title: APP-TG-Cel-THC, snRNAseq

city: San Antonio

first: Chu

state: Texas

address: 7703 Floyd Curl Dr

department: Cellular and Integrative Physiology

institute: UT Health San Antonio

description:
Library name: sample_APP-TG-Cel-THC
10x Genomics

data_processing:
The demultiplexing, barcoded processing, gene counting and aggregation were  generated by using Cellranger 8.0
Ambient RNA was removed using Cellbender
Assembly: mm10
Supplementary files format and content: matrix h5 files
Supplementary files format and content: seurat RDS files

source_name: Hippocampus

extract_protocol:
Tissue samples were subjected to lysis in 1 ml of lysis buffer (10 mM Tris-HCl, 5% Nonidet P40, 3 mM MgCl2, and 10 mM NaCl) along with 1 U/μl RNasin Plus RNase Inhibitor (Promega) for 15 minutes in a douncing tube placed on ice. The tissue was then homogenized using a loose pestle with ten dounces. The resulting suspension was filtered through a 70 μm mesh and centrifuged at 500 g for 5 minutes at 4°C. Post-lysis, the sample was treated with 2 ml of ice-cold nucleus wash buffer (5% wt/vol BSA, 0.25% wt/vol glycerol, 40 U/mL Protector RNAse inhibitor, 0.5X PBS), passed through a 20 μm mesh twice, and re-centrifuged under the same conditions. The supernatant was discarded, and the nuclear pellet was resuspended in 500 μl of wash buffer. An additional 500 μl of 50% (wt/vol) iodixanol (Optiprep) working solution was added to aid in further cleaning. This suspension was then layered over 1 mL of 29% (wt/vol) iodixanol solution in a 2 mL centrifuge tube and centrifuged at 10,000g for 30 minutes at 4°C. Finally, the nuclei were resuspended in a suitable volume of nuclei buffer to achieve a concentration of 500-1,000 nuclei/μl for subsequent capture.
Library was constructed according to manufacter's instructions (https://cdn.10xgenomics.com/image/upload/v1668017706/support-documents/CG000315_ChromiumNextGEMSingleCell3-_GeneExpression_v3.1_DualIndex__RevE.pdf).

value: Hippocampus

value: Brain cells

value: 5xFAD mice


title: r1_ST_HMinput

status: Public on Dec 04 2025

type: SRA

city: Vienna

first: Andreas

last: Lackner

address: Schwarzspanierstrasse 17

department: Center for Anatomy and Cell Biology

country: Austria

institute: Medical University of Vienna

library_source: genomic

data_processing:
adapter and quality trimming; cutadapt
genomic alignment; bowtie2
peakcalling; Genrich
read counts and normalization; DiffBind
bigwig generation; deeptools
Assembly: GENCODE V38
Supplementary files format and content: Genrich peaks considering all matched replicates and inputs
Supplementary files format and content: Bigwig of ChIP signal

molecule: genomic DNA

organism: Homo sapiens

source_name: placenta

extract_protocol:
The cells were fixed with 1% formaldehyde (ThermoFisher, 28908) for 7 minutes at room temperature. The reaction was quenched by 0.125M glycine. The cells were harvested in PBS containing 1x complete EDTA-free Protease inhibitor cocktail (Sigma Aldrich, 5056489001), centrifuged, and resuspended in ice-cold immunoprecipitation (IP) buffer. IP buffer was freshly made by 2:1 mixture of SDS buffer (100mM NaCl, 50mM Tris pH8, 5mM EDTA pH8, 0.5% SDS) and TritonX buffer (100mM NaCl, 100mM Tris pH 8.6, 5mM EDTA pH8, 5% TritonX) and 1x complete EDTA-free Protease inhibitor cocktail. Sonication was performed using Bioruptor Pico (Diagenode) at 4°C for 23 cycles, 15 seconds ON/ 30 seconds OFF. 30µg (for transcription factors) and 10µg (for histone modifications) of chromatin (DNA equivalent) were immunoprecipitated at 4°C overnight with primary antibodies. Detailed information on antibodies is provided in Table X. at the end of this chapter. Spike in chromatin (Active Motif, 53083) and Spike in antibody (Active Motif, 61686) were used for normalization of sample processing bias, technical variation, and monitoring of inhibitory effects. Protein G Dynabeads (Invitrogen, 10004D) were blocked in IP buffer supplemented with 1mg/mL BSA (New England Biolabs, B9000S) and yeast tRNA for 60 minutes at 4°C. Next, the beads were washed and added to the immunoprecipitation reaction for 3 hours at 4°C. The samples were washed with low salt buffer (50mM HEPES pH7.5, 140mM NaCl, 1%TritonX, 1x complete EDTA-free Protease inhibitor cocktail), high salt buffer (50mM HEPES pH7.5, 500mM NaCl, 1%TritonX, 1x complete EDTA-free Protease inhibitor cocktail) and TE buffer. Each sample was eluted in 200µL of ChIP elution buffer (100Mm NaHCO3, 1%SDS) and de-crosslinked using 0.2M NaCl at 65°C, 600 rpm overnight. On the next day, the samples were treated with RNAse A (60 minutes at 37°C, 600 rpm) and Proteinase K (30 min at 65°C). The samples were purified with MinElute PCR purification kit (QIAGEN). The DNA content was quantified by QUBIT dsDNA HS assay kit (ThermoFisher, Q33230). 10ng of DNA per sample was used for library preparation using NEBNext Ultra II DNA library preparation master mix (New England Biolabs, E7645).
NEBnext Ultra II

