title: Dome_dnmt1_mKD_H3K27ac_rep1

description: STAR ChIP-seq


title: Dome_dnmt1_mKD_H3K27ac_rep2

status: Public on Dec 29 2021

type: SRA

city: Beijing

first: Wei

last: Xie

address: Zhongguancun street, Haidian

department: THU-PKU Center for Life Sciences

country: China

institute: Tsinghua University

description: STAR ChIP-seq

library_source: genomic

data_processing:
All STEM-seq datasets were mapped to the danRer7 reference genome by Bismark (Krueger and Andrews, 2011). Reads were trimmed with cutadaptor (Martin, 2011) using parameters: --minimum-length 20 --pair-filter=any. Alignments were performed with the following parameters: -N 1 -X 600 --score_min L,0,-0.6. Multi-mapped reads and PCR duplicates were removed. bismark_methylation_extractor was used to calculate the DNA methylation level.
Total RNA-seq data were firstly processed using Trim Galore! with default parameters to trim the adapter-containing and low quality reads. The filtered data were then mapped to the zebrafish reference genome (danRer7) by STAR (version: STAR_2.5.3a_modified) (Dobin et al., 2013) with the following parameters: --outSAMstrandField intronMotif --outSAMattributes All --outSAMunmapped Within --outSAMattrIHstart 0 --outWigStrand Stranded --outFilterMultimapNmax 20 --twopassMode Basic. The gene expression level was normalized to fragments per kilobase of transcript per million mapped (FPKM) values using Cufflinks (version 2.2.1) (Trapnell et al., 2012).
The scRNA-seq data were processed with Cell Ranger 3.1 for genome alignment (danRer10), transcript counting, and gene-cell-barcode matrix generation. Before the downstream analysis, cells with unique detected genes lower than <2,000 and higher than 6,000 genes were discarded, and cells with high percentage of mitochondrial genes (>5%) were removed too. Subtypes of cells were identified with Seurat 3.0 through the integrating of control and mKD embryos at dome and shield stages with setting control embryos as reference. To make the data comparable samples, we performed SCTransform normalization separately for each dataset. To further reduce the bais caused by sequencing depth of scRNA-seq and percentage of mitochondrial genes, UMI variance and percent.mt were regressed out from SCTransform normalized data matrix by linear model with negative binomial distribution.
All ChIP-seq reads were aligned to the zebrafish reference genome (danRer7) using Bowtie2 (version 2.2.2) (Langmead and Salzberg, 2012) with the parameters –t –q –N 1 –L 25. All unmapped reads, non-uniquely mapped reads and PCR duplicates were removed. For downstream analysis, the read counts were normalized by computing the numbers of reads per kilobase of bin per million of reads sequenced (RPKM). To visualize the STAR ChIP-seq signal in the UCSC genome browser, each read was extended by 250 bp and the coverage for each base was counted. Replicates of STAR ChIP-seq were pooled for the downstream analysis.
The ATAC-seq data were mapped to the zebrafish reference genome (danRer7) using Bowtie2 (version 2.2.2) (Langmead and Salzberg, 2012) with the parameters –t –q –N 1 –L 25. All unmapped reads, non-uniquely mapped reads and PCR duplicates were removed. For downstream analysis, the read counts were normalized by computing the numbers of reads per kilobase of bin per million of reads sequenced (RPKM). To minimize the batch and cell type variation, RPKM values across whole genome were further Z-score normalized. To visualize the CUT&RUN signals in the UCSC genome browser, each read was extended by 250 bp and the coverage for each base was counted.
Genome_build: danRer7
Supplementary_files_format_and_content: Matrix for scRNA-seq data, gene expression table for total RNA-seq data, Bigwig and narrowPeak for ChIP-seq and ATAC-seq data

molecule: genomic DNA

organism: Danio rerio

source_name: embryo

growth_protocol: The wild-type AB strain was used in the experiments. The females after OMIS were fed with live adult brine shrimp thrice a day. All embryos were raised in Holtfreter’s solution at 28.5C and staged as described previously (Kimmel et al., 1995).

extract_protocol:
The ChIP procedure was based on a previously described method (Zhang et al., 2018a). Embryos were deyolked by repeatedly blowing with a 200 µl pipette and cell pellets were collected by spinning down at 5000 rpm for 5 min at 4℃. After centrifuge, cell pellet was lysed in 40 µl lysis buffer (0.5% NP-40, 0.5% Tween, 0.1% SDS and proteinase inhibitor) with pipetting up and down several times.
0.1 unit of MNase (Sigma, Cat N3755) was added for chromatin digestion at 37℃ for 5 min. The reaction was then terminated by adding 1 µl 0.5 M EGTA. IP sample was incubated with 1 µg H3K4me3 antibody (Homemade) (Zhang et al., 2016) and 2 µg H3K27me3 antibody (Active Motif, Cat 61017) overnight with rotation at 4℃. In the next day, the sample was incubated with 300 µg protein A or protein G dynabeads (Life technologies, Cat 10001D or 10003D) for 2hrs with rotation at 4℃. The beads were washed 5 times in 150 µl RIPA buffer and once in 150 µl LiCl buffer. After washing, spin tubes briefly and remove the supernatant. For each IP sample, resuspend beads with 27 µl ddH2O and 1 µl 10x Ex-Taq buffer (TaKaRa). 1 µl proteinase K (Roche, Cat 10910000) was then added and the mix was incubated at 55℃ for 90 min to elute DNA from beads. The supernatant was then transferred to a new tube and the proteinase K was inactivated at 72℃ for 40 min. 1 µl rSAP (NEB, Cat M0371) was then added to dephosphorylate 3’ end of DNA at 37℃ for 1hr. rSAP was inactivated at 65℃ for 10 min. The resulting sample was subjected to TELP library preparation as previously described (Peng et al., 2015). The amplified DNA was size-selected using AMPure Beads for 200-800 bp DNA fragments. All libraries were sequenced by Illumina Hi-Seq 1500 or 2500 or XTen platform according to manufacturer’s instruction.

treatment_protocol: Briefly, on the first day of OMIS (Wu et al., 2018b), adult females at 5-12 month old were anesthetized in 550 µg/ml tricaine (Sigma, Cat A5040) in a petri dish. Then the fish was placed on a damp sponge with specific buffer (5.4 mM KCl, 136.8 mM NaCl, 4.2 mM NaHCO3, 0.44 mM KH2PO4, 0.25 mM Na2HPO4, and 0.5% (wt/vol) BSA). A cut was made on one side of belly to expose the ovary. The diluted MOs were microinjected into each oocyte. Rhodamine B (Sigma, Cat R8881) was co-injected with MOs as a dye. After injection, the wound on the belly was sewed with a surgical sewing needle carefully and quickly. Once the operation was done, the female was transferred into fish water supplemented with 32 µg/ml tricaine, 10 unit/ml penicillin and 10 µg/ml streptomycin (HyClone, Cat SV30010). Then the fish was transferred to fish water containing gradually reduced concentrations of tricaine. In the evening of the second day, the female was paired with a wild type male. In the morning of the third day, the pair started to chase and lay fertilized eggs naturally. The injected oocyte-derived embryos were identified by co-injected dye (rhodamine B) at very early developmental stages. The injection doses of dnmt1 MO were 5 ng per oocyte in the same assay. MOs were dissolved in RNase-free water, and heated to 65°C for 11 min before microinjection.

tag: strain

value: AB

tag: genotype

value: WT

tag: developmental stage

value: Dome

tag: tissue

value: embryo

tag: treatment

value: Oocyte microinjection with Rhodamine B and dnmt1 MO at oogenesis III stage (GV)


title: Dome_ctrl_H3K27ac_rep2

description: STAR ChIP-seq

treatment_protocol: Briefly, on the first day of OMIS (Wu et al., 2018b), adult females at 5-12 month old were anesthetized in 550 µg/ml tricaine (Sigma, Cat A5040) in a petri dish. Then the fish was placed on a damp sponge with specific buffer (5.4 mM KCl, 136.8 mM NaCl, 4.2 mM NaHCO3, 0.44 mM KH2PO4, 0.25 mM Na2HPO4, and 0.5% (wt/vol) BSA). A cut was made on one side of belly to expose the ovary. The diluted MOs were microinjected into each oocyte. Rhodamine B (Sigma, Cat R8881) was co-injected with MOs as a dye. After injection, the wound on the belly was sewed with a surgical sewing needle carefully and quickly. Once the operation was done, the female was transferred into fish water supplemented with 32 µg/ml tricaine, 10 unit/ml penicillin and 10 µg/ml streptomycin (HyClone, Cat SV30010). Then the fish was transferred to fish water containing gradually reduced concentrations of tricaine. In the evening of the second day, the female was paired with a wild type male. In the morning of the third day, the pair started to chase and lay fertilized eggs naturally. The injected oocyte-derived embryos were identified by co-injected dye (rhodamine B) at very early developmental stages. The injection doses of standard control MO (cMO) were 5 ng per oocyte in the same assay. MOs were dissolved in RNase-free water, and heated to 65°C for 10 min before microinjection.

value: Oocyte microinjection with Rhodamine B and control MO at oogenesis III stage (GV)


title: 256_cell_mut_rescued_BS_seq

data_processing:
Library strategy: STEM-seq
All STEM-seq datasets were mapped to the danRer7 reference genome by Bismark (Krueger and Andrews, 2011). Reads were trimmed with cutadaptor (Martin, 2011) using parameters: --minimum-length 20 --pair-filter=any. Alignments were performed with the following parameters: -N 1 -X 600 --score_min L,0,-0.6. Multi-mapped reads and PCR duplicates were removed. bismark_methylation_extractor was used to calculate the DNA methylation level.
Total RNA-seq data were firstly processed using Trim Galore! with default parameters to trim the adapter-containing and low quality reads. The filtered data were then mapped to the zebrafish reference genome (danRer7) by STAR (version: STAR_2.5.3a_modified) (Dobin et al., 2013) with the following parameters: --outSAMstrandField intronMotif --outSAMattributes All --outSAMunmapped Within --outSAMattrIHstart 0 --outWigStrand Stranded --outFilterMultimapNmax 20 --twopassMode Basic. The gene expression level was normalized to fragments per kilobase of transcript per million mapped (FPKM) values using Cufflinks (version 2.2.1) (Trapnell et al., 2012).
The scRNA-seq data were processed with Cell Ranger 3.1 for genome alignment (danRer10), transcript counting, and gene-cell-barcode matrix generation. Before the downstream analysis, cells with unique detected genes lower than <2,000 and higher than 6,000 genes were discarded, and cells with high percentage of mitochondrial genes (>5%) were removed too. Subtypes of cells were identified with Seurat 3.0 through the integrating of control and mKD embryos at dome and shield stages with setting control embryos as reference. To make the data comparable samples, we performed SCTransform normalization separately for each dataset. To further reduce the bais caused by sequencing depth of scRNA-seq and percentage of mitochondrial genes, UMI variance and percent.mt were regressed out from SCTransform normalized data matrix by linear model with negative binomial distribution.
All ChIP-seq reads were aligned to the zebrafish reference genome (danRer7) using Bowtie2 (version 2.2.2) (Langmead and Salzberg, 2012) with the parameters –t –q –N 1 –L 25. All unmapped reads, non-uniquely mapped reads and PCR duplicates were removed. For downstream analysis, the read counts were normalized by computing the numbers of reads per kilobase of bin per million of reads sequenced (RPKM). To visualize the STAR ChIP-seq signal in the UCSC genome browser, each read was extended by 250 bp and the coverage for each base was counted. Replicates of STAR ChIP-seq were pooled for the downstream analysis.
The ATAC-seq data were mapped to the zebrafish reference genome (danRer7) using Bowtie2 (version 2.2.2) (Langmead and Salzberg, 2012) with the parameters –t –q –N 1 –L 25. All unmapped reads, non-uniquely mapped reads and PCR duplicates were removed. For downstream analysis, the read counts were normalized by computing the numbers of reads per kilobase of bin per million of reads sequenced (RPKM). To minimize the batch and cell type variation, RPKM values across whole genome were further Z-score normalized. To visualize the CUT&RUN signals in the UCSC genome browser, each read was extended by 250 bp and the coverage for each base was counted.
Genome_build: danRer7
Supplementary_files_format_and_content: Matrix for scRNA-seq data, gene expression table for total RNA-seq data, Bigwig and narrowPeak for ChIP-seq and ATAC-seq data

growth_protocol: The wild-type AB strain was used in the experiments. The females after OMIS were fed with live adult brine shrimp thrice a day. All embryos were raised in Holtfreter’s solution at 28.5C and staged as described previously (Kimmel et al., 1998).

extract_protocol:
The deyolked embryos were lysed with 20 µl lysis buffer (10 mM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.1 mM EDTA, pH 8.0, 0.5% NP-40) and 2 µl protease K (Roche, Cat 10910000) for at least 3hrs at 57℃.
After heat-inactivation, spike-in λ-DNA (Promega, Cat D150A) was added at a mass ratio of 1/200. Bisulfite conversion was performed with the EpiTect Fast Bisulfite Conversion Kit (Qiagen, Cat 59824). The converted DNA was subjected to column purification and desulfonation on MinElute DNA spin columns (Qiagen, Cat 59824) with carrier RNA (Qiagen, Cat 59824) according to the manufacturer’s instructions. The purified DNA was eluted in 30 µl of elution buffer and ready for TELP library preparation (Peng et al., 2018).

value: Oocyte microinjection with Rhodamine B, dnmt1 MO and mut dnmt1 mRNA at oogenesis III stage (GV)


title: 256_cell_WT_rescued_BS_seq

growth_protocol: The wild-type AB strain was used in the experiments. The females after OMIS were fed with live adult brine shrimp thrice a day. All embryos were raised in Holtfreter’s solution at 28.5C and staged as described previously (Kimmel et al., 1997).

