrp6L2 (5.8S rRNA mature 3’ end)_replicate 1

source_name: rrp6L2 (5.8S rRNA mature 3’ end)

value: rrp6L2 (5.8S rRNA mature 3-prime end)

value: 5.8S  mature rRNA


title: RNASEQ_mDCs_ZBK4_48h_uninfected


title: RNASEQ_mDCs_ZBK4_24h_infected


title: RNASEQ_mDCs_ZBK5_24h_uninfected


title: Col-0 (5.8S rRNA mature 3’ end)_replicate 1

source_name: Col-0 (5.8S rRNA mature 3’ end)

value: Col-0 (5.8S rRNA mature 3-prime end)


title: RNASEQ_mDCs_ZBK2_48h_uninfected


title: RNASEQ_mDCs_ZBK2_48h_infected


title: RNASEQ_mDCs_ZBK5_48h_uninfected


title: RNASEQ_mDCs_ZBK2_24h_uninfected


title: RNASEQ_mDCs_ZBK2_24h_infected


title: RNASEQ_mDCs_ZBK2_12h_uninfected


title: RNASEQ_mDCs_ZBK2_6h_infected


title: Interface between haustorial tissue and attached host stem, replicate 1

city: University Park

middle: J

last: Axtell

state: PA

address: 280 Mueller Lab

institute: Pennsylvania State University

description:
small RNA
I1

data_processing:
FASTQ files were processed with Cutadapt version 1.9.1 with settings "-a TGGAATTCTCGGGTGCCAAGG --discard-untrimmed -m 16 --max-n=0" to produce trimmed reads in FASTQ format
Trimmed reads that aligned with zero or one mismatch (using bowtie version 1.1.2, settings "-v 1") to the A. thaliana plastid genome, the C. gronovii plastid genome (C. gronovii was the closest relative to C. pentagona that had a publically available completed plastid genome assembly available), A. thaliana rRNAs, tRNAs, snRNAs, or snoRNAs were removed.
The remaining 'clean' reads were then aligned to the combined TAIR10 A. thaliana reference genome and TAIR10 reference cDNAs, demanding perfect matches, using bowtie version 1.1.2 with settings "-v 0". Sequences that matched were initially designated as host-derived, while those that didn't were initially designated as parasite-derived.
Species of origin assignments were then adjusted based on comparing expression levels in the host stem (HS) vs. parasite stem (PS) samples. Let HSrpm indicate the summed reads-per-million value in both HS samples, and HSraw indicate the summed number of raw reads in both HS samples, and similarly for PSrpm and PSraw.  For A. thaliana-matched sequences, if HSrpm / (HSrpm + PSrpm) = 1 or if HSrpm / (HSrpm + PSrpm) >= 0.95 and HSraw + PSraw >= 5, the sequence was re-assigned to be in the parasite-derived set. Similarly, for sequences not exactly matched to A. thaliana, if HSrpm / (HSrpm + PSrpm) = 0 or if HSrpm / (HSrpm + PSrpm) <= 0.05 and HSraw + PSraw >= 5, the sequence was re-assigned to the host-derived set.
Parasite-derived small RNAs between 20 and 24 nts in length were clustered according to sequence similarity. Beginning with a list of parasite-derived 20-24 nt RNA sequences sorted in descending order by abundance (summed across all libraries), each sequence was queried against all remaining others to find less abundant sequences within a Levenshtein edit distance of one or two. The most abundant sequence in each resulting cluster was termed the 'head', while all other variants were termed 'isos'. For computational expediency, this process was limited to 'heads' with a raw read count of 20 or more. Parasite-derived sequences with total read counts of less than 20 that were not found as 'isos' were discarded.  This resulted in a total of 29,988 parasite-derived small RNA clusters. The total abundance in each cluster was calculated as the sum of read counts for the 'head' and all its 'iso' sequence variants.
The final set of host-derived reads were aligned to the TAIR10 A. thaliana nuclear genome using ShortStack version 3.4 with settings "--bowtie_cores 5 --sort_mem 4G --nostitch --mincov 1rpm", resulting in the definition of 36,918 small RNA-producing genomic intervals from A. thaliana.  Alignment counts in each of these clusters were tallied.
Genome_build: Host-derived reads: TAIR10 Arabidopsis thaliana. Parasite-derived reads: None
Supplementary_files_format_and_content: There are two processed files. One is for the host-derived reads, and includes read counts for each ShortStack-derived cluster in each of the six samples. The other is for the parasite-derived reads, and contains read counts for each head+iso cluster (see above) in each of the six samples. Both are tab-delimited ASCII plain-text formatted.