tag: tissue

value: placenta

tag: cell line

tag: cell type

value: ST

tag: genotype

value: WT

tag: treatment

value: Forskolin


title: Rned500/pFL, bio-repeat 3

city: Taipei

first: Sue

last: Lin-Chao

address: 128 Academia Road, Section 2, Nankang,

department: Institute of Molecular Biology

country: Taiwan

institute: Academia Sinica

library_source: transcriptomic

data_processing:
The single-end, 76-bp raw sequencing reads for each sample were aligned to the reference genome and transcriptome of E. coli. (GCF_000005845.2; ASM584v2) using STAR (v 2.7.10)
The read counts of 4,626 genes, including 92 spike-in ERCC RNAs, were estimated by RSEM (v1.3.3)
The spike-in ERCC RNAs as the internal control showed the highly correlation (> 0.9) with the input concentration. Subsequently, the read-count-per-gene measurements were normalized across all samples using ERCC RNAs according to the method in Potts AH et. al.
The normalization factors, k values, were calculated for the 24 most abundant RNAs in the ERCC spike-in (top 6 abundances from each A, B, C and D group) from a WT sample, R419-R-177_S1, and the geometric average of these was then used as the library normalization factor.
Assembly: ASM584v2
Supplementary files format and content: tab-delimited text file includes raw read counds for each sample

molecule: total RNA

organism: Escherichia coli K-12

source_name: bacterial cell

growth_protocol: Overnight E. coli liquid culture were stab into 0.35 % soft agar plate and incubate at 30 ℃ for 24 h. Plasmid ectopic expressed proteins are under the transcription control of rne native promoter.

extract_protocol:
To extract RNA from plate culture, we collected ~ 3 to 4 ml of soft-agar into 50 ml falcon tube. Bacterial enzymatic activity was stop by incubating in 8 ml of stop solution for 3 min. Soft-agar that contained bacterial cells were pelleted by centrifugation at 12,000 rpm, 5 min, 4 ℃. After that, agar pellets were resuspended in 4 ml of KJ medium and 4 ml of lysis buffer. To lyse the bacteria in soft-agar, the mixture was boiled in hot water for 3 min. Total RNE were extracted by adding 4 ml of acid phenol (pH 4.5) and mixed thoroughly by slowly inverting the tube ~ 30 times. Total RNA were extracted in aqueous phase by centrifugation at 4000 g, 1 h, 4 ℃. Total RNA were precipitated in 1 volume of isopropanol and 1/10 volume of 3 M sodium acetate (pH 7.8) at – 20 ℃ for at least 2 h as described above. All RNA samples were maintained in isopropanol at – 20 ℃ before further experiments.
five ug total RNA with ERCC control RNA were prepared for libraries using  Ribominus bacteria 2.0  Kit (ThermoFisher A47335) and Illumina TruSeq total  RNA standard Sample Prep protocol.RNAseq on Illumina NextSeq 500 platform as single read 75 bp.

treatment_protocol: Stop solution (95 % EtOH, 5 % phenol saturated with buffer, pH 6.6-7.9) was added to plate culture to stop all enzymatic activity before sujected for RNA isolation.