extract_protocol:
The deyolked embryos were lysed with 20 µl lysis buffer (10 mM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.1 mM EDTA, pH 8.0, 0.5% NP-40) and 2 µl protease K (Roche, Cat 10910000) for at least 3hrs at 56℃.
After heat-inactivation, spike-in λ-DNA (Promega, Cat D150A) was added at a mass ratio of 1/200. Bisulfite conversion was performed with the EpiTect Fast Bisulfite Conversion Kit (Qiagen, Cat 59824). The converted DNA was subjected to column purification and desulfonation on MinElute DNA spin columns (Qiagen, Cat 59824) with carrier RNA (Qiagen, Cat 59824) according to the manufacturer’s instructions. The purified DNA was eluted in 30 µl of elution buffer and ready for TELP library preparation (Peng et al., 2017).

value: Oocyte microinjection with Rhodamine B, dnmt1 MO and WT dnmt1 mRNA at oogenesis III stage (GV)


title: Dome_dnmt1_mKD_H3K4me3_rep1

data_processing:
Library strategy: CUT&RUN
All STEM-seq datasets were mapped to the danRer7 reference genome by Bismark (Krueger and Andrews, 2011). Reads were trimmed with cutadaptor (Martin, 2011) using parameters: --minimum-length 20 --pair-filter=any. Alignments were performed with the following parameters: -N 1 -X 600 --score_min L,0,-0.6. Multi-mapped reads and PCR duplicates were removed. bismark_methylation_extractor was used to calculate the DNA methylation level.
Total RNA-seq data were firstly processed using Trim Galore! with default parameters to trim the adapter-containing and low quality reads. The filtered data were then mapped to the zebrafish reference genome (danRer7) by STAR (version: STAR_2.5.3a_modified) (Dobin et al., 2013) with the following parameters: --outSAMstrandField intronMotif --outSAMattributes All --outSAMunmapped Within --outSAMattrIHstart 0 --outWigStrand Stranded --outFilterMultimapNmax 20 --twopassMode Basic. The gene expression level was normalized to fragments per kilobase of transcript per million mapped (FPKM) values using Cufflinks (version 2.2.1) (Trapnell et al., 2012).
The scRNA-seq data were processed with Cell Ranger 3.1 for genome alignment (danRer10), transcript counting, and gene-cell-barcode matrix generation. Before the downstream analysis, cells with unique detected genes lower than <2,000 and higher than 6,000 genes were discarded, and cells with high percentage of mitochondrial genes (>5%) were removed too. Subtypes of cells were identified with Seurat 3.0 through the integrating of control and mKD embryos at dome and shield stages with setting control embryos as reference. To make the data comparable samples, we performed SCTransform normalization separately for each dataset. To further reduce the bais caused by sequencing depth of scRNA-seq and percentage of mitochondrial genes, UMI variance and percent.mt were regressed out from SCTransform normalized data matrix by linear model with negative binomial distribution.
All ChIP-seq reads were aligned to the zebrafish reference genome (danRer7) using Bowtie2 (version 2.2.2) (Langmead and Salzberg, 2012) with the parameters –t –q –N 1 –L 25. All unmapped reads, non-uniquely mapped reads and PCR duplicates were removed. For downstream analysis, the read counts were normalized by computing the numbers of reads per kilobase of bin per million of reads sequenced (RPKM). To visualize the STAR ChIP-seq signal in the UCSC genome browser, each read was extended by 250 bp and the coverage for each base was counted. Replicates of STAR ChIP-seq were pooled for the downstream analysis.
The ATAC-seq data were mapped to the zebrafish reference genome (danRer7) using Bowtie2 (version 2.2.2) (Langmead and Salzberg, 2012) with the parameters –t –q –N 1 –L 25. All unmapped reads, non-uniquely mapped reads and PCR duplicates were removed. For downstream analysis, the read counts were normalized by computing the numbers of reads per kilobase of bin per million of reads sequenced (RPKM). To minimize the batch and cell type variation, RPKM values across whole genome were further Z-score normalized. To visualize the CUT&RUN signals in the UCSC genome browser, each read was extended by 250 bp and the coverage for each base was counted.
Genome_build: danRer7
Supplementary_files_format_and_content: Matrix for scRNA-seq data, gene expression table for total RNA-seq data, Bigwig and narrowPeak for ChIP-seq and ATAC-seq data

extract_protocol:
CUT&RUN was conducted based on previously published protocol (Xia et al., 2019) with modifications in cell permeation to adapt it for zebrafish embryos. Embryos were deyolked by tweezers manually and transferred into 1.5 mL conventional, non-low-binding tube (Axygen). Then tubes were flicked several times to disperse cells in embryos, and resuspended by 60 ul washing buffer (20 mM HEPES-KOH, pH = 7.5; 150 mM NaCl; 0.5 mM Spermidine and Roche complete protease inhibitor). 10 µl Concanavalin-coated magnetic beads (Polyscience, Cat 86057) for each sample were gently washed twice, resuspended by binding buffer (20 mM HEPES-KOH, pH = 7.5; 10 mM KCl; 1 mM CaCl2; 1 mM MnCl2), and added carefully to the cells.
The cells with beads were incubated at 23℃ for 30 min on Thermomixer (Eppendorf) at 400 rpm, then held at magnetic stand to exclude buffer, and resuspended by 75 µl antibody buffer (washing buffer supplied with 0.02% digitonin and 2 mM EDTA, freshly made) with H3K4me3 (validated homemade) (Zhang et al., 2016) antibody, or H3K27me3 antibody (Active Motif, Cat 61017), or H2AK119ub antibody (CST, Cat 8240s) diluted at ratio of 1:100. Then the samples were incubated at 4℃ on Thermomixer overnight at 400 rpm. On the second day, the samples were washed by digitonin-washing buffer several times on magnetic stand, and resuspended with 50 µl digitonin-washing buffer supplied with 700 ng/ml pA-MNase, which is kindly provided by Dr. Steven Henikoff, and incubated at 4℃ on Thermomixer for 3hrs at 400 rpm. After that, the cells were washed by digitonin-washing buffer on magnetic stand, and resuspended by 100 µl digitonin-washing buffer on ice for at least 2 min. Targeted region digestion was activated by adding 2 µl 100 mM CaCl2 for 30 min in ice, then stopped by 100 µl 2 X stop buffer (340 mM NaCl; 20 mM EDTA, pH = 8.0; 4 mM EGTA, pH = 8.0; 50 µg/ml RNase; 100 µg/ml glycogen; 0.02% digitonin suppled with spike-in DNA) and fully vortexed. To release fragments, the samples were incubated at 37℃ on Thermomixer at 400 rpm for 20 min. Then the supernatants were purified by phenol chloroform and ethanol purification, and subjected to Tru-seq library construction using NEBNext Ultra II DNA Library Prep kit (NEB, Cat E7645S) as standard protocols. The amplified DNA was size-selected using AMPure Beads for 200-800 bp DNA fragments. All libraries were sequenced by Illumina Hi-Seq 1500 or 2500 or XTen platform according to manufacturer’s instruction.


title: Dome_dnmt1_mKD_H3K4me3_rep2


title: Control 635, islet miRNA

type: RNA

city: Wallace Wurth Building, Sydney

first: Margaret

middle: J

last: Morris

state: NSW

address: University of New South Wales

department: School of Medical Sciences

country: Australia

institute: University of New South Wales

description: miRNA gene expression of islets from female offspring of fathers fed standard chow.

hyb_protocol: Cy3-labelled miRNA was added to a hybridization cocktail containing 10X GE Blocking agent, 2X Hi-RPM Hybridisation buffer and Hyb spikes according to the manufacturer’s instructions (Agilent). This whole hybridization mixture was denatured at 100°C for 5 minutes, cooled on ice for 5 minutes and hybridized to Agilent Whole Rat miRNA Microarrays (AMADID: 019159 for 613, 639, 615, 603, 607, 653 and AMADID: 031189 for 640, 652, 635) for 20 hours at 55°C in a rotating (20 rpm) Agilent hybridization oven. After hybridization, microarrays were washed 5 minute at room temperature with GE Wash Buffer 1 (Agilent) and 5 minute with 37°C GE Wash buffer 2 (Agilent).

scan_protocol: Slides were scanned immediately after washing on the Agilent DNA Microarray Scanner (G2505B) using one colour scan setting for 8x15K array slides (Scan area Scan Area 61x21.6 mm, Scan resolution 5um, Dye channel is set to Green and Green PMT is set to 100%). The scanned images were analyzed with Feature Extraction Software v10.7.3.1 (Agilent) using protocol ffmiRNA107_sep09 to obtain background subtracted and spatially detrended.

data_processing: Raw data on each array were normalized independently using RMA (Lopez-Romero P, Gonzalez MA, Callejas S, Dopazo A, and Irizarry RA. Processing of Agilent microRNA array data. BMC Res Notes 3: 18, 2010.), implemented in the Partek (Partek Genome Suite v6.4) miRNA expression workflow. Control probes (n=22) and miRNAs detected on none of the arrays using the IsGeneDetected flag were filtered out. Processed signal intensities are presented in the GeneView.txt file. Differential gene expression between HFD vs. Control were detected using ANOVA.

molecule: total RNA

organism: Rattus norvegicus

source_name: islet from female offspring of fathers fed on control chow

label_protocol: Cyanine-3 (Cy3) labeled miRNA was prepared from 100 ng total RNA using the miRNA Microarray System with miRNA Complete Labeling and Hyb Kit (Agilent) according to the manufacturer's instructions.

growth_protocol: At 15 weeks of age, fathers were mated with normal females consuming chow to generate the F1 offspring.

extract_protocol: Total RNA was extracted using the miRNeasy kit (Qiagen) according to the manufacturer's instructions. RNA was quantified using a NanoDrop-1000 spectrophotometer, and quality was monitored with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA).

treatment_protocol: Fathers fed on HFD vs. control were mated with females on normal chow. The female offspring's islet transcriptomics were analyzed through microarray analysis.

value: Sprague Dawley

tag: gender

value: female

value: islets

value: father fed standard diet


title: Control 652, islet miRNA


title: HFD 640, islet miRNA

description: miRNA gene expression of islets from female offspring of fathers fed high-fat chow.

source_name: islet from female offspring of fathers fed on high-fat diet

value: father fed high-fat diet


title: HFD 624, fat miRNA

description: miRNA gene expression of fat from female offspring of fathers fed high-fat chow.

hyb_protocol: Cy3-labelled miRNA was added to a hybridization cocktail containing 10X GE Blocking agent, 2X Hi-RPM Hybridisation buffer and Hyb spikes according to the manufacturer’s instructions (Agilent). This whole hybridization mixture was denatured at 100°C for 5 minutes, cooled on ice for 5 minutes and hybridized to Agilent Whole Rat miRNA Microarrays (AMADID: 031189) for 20 hours at 55°C in a rotating (20 rpm) Agilent hybridization oven. After hybridization, microarrays were washed 5 minute at room temperature with GE Wash Buffer 1 (Agilent) and 5 minute with 37°C GE Wash buffer 2 (Agilent).

source_name: fat from female offspring of fathers fed on high-fat diet

treatment_protocol: Fathers fed on HFD vs. control were mated with females on normal chow. The female offspring's fat transcriptomics were analyzed through microarray analysis.

value: fat


title: HFD 663, fat miRNA


title: Dome_dnmt1_mKD_H2AK119ub_rep1


title: HFD 629, fat miRNA


title: Shield_ctrl_H3K27me3_rep1

value: Shield


title: Dome_dnmt1_mKD_H3K27me3_rep2


title: Dome_dnmt1_mKD_H3K27me3_rep1


title: Dome_ctrl_H3K27ac_rep1

description: STAR ChIP-seq


title: Dome_dnmt1_mKD_H3K4me1_rep1


title: Dome_dnmt1_mKD_scRNA_seq_rep1

description:
single cell RNA
scRNA-seq

library_source: transcriptomic

extract_protocol:
Cell dissociation protocol was based on a previously described method (Farrell et al., 2018) with modifications to adapt it for 10x Genomics platform. Briefly, dnmt1 mKD and control embryos were collected 20 min after fertilization and cultured as mentioned before. Then 15 embryos at dome or shield stages for each sample were transferred into plastic Petri dishes that had previously been coated with 2% agarose and soaked with DMEM/F12 media (Gibco/Life Technologies, Cat 11330032) at least 2hrs. Next, embryos at desired stages were dechorionated and deyolked manually by forceps and transferred to a 1.5 ml Eppendorf tube with 50 µl DMEM/F12 media. Dissections were performed for up 15 min. The volume of DMEM/F12 meida containing embryos was adjusted to 200 µl, then cells were mechanically dissociated by flicking the tube 30 times and pipetting mixture 10 times through a 200 µl tip. The volume was adjusted to 1 ml with PBS containing 1.0% BSA, and spun to pellet cells at 300 g for 30s. The supernatant was removed and cells were resuspended in 80 µl of PBS containing 0.1% BSA and 20% Optiprep (StemCell, Cat 07820), aiming for a concentration above 100 cells/µl. Cells were then passed through a cell sieve (100 µm for dome stage and 70 µm for shield stage).
Single cell RNA-seq library was performed with Chromium Next GEM Single Cell kit (10x Genomics, Cat PN-1000121) based on standard protocol. All libraries were sequenced by Illumina Hi-Seq 1500 or 2500 or XTen platform according to manufacturer’s instruction.


title: HFD 619, fat miRNA


title: Control 658, fat miRNA

description: miRNA gene expression of fat from female offspring of fathers fed standard chow.