organism:
Arabidopsis thaliana
Cuscuta pentagona

source_name: Cuscuta pentagona haustoria with attached Arabidopsis thaliana stem

growth_protocol: Arabidopsis thaliana ecotype Columbia were grown in a growth room at 18-20°C with 12-h light per day , illuminated (200 µmol m-2s-1) with metal halide (400W, GE multi-vapor lamp) and spot-gro (65W, Sylvania) lamps. Cuscuta pentagona (Engelm.) seeds were scarified in concentrated sulfuric acid for 45 min, followed by 5-6 rinses with distilled water and dried. C. pentagona seeds were placed in potting medium at the base of four-week-old Arabidopsis seedlings and allowed to germinate and attach to hosts. The C. pentagona plants were allowed to grow and spread on host plants for an additional three weeks to generate a supply of uniform shoots for use in the experiment. Sections of C. pentagona shoot tip (~10 cm long) were placed on the floral stem of a fresh set of Arabidopsis plants. Parasite shoots coiled around the Arabidopsis stems and formed haustorial connections. Only tissues from plants that had established C. pentagona with at least two coils around healthy host stems and clear parasite growth were used in these studies

extract_protocol:
Small RNA was extracted from ~ 100 mg of host stem, interface, and parasite stem tissue using the mirPremier microRNA Isolation Kit (Sigma-Aldrich, St. Louis, MO, USA) according to the manufacturer’s protocol. Plant tissues were ground to a fine power in liquid nitrogen using mortar and pestle. Small RNA was analyzed using an Agilent small RNA Kit on a 2100 Bioanalyzer platform.
Illumia Tru-Seq Indexed small RNA kit

value: Stem

value: Haustorium


title: RNASEQ_mDCs_BK78_48h_infected


title: RNASEQ_mDCs_BK78_48h_uninfected


title: RNASEQ_mDCs_ZBK2_6h_uninfected


title: Interface between haustorial tissue and attached host stem, replicate 2

description:
small RNA
I2


title: RNASEQ_mDCs_BK78_24h_uninfected


title: RNASEQ_mDCs_BK78_12h_uninfected


title: RNASEQ_mDCs_BK68_12h_uninfected


title: RNASEQ_mDCs_BK78_24h_infected


title: RNASEQ_mDCs_ZBK2_12h_infected


title: RNASEQ_mDCs_BK78_6h_infected


title: RNASEQ_mDCs_BK78_12h_infected


title: RNASEQ_mDCs_ZBK4_24h_uninfected


title: RNASEQ_mDCs_BK68_12h_infected


title: RNASEQ_mDCs_BK68_6h_uninfected


title: RNASEQ_mDCs_ZBK4_48h_infected


title: RNASEQ_mDCs_BK68_6h_infected


title: RNASEQ_mDCs_HD-3

value: in vivo


title: RNASEQ_mDCs_HD-5


title: RNASEQ_mDCs_HD-4


title: RNASEQ_mDCs_HD-2


title: RNASEQ_mDCs_HD-1


title: RNASEQ_mDCs_Patient_B


title: RNASEQ_mDCs_Patient_A


title: Host Stem, replicate 2

description:
small RNA
HS2

source_name: Arabidopsis thaliana stem ~4cm above site of Cuscuta pentagona haustorial attachment