value: bacterial cell

tag: phenotype

value: full-length RNase E


title: APP-TG-Cel, snRNAseq

last: Chen

country: USA

description:
Library name: sample_APP-TG-Cel
10x Genomics

molecule: nuclear RNA

organism: Mus musculus

value: Celecoxib


title: Rned500/pFL, bio-repeat 2


title: r1_ST_BRG1

description: BRG1_ST_215351vs215349_215381vs215379_223300vs223298_a20_ATACmode.narrowPeak


title: NRK-49F, siControl, TGFb, Input

city: Tianjin

first: Zhiheng

last: Liu

state: Tianjin

address: No.22 Qixiangtai Road

department: Tianjin Research Center for Basic Medical Science

country: China

institute: Tianjin Medical University

description: Library name: siCtrl_TGFb_Input

data_processing:
Reads were trimmed using Trim Galore
Aligned to the rat reference genome (rn6) using Bowtie (v2.3.5.1).
Visualization of ChIP-seq data, including heatmaps and profile plots, was conducted using deepTools
For RNA, gene quantification was performed with featureCounts
Assembly: rat reference genome (rn6)
Supplementary files format and content: bigwig
Supplementary files format and content: FPKM table

organism: Rattus norvegicus

source_name: cell line

growth_protocol: NRK-49F cells were procured from the American Type Culture Collection (ATCC) and maintained in Dulbecco’s Modified Eagle’s Medium (DMEM, GIBCO) supplemented with 4.5 g/L glucose and 10% fetal calf serum (Viva cells) at 37°C in a 5% CO2 atmosphere.

extract_protocol:
Total RNA was extracted from cells using TRIzol, and its integrity was evaluated using a Qubit 4 analyzer.ChIP enriched DNA fragments were extracted and evaluated using a Qubit 4 analyzer.
The DNA fragments were utilized for library amplification using a VAHTS Universal Library Prep Kit (ND601, Vazyme) following the manufacturer’s instructions.

treatment_protocol: Prior to treatment, NRK-49F cells were starved for 24 hours with DMEM containing 0.2% FBS and then exposed to 5 ng/μL of TGF-β1 (240-B, R&D Systems). For methionine restriction (MetR) treatment, the medium was composed of Eagle's balanced salt solution 10x (E7510, Sigma-Aldrich), MEM vitamins solution 100x (M6895, Sigma-Aldrich), NaHCO3, dialyzed FBS (04-011-1B, Viva cells), MilliQ water, and amino acids at the following concentrations: L-methionine (Met, 200 μM for Ctrl, 30 μM for MetR).

value: cell line

value: Fibroblast

value: siControl+TGFb


title: Rned500/pFL, bio-repeat 1


title: APP-TG-THC, snRNAseq

description:
Library name: sample_APP-TG-THC
10x Genomics


title: r1_ST_BRM

description: BRM_ST_215350vs215349_215380vs215379_223299vs223298_a20_ATACmode.narrowPeak


title: r1_ST_TFinput


title: r1_SR_BRM014_H3K4me3

description: H3K4me3_SRinh_215348vs215346_215372vs215370_223297_223294_def.narrowPeak

value: hTSC


title: WT, snRNAseq.

description:
Library name: sample_WT-Veh
10x Genomics

value: Wild type

value: Vehicle


title: S15_decidualization oocktail + ET-1-3

city: chapel Hill

first: Feng

last: Li

state: NC

address: 101 medical drive

department: Pathology

institute: UNC at CH

description: Library name: S15

data_processing:
These raw sequences were aligned to the ensembl gene database using the SALMON aligner, followed by annotation using Gencode v44. Quantification of gene expression levels was conducted with the Stringtie transcriptome aligner. Utilizing a Python script (prepDE.py) provided by Stringtie, count matrices for genes and transcripts were generated from the output files.
Assembly: ensembl
Supplementary files format and content: text file
Supplementary files format and content: csv. File

source_name: HESC

extract_protocol:
Total cell RNA was extracted using RNeasy mini kit (Qiagen, Hilden, Germany) according to the manufacture’s protocol.
Library preparation and sequencing were performed by High Throughput Sequencing Facility at UNC Chapel Hill. Paired-end raw sequences of 100 bp were acquired by NextSeq 2000 (Illumina, San Diego, CA), and subsequent demultiplexing was performed using bclconvert with a 1-mismatch threshold to segregate reads based on indexes.