source_name: fat from female offspring of fathers fed on control chow


title: Dome_ctrl_scRNA_seq_rep1

description:
single cell RNA
scRNA-seq


title: Control 662, fat miRNA


title: Control 656, fat miRNA


title: Dome_ctrl_total_RNA_seq_rep2

description: Total RNA-seq

extract_protocol:
The embryos were dechorionated manually by tweezers and transferred into 750 µl Trizol (Invitrogen, Cat 15596018). About 10 fresh embryos were transferred into Trizol and vortexed until no visible particles. 150 µl chloroform (Amresco, Cat 0757) was added and mixed thoroughly. The mixture was then transferred into phasemaker tube (Invitrogen, Cat A33248) and spun at 14,000 rpm for 15 min. Next, the top phase was taken out from the tube, added 1 µl LPA (Sigma, Cat 56575) and mixed well using pipettes. Then, RNA was precipitated by adding 750 µl isopropanol (Sigma, Cat 59304) at -20℃ overnight. At next day, the tube was spun at 14,000 rpm for 30 min and supernatant was removed. The pellet was washed with freshly 70% ethanol, re-suspend in 20 µl RNase-free water and stored at -80℃ for later usage.
NEBNext rRNA Depletion Kit (NEB, Cat E6310S) was used to deplete ribosomal RNA according to the manufacture’s instruction. Briefly, rRNA were hybridized with probes and digested with RNase H, then excess probes were digested with DNase I. After that, NEBNext RNA sample purification beads were used to purify rRNA depleted RNA. Purified RNA was fragmented before cDNA synthesis at 95℃ for 8 min. Double-stranded cDNA was synthesized with NEB Next first-strand (NEB, Cat E7771S) and second-strand synthesis modules (NEB, Cat E7550S), then purified with Ampure XP beads (Beckman, Cat A63882). Synthesized cDNA was subjected to library preparation with NEBNext Ultr II DNA Library Prep Kit (NEB, Cat E7645S). DNA was end-repaired, adenylated, and ligated to TruSeq sequencing adaptors. DNA were amplified using KAPA HF HotStart ReadyMix (KAPABiosystem, Cat RR2602). The amplified DNA was size-selected using Ampure XP beads for 200-500 bp DNA fragments. All libraries were sequenced by Illumina Hi-Seq 1500 or 2500 or XTen platform according to manufacturer’s instruction.


title: Control 627, fat miRNA


title: Dome_ctrl_total_RNA_seq_rep1

description: Total RNA-seq


title: Control 631, fat miRNA


title: Control 622, fat miRNA


title: HFD 660, fat miRNA


title: 5dpf_tail_dnmt1_zKO_BS_seq

description: STEM-seq

source_name: larva

growth_protocol: The dnmt1 mutant TL strain was used in the experiments. The adult fish were fed with live adult brine shrimp in the morning and evening. All embryos were raised in Holtfreter’s solution at 28.5C and staged as described previously (Kimmel et al., 1995).

extract_protocol:
The deyolked oocytes were lysed with 20 µl lysis buffer (10 mM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.1 mM EDTA, pH 8.0, 0.5% NP-40) and 2 µl protease K (Roche, Cat 10910000) for at least 3hrs at 55℃.
After heat-inactivation, spike-in λ-DNA (Promega, Cat D150A) was added at a mass ratio of 1/200. Bisulfite conversion was performed with the EpiTect Fast Bisulfite Conversion Kit (Qiagen, Cat 59824). The converted DNA was subjected to column purification and desulfonation on MinElute DNA spin columns (Qiagen, Cat 59824) with carrier RNA (Qiagen, Cat 59824) according to the manufacturer’s instructions. The purified DNA was eluted in 30 µl of elution buffer and ready for TELP library preparation (Peng et al., 2015).

treatment_protocol: Embryos at 5 days post fertilization were euthanized with tricaine, and tail was dissected carefully by tweezers. After brief grinding, tissues froze at -80℃ for later usage.

value: TL

value: larva tail

value: untreated


title: 5dpf_tail_WT_BS_seq

description: STEM-seq

growth_protocol: The wild-type TL strain was used in the experiments. The adult fish were fed with live adult brine shrimp in the morning and evening. All embryos were raised in Holtfreter’s solution at 28.5C and staged as described previously (Kimmel et al., 1995).

value: WT


title: 5dpf_head_WT_BS_seq

description: STEM-seq

treatment_protocol: Embryos at 5 days post fertilization were euthanized with tricaine, and head was dissected carefully by tweezers. After brief grinding, tissues froze at -80℃ for later usage.

value: larva head


title: RbKO_100 J/m2 UVC_Replicate2

city: Stanford

first: Ashby

last: Morrison

state: CA

address: 371 Serra Mall Gilbert Bldg, Room 326

department: Biology

country: USA

institute: Stanford University

data_processing:
Library strategy: CPD-Seq
ChIP-seq reads were aligned to the hg19 genome assembly using bwa
Reads were filttered by mapping quality and deduplicated.
Signal tracks were generated from reads by calculating ChIP fold-enrichment over input.
Genome_build: hg19
Supplementary_files_format_and_content: bigwig file was generated using ENCODE pipeline; score represents log2 fold change (IP/Input)

organism: Homo sapiens

source_name: Human fetal lung fibroblast

growth_protocol: Cells were grown in 37°C and 5% CO2 in DMEM with high glucose, 15%(v/v) FBS and 1% Pen/Strep.

extract_protocol:
Wildtype and RB1 KO IMR-90 cells were grown to full confluency in order to eliminate cell cycle effects on UV lesion acquisition. CPD immunoprecipitation was performed as previously described (García‐Nieto et al, 2017). Cells were irradiated with 100J/m2 UVC and were immediately lysed with 1% SDS buffer. Cell lysates were treated with RNase A  and proteinase K , followed by DNA precipitation with ethanol/sodium acetate. Purified DNA was then sonicated by a Bioruptor (Diagenode), and heated to 99C to denature.  The resulting single-stranded fragments were incubated with anti-CPD antibody (Cosmos Bio, clone TDM-2). Immunoprecipitated DNA fragments were repaired by CPD and 6-4PP photolyases (Selby & Sancar, 2012).
Libraries were prepped for Illumina sequencing using second‐strand DNA synthesis, end repair, and adapter ligation with NEBNext Directional Second‐Strand Synthesis (cat. no. E7550), and ChIP‐seq Library Prep Master Mix for Illumina (cat. no. E6240) kits

treatment_protocol: RB1 was knocked out with CRISPR-Cas9.

value: RB1 knockout

value: 100 J/m2 UVC

tag: cell line


title: 5dpf_head_dnmt1_zKO_BS_seq

description: STEM-seq


title: miRNA_MGC-803_DDP_rep1

city: Guangzhou

first: Shu-Zhong

last: Cui

state: Guangdong

address: hengzhigang road NO78, yuexiu region

department: Department of Gastrointestinal Surgery II

institute: Affiliated Cancer Hospital & Institute of Guangzhou Medical University

description: miRNA

data_processing:
Data generated from Illumina HiSeq TM were transformed into sequence reads by base calling.
The raw sequencing reads were filtered and cleaned by Cutadapt, whereas FastQC was conducted to verify the sequence quality. The clean reads were mapped to the reference genome using HISAT2 (v2.0.4) for transcripts and Bowite (v2.2.5) for miRNA as described.
The lncRNA and mRNA expression levels of each sample are calculated by StringTie (v.2.1.2) with the fragments per kilobase of exon model per million mapped fragments (FPKM) values. The small RNA expression level is calculated by FeatureCounts (v1.6.1) with transcripts per kilobase million (TPM).
Genome_build: Hg38
Supplementary_files_format_and_content: text file including FPKM for every lncRNA and every mRNA expression of each sample.
Supplementary_files_format_and_content: text file including TPM for every miRNA expression of each sample.

source_name: Stomach

growth_protocol: The human GC cell line MGC-803 was cultured in RPMI-1640 supplemented with 10% fetal bovine serum (FBS) at 37℃ with an atmosphere of 5% CO2.

extract_protocol:
Total RNA from MGC-803 and MGC-803/DDP cells was isolated using TRIzol reagent. RNA purity and concentration were measured by the NanoPhotometer spectrophotometer and Qubit RNA Assay Kit in Qubit® 2.0 Flurometer. Approximately 3 μg total RNA was treated by Epicentre Ribo-ZeroTM rRNA Removal Kit (Epicentre, USA) to remove ribosomal RNA, then sequencing libraries were generated using the rRNA-depleted RNA by NEBNext® UltraTM Directional RNA libarary Prep Kit for Illumina® (NEB, USA). Total RNA (1 μg) was used as input material for the small RNA library. Sequencing libraries were generated using NEBNext® Multiplex Small RNA Library Prep Set for Illumina® (NEB, USA) following manufacture’s recommendations and index codes were added to attribute sequences to each sample.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: MGC-803/DDP cells were continuously exposed to increasing concentrations of cisplatin and cultured in drug free madia for at least two passages before each experiment.

tag: cell type

value: gastric cancer cell

tag: phenotype

value: Cisplatin resistant


title: miRNA_MGC-803_rep2

description: miRNA

value: Cisplatin sensitive


title: miRNA_MGC-803_DDP_rep2

description: miRNA


title: Shield_dnmt1_zKO_BS_seq

description: STEM-seq

treatment_protocol: Embryos at shield stage were dissected carefully by tweezers into two parts. One part was identified by PCR genotyping in order to choose dnmt1-/- embryos, and the other part was froze at -80℃ for later BS-seq.

value: embryo


title: RbKO_100 J/m2 UVC_Replicate1


title: Shield_WT_BS_seq

description: STEM-seq

treatment_protocol: Embryos at shield stage were dissected carefully by tweezers into two parts. One part was identified by PCR genotyping in order to choose dnmt1+/+ embryos, and the other part was froze at -80℃ for later BS-seq.


title: Control 664, fat miRNA

value: Sprague Dawley

value: female


title: HFD 620, fat miRNA


title: 256_cell_dnmt1_zKD_BS_seq

description: STEM-seq

growth_protocol: The wild-type AB strain was used in the experiments. The adult fish were fed with live adult brine shrimp in the morning and evening. All embryos were raised in Holtfreter’s solution at 28.5C and staged as described previously (Kimmel et al., 1995).

treatment_protocol: dnmt1 MO was injected into naturally fertilized 1-cell stage embryos, according to commonly used zebrafish microinjection protocol (Yuan and Sun, 2009). After injection, embryos were grown in fresh Holtfreter solution (0.05 g/L KCl, 0.1 g/L CaCl2, 0.025 g/L NaHCO3, 3.5 g/L NaCl, pH 7.0) at 28.5℃ and were staged according to standard morphological criteria (Kimmel et al., 1995).

value: AB

value: 256 cell

value: Zygote microinjection with dnmt1 MO


title: Shield_dnmt1_zKD_BS_seq

description: STEM-seq

value: Shield


title: 256_cell_zKD_ctrl_BS_seq

description: STEM-seq

treatment_protocol: Standard control MO was injected into naturally fertilized 1-cell stage embryos, according to commonly used zebrafish microinjection protocol (Yuan and Sun, 2009). After injection, embryos were grown in fresh Holtfreter solution (0.05 g/L KCl, 0.1 g/L CaCl2, 0.025 g/L NaHCO3, 3.5 g/L NaCl, pH 7.0) at 28.5℃ and were staged according to standard morphological criteria (Kimmel et al., 1995).

value: Zygote microinjection with control MO


title: Shield_zKD_ctrl_BS_seq

description: STEM-seq


title: Dome_dnmt1_mKD_BS_seq

description: STEM-seq

value: Dome

value: Oocyte microinjection with Rhodamine B and dnmt1 MO at oogenesis III stage (GV)


title: Shield_mKD_ctrl_BS_seq

description: STEM-seq

value: WT

value: Oocyte microinjection with Rhodamine B and control MO at oogenesis III stage (GV)


title: IPISRC020T1_rna_treg_S35

city: San Francisco

first: Bushra

last: Samad

address: 505 Parnassus Ave

institute: USCF Immunoprofiler

data_processing:
RNAseq reads were first aligned to reference of rRNA and mitochondrial rRNA using BWA-mem
The remaining reads were aligned to the Ensembl GRCh38.85 transcriptome build using STAR
Genome_build: GRCh38

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a primary Sarcoma tumor specimen

extract_protocol:
The mRNA was isolated via DinaBead Direct, then converted into amplified   cDNA using Tecan Ovation RNA-Seq System V2 kit, following the manufacturer protocol.
The dsDNA went through tagmentation, amplification and clean up with   AMPure XP beads steps, using the Illumina Nextera XT DNA Library Prep Kit. Quality control analysis was performed on the resulting pooled libraries with the Agilent Bioanalyzer HS DNA chip to assess fragment size distribution and concentration

value: arm

tag: sorted compartment

value: treg

tag: disease

value: Sarcoma


title: 256_cell_mKD_ctrl_BS_seq

description: STEM-seq


title: 256_cell_dnmt1_mKD_BS_seq

description: STEM-seq


title: IPISRC016T1_rna_stroma_S56

source_name: CD45- CD90+ CD44+ stromal cells  sorted by flow cytometry from a primary Sarcoma tumor specimen

value: stroma


title: IPISRC019T1_rna_live_S5

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a primary Sarcoma tumor specimen

value: live


title: SRC015_T1_rna_stroma_S22

value: abdomen


title: miRNA_MGC-803_rep1

description: miRNA

value: gastric cancer cell

value: Cisplatin sensitive


title: SRC015_T1_rna_live_S34


title: Oocyte_mKD_ctrl_BS_seq_rep2

description: STEM-seq

source_name: oocyte

value: AB

value: Oocyte

value: oocyte


title: Oocyte_mKD_ctrl_BS_seq_rep1

description: STEM-seq


title: SRC014_T1_rna_stroma_S54


title: SRC014_T1_rna_tumor_S24

source_name: CD45- CD90- CD44- Tumor cells sorted by flow cytometry from a Primary Sarcoma tumor specimen

value: tumor


title: SRC014_T1_rna_live_S29


title: SRC014_T1_rna_treg_S9


title: non_Diabetes_non_TB_73 [PUN_B_99_10363]

city: Salvador

first: Artur

middle: Trancoso Lopo

last: Queiroz

address: Rua Waldemar Falcão, 121

country: Brazil

institute: Instituto Gonçalo Moniz

data_processing:
bcl2fastq software (Illumina Inc.)
Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence with trimmomatic, then mapped to transcriptome GRCh38 version using salmon.
Genome_build: GRCh38
Supplementary_files_format_and_content: *.txt: Tab-delimited text files include counts values for each Sample.
Supplementary_files_format_and_content: count_data.csv: Comma-separated matrix table with raw gene counts for every gene and every sample.

source_name: whole blood

extract_protocol:
RNA was isolated using the RNeasy Serum/Plasma Advanced Kit (50) (cat# 217204) according to the manufacturers’ recommendation (QIAGEN).
The library preparation was done using the QIAseq RNA Library Kit (QIAGEN). A total of 5ul total RNA was converted into RNA NGS libraries. Adapters containing UMIs were ligated to the RNA. Then RNA was converted to cDNA. The cDNA was amplified using PCR (22 cycles) and during the PCR indices were added. After PCR, the samples were purified. Library preparation QC was performed using either Bioanalyzer 2100 (Agilent) or TapeStation 4200 (Agilent).