tag: ecotype


title: RNASEQ_mDCs_Patient_C


title: RNASEQ_mDCs_BK78_6h_uninfected


title: Host Stem, replicate 1

description:
small RNA
HS1


title: sur2.rep2

data_processing:
Sequencing Read Alignment: ChIP-seq libraries were sequenced on the Hi-Seq 2500 platforms. 36bp single end sequencing data was aligned to a reference mouse genome (mm9) downloaded from UCSC genome browser by using Bowtie. Unmapped and non-uniquely mapped reads were removed, and PCR duplicate reads were removed with Picard.
Peak Identification: H3K4me1 and H3K4me3 peaks were defined by using MACS2 with default parameters except following options “–m 5 50 –p 1e-5” for each biological replicate. After that we selected the best quality replicate for each modification based on number of identified peaks. From the best quality replicate, we only selected reproducible peaks at least two biological replicates. H3K4me1 and H3K4me3 peaks were merged together and classified into H3K4me1 peaks, H3K4me3 peaks, and common H3K4me1/me3 peaks. Chromatin regulator (CR) peaked regions were defined by comparing predefined H3K4me1/me3 peaked regions. Due to the limited quality of CR ChIP-seq results we first calculated input normalized CR ChIP-seq RPKMs on H3K4me1/me3 peaked regions for each biological replicate. If CR ChIP-seq RPKMs is enriched more than 1.5 fold compared to input RPKMs at least two biological replicates the h3k4me1/me3 peaked region was defined as occupied by the corresponding CR. H3K27ac ChIP-seq data was processed similarly as described in CR ChIP-seq data analysis except using 2-fold enrichment threshold when we define H3K27ac peaked regions. The density of histone modifications and CR binding was defined by taking average input normalized RPKMs of reproducible peaks across multiple biological replicates.
Clustering of CR-binding patterns: K-means clustering was performed for CR binding patterns according to poised enhancer and active enhancer regions. The peaks occupied by H3K4me1 but depleted by H3K4me3 were considered as enhancer regions after excluding upstream and downstream 2.5kb from RefSeq transcription start sites. Active enhancers were defined if the enhancer regions were overlapped with H3K27ac peaked regions (n=13,811). Otherwise the region was defined as poised enhancer regions (n=28,008). We performed K-mean clustering based on 13 CR binding patterns at active and poised enhancer regions separately, and generated 15 different clusters. Based on the enrichment of CR binding patterns in each cluster we manually assigned each cluster as ‘No CR bind’, ‘CR-specific bind’, and ‘Multiple CR bind’.
Identification of KMT2C/D dependent and independent H3K4me1 and H3K4me3 peaks: We defined KMT2C/D dependent and independent sites based on H3K4me1 levels between WT and KMT2C/D DKO cell lines. If the region is occupied by H3K4me1 more than 2-fold compared to input data and depleted more than 2-fold in KMT2C/D DKO cell lines the region was defined as a KMT2C/D dependent site, otherwise defined as a KMT2C/D independent site.
Analysis of CR-binding patterns in KMT2C/D DKO cell lines: To determine whether CR binding patterns are dependent on H3K4me1, we performed additional ChIP-seq for BRG1, SMC3, CHD1, PHF5A, MED23, PHRF1, and POUF51 for KMT2C/D DKO cell lines.  BRG1, SMC3, PHF5A, MED23, and PHRF1 were selected based on the strong association with H3K4me1 peaked regions in WT. POUF51 was selected as a negative control because POUF51 can be considered to bind as H3K4me1 independently.  Sequence read alignment was performed as described in WT CR ChIP-seq data. During downstream analysis of DKO cell lines we only considered CR ChIP-seq peaked regions defined in WT, resulting in 1939 peaks for BRG1, 20,412 peaks for CHD1, 12,225 peaks for POUF51, 2793 peaks for PHF5A, 7,425 peaks for PHRF1, 9,614 peaks for SMC3, and 6,712 peaks for MED23.
Genome_build: mm9

source_name: mESC

growth_protocol: mESCs were propagated on feeder cultures then passaged twice feeder free before crosslinking and harvesting.

extract_protocol:
Crosslinkedand sonicated chromatin was incubated with the ab indicated. Complex associated DNA was purified and sequenced.
Libraries were constructed as per manufacturers instructions for Illumina Tru-seq.

treatment_protocol: MLL3/4 DKO cells were obtained as referenceed in the manuscript.

tag: strain

tag: antibody catalog#

value: BD pharmingen


title: wstf.rep4

value: wstf

value: abcam


title: wstf.rep1


title: sur2.rep4


title: ssrp1.rep1

value: santa cruz


title: smc3.rep5


title: snf2h.rep1

value: active motif


title: smc3.rep4


title: snf2h.rep4


title: srsf1.rep1

value: invitrogen


title: srsf1.rep4


title: srsf2.rep1


title: sap18.rep1


title: srsf2.rep4


title: ruvbl2.rep1.

value: bethyl


title: sap18.rep3


title: smc3.rep1


title: WT_H3K4me2_ChIPSeq.rep2

source_name: embryonic stem cells

value: R1 ESC

value: wild-type

value: Active Motif


title: ruvbl1.rep3

value: upstate


title: phrf1_wt.rep2

value: MLL3/4 flox flox parental


title: ruvbl2.rep3


title: phrf1.rep4


title: phrf1_dko.rep1.filte

value: MLL3/4 double KO


title: phrf1_wt.rep1


title: ruvbl1.rep1


title: phf5a.rep2


title: phrf1_dko.rep2


title: phrf1.rep1


title: phf5a.rep1


title: phf5a_dko.rep3_new


title: med1.rep1


title: med12.rep2


title: med1.rep2


title: med12.rep1


title: input_wt.rep2


title: input.rep6.filter


title: input.rep7.