value: HESC

value: endometrial stromal


title: NRK-49F, siControl, Pol II Ser2P ChIP

description: Library name: siCtrl_S2P

value: siControl


title: NRK-49F, siControl, Input

description: Library name: siCtrl_Input


title: NRK-49F, siControl, TGFb, Hoxc8 ChIP

description: Library name: siCtrl_TGFb_HOXC8


title: Sample 6-4, UUO surgery + Late intervention

city: Toronto

first: Andrew

last: Advani

state: Ontario

address: 6-151 61 Queen Street East

department: Medicine

country: Canada

institute: St. Michael's Hospital

description: Library name: Sample 24

data_processing:
Image analysis and base calling were performed using Solexa pipeline v1.8 (Off-Line Base Caller software, v1.8) Trimmed reads (trimmed 5’, 3’-adaptor bases using cutadapt) were aligned to reference genome using Hisat2 software Transcript abundances for each sample were estimated with StringTie, and the FPKM value for gene and transcript level were calculated with R package Ballgown
Assembly: GRCm38
Supplementary files format and content: FPKM values for each sample

source_name: Left kidney

extract_protocol:
Total RNA from kidney tissue was isolated using Trizol and quantified using NanoDrop ND-1000.
Total RNA was used to prepare sequencing libraries with a KAPA Stranded RNA-Seq Library Prep Kit (Illumina)

value: Left kidney

value: Wildtype

value: UUO surgery + Late intervention


title: r1_ST_H3K4me3

description: H3K4me3_ST_215354vs215352_215378vs215376_223304_223301_def.narrowPeak

value: placenta

value: ST

value: WT


title: r1_SR_BRM014_HMinput


title: S13_decidualization oocktail + ET-1 + medium dose NAM-3

description: Library name: S13

value: DC+ET1+1mM NAM-3


title: Sample 6-3, UUO surgery + Late intervention

description: Library name: Sample 23


title: NRK-49F, siControl, Hoxc8 ChIP

description: Library name: siCtrl_HOXC8


title: r1_SR_BRM014_BRG1

description: BRG1_SRinh_215345vs215343_215369vs215367_223293vs223291_a20_ATACmode.narrowPeak


title: r1_SR_BRM014_BRM

description: BRM_SRinh_215344vs215343_215368vs215367_223292vs223291_a20_ATACmode.narrowPeak


title: S11_decidualization oocktail + ET-1 + medium dose NAM-1

description: Library name: S11

value: DC+ET1+1mM NAM-1


title: Sample 6-2, UUO surgery + Late intervention

description: Library name: Sample 22


title: APP-TG-Veh, snRNAseq

description:
Library name: sample_APP-TG-Veh
10x Genomics

value: Hippocampus

value: Brain cells

value: 5xFAD mice


title: NRK-49F, TGFb, MetR, H3K4me3 ULI-NChIP

description: Library name: NRK49F_TGFb_MetR_H3K4me3

value: cell line

value: Fibroblast

value: TGFb+MetR


title: Sample 6-1, UUO surgery + Late intervention

description: Library name: Sample 21


title: Sample 5-4, Sham surgery + Late intervention

description: Library name: Sample 20

value: Sham surgery + Late intervention


title: NRK-49F, TGFb, MetR, H3K36me3 ULI-NChIP

description: Library name: NRK49F_TGFb_MetR_H3K36me3


title: r1_SR_BRM014_TFinput

value: hTSC


title: r1_SR_H3K4me3

description: H3K4me3_SR_215342vs215364_215366vs215340_223290_223287_def.narrowPeak


title: Sample 5-3, Sham surgery + Late intervention

description: Library name: Sample 19


title: S9_decidualization oocktail + ET-1 + high dose NAM-2

description: Library name: S9

value: HESC

value: endometrial stromal

value: DC+ET1+10mM NAM-2


title: NRK-49F, TGFb, ULI-NChIP Input

description: Library name: NRK49F_TGFb_Input

value: TGFb


title: r1_SR_HMinput

value: placenta


title: Sample 5-2, Sham surgery + Late intervention

description: Library name: Sample 18

value: Left kidney

value: Wildtype


title: NRK-49F, TGFb, H3K4me3 ULI-NChIP

description: Library name: NRK49F_TGFb_H3K4me3


title: r1_SR_BRG1

description: BRG1_SR_215339vs215337_215363vs215361_223286vs223284_a20_ATACmode.narrowPeak