tag: site

value: Pune, India

tag: timepoint

tag: disease state

value: non Diabetes

tag: tb status

value: non TB

tag: Sex

value: Male

value: whole blood

tag: donor id


title: non_Diabetes_non_TB_80 [PUN_B_99_10443]


title: non_Diabetes_non_TB_77 [PUN_B_99_10415]

value: Female


title: non_Diabetes_non_TB_76 [PUN_B_99_10410]


title: non_Diabetes_non_TB_75 [PUN_B_99_10400]


title: Diabetes_non_TB_79 [PUN_B_99_10440_03]

value: Diabetes


title: SRC013T1_St_S67

value: leg

value: Sarcoma


title: non_Diabetes_non_TB_72 [PUN_B_99_10358]


title: SRC013T1_My_S52

source_name: Tumor assocaited HLA DR+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Sarcoma tumor specimen

value: myeloid


title: SRC013T1_Li_S17

value: live


title: non_Diabetes_non_TB_70 [PUN_B_99_10325]


title: SRC012T1_Li_S37


title: non_Diabetes_non_TB_71 [PUN_B_99_10328]


title: IPISRC014_T1_rna_myeloid_S22

value: arm


title: SRC012T1_Tu_S72


title: Diabetes_non_TB_78 [PUN_B_99_10440_02]


title: non_Diabetes_non_TB_65 [PUN_B_99_10227]


title: non_Diabetes_non_TB_69 [PUN_B_99_10318]


title: Diabetes_non_TB_67 [PUN_B_99_10268]


title: Diabetes_non_TB_68 [PUN_B_99_10305]


title: non_Diabetes_non_TB_64 [PUN_B_99_10219]


title: non_Diabetes_non_TB_66 [PUN_B_99_10253]


title: SRC012T1_Tr_S23

value: treg


title: non_Diabetes_non_TB_74 [PUN_B_99_10366]


title: SRC012T1_My_S32

source_name: Tumor assocaited HLA DR+ CD11b+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Sarcoma tumor specimen


title: SRC011T1_Tu_S31

value: liver


title: SRC013T1_Tr_S25


title: Diabetes_non_TB_62 [PUN_B_99_10198]


title: Diabetes_non_TB_61 [PUN_B_99_10153]


title: non_Diabetes_non_TB_55 [PUN_B_99_10104]


title: non_Diabetes_non_TB_53 [PUN_B_99_10066]


title: SRC011T1_My_S7


title: non_Diabetes_non_TB_59 [PUN_B_99_10139]


title: SRC011T1_Li_S19


title: SRC009T1_Tc_S83

source_name: Tumor assocaited conventional T cell both CD4+ and CD8+ sorted by flow cytometry from a primary Sarcoma tumor specimen

value: back

value: tcell


title: SRC011T1_Tc_S36


title: SRC009T1_Tu_S22

value: tumor


title: SRC004T1_Tr_S37


title: SRC012T1_St_S9

value: stroma


title: non_Diabetes_non_TB_51 [PUN_B_99_10062]

value: Pune, India

value: non Diabetes


title: SRC004T1_Tu_S29


title: non_Diabetes_non_TB_57 [PUN_B_99_10117]

value: non TB

value: Male


title: SRC009T1_Tc_S27


title: Diabetes_non_TB_54 [PUN_B_99_10086]

value: whole blood


title: SRC009T1_Li_S20


title: SRC009T1_My_S4


title: SRC004T1_My_S29


title: non_Diabetes_non_TB_49 [PUN_B_99_10054]


title: non_Diabetes_non_TB_58 [PUN_B_99_10122]

value: Female


title: non_Diabetes_non_TB_56 [PUN_B_99_10110]


title: Diabetes_non_TB_63 [PUN_B_99_10204]

value: Diabetes


title: SRC004T1_St_S71

value: leg

value: Sarcoma


title: Diabetes_non_TB_47 [PUN_B_99_10051_01]


title: non_Diabetes_non_TB_50 [PUN_B_99_10056]


title: SRC004T1_Li_S10

value: live


title: non_Diabetes_non_TB_60 [PUN_B_99_10140]


title: non_Diabetes_non_TB_52 [PUN_B_99_10064]


title: SRC003T1_My_S21

value: myeloid


title: SRC001T1_St_S35

value: buttock


title: SRC003T1_Li_S89


title: non_Diabetes_non_TB_46 [PUN_B_99_10047]


title: SRC001T1_Tr_S64

value: treg


title: non_Diabetes_non_TB_48 [PUN_B_99_10051_03]


title: non_Diabetes_non_TB_44 [PUN_B_99_10036]


title: non_Diabetes_non_TB_45 [PUN_B_99_10043]


title: SRC003T1_Tu_S72


title: IPIPNET016T1_rna_live_S65

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a primary Brain Neuroendocrine tumor specimen

value: Brain

value: Pancreatic neuroendocrine cancer


title: non_Diabetes_TB_38 [PUN_A_99_10427]

value: TB


title: non_Diabetes_TB_37 [PUN_A_99_10418]


title: non_Diabetes_non_TB_41 [PUN_B_99_10015]


title: non_Diabetes_TB_34 [PUN_A_99_10409]


title: SRC001T1_Tu_S39

value: tumor


title: IPIPNET016T1_rna_epcam_S22

source_name: CD45- CD90- CD44- EPCAM+ Tumor cells sorted by flow cytometry from a primary Brain Neuroendocrine tumor specimen

value: epcam


title: non_Diabetes_TB_33 [PUN_A_99_10396]

value: Pune, India

value: non Diabetes


title: Diabetes_non_TB_42 [PUN_B_99_10018_01]

value: non TB


title: IPIPNET016T1_rna_tregs_S3

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a primary Brain Neuro endocrine tumor specimen


title: Diabetes_TB_36 [PUN_A_99_10415]

value: whole blood


title: SRC003T1_St_S26

value: stroma


title: SRC001T1_Li_S51


title: Diabetes_TB_39 [PUN_A_99_10429]

value: Diabetes

value: Male


title: PNET014T1_My_S34

source_name: Tumor assocaited HLA DR+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Brain Neuroendocrine tumor specimen

value: Pancreatic cancer


title: PNET014T1_Li_S77

value: live


title: non_Diabetes_non_TB_43 [PUN_B_99_10018_04]

value: Female


title: non_Diabetes_TB_31 [PUN_A_99_10373]


title: non_Diabetes_TB_32 [PUN_A_99_10378]


title: non_Diabetes_TB_40 [PUN_A_99_10432]


title: non_Diabetes_TB_35 [PUN_A_99_10411]


title: PNET014T1_Ep_S60


title: PNET009T1Tr_S48


title: non_Diabetes_TB_27 [PUN_A_99_10333]


title: PNET010T1_Li_S54


title: PNET009T1Tu_S37

source_name: CD45- CD90- CD44- Tumor cells sorted by flow cytometry from a primary brain tumor specimen


title: non_Diabetes_TB_30 [PUN_A_99_10358]


title: non_Diabetes_TB_29 [PUN_A_99_10354]


title: non_Diabetes_TB_28 [PUN_A_99_10336]


title: PNET010T1_Tu_S75


title: non_Diabetes_TB_26 [PUN_A_99_10317]


title: PNET007T1Li_S47


title: non_Diabetes_TB_22 [PUN_A_99_10210]


title: non_Diabetes_TB_25 [PUN_A_99_10236]


title: non_Diabetes_TB_24 [PUN_A_99_10234]


title: PNET009T1Li_S1


title: Diabetes_TB_21 [PUN_A_99_10204]


title: PNET005T1My_S25

source_name: Tumor assocaited HLA DR+ CD11b+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Brain Neuroendocrine tumor specimen

value: myeloid


title: Diabetes_TB_19 [PUN_A_99_10181]


title: Diabetes_TB_20 [PUN_A_99_10195]


title: PNET005T1Li_S6


title: Diabetes_TB_18 [PUN_A_99_10177]


title: PDAC037T1_St_S4

source_name: CD45- CD90+ CD44+ stromal cells  sorted by flow cytometry from a primary Pancreatic tumor specimen

value: Pancreas


title: PNET005T1Ep_S28

value: Brain


title: PDAC037T1_Tr_S59

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a primary Pancreatic tumor specimen

value: treg


title: non_Diabetes_TB_17 [PUN_A_99_10176]

value: TB


title: PDAC037T1_Li_S47

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a primary Pancreatic tumor specimen


title: non_Diabetes_TB_16 [PUN_A_99_10154]


title: non_Diabetes_TB_15 [PUN_A_99_10149]


title: non_Diabetes_TB_14 [PUN_A_99_10146]


title: PNET009T1My_S46


title: PDAC037T1_My_S45

source_name: Tumor assocaited HLA DR+ CD11b+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Pancreatic tumor specimen


title: non_Diabetes_TB_13 [PUN_A_99_10129]


title: non_Diabetes_TB_23 [PUN_A_99_10223]


title: non_Diabetes_TB_12 [PUN_A_99_10120]


title: PDAC029T1_St_S9


title: MELB003T3_Li_S15

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a Primary Melanoma tumor specimen

value: Skin

value: Melanoma


title: Diabetes_TB_11 [PUN_A_99_10106]

value: Pune, India


title: MELB003T3_My_S41

source_name: Tumor assocaited HLA DR+ CD11b+ CD3-CD1920-CD56- myeloid cells sorted by flow cytometry from a Primary Melanoma tumor specimen


title: non_Diabetes_TB_9 [PUN_A_99_10073]

value: non Diabetes


title: non_Diabetes_TB_8 [PUN_A_99_10072]


title: MELB003T2_Tc_S43

source_name: Tumor assocaited conventional T cell both CD4+ and CD8+ sorted by flow cytometry from a primary Melanoma tumor specimen

value: tcell


title: non_Diabetes_TB_10 [PUN_A_99_10104]

source_name: whole blood

value: whole blood


title: MELB003T3_Tc_S34


title: PDAC037T1_Ep_S76

source_name: CD45- CD90- CD44- EPCAM+ Tumor cells sorted by flow cytometry from a primary Pancreatic tumor specimen

value: epcam


title: non_Diabetes_TB_6 [PUN_A_99_10062]


title: Diabetes_TB_7 [PUN_A_99_10069]

value: Diabetes


title: MELB003T2_My_S10


title: Diabetes_TB_4 [PUN_A_99_10038]

value: Male


title: MELB003T2_Li_S9


title: Diabetes_TB_5 [PUN_A_99_10047]


title: MELB003T1_Tu_S16

source_name: CD45- CD90- CD44- Tumor cells sorted by flow cytometry from a primary melanoma tumor specimen

value: tumor


title: MELB003T1_Li_S7

value: live


title: MELB002T1_Tu_S54


title: non_Diabetes_TB_3 [PUN_A_99_10024]


title: non_Diabetes_TB_2 [PUN_A_99_10020]


title: non_Diabetes_TB_1 [PUN_A_99_10013]


title: Sample_210_Diabetes_non TB [B505336_END]

value: Salvador, Brazil

value: non TB

value: Female


title: MELB002T1_Tr_S12

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a primary Melanoma tumor specimen


title: Sample_210_Diabetes_non TB [B505336_BAS]


title: MELB002T1_Tc_S20


title: MELB002T1_My_S13

value: myeloid


title: Sample_209_Diabetes_non TB [B505320_BAS]


title: MELB002T1_Li_S40


title: Sample_207_Diabetes_non TB [B505316_END]


title: IPIMEL353T1_rna_treg_S15

value: treg


title: IPIMEL353T1_rna_live_S14


title: Sample_207_Diabetes_non TB [B505316_BAS]


title: Sample_206_non Diabetes_non TB [B505294_END]


title: IPIMEL353T1_rna_tumor_S37


title: Sample_208_Diabetes_non TB [B505319_BAS]


title: IPIMEL353T1_rna_myeloid_S25

source_name: Tumor assocaited HLA DR+ CD3-CD1920-CD56- myeloid cells sorted by flow cytometry from a Primary Melanoma tumor specimen


title: IPIMEL348_T1_rna_tumor_S12


title: MELB003T1_My_S11


title: IPIMEL348_T1_rna_myeloid_S46


title: IPIMEL348_T1_rna_treg_S18


title: Sample_204_Diabetes_non TB [B505291_END]


title: Sample_205_non Diabetes_non TB [B505292_END]


title: Sample_205_non Diabetes_non TB [B505292_BAS]


title: Sample_206_non Diabetes_non TB [B505294_BAS]


title: IPIMEL348_T1_rna_live_S25


title: Sample_203_non Diabetes_non TB [B505285_END]


title: IPIMEl343_T1_rna_Treg_S27


title: Sample_202_non Diabetes_non TB [B505279_END]


title: Sample_203_non Diabetes_non TB [B505285_BAS]


title: Sample_209_Diabetes_non TB [B505320_END]


title: IPIMEL343_T1_rna_Live_S43


title: Sample_202_non Diabetes_non TB [B505279_BAS]


title: Sample_208_Diabetes_non TB [B505319_END]


title: Sample_201_non Diabetes_non TB [B505278_END]


title: MEL325T1St_S11

source_name: CD45- CD90+ CD44+ stromal cells  sorted by flow cytometry from a primary Lung tumor specimen

value: stroma


title: Sample_204_Diabetes_non TB [B505291_BAS]


title: MEL325T1My_S10

value: Skin


title: MEL325T1Li_S44

value: Melanoma


title: Sample_200_Diabetes_non TB [B505277_BAS]


title: MEL325T1Tr_S41


title: Sample_199_Diabetes_non TB [B505276_END]


title: Sample_198_non Diabetes_non TB [B505273_END]


title: MEL321T1Tu_S69


title: Sample_200_Diabetes_non TB [B505277_END]


title: Sample_201_non Diabetes_non TB [B505278_BAS]


title: Sample_199_Diabetes_non TB [B505276_BAS]


title: Sample_198_non Diabetes_non TB [B505273_BAS]


title: MEL301T1My_S42


title: Sample_197_Diabetes_non TB [B505265_END]