title: input_dko.rep3_new


title: input_dko.rep1


title: input_dko.rep2


title: h3k4me3_wt.rep3

value: millipore


title: h3k4me3.rep1


title: h3k4me3.rep2


title: phf5a_wt.rep3_new


title: h3k4me3_dko.rep1


title: h3k4me1_wt.rep2


title: h3k4me1_wt.rep3_new


title: h3k4me1.rep5


title: h3k4me1.rep3_new


title: h3k4me3_dko.rep3_new


title: h3k4me1_dko.rep2


title: h3k4me1_dko.rep1


title: h3k4me1.rep1


title: input_wt.rep1


title: input_wt.rep3_new


title: input.merge_rep1_2


title: h3k27ac.rep4


title: h3k27ac.rep1


title: h3k27ac_dko.rep3_new


title: h3k27ac_wt.rep1


title: brg1.rep1


title: brg1_wt.rep1


title: h3k4me3_wt.rep2


title: brg1_dko.rep1


title: h3k4me1_wt.rep1


title: brg1_dko.rep2


title: baz1a.rep3


title: baz1a.rep1


title: baf155.rep1.


title: Parasite Stem, replicate 2

description:
small RNA
PS2

organism: Cuscuta pentagona

source_name: Cuscuta pentagona stem ~4cm above site of haustorial attachment

value: Stem


title: h3k27ac_wt.rep3_new


title: Parasite Stem, replicate 1

description:
small RNA
PS1


title: P45-DH-1

status: Public on Dec 17 2017

city: Daejeon

first: Jong Hwan

last: Kim

address: 125 Gwahak-ro, Yuseong-gu

department: Genome structure research center

country: South Korea

institute: Korea Research Institute of Bioscience and Biotechnology

data_processing:
Paired-end sequencing (150 x 2) was performed using a Nextseq-500 (Illumina).
Reference genome sequence data from Homo sapiens were obtained from the University of California Santa Cruz Genome Browser Gateway (assembly ID: rn5). The reference genome index was built using SAMtools (v. 0.1.19) and the Bowtie2-build component of Bowtie2 (v. 2.1.0). Reads were mapped to the reference genome using Tophat2 (v. 2.0).
The number of fragments per kilobase per million mapped reads (fpkm) for each gene of 17,070 RefSeq (UCSC rn5) gene models was calculated using Cufflinks (v. 2.2.1).
Heat maps were constructed using Mev (v. 4.9.0). Statistical analyses and graph construction were performed using R (v. 3.3.0) and PYTHON (v. 2.7.6).
Genome_build: rn5
Supplementary_files_format_and_content: tab-delimited text files include FPKM values for each Sample.

organism: Rattus norvegicus

source_name: Dorsal hippocampus from P45

extract_protocol:
Total RNA was isolated from the infected cells using the RNeasy RNA extraction Mini-Kit (Qiagen) and the quality of the RNA was confirmed by agarose gel electrophoresis.
The sequencing library was prepared using the Illumina TruSeqStranded mRNA Sample Preparation Kits (Illumina).
The mRNA derived from total RNA using poly-T oligo-attached magnetic beads was fragmented and converted into cDNA. Adapters were ligated to the cDNA and the fragments were amplified by PCR.

value: Dorsal hippocampal tissue

tag: age

value: Dorsal hippocampus from P45 brain

value: Sprague-Dawley


title: P28-VH-1

source_name: Ventral hippocampus from P28

value: Ventral hippocampal tissue

value: Ventral hippocampus from P28 brain


title: P45-VH-1

source_name: Ventral hippocampus from P45

value: Ventral hippocampus from P45 brain


title: P28-VH-2


title: P28-DH-2

source_name: Dorsal hippocampus from P28

value: Dorsal hippocampus from P28 brain


title: P45-DH-2


title: P28-DH-1


title: brg1_wt.rep2

value: santa cruz


title: h3k27ac_dko.rep1

value: active motif


title: baf155.rep3


title: P14-DH-2

source_name: Dorsal hippocampus from P14

value: Dorsal hippocampus from P14 brain


title: P14-VH-2

source_name: Ventral hippocampus from P14

value: Ventral hippocampus from P14 brain


title: P14-DH-1


title: brg1.rep4.


title: P14-VH-1