value: WT


title: Sample 5-1, Sham surgery + Late intervention

description: Library name: Sample 17


title: kidney, control, untreated, rep2

city: Hangzhou

first: Cao

last: Jiawei

address: No. 1630 Huan Ding Road, Shangcheng District

institute: Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University

description:
Library name: Sample 2
C2

data_processing:
Reads obtained from the sequencing machines includes raw reads containing adapters or low quality bases which will affect the following assembly and analysis. Thus, to get high quality clean reads, reads were further filtered by Cutadapt (https://cutadapt.readthedocs.io/en/stable/,version:cutadapt-1.9). We aligned reads of all samples to the research species reference genome using HISAT2 (https://daehwankimlab.github.io/hisat2/,version:hisat2-2.2.1) package, which initially remove a portion of the reads based on quality information accompanying each read and then maps the reads to the reference genome.
The mapped reads of each sample were assembled using StringTie (http://ccb.jhu.edu/software/stringtie/,version:stringtie-2.1.6) with default parameters. Then, all transcriptomes from all samples were merged to reconstruct a comprehensive transcriptome using gffcompare software(http://ccb.jhu.edu/software/stringtie/gffcompare.shtml,version:gffcompare-0.9.8). After the final transcriptome was generated, StringTie and ballgown (http://www.bioconductor.org/packages/release/bioc/html/ballgown.html) were used to estimate the expression levels of all transcripts and perform expression abundance for mRNAs by calculating FPKM (fragment per kilobase of transcript per million mapped reads) value.
Genes differential expression analysis was performed by DESeq2 software between two different groups (and by edgeR between two samples). The genes with the parameter of false discovery rate (FDR) below 0.05 and absolute fold change ≥ 2 were considered differentially expressed genes. Differentially expressed genes were then subjected to enrichment analysis of GO functions and KEGG pathways.
Assembly: Ensembl_v104
Supplementary files format and content: tab-delimited text files include FPKM values for each Sample

source_name: kidney

extract_protocol:
Total RNA was extracted using Trizol reagent (thermofisher, 15596018) following the manufacturer's procedure. The total RNA quantity and purity were analysis of Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA, 5067-1511) , high-quality RNA samples with RIN number > 7.0 were used to construct sequencing library.
mRNA was purified from total RNA (5ug) using Dynabeads Oligo (dT) (Thermo Fisher, CA, USA) with two rounds of purification. Following purification, the mRNA was fragmented into short fragments using divalent cations under elevated temperature (Magnesium RNA Fragmentation Module (NEB, cat.e6150, USA) under 94℃ 5-7min). Then the cleaved RNA fragments were reverse-transcribed to create the cDNA by SuperScript™ II Reverse Transcriptase (Invitrogen, cat. 1896649, USA), which were next used to synthesise U-labeled second-stranded DNAs with E. coli DNA polymerase I (NEB, cat.m0209, USA), RNase H (NEB, cat.m0297, USA) and dUTP Solution (Thermo Fisher, cat.R0133, USA). An A-base was then added to the blunt ends of each strand, preparing them for ligation to the indexed adapters. Each adapter contained a T-base overhang for ligating the adapter to the A-tailed fragmented DNA. Dual-index adapters were ligated to the fragments, and size selection was performed with AMPureXP beads. After the heat-labile UDG enzyme (NEB, cat.m0280, USA) treatment of the U-labeled second-stranded DNAs, the ligated products were amplified with PCR by the following conditions: initial denaturation at 95℃ for 3 min; 8 cycles of denaturation at 98℃ for 15 sec, annealing at 60℃ for 15 sec, and extension at 72℃ for 30 sec; and then final extension at 72℃ for 5 min. The average insert size for the final cDNA librarys were 300±50 bp. At last, we performed the 2×150bp paired-end sequencing (PE150) on an Illumina NovaseqTM 6000 following the vendor's recommended protocol.