title: Sample_196_non Diabetes_non TB [B505259_BAS]


title: MEL321T1Li_S49


title: Sample_196_non Diabetes_non TB [B505259_END]


title: IPIMEL343_T1_rna_Myeloid_S36


title: MEL301T1Tc_S3


title: MEL298T1My_S32_S22


title: Sample_195_non Diabetes_non TB [B505252_BAS]


title: MEL298T1Tc_S80_S54


title: MEL298T1Li_S42_S52


title: MEL325T1Tc_S42


title: Sample_195_non Diabetes_non TB [B505252_END]


title: Sample_194_non Diabetes_non TB [B505250_END]


title: MEL288T1Tu_S44

source_name: CD45- CD90- CD44- Tumor cells sorted by flow cytometry from a metastatic melanoma tumor specimen


title: MEL288T1Tr_S23

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a Metastic Melanoma tumor specimen


title: MEL296T1Li_S223

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a Metastatic Melanoma tumor specimen


title: MEL301T1Li_S25


title: Sample_193_non Diabetes_non TB [B505248_END]


title: Sample_192_non Diabetes_non TB [B505247_END]


title: MEL288T1Li_S36


title: Sample_193_non Diabetes_non TB [B505248_BAS]


title: MEL321T1My_S24


title: Sample_192_non Diabetes_non TB [B505247_BAS]


title: Sample_191_non Diabetes_non TB [B505246_END]


title: Sample_197_Diabetes_non TB [B505265_BAS]


title: MEL283T1Tu_S40


title: MEL283T1Tr_S50


title: MEL283T1My_S49


title: MEL274T1Tr_S2


title: MEL274T1My_S42

source_name: Tumor assocaited HLA DR+ CD11b+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a Metastatic Melanoma tumor specimen


title: MEL274T1Li_S27


title: MEL288T1My_S21


title: Sample_190_Diabetes_non TB [B505242_BAS]


title: Sample_190_Diabetes_non TB [B505242_END]


title: Sample_188_Diabetes_non TB [B505239_END]


title: Sample_187_non Diabetes_non TB [B505238_END]


title: Sample_189_Diabetes_non TB [B505241_END]


title: Sample_187_non Diabetes_non TB [B505238_BAS]


title: Sample_188_Diabetes_non TB [B505239_BAS]


title: Sample_189_Diabetes_non TB [B505241_BAS]


title: Sample_191_non Diabetes_non TB [B505246_BAS]


title: MEL273T1Tc_S51

source_name: Tumor assocaited conventional T cell both CD4+ and CD8+ sorted by flow cytometry from a metastatic Melanoma tumor specimen


title: MEL273T1Tr_S2


title: MEL273T1My_S45


title: MEL283T1Li_S48


title: MEL273T1Li_S47


title: MEL271T1Tu_S54_S37


title: MEL271T1St_S12_S4


title: MEL271T1Tr_S20_S57


title: Sample_194_non Diabetes_non TB [B505250_BAS]


title: MEL271T1My_S57_S55


title: Sample_184_Diabetes_non TB [B505227_END]


title: Sample_183_Diabetes_non TB [B505226_END]


title: Sample_182_Diabetes_non TB [B505225_END]


title: Sample_184_Diabetes_non TB [B505227_BAS]


title: Sample_185_non Diabetes_non TB [B505229_END]


title: Sample_183_Diabetes_non TB [B505226_BAS]


title: Sample_185_non Diabetes_non TB [B505229_BAS]


title: Sample_186_non Diabetes_non TB [B505237_BAS]


title: Sample_186_non Diabetes_non TB [B505237_END]


title: MEL271T1Li_S28_S20


title: MEL255T1My_S14_S9


title: MEL255T1Tu_S30_S50


title: MEL255T1Tr_S6_S30


title: Sample_180_Diabetes_TB [A105191_BAS]

value: TB


title: Sample_181_Diabetes_non TB [B505224_BAS]


title: MEL255T1Li_S38_S5


title: Sample_181_Diabetes_non TB [B505224_END]


title: Sample_180_Diabetes_TB [A105191_INT]


title: MEL253T1Tc_S33


title: Sample_180_Diabetes_TB [A105191_END]


title: Sample_179_Diabetes_TB [A105186_BAS]


title: Sample_179_Diabetes_TB [A105186_END]


title: Sample_179_Diabetes_TB [A105186_INT]


title: MEL252T1Tr_S36


title: Sample_178_Diabetes_TB [A105182_BAS]


title: MEL253T1Li_2_S46


title: Sample_182_Diabetes_non TB [B505225_BAS]


title: MEL255T1Tc_S22_S56


title: Sample_178_Diabetes_TB [A105182_END]


title: MEL252T1Li2_S5


title: MEL221T1Tr_S18


title: MEL221T1My_S14


title: MEL221T1Tu_S44


title: Sample_178_Diabetes_TB [A105182_INT]


title: Sample_177_Diabetes_TB [A105174_BAS]


title: Sample_176_Diabetes_TB [A105173_INT]


title: Sample_177_Diabetes_TB [A105174_END]


title: Sample_177_Diabetes_TB [A105174_INT]


title: Sample_176_Diabetes_TB [A105173_BAS]


title: MEL212T1Tu_S23


title: MEL253T1Tu_S40


title: Sample_176_Diabetes_TB [A105173_END]


title: MEL212T1Tr_S8


title: MEL221T1Li_S19


title: Sample_175_Diabetes_TB [A105171_INT]


title: Sample_175_Diabetes_TB [A105171_END]


title: MEL212T1Li_S31


title: MEL208T1Tu_S225


title: IPIMEL175_T1_rna_live_S16


title: Sample_174_Diabetes_TB [A105155_BAS]


title: MEL147T1_Tr_S19_L003


title: Sample_174_Diabetes_TB [A105155_INT]


title: Sample_174_Diabetes_TB [A105155_END]


title: Sample_173_non Diabetes_TB [A105154_BAS]

value: non Diabetes


title: Sample_173_non Diabetes_TB [A105154_INT]


title: MEL146T1_Li_S20_L003


title: Sample_173_non Diabetes_TB [A105154_END]


title: MEL141T2_Tc_S26_L003

value: tcell


title: MEL141T2_Tr_S46_L006


title: Sample_172_non Diabetes_TB [A105153_END]

value: whole blood


title: Sample_172_non Diabetes_TB [A105153_INT]


title: MEL141T2_Li_S4


title: Sample_172_non Diabetes_TB [A105153_BAS]


title: Sample_175_Diabetes_TB [A105171_BAS]


title: MEL141T1_St_S22_L003


title: MEL113T1_To_S24


title: MEL141T1_Tr_S44_L006


title: MEL208T1Li_S1


title: Sample_171_non Diabetes_TB [A105152_BAS]


title: MEL108T1_My_S53


title: Sample_171_non Diabetes_TB [A105152_END]


title: MEL105T2_To_P2_4_S19


title: MEL069T1_Tu_S46


title: MEL069T1_My_S49


title: MEL108T1_To_S50


title: Sample_170_Diabetes_TB [A105147_BAS]


title: Sample_169_Diabetes_TB [A105144_END]


title: Sample_170_Diabetes_TB [A105147_INT]


title: Sample_169_Diabetes_TB [A105144_INT]


title: Sample_168_non Diabetes_TB [A105141_BAS]


title: Sample_171_non Diabetes_TB [A105152_INT]


title: Sample_169_Diabetes_TB [A105144_BAS]


title: Sample_170_Diabetes_TB [A105147_END]


title: MEL056T1_To_S13


title: Sample_168_non Diabetes_TB [A105141_END]


title: IPILUNG088T1_rna_treg_S15

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a primary Lung tumor specimen

value: Lung

value: Lung cancer


title: Sample_167_Diabetes_TB [A105139_END]

value: Diabetes


title: Sample_167_Diabetes_TB [A105139_INT]


title: Sample_167_Diabetes_TB [A105139_BAS]


title: IPILUNG088T1_rna_epcam_S2

source_name: CD45- CD90- CD44- EPCAM+ Tumor cells sorted by flow cytometry from a primary Lung tumor specimen

value: epcam


title: LUNG087_T1_rna_tregs_S38


title: Sample_166_Diabetes_TB [A105136_END]

value: Male


title: Sample_168_non Diabetes_TB [A105141_INT]

value: Salvador, Brazil


title: LUNG081T1St_S56


title: Sample_166_Diabetes_TB [A105136_INT]


title: Sample_165_Diabetes_TB [A105131_END]


title: MEL069T1_Li_S17

value: live


title: Sample_165_Diabetes_TB [A105131_BAS]


title: LUNG085T1Li_S71

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a primary Lung tumor specimen


title: Sample_165_Diabetes_TB [A105131_INT]


title: LUNG081T1Ep_S54


title: LUNG080T1My_S65

source_name: Tumor assocaited HLA DR+ CD11b+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Bladder tumor specimen


title: Sample_164_non Diabetes_TB [A105128_INT]


title: LUNG080T1Ep_S57


title: Sample_163_Diabetes_TB [A105124_INT]

value: Female


title: LUNG081T1My_S61

value: myeloid


title: Sample_164_non Diabetes_TB [A105128_END]


title: Sample_163_Diabetes_TB [A105124_BAS]


title: LUNG080T1Tr_S39

value: treg


title: LUNG077T1Tr_S45


title: Sample_162_non Diabetes_TB [A105121_BAS]


title: Sample_162_non Diabetes_TB [A105121_INT]


title: Sample_166_Diabetes_TB [A105136_BAS]


title: Sample_162_non Diabetes_TB [A105121_END]


title: Sample_161_non Diabetes_TB [A105113_INT]


title: LUNG077T1My_S13


title: Sample_161_non Diabetes_TB [A105113_BAS]


title: Sample_160_non Diabetes_TB [A105112_END]


title: Sample_161_non Diabetes_TB [A105113_END]


title: LUNG076T1My_S7


title: Sample_160_non Diabetes_TB [A105112_INT]


title: LUNG076T1Ep_S24


title: Sample_159_non Diabetes_TB [A105104_BAS]


title: Sample_159_non Diabetes_TB [A105104_END]


title: Sample_164_non Diabetes_TB [A105128_BAS]


title: Sample_163_Diabetes_TB [A105124_END]


title: LUNG074_T1_rna_myeloid_S47


title: Sample_158_non Diabetes_TB [A105101_INT]


title: Sample_159_non Diabetes_TB [A105104_INT]


title: Sample_158_non Diabetes_TB [A105101_BAS]


title: LUNG074_T1_rna_treg_S48


title: LUNG070_T1_rna_stroma_S8

value: stroma


title: Sample_157_Diabetes_TB [A105100_END]


title: Sample_157_Diabetes_TB [A105100_INT]


title: Sample_157_Diabetes_TB [A105100_BAS]


title: Sample_158_non Diabetes_TB [A105101_END]


title: Sample_156_non Diabetes_TB [A105096_END]


title: Sample_156_non Diabetes_TB [A105096_INT]


title: LUNG070_T1_rna_myeloid_S11


title: LUNG070_T1_rna_treg_S13


title: LUNG076T1Tr_S23


title: Sample_160_non Diabetes_TB [A105112_BAS]


title: LUNG069_T1_rna_tregs_S39


title: Sample_154_Diabetes_TB [A105084_END]


title: LUNG074T1St_S10


title: LUNG066_T1_rna_treg_S20


title: Sample_155_non Diabetes_TB [A105088_END]


title: Sample_156_non Diabetes_TB [A105096_BAS]


title: LUNG066_T1_rna_live_S10


title: Sample_155_non Diabetes_TB [A105088_INT]


title: Sample_154_Diabetes_TB [A105084_INT]


title: Sample_155_non Diabetes_TB [A105088_BAS]


title: LUNG064_T1_rna_live_S43


title: Sample_152_non Diabetes_TB [A105080_BAS]


title: Sample_152_non Diabetes_TB [A105080_INT]


title: Sample_153_Diabetes_TB [A105081_INT]


title: LUNG056T1Ep_S31


title: LUNG058T1Li_S24


title: LUNG062T1Tr_S15


title: Sample_151_Diabetes_TB [A105079_INT]


title: LUNG067T1Tr_S53


title: Sample_150_non Diabetes_TB [A105077_BAS]


title: Sample_151_Diabetes_TB [A105079_BAS]


title: LUNG055T1Tu_S6

source_name: CD45- CD90- CD44- Tumor cells sorted by flow cytometry from a primary Lung tumor specimen

value: tumor


title: Sample_153_Diabetes_TB [A105081_END]


title: LUNG062T1Li_S20


title: Sample_153_Diabetes_TB [A105081_BAS]


title: Sample_152_non Diabetes_TB [A105080_END]


title: LUNG069_T1_rna_myeloid_S44


title: LUNG055T1Li_S7


title: LUNG056T1Li_S11


title: LUNG054T1Tu_S16


title: Sample_149_non Diabetes_TB [A105074_END]


title: Sample_149_non Diabetes_TB [A105074_INT]


title: Sample_150_non Diabetes_TB [A105077_INT]


title: Sample_148_non Diabetes_TB [A105073_INT]


title: Sample_148_non Diabetes_TB [A105073_BAS]


title: LUNG057T1Tr_S24


title: Sample_151_Diabetes_TB [A105079_END]


title: Sample_154_Diabetes_TB [A105084_BAS]


title: LUNG051T1Tr_S48


title: LUNG054T1Tr_S3


title: Sample_150_non Diabetes_TB [A105077_END]


title: Sample_149_non Diabetes_TB [A105074_BAS]


title: LUNG055T1Tr_S48


title: Sample_148_non Diabetes_TB [A105073_END]


title: LUNG051T1Tu_S35


title: Sample_146_non Diabetes_TB [A105062_BAS]


title: Sample_147_Diabetes_TB [A105065_BAS]


title: Sample_146_non Diabetes_TB [A105062_END]


title: Sample_147_Diabetes_TB [A105065_INT]


title: Sample_145_non Diabetes_TB [A105061_END]


title: Sample_147_Diabetes_TB [A105065_END]


title: Sample_144_Diabetes_TB [A105056_BAS]


title: LUNG054T1Li_S32


title: Sample_144_Diabetes_TB [A105056_END]


title: LUNG049T1St_S13


title: LUNG049T1Tu_S230


title: Sample_143_Diabetes_TB [A105055_BAS]


title: Sample_143_Diabetes_TB [A105055_END]


title: Sample_146_non Diabetes_TB [A105062_INT]


title: Sample_143_Diabetes_TB [A105055_INT]


title: Sample_145_non Diabetes_TB [A105061_INT]


title: Sample_144_Diabetes_TB [A105056_INT]


title: LUNG052T1Tr_S41


title: LUNG041T1Li_S5


title: Krummel_0610_P7_LUNG041T1Tr_S31


title: Sample_145_non Diabetes_TB [A105061_BAS]


title: Krummel_0610_P7_LUNG037T2Li1_S29


title: LUNG049T1Tr_S14


title: LUNG041T1Tu_S38


title: Sample_142_non Diabetes_TB [A105052_BAS]


title: LUNG037T1Tr_S41


title: Sample_142_non Diabetes_TB [A105052_END]


title: Sample_141_non Diabetes_TB [A105050_BAS]


title: LUNG037T1Li_S27


title: LUNG030T2_Tc_S20

source_name: Tumor assocaited conventional T cell both CD4+ and CD8+ sorted by flow cytometry from a primary Lung tumor specimen


title: Krummel_0610_P7_LUNG031T1Li1_S32


title: Sample_141_non Diabetes_TB [A105050_END]

source_name: whole blood


title: Sample_142_non Diabetes_TB [A105052_INT]


title: Sample_140_non Diabetes_TB [A105049_INT]


title: Sample_141_non Diabetes_TB [A105050_INT]


title: Sample_139_Diabetes_TB [A105048_END]


title: Sample_139_Diabetes_TB [A105048_INT]


title: LUNG037T1Tu_S232


title: Krummel_0610_P7_LUNG031T2Tr_S50


title: Sample_140_non Diabetes_TB [A105049_END]


title: Sample_139_Diabetes_TB [A105048_BAS]


title: LUNG030T1_Tr_S23


title: LUNG030T2_Li_S63


title: Sample_137_Diabetes_TB [A105040_BAS]


title: Sample_137_Diabetes_TB [A105040_INT]


title: Sample_138_Diabetes_TB [A105047_BAS]


title: LUNG025T1Tr_S43


title: Sample_138_Diabetes_TB [A105047_END]


title: LUNG021T1_Tr_S38


title: Krummel_0610_P7_LUNG025T1Li1_S53


title: Sample_137_Diabetes_TB [A105040_END]


title: Sample_136_non Diabetes_TB [A105039_END]


title: Sample_136_non Diabetes_TB [A105039_INT]


title: Sample_136_non Diabetes_TB [A105039_BAS]


title: Sample_135_non Diabetes_TB [A105037_BAS]


title: Sample_140_non Diabetes_TB [A105049_BAS]


title: Sample_135_non Diabetes_TB [A105037_INT]


title: Sample_135_non Diabetes_TB [A105037_END]


title: Sample_134_Diabetes_TB [A105036_INT]


title: LUNG015_T1_rna_tumor_S57


title: Sample_134_Diabetes_TB [A105036_BAS]


title: Sample_134_Diabetes_TB [A105036_END]


title: Sample_138_Diabetes_TB [A105047_INT]


title: Sample_133_non Diabetes_TB [A105034_INT]


title: Sample_133_non Diabetes_TB [A105034_BAS]


title: LUNG014_T1_rna_tumor_S33


title: Sample_132_non Diabetes_TB [A105028_INT]


title: Sample_132_non Diabetes_TB [A105028_BAS]


title: Sample_132_non Diabetes_TB [A105028_END]


title: Sample_131_Diabetes_TB [A105027_END]


title: Sample_131_Diabetes_TB [A105027_BAS]


title: LUNG011_T1_rna_live_S3


title: LUNG009_T1_rna_tumor_S33


title: Sample_131_Diabetes_TB [A105027_INT]


title: Sample_130_non Diabetes_TB [A105022_INT]


title: Sample_130_non Diabetes_TB [A105022_END]


title: LUNG008_T1_rna_tumor_S39


title: Sample_129_Diabetes_TB [A105016_BAS]


title: Sample_128_Diabetes_TB [A105015_BAS]


title: Sample_129_Diabetes_TB [A105016_END]


title: LUNG004-T1Stroma500_S45_S12_L001


title: Sample_128_Diabetes_TB [A105015_END]


title: Sample_128_Diabetes_TB [A105015_INT]


title: Sample_127_non Diabetes_TB [A105014_INT]


title: Sample_127_non Diabetes_TB [A105014_END]


title: IPIKID110T1_rna_tumor_S66

source_name: CD45- CD90- CD44- Tumor cells sorted by flow cytometry from a primary Kidney tumor specimen

value: Kidney

value: Kidney cancer


title: LUNG004-T1Treg2k_S44_S31_L006


title: IPIKID110T1_rna_myeloids_S65

source_name: Tumor assocaited HLA DR+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Kidney tumor specimen


title: Sample_133_non Diabetes_TB [A105034_END]

value: non Diabetes

value: TB


title: Sample_126_Diabetes_TB [A105007_BAS]

value: whole blood


title: Sample_125_Diabetes_TB [A105006_INT]


title: Sample_126_Diabetes_TB [A105007_INT]


title: Sample_127_non Diabetes_TB [A105014_BAS]


title: Sample_125_Diabetes_TB [A105006_END]


title: IPIKID109T1_rna_stroma_S6

source_name: CD45- CD90+ CD44+ stromal cells  sorted by flow cytometry from a primary Kidney tumor specimen


title: Sample_130_non Diabetes_TB [A105022_BAS]


title: Sample_125_Diabetes_TB [A105006_BAS]


title: IPIKID109T1_rna_tumor_S69


title: Sample_129_Diabetes_TB [A105016_INT]


title: IPIKID109T1_rna_live3_S43

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a primary Kidney tumor specimen


title: Sample_124_non Diabetes_TB [A105004_BAS]


title: Sample_123_Diabetes_TB [A105003_END]


title: Sample_123_Diabetes_TB [A105003_INT]


title: Sample_122_Diabetes_TB [A105001_BAS]


title: Sample_122_Diabetes_TB [A105001_END]


title: Sample_122_Diabetes_TB [A105001_INT]


title: Sample_123_Diabetes_TB [A105003_BAS]


title: IPIKID106T1_rna_epcam_S49

source_name: CD45- CD90- CD44- EPCAM+ Tumor cells sorted by flow cytometry from a primary Kidney tumor specimen


title: Sample_126_Diabetes_TB [A105007_END]


title: Sample_121_non Diabetes_TB [A105000_INT]


title: IPIKID104_T1_rna_Tumor_S25


title: Sample_121_non Diabetes_TB [A105000_END]


title: IPIKID104_T1_rna_Treg_S31

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a primary Kidney tumor specimen


title: IPIKID110T1_rna_live_S2


title: Sample_121_non Diabetes_TB [A105000_BAS]


title: IPIKID103_T1_rna_Treg_S5


title: Sample_117_Diabetes_non TB [MSTDI_057]

value: Chennai, India

value: non TB


title: Sample_119_Diabetes_non TB [MSTDI_059]

value: Diabetes


title: Sample_114_Diabetes_non TB [MSTDI_054]


title: Sample_124_non Diabetes_TB [A105004_INT]


title: Sample_124_non Diabetes_TB [A105004_END]


title: IPIKID103_T1_rna_EpCAM_S54

value: epcam


title: IPIKID102_T1_rna_treg_S55


title: Sample_118_Diabetes_non TB [MSTDI_058]


title: Sample_110_Diabetes_non TB [MSTDI_050]


title: Sample_113_Diabetes_non TB [MSTDI_053]


title: Sample_111_Diabetes_non TB [MSTDI_051]


title: Sample_109_Diabetes_non TB [MSTDI_049]


title: Sample_112_Diabetes_non TB [MSTDI_052]


title: IPIKID100_T1_rna_tumor_S51


title: Sample_108_Diabetes_non TB [MSTDI_048]


title: Sample_106_Diabetes_non TB [MSTDI_046]


title: Sample_120_Diabetes_non TB [MSTDI_060]


title: Sample_104_Diabetes_non TB [MSTDI_044]


title: Sample_105_Diabetes_non TB [MSTDI_045]


title: Sample_116_Diabetes_non TB [MSTDI_056]


title: Sample_102_Diabetes_non TB [MSTDI_042]


title: IPIKID099_T1_rna_treg_S15


title: Sample_101_Diabetes_non TB [MSTDI_041]


title: Sample_115_Diabetes_non TB [MSTDI_055]


title: IPIKID100_T1_rna_Treg_S30


title: Sample_103_Diabetes_non TB [MSTDI_043]


title: Sample_100_Diabetes_non TB [MSTDI_040]


title: Sample_99_Diabetes_non TB [MSTDI_039]


title: Sample_97_Diabetes_non TB [MSTDI_037]


title: Sample_96_Diabetes_non TB [MSTDI_036]


title: Sample_98_Diabetes_non TB [MSTDI_038]


title: Sample_95_Diabetes_non TB [MSTDI_035]


title: IPIKID098_T1_rna_treg_S59


title: IPIKID099_T1_rna_epcam_S8


title: IPIKID098_T1_rna_tumor_S26


title: Sample_94_Diabetes_non TB [MSTDI_034]


title: IPIKID102_T1_rna_EpCAM_S58


title: Sample_92_Diabetes_non TB [MSTDI_032]


title: Sample_107_Diabetes_non TB [MSTDI_047]


title: IPIKID097_T1_rna_stroma_S15


title: Sample_93_Diabetes_non TB [MSTDI_033]


title: Sample_91_Diabetes_non TB [MSTDI_031]


title: IPIKID097_T1_rna_myeloid_S21


title: Sample_88_non Diabetes_non TB [MSTDI_028]


title: IPIKID095_T1_rna_tumor_S5


title: Sample_87_non Diabetes_non TB [MSTDI_027]


title: IPIKID097_T1_rna_epcam_S64


title: Sample_84_non Diabetes_non TB [MSTDI_024]


title: Sample_83_non Diabetes_non TB [MSTDI_023]


title: Sample_89_non Diabetes_non TB [MSTDI_029]


title: IPIKID095_T1_rna_treg_S28


title: Sample_82_non Diabetes_non TB [MSTDI_022]


title: KID094T2_Tu_S21


title: KID094T2_St_S25


title: Sample_81_non Diabetes_non TB [MSTDI_021]


title: KID094T2_Tc_S13

source_name: Tumor assocaited conventional T cell both CD4+ and CD8+ sorted by flow cytometry from a primary Kidney tumor specimen

value: tcell


title: KID094T2_Li_S6


title: KID094T2_My_S11


title: Sample_77_non Diabetes_non TB [MSTDI_017]


title: Sample_79_non Diabetes_non TB [MSTDI_019]


title: Sample_80_non Diabetes_non TB [MSTDI_020]


title: KID094T1_St_S18


title: Sample_90_non Diabetes_non TB [MSTDI_030]


title: Sample_74_non Diabetes_non TB [MSTDI_014]


title: KID094T1_Tu_S85


title: Sample_73_non Diabetes_non TB [MSTDI_013]


title: KID094T1_Tr_S12


title: Sample_78_non Diabetes_non TB [MSTDI_018]


title: Sample_76_non Diabetes_non TB [MSTDI_016]


title: Sample_72_non Diabetes_non TB [MSTDI_012]


title: Sample_85_non Diabetes_non TB [MSTDI_025]


title: Sample_86_non Diabetes_non TB [MSTDI_026]


title: Sample_71_non Diabetes_non TB [MSTDI_011]


title: KID093T2_Li_S51


title: KID093T2_St_S30


title: Sample_70_non Diabetes_non TB [MSTDI_010]


title: Sample_69_non Diabetes_non TB [MSTDI_009]


title: KID093T2_Tr_S27


title: KID093T2_Tu_S62


title: KID093T2_My_S28


title: Sample_68_non Diabetes_non TB [MSTDI_008]


title: KID093T1_Tu_S61


title: KID093T2_Tc_S33


title: Sample_66_non Diabetes_non TB [MSTDI_006]


title: Sample_75_non Diabetes_non TB [MSTDI_015]


title: Sample_62_non Diabetes_non TB [MSTDI_002]


title: Sample_64_non Diabetes_non TB [MSTDI_004]


title: Sample_60_non Diabetes_TB [300403_2m]

value: Male


title: Sample_60_non Diabetes_TB [300403_0m]


title: KID092T1_Tr_S63


title: Sample_65_non Diabetes_non TB [MSTDI_005]


title: KID092T1_Tu_S69


title: Sample_61_non Diabetes_non TB [MSTDI_001]


title: Sample_59_Diabetes_TB [300383_6m]


title: Sample_67_non Diabetes_non TB [MSTDI_007]


title: Sample_59_Diabetes_TB [300383_2m]


title: KID091T1_Tu_S29


title: KID093T1_Tr_S50


title: KID091T1_Tr_S36


title: Sample_58_non Diabetes_TB [300350_6m]


title: Sample_59_Diabetes_TB [300383_0m]


title: Sample_58_non Diabetes_TB [300350_2m]


title: Sample_60_non Diabetes_TB [300403_6m]


title: Sample_58_non Diabetes_TB [300350_0m]


title: Sample_63_non Diabetes_non TB [MSTDI_003]


title: Sample_57_Diabetes_TB [300313_2m]


title: Sample_56_non Diabetes_TB [300244_6m]


title: Sample_57_Diabetes_TB [300313_0m]


title: Sample_56_non Diabetes_TB [300244_0m]


title: Sample_56_non Diabetes_TB [300244_2m]


title: KID090T1_Li_S4

value: live


title: Sample_54_non Diabetes_TB [300055_6m]


title: Sample_55_non Diabetes_TB [300112_6m]


title: KID086T2_Tu_S39


title: KID089T1_Tr_S35


title: KID089T1_Tu_S37


title: Sample_55_non Diabetes_TB [300112_2m]


title: Sample_54_non Diabetes_TB [300055_0m]


title: Sample_55_non Diabetes_TB [300112_0m]