value: kidney

value: injected with saline


title: NRK-49F, TGFb, H3K36me3 ULI-NChIP

description: Library name: NRK49F_TGFb_H3K36me3


title: r1_SR_BRM

description: BRM_SR_215338vs215337_215362vs215361_223285vs223284_a20_ATACmode.narrowPeak


title: S6_decidualization oocktail-3

description: Library name: S6


title: NRK-49F, control, ULI-NChIP Input

description: Library name: NRK49F_Control_Input

value: Control


title: r1_SR_TFinput


title: S5_decidualization oocktail-2

description: Library name: S5


title: S10_decidualization oocktail + ET-1 + high dose NAM-3

description: Library name: S10

value: DC+ET1+10mM NAM-3


title: r1_SR_H3K27ac

description: H3K27ac_SR_215328_223313vs215340_223277vs215364_223289_223287_def.narrowPeak


title: Sample 4-3, UUO surgery + Early intervention

description: Library name: Sample 15

value: UUO surgery + Early intervention


title: S12_decidualization oocktail + ET-1 + medium dose NAM-2

description: Library name: S12

value: DC+ET1+1mM NAM-2


title: Sample 4-2, UUO surgery + Early intervention

description: Library name: Sample 14


title: NRK-49F, control, H3K4me3 ULI-NChIP

description: Library name: NRK49F_Control_H3K4me3

value: cell line

value: Fibroblast


title: NRK-49F, control, H3K36me3 ULI-NChIP

description: Library name: NRK49F_Control_H3K36me3


title: S4_decidualization oocktail-1

description: Library name: S4


title: S8_decidualization oocktail + ET-1 + high dose NAM-1

description: Library name: S8

value: DC+ET1+10mM NAM-1


title: Sample 4-1, UUO surgery + Early intervention

description: Library name: Sample 13


title: S3_control group-3

description: Library name: S3

value: HESC


title: r1_SR_H2BK20ac

description: H2B_SR_215327_223312vs215340_223276vs215364_223288_223287_a500.narrowPeak

value: hTSC


title: NRK-49F, TGFb, MetR, ULI-NChIP Input

description: Library name: NRK49F_TGFb_MetR_Input

value: TGFb+MetR


title: Sprague-Dawley rat,ARC_352_IP RNA

city: Shanghai

first: xiaoqin

last: yin

address: 355 Luding Road, Putuo District

institute: School of medicine, Shanghai Jiao Tong University

data_processing:
Base calling software: BCL convert
Data filter: fastp(0.19.4)，remove adapters, repeat sequences and low quality sequences
reads alignment : HISAT2(2.0.4)
Peak calling diffpeak : R package: exomePeak (1.5.0)
Peak annotation : ANNOVAR
Assembly: eg GRCH38
Supplementary files format and content: ARC_212_IPVSARC_212_input_peak.xlsx,ARC_352_IPVSARC_352_input_peak.xlsx,which contain methylation site information of m6A
Supplementary files format and content: ARC_352VSARC_212_diffPeak_result.xlsx, which contains the results of differential methylation sites

molecule: polyA RNA

source_name: arucate nucleus of hypothalamus

extract_protocol:
Total RNA was isolated and purified using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer's procedure. The RNA amount and purity of each sample was quantified using NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA), and the RNA integrity was assessed by Bioanalyzer 2100 (Agilent, CA, USA). Poly (A) RNA was purified from 50μg total RNA using Dynabeads Oligo (dT)25-61005 (Thermo Fisher, CA, USA) by two rounds of purification.
the poly(A) RNA was fragmented into small pieces using Magnesium RNA Fragmentation Module (NEB, cat.e6150, USA) under 86℃ 7min. The cleaved RNA fragments were incubated for 2h at 4℃ with m6A-specific antibody (No. 202003, Synaptic Systems, Germany) in IP buffer (50 mM Tris-HCl, 750 mM NaCl and 0.5% Igepal CA-630). The IP RNA was reverse-transcribed to cDNA by SuperScript™ II Reverse Transcriptase (Invitrogen, cat. 1896649, USA), which was next used to synthesise U-labeled second-stranded DNAs with E. coli DNA polymerase I (NEB, cat.m0209, USA), RNase H (NEB, cat.m0297, USA) and dUTP Solution (Thermo Fisher, cat.R0133, USA）. An A-base was added to the blunt ends of each strand, preparing for ligation to the indexed adapters. Dual-index adapters were ligated to the fragments, and size selection was performed with AMPureXP beads. After the heat-labile UDG enzyme (NEB, cat.m0280, USA) treatment of the U-labeled second-stranded DNAs, the ligated products were amplified with PCR by the following conditions: initial denaturation at 95℃ for 3 min; 8 cycles of denaturation at 98℃ for 15 sec, annealing at 60℃ for 15 sec, and extension at 72℃ for 30 sec; and then final extension at 72℃ for 5 min. At last, we performed paired-end sequencing (PE150) on an Illumina Novaseq™ 6000 platform(LC-Bio Technology CO., Ltd., Hangzhou, China) following the vendor's recommended protocol
m6A-seq