title: KID086T2_Li_S16


title: KID086T1_Tu_S62


title: KID086T1_Tr_S22


title: Sample_53_Diabetes_TB [200377_2m]


title: Sample_53_Diabetes_TB [200377_0m]


title: KID086T2_My_S55

source_name: Tumor assocaited HLA DR+ CD11b+ CD3-CD1920-CD56- myeloid cells  sorted by flow cytometry from a primary Kidney tumor specimen


title: Sample_52_non Diabetes_TB [200353_6m]

value: Female


title: Sample_52_non Diabetes_TB [200353_0m]


title: Sample_51_non Diabetes_TB [200300_6m]


title: Sample_52_non Diabetes_TB [200353_2m]


title: Sample_53_Diabetes_TB [200377_6m]


title: Sample_51_non Diabetes_TB [200300_2m]


title: KID085T1_Tu_S21


title: Sample_51_non Diabetes_TB [200300_0m]


title: Sample_50_non Diabetes_TB [200295_6m]


title: KID084T1_Tu_S23


title: Sample_50_non Diabetes_TB [200295_2m]


title: Sample_54_non Diabetes_TB [300055_2m]


title: Sample_50_non Diabetes_TB [200295_0m]


title: KID083T1_Tu_S38


title: Sample_48_non Diabetes_TB [200289_6m]


title: Sample_49_non Diabetes_TB [200294_0m]


title: Sample_48_non Diabetes_TB [200289_2m]


title: Sample_49_non Diabetes_TB [200294_2m]


title: KID079T1St_S58


title: Sample_47_non Diabetes_TB [200277_2m]


title: KID079T1Tr_S27


title: Sample_57_Diabetes_TB [300313_6m]


title: Sample_46_non Diabetes_TB [200122_6m]


title: Sample_46_non Diabetes_TB [200122_0m]


title: Sample_46_non Diabetes_TB [200122_2m]


title: Sample_47_non Diabetes_TB [200277_0m]


title: KID078T1Tu_S50


title: KID079T1Ep_S60


title: Sample_45_Diabetes_TB [200076_6m]


title: Sample_45_Diabetes_TB [200076_2m]


title: Sample_45_Diabetes_TB [200076_0m]


title: KID078T1Tr_S59


title: Sample_44_non Diabetes_TB [100380_2m]


title: KID084T1_Tr_S40


title: Sample_44_non Diabetes_TB [100380_6m]


title: Sample_49_non Diabetes_TB [200294_6m]


title: Sample_44_non Diabetes_TB [100380_0m]


title: KID083T1_Tr_S25


title: Sample_43_Diabetes_TB [100344_6m]


title: Sample_48_non Diabetes_TB [200289_0m]


title: Sample_43_Diabetes_TB [100344_0m]


title: KID077T1Ep_S44


title: Sample_47_non Diabetes_TB [200277_6m]


title: Sample_42_Diabetes_TB [100334_6m]


title: KID077T1Tr_S54


title: Sample_42_Diabetes_TB [100334_2m]


title: Sample_42_Diabetes_TB [100334_0m]


title: Sample_41_non Diabetes_TB [100322_6m]


title: Sample_41_non Diabetes_TB [100322_2m]


title: Sample_40_non Diabetes_TB [100316_0m]


title: Sample_39_Diabetes_TB [100305_6m]


title: Sample_40_non Diabetes_TB [100316_2m]


title: Sample_41_non Diabetes_TB [100322_0m]


title: KID074_T1_rna_tumor_S2


title: KID074T1_Tr_S22_L001


title: KID074T1_Tr_S55


title: Sample_39_Diabetes_TB [100305_2m]


title: Sample_39_Diabetes_TB [100305_0m]


title: Sample_43_Diabetes_TB [100344_2m]


title: KID073_T1_rna_stroma_S29


title: Sample_38_Diabetes_TB [100290_2m]


title: Sample_38_Diabetes_TB [100290_6m]


title: Sample_38_Diabetes_TB [100290_0m]


title: KID073_T1_rna_treg_S56


title: Sample_37_Diabetes_TB [100280_6m]


title: KID076T1Tu_S35


title: Sample_37_Diabetes_TB [100280_2m]


title: KID073_T1_rna_tumor_S19


title: KID076T1Tr_S43


title: KID071_T1_rna_tumor_S3


title: Sample_37_Diabetes_TB [100280_0m]


title: Sample_36_Diabetes_TB [100268_2m]


title: Sample_36_Diabetes_TB [100268_0m]


title: Sample_36_Diabetes_TB [100268_6m]


title: Sample_40_non Diabetes_TB [100316_6m]


title: KID071T1_Tr_S35


title: Sample_35_Diabetes_TB [100258_6m]


title: KID070_T1_rna_stroma_S4


title: Sample_35_Diabetes_TB [100258_0m]


title: Sample_34_Diabetes_TB [100257_6m]


title: Sample_34_Diabetes_TB [100257_2m]


title: Sample_34_Diabetes_TB [100257_0m]


title: KID070_T1_rna_tumor_S52


title: KID070_T1_rna_treg_S10


title: Sample_33_Diabetes_TB [100228_2m]


title: Sample_33_Diabetes_TB [100228_0m]


title: Sample_33_Diabetes_TB [100228_6m]


title: KID069_T1_rna_treg_S27


title: Sample_32_Diabetes_TB [100226_6m]


title: Sample_32_Diabetes_TB [100226_0m]


title: KID067T1Tu_S46


title: Sample_32_Diabetes_TB [100226_2m]


title: Sample_31_non Diabetes_TB [100210_2m]


title: Sample_31_non Diabetes_TB [100210_0m]


title: Sample_30_Diabetes_TB [100199_6m]


title: Sample_35_Diabetes_TB [100258_2m]


title: KID066_T1_rna_tregs_S29


title: Sample_30_Diabetes_TB [100199_2m]


title: Sample_29_non Diabetes_TB [100188_2m]


title: Sample_31_non Diabetes_TB [100210_6m]


title: KID066_T1_rna_tumor_S9


title: Sample_28_non Diabetes_TB [100186_6m]


title: KID066T1_My_S48

value: myeloid


title: Sample_29_non Diabetes_TB [100188_6m]


title: Sample_29_non Diabetes_TB [100188_0m]


title: Sample_30_Diabetes_TB [100199_0m]


title: KID062T1_Tu_S31


title: Sample_28_non Diabetes_TB [100186_2m]


title: Sample_27_Diabetes_TB [100179_2m]


title: Sample_27_Diabetes_TB [100179_6m]


title: Sample_26_non Diabetes_TB [100175_6m]


title: Sample_27_Diabetes_TB [100179_0m]


title: Sample_26_non Diabetes_TB [100175_2m]


title: Sample_26_non Diabetes_TB [100175_0m]


title: KID061_T1_rna_tumor_S31


title: KID061_T1_rna_stroma_S28


title: KID061_T1_rna_treg_S51

value: treg


title: KID060_T1_rna_tregs_S5


title: Sample_25_Diabetes_TB [100147_2m]


title: Sample_25_Diabetes_TB [100147_6m]


title: Sample_25_Diabetes_TB [100147_0m]


title: KID060_T1_rna_tumor_S25


title: Sample_24_non Diabetes_TB [100130_6m]


title: Sample_24_non Diabetes_TB [100130_2m]


title: Sample_24_non Diabetes_TB [100130_0m]


title: KID059T1Tr_S14


title: Sample_23_non Diabetes_TB [100123_6m]


title: KID057T1Tu_S215


title: Sample_28_non Diabetes_TB [100186_0m]


title: Sample_23_non Diabetes_TB [100123_2m]


title: Sample_22_non Diabetes_TB [100120_6m]


title: Sample_22_non Diabetes_TB [100120_2m]


title: Sample_23_non Diabetes_TB [100123_0m]


title: Sample_22_non Diabetes_TB [100120_0m]


title: KID057T1My_S29


title: KID057T1Tr_S213


title: KID054T1Tr_S21


title: Sample_21_Diabetes_TB [100118_2m]


title: KID052T1Tr_S52


title: Sample_20_Diabetes_TB [100102_2m]


title: Sample_20_Diabetes_TB [100102_0m]


title: KID051T1Tu_S10


title: Sample_20_Diabetes_TB [100102_6m]


title: Sample_19_non Diabetes_TB [100098_2m]


title: Sample_19_non Diabetes_TB [100098_6m]


title: KID051T1Tr_S12


title: Sample_21_Diabetes_TB [100118_0m]


title: Sample_18_Diabetes_TB [100097_2m]


title: Sample_18_Diabetes_TB [100097_0m]


title: Sample_18_Diabetes_TB [100097_6m]


title: Sample_17_non Diabetes_TB [100096_2m]


title: KID049T1Tu_S77_S1


title: KID049T1Tr_S91_S26


title: Sample_17_non Diabetes_TB [100096_6m]


title: KID049T1Li2_S84_S24


title: KID050_T1_rna_live_S11


title: Sample_16_Diabetes_TB [100091_0m]


title: Sample_21_Diabetes_TB [100118_6m]


title: Sample_16_Diabetes_TB [100091_6m]


title: Sample_17_non Diabetes_TB [100096_0m]


title: Sample_19_non Diabetes_TB [100098_0m]


title: Sample_15_Diabetes_TB [100086_2m]


title: KID048T1Tr_S82_S42


title: Sample_15_Diabetes_TB [100086_0m]


title: Sample_15_Diabetes_TB [100086_6m]


title: Sample_14_non Diabetes_TB [100082_2m]


title: Sample_14_non Diabetes_TB [100082_0m]


title: Sample_13_Diabetes_TB [100079_2m]


title: KID047T1_Tu_S68


title: KID047T1_Li_S50


title: Sample_13_Diabetes_TB [100079_0m]


title: Sample_14_non Diabetes_TB [100082_6m]


title: KID043T1Tu_S6


title: Sample_12_non Diabetes_TB [100077_6m]


title: KID043T1Li_S7


title: Sample_12_non Diabetes_TB [100077_2m]


title: Krummel_0610_P7_KID033T2Li2_S25


title: KID031T2_Tr_S11


title: Sample_12_non Diabetes_TB [100077_0m]


title: KID047_T1_rna_treg_S21


title: Sample_11_non Diabetes_TB [100070_2m]


title: KID031T1_Tr_S70


title: KID031T2_My_S8


title: Sample_16_Diabetes_TB [100091_2m]


title: KID031T2_Li_S13


title: Sample_11_non Diabetes_TB [100070_0m]


title: Sample_13_Diabetes_TB [100079_6m]


title: Sample_10_Diabetes_TB [100064_6m]


title: KID047T1_Tu_S35_L001


title: Sample_10_Diabetes_TB [100064_2m]


title: Sample_9_Diabetes_TB [100056_6m]


title: Sample_9_Diabetes_TB [100056_2m]


title: KID030T1_Tr_S16


title: KID030T1_Tu_S36


title: KID025-T1Treg2k_S37_S30_L006


title: Sample_11_non Diabetes_TB [100070_6m]


title: KID021_T1_rna_treg_S43


title: Sample_7_Diabetes_TB [100040_6m]


title: Sample_7_Diabetes_TB [100040_2m]


title: KID031T1_Li_S65


title: Sample_6_Diabetes_TB [100030_2m]


title: Sample_6_Diabetes_TB [100030_6m]


title: Sample_5_Diabetes_TB [100028_6m]


title: Sample_5_Diabetes_TB [100028_0m]


title: KID030T1_Li2_S34


title: Sample_6_Diabetes_TB [100030_0m]


title: Sample_10_Diabetes_TB [100064_0m]


title: IPIHNSC079T1_rna_treg_S33

source_name: Tumor assocaited CD4+ CD25+ Regulatory T cell sorted by flow cytometry from a primary tumor specimen located in the Head and Neck region

value: Head & Neck

value: Head & Neck cancer


title: IPIHNSC078T1_rna_epcam_S12

source_name: CD45- CD90- CD44- EPCAM+ Tumor cells sorted by flow cytometry from a primary tumor specimen located in the Head and Neck region


title: Sample_4_Diabetes_TB [100026_2m]


title: Sample_9_Diabetes_TB [100056_0m]


title: Sample_8_non Diabetes_TB [100048_6m]


title: KID027_T1_rna_stroma_S18

value: Kidney

value: stroma


title: IPIHNSC077T1_rna_stroma_S15

source_name: CD45- CD90+ CD44+ stromal cells  sorted by flow cytometry from a primary tumor specimen located in the head and neck region


title: Sample_8_non Diabetes_TB [100048_2m]

value: non Diabetes


title: Sample_8_non Diabetes_TB [100048_0m]

value: TB


title: Sample_7_Diabetes_TB [100040_0m]

value: whole blood


title: IPIHNSC078T1_rna_treg_S20


title: Sample_4_Diabetes_TB [100026_6m]

value: Chennai, India


title: Sample_3_non Diabetes_TB [100020_6m]


title: IPIHNSC077T1_rna_tumor_S38

source_name: CD45- CD90- CD44- Tumor cells sorted by flow cytometry from a primary tumor specimen located in the Head and Neck region

value: tumor


title: Sample_5_Diabetes_TB [100028_2m]

value: Diabetes


title: Sample_2_non Diabetes_TB [100019_6m]


title: Sample_2_non Diabetes_TB [100019_2m]


title: Sample_3_non Diabetes_TB [100020_2m]


title: Sample_3_non Diabetes_TB [100020_0m]


title: IPIHNSC076_T1_rna_stroma_S29


title: Sample_2_non Diabetes_TB [100019_0m]


title: Sample_1_Diabetes_TB [100002_6m]


title: Sample_4_Diabetes_TB [100026_0m]


title: Sample_1_Diabetes_TB [100002_2m]


title: IPIHNSC076_T1_rna_treg_S58


title: IPIHNSC076_T1_rna_epcam_S2

value: epcam


title: P10

city: NanJing

first: Fei

last: jia

state: Jiangsu

address: Xinghuo Road

institute: singleron

data_processing:
Quality control
scRNA-seq reads were aligned to the GRCh38 genome assembly using STAR version 2.6.1a
aligned bam files were dealing with Featurecounts Version 1.6.2 to get UMI counts of each cell
Genome_build: GRCh38
Supplementary_files_format_and_content: expression matrix file using RNA raw count

molecule: polyA RNA

source_name: Lung

extract_protocol:
The concentration of single-cell suspension was adjusted to 1×105 cells/mL in PBS. Single cell suspension was then loaded onto a microfluidic chip (part of Singleron GEXSCOPETM Single Cell RNAseq Kit, Singleron Biotechnologies) and single cell RNA-seq libraries were constructed according to the manufacturer’s instructions (Singleron Biotechnologies).
scRNA-seq

treatment_protocol: the specimens were washed with Hanks Balanced Salt Solution (HBSS) for three times and minced into 1–2 mm pieces. The tissue pieces were digested in 2ml GEXSCOPETM Tissue Dissociation Solution (Singleron Biotechnologies) at 37°C for 15min in a 15ml centrifuge tube with continuous agitation

value: Lung

tag: age

value: male


title: Sample_1_Diabetes_TB [100002_0m]

value: Male


title: P7


title: P6

value: female


title: IPIHNSC075_T1_rna_treg_S3


title: IPIHNSC075_T1_rna_live_S9

source_name: Tumor infiltrating viable cells sorted by flow cytometry from a primary tumor specimen located in the head and neck region

value: live


title: IPIHNSC074_T1_rna_treg_S22

value: treg


title: IPIHNSC077T1_rna_treg_S17

value: Head & Neck


title: P8


title: IPIHNSC075_T1_rna_tumor_S6

value: Head & Neck cancer


title: P9


title: P3


title: IPIHNSC075_T1_rna_stroma_S19


title: P5


title: P4


title: IPIHNSC074_T1_rna_tumor_S20


title: HNSC073T1_Tu_S14


title: lnc_PT5

city: Shenyang

first: Caixia

last: Liu

state: Liaoning

address: No.36 SanHao Street, HePing Area

department: Department of Obstetrics and Gynecology

institute: Shengjing Hospital of China Medical

data_processing:
Data were filtered using SOAP version 1.5.2
Data were assembled using HISAT version 2.0.4 and StringTie version 1.0.4
Coding ability prediction using CPC version 0.9-r2, txCdsPredict, CNCI and pfam
Quantitative analysis using Bowtie2 version 2.2.5 and RSEM version 1.2.12
Gene coverage analysis using Bowtie2 version 2.2.5
Difference analysis using DEGseq
Cluster analysis using pheatmap version 1.0.8
Gene annotation using blast version 2.2.23, Diamond version 0.8.31 and Blast2GO version 2.5.0
Rich analysis
Gene fusion analysis using SOAPfuse version 1.18
SNP and InDel analysis using GATK version 3.4-0
alternative splicing analysis using Asprofile version b-1.0.4
Rich analysis using Bowtie2 version 2.2.5
Conservation analysis using phastCons and phyloP
CircRNA prediction using CIRI version 2.0.5
pre-miRNA prediction using blast version 2.2.23
Target of lncRNA analysis
LncRNA family analysis using infernal version 1.2
Interaction analysis
Genome_build: hg19
Supplementary_files_format_and_content: FASTQ files were generated using Illumina HiSeq platform, which include biological sequence and corresponding quality evaluation

source_name: placenta accreta_palcenta

extract_protocol:
Total RNA was extracted using TRIzol solution according to the manufacturer’s instructions (Invitrogen, Carlsbad, CA, USA) with strict quality control at each step.
First, rRNA is removed from the extracted total RNA with a biotin-labeled specific probe (Ribo-Zero ™ rRNA Removal Kit). After purification, the RNA is fragmented under a certain temperature and ionic environment. Then use the random primers and reverse transcriptase to synthesize the first strand of cDNA with TruSeq® Stranded kit , and then use DNA polymerase I and RNaseH to synthesize the double-stranded cDNA. During the second-strand cDNA synthesis, the RNA template is removed and dTTP is replaced by dUTP. The double-stranded cDNA product was subsequently ligated with an "A" base and a linker. The ligation product will be amplified and the final cDNA library will be obtained after purification.

treatment_protocol: The placental samples were washed in normal saline to remove excess blood, immediately immersed in liquid nitrogen, and transferred −80°C for storage.

tag: subject status

value: placenta accreta patient

tag: maternal age (yrs)

tag: bmi

tag: gravidity

tag: parity

tag: artificial abortion times

tag: gestational age (wks)


title: lnc_PT3


title: lnc_PT4


title: HNSC073T1_Tc_S56

source_name: Tumor assocaited conventional T cell both CD4+ and CD8+ sorted by flow cytometry from a primary tumor specimen in the Head and Neck region

tag: tissue

value: tcell


title: HNSC073T1_Tr_S49

tag: sorted compartment


title: HNSC073T1_Li_S87

tag: disease


title: HNSC070T1_St_S50

value: stroma


title: lnc_PT1


title: lnc_PT2


title: HNSC070T1_Tu_S20


title: lnc_PC3

value: control patient


title: lnc_PC5


title: lnc_PC1


title: HNSC070T1_Tr_S17


title: P1


title: HNSC069T1_Tu_S10


title: HNSC069T1_St_S27


title: HNSC065T1_Li_S80


title: DM_IP_Rep3

city: Shenzhen

first: Xinran

last: Yang

state: --- Select One ---

address: Xueyuan street 1068, Shenzhen

department: Shenzhen Institute of Synthetic Biology

institute: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

data_processing:
Library strategy: MeRIP-seq
Cutadapt and perl scripts in house were used to remove the reads that contained adaptor contamination, low quality bases and undetermined bases.
The sequence quality was verified using fastp.
We used HISAT2 to map reads to the genome of bos taurus (Version: V96) with default parameters. Mapped reads of IP and input libraries were provided for R package exomePeak, which identifies m6A peaks with bed or bam format that can be adapted for visualization on the UCSC genome browser or IGV software (http://www.igv.org/).
MEME and HOMER were used for de novo and known motif finding followed by localization of the motif with respect to peak summit by perl scripts in house.
Called peaks were annotated by intersection with gene architecture using ChIPseeker.
Then StringTie was used to perform expression level for all mRNAs from input libraries by calculating FPKM (FPKM=[total_exon_fragments/mapped_reads(millions)×exon_length(kB)]).
Genome_build: ARS-UCD1.2
Supplementary_files_format_and_content: tab-delimited text files include FPKM values for each Sample
Supplementary_files_format_and_content: peak text files

organism: Bos taurus

source_name: myotubes

growth_protocol: Primary myoblasts were isolated from the longissimus dorsi of newborn Qinchuan cattle. The isolated myoblasts were cultured to 80% density in the growth medium (GM), and then myogenic differentiation was induced in the differentiation medium (DM). The culture condition was in a humidified incubator (Thermo Fisher Scientific, MA, USA) containing 5% carbon dioxide at 37°C. The growth medium of myoblasts was composed of Dulbecco’s modified Eagle’s medium: Nutrient Mixture F-12 (DMEM/F12), 20% fetal bovine serum (FBS; GIBCO, USA) and 1% penicillin/streptomycin. The differentiation medium of myoblasts was consisted of DMEM/F12 containing 2% horse serum (HS; GIBCO, USA), and 1% penicillin/streptomycin. The medium was changed every two days.

extract_protocol:
Total RNA was extracted using RNAiso reagent (Takara, Daling, China). The quality and quantity of the total RNA were analyzed by Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA) with RIN > 7.0. Poly (A) mRNA was isolated from total RNA over 200 ug using poly-T oligo attached magnetic beads (Invitrogen, Massachusetts, USA).
Following purification, the poly(A) mRNA fractions are fragmented into about 100-nt-long oligonucleotides by divalent cations at high temperatures. The cleaved RNA fragments were then incubated with m6A-specific antibody (202003, Synaptic Systems, Germany) in IP buffer (50 mM Tris-HCl, 750 mM NaCl and 0.5% Igepal CA-630) supplemented with BSA (0.5 μg μl−1) at 4 °C for 2h. Then the mixture was incubated with protein-A beads and eluted with elution buffer (1 × IP buffer and 6.7mM m6A). The eluted RNA was precipitated with 75% ethanol. According to the strand-specific library prepared by dUTP method, the eluted fragments containing m6A (IP) and the untreated input control fragments were converted to final cDNA library. The average insert size for the paired terminal libraries was ~100 ± 50 bp. And then we performed the paired-end 2×150bp sequencing on an Illumina Novaseq™ 6000 platform at the LC-BIO Bio-tech ltd (Hangzhou, China) following the vendor's recommended protocol.

treatment_protocol: The isolated myoblasts were cultured to 80% density in the growth medium (GM), and then myogenic differentiation was induced in the differentiation medium for 4 days (DM).

tag: breed

value: Qinchuan cattle

value: Newborn cattle

value: longissimus dorsi muscle

tag: antibody


title: KG1a_ATF4_chip

first: Yan

last: Sun

address: Zhong shan 2nd Road, Building 74

institute: Sun Yat-sen University

data_processing:
Basecalls performed using CASAVA version 1.4
ChIP-seq data were mapped to the human genome (GRCh38) or mouse genome (GRCm38 ) by using Bowtie2
Data were filtered using the following specifications…
ChIP peaks were called using model-based analysis of ChIP-seq 14 (MACS2), with the input sample as the control.
Enrichment heatmaps that surrounds ChIP peaks were produced by using deeptools, and signal plotting of individual genes was generated using the Integrated Genome Viewer
Genome_build: GRCh38 and GRCm38
Supplementary_files_format_and_content: peak were called using macs2

growth_protocol: KG1a cells culture:  To make the complete growth medium, add the following components to the base medium: fetal bovine serum to a final concentration of 20%.

extract_protocol:
The ChIP procedure was performed according to a previously described protocol (Lee et al., 2006; Ying et al., 2017), using 10mg anti-ATF4 antibody (Abcam)
Enriched DNA fragments were subjected to the preparation of standard libraries for ChIP-seq, according to the manufacturer’s instructions, and the resulting ChIP-seq libraries were sequenced on an Illumina Hi-seq X-Ten (Annoroad Gene Technology Co., Ltd).

tag: cell type

value: acute myeloid leukemia (AML) cell line

tag: cell line

tag: chip antibody

value: anti-ATF4 antibody (Abcam, ab184909)


title: KG1a_ATF4_input


title: HNSC063T1Tu_S53_S33

value: tumor


title: DM_IP_Rep2


title: DM_IP_Rep1


title: HNSC063T1Tr_S47_S44


title: DM_input_Rep3

data_processing:
Cutadapt and perl scripts in house were used to remove the reads that contained adaptor contamination, low quality bases and undetermined bases.
The sequence quality was verified using fastp.
We used HISAT2 to map reads to the genome of bos taurus (Version: V96) with default parameters. Mapped reads of IP and input libraries were provided for R package exomePeak, which identifies m6A peaks with bed or bam format that can be adapted for visualization on the UCSC genome browser or IGV software (http://www.igv.org/).
MEME and HOMER were used for de novo and known motif finding followed by localization of the motif with respect to peak summit by perl scripts in house.
Called peaks were annotated by intersection with gene architecture using ChIPseeker.
Then StringTie was used to perform expression level for all mRNAs from input libraries by calculating FPKM (FPKM=[total_exon_fragments/mapped_reads(millions)×exon_length(kB)]).
Genome_build: ARS-UCD1.2
Supplementary_files_format_and_content: tab-delimited text files include FPKM values for each Sample
Supplementary_files_format_and_content: peak text files


title: DM_input_Rep1


title: DM_input_Rep2


title: lnc_PC4


title: HNSC062T1St_S58_S15


title: P2

value: Lung

tag: Sex


title: lnc_PC2


title: GM_IP_Rep3

source_name: myoblasts

tag: age


title: PC-3 cells with high metastatic potential M2

city: Barcelona

first: Marta

last: Garcia Lopez

address: Pg. de la Vall d'Hebron, 119-129

department: Oncology

country: Spain

institute: Vall d'Hebron Research Institute

description: test

data_processing:
Relative expression levels were calculated according to the 2-ΔΔCt method normalizing by RNU48 snRNA.
Fold Change worksheet reports PC-3-BM/PC-3 ratios.

label: SYBER green

source_name: highly metastatic PC-3 cells

label_protocol: Total RNA was reverse transcribed, using an ABI Taqman miRNA reverse transcription kit (Applied Biosystems, CA, USA). MiRNA expression was profiled with the TaqMan® Array Human MicroRNA A and B Cards Set v3.0 (Applied Biosystems). All reactions were performed as specified in the manufacturer's protocols. Cards were run in a 7900HT Fast Real-Time PCR System (Applied Biosystems) under the following thermal cycler conditions: 55ºC for 2 minutes and 95ºC for 10 minutes, followed by 40 cycles of 95ºC for 15 seconds and 55ºC for 1 minute.

growth_protocol: Prostate cancer cells were grown in immunocompromised mice

extract_protocol: Total RNA was extracted with miRNeasy Mini Kit (Qiagen) following the instructions provided by the manufacturer.

treatment_protocol: Metastatic prostate cancer cells were isolated from bones

value: prostate cancer cell line PC-3

tag: metastatic potential

value: high


title: PC-3 cells with low metastatic potential C3

description: control

source_name: parental PC-3 cells

value: poor


title: PC-3 cells with low metastatic potential C2

description: control


title: GM_IP_Rep2


title: GM_IP_Rep1


title: GM_input_Rep3


title: PC-3 cells with high metastatic potential M1

description: test


title: GM_input_Rep2


title: HNSC062T1Tr_S89_S23

value: treg


title: GM_input_Rep1


title: HNSC059T1Tu_S38

value: Head & Neck


title: HNSC061T1_Tr_S51

value: Head & Neck cancer


title: HNSC057T1Tu_S21_S35


title: HNSC057T1St_S23_S3


title: HNSC057T1Tr_S45_S45


title: HNSC056_T1_rna_tumor_S36


title: HNSC056T1_Tr_S3


title: HNSC056_T1_rna_stroma_S18


title: HNSC054T1St_S36


title: HNSC054T1Tr_S24


title: HNSC031T1_St_S25


title: HNSC031T1_Tr_S34


title: HNSC026T1Tr_S86_S48


title: HNSC061T1_Tu_S40


title: HNSC030T1Tr_S227


title: HNSC024T1_Tu_S29