tag: strain

value: Sprague-Dawley

tag: Sex

value: female

value: arucate nucleus of hypothalamus

tag: rip antibody


title: S2_control group-2

description: Library name: S2

value: endometrial stromal


title: Sprague-Dawley rat,ARC_352_Input RNA


title: 5_ST

data_processing:
adapter and quality trimming; cutadapt
genomic alignment; STAR
peakcalling; Genrich
read counts and normalization; DiffBind
bigwig generation; deeptools
Assembly: GENCODE V38
Supplementary files format and content: Genrich peaks

source_name: ST

extract_protocol:
The cells were treated with DNase I (Worthington, LS002006,final concentration 200 Kunitz units/mL) for 30 minutes at 37°C. Next, the cells were harvested using TrypLE as described above, washed with PBS, counted and 50000 cells were aliquoted into DNA LoBinding tubes (Eppendorf, EP0030108051). The cell pellet was resuspended in ice-cold ATAC-seq Lysis Buffer (10mM Tris pH7.5, 10mM NaCl, 3mM MgCl2, 0.1% Nonidet P40, 0.1% Tween20, 0.01% Digitonin) and incubated for 3 minutes on ice. The lysis was stopped by dilution with ice-cold ATAC-seq Wash buffer (10mM Tris pH7.5, 10mM NaCl, 3mM MgCl2, 0.1% Tween20). Then, the nuclei were pelleted and resuspended in Transposition mix (1x TD buffer and 2.5 µL TDE1 TD enzyme (both from Illumina, 20034198), 16.5 µL PBS, 0.01% digitonin, 0.1% Tween20). The transposition reaction was incubated for 30 minutes at 37°C 1000 rpm. The transposition reaction was terminated by addition of five-time volume of DNA Binding Buffer from DNA clean and concentrator-5 kit (Zymo Research, D4013) and cleaned up with DNA clean and concentrator-5 kit, following the manufacturer’s instruction. The library amplification and barcoding were done using NEBNext Ultra II DNA library preparation master mix (New England Biolabs, E7645) and purified with DNA clean and concentrator-5 kit (Zymo Research, D4013). The DNA content was quantified by QUBIT dsDNA HS assay kit (ThermoFisher, Q33230).
Tn5/NEBnext Ultra II

value: ST

value: WT

value: Forskolin


title: Sample 3-3, Sham surgery + Early intervention

description: Library name: Sample 11

value: Left kidney

value: Wildtype

value: Sham surgery + Early intervention


title: Sprague-Dawley rat,ARC_212_IP RNA

value: m6A-specific antibody (No. 202003, Synaptic Systems, Germany)


title: S1_control group-1

description: Library name: S1


title: 5_SRBRM

source_name: TSC

value: TSC


title: TSC differentiation into EVT, Control, KD, rep3

city: Rensselaer

first: Bum-Kyu

last: Lee

state: New York

address: One Discovery Drive, Cancer Research Center, RM332

institute: University of Albany-SUNY

description: Library name: EVT_Cont_KD_rep3

data_processing:
Paired-end reads were aligned to human transcript (hg38) using Salmon mapper  (v1.10.2)
Expression levels of each gene were calculated using R library tximport as transcripts per million (TPM). The read counts were quantified and normalized by median of ratio method and differentially expressed genes (DEGs) were obtained with the selection criteria of P-adjusted value < 0.01 and fold change > 2 using the R package DESeq2 (v1.30.1).
Assembly: hg38
Supplementary files format and content: xlsx, TPM

source_name: Placenta

extract_protocol:
mRNAs were enriched from total RNAs with Magnetic mRNA Isolation Kit (oligo(dT) beads) (NEB, E7490), and then cDNAs were synthesized using random primers. cDNAs were purified by NEBNext Sample Purification Beads (NEB, E7767). End prep reactions were performed followed by ligation with a sample-specific adaptor and index.
RNA sequencing was conducted to characterize global transcriptional profiles. Libraries were prepared from 500 ng total RNA using the NEBNext Ultra II RNA Library Prep Kit (NEB, E7770). Polyadenylated mRNA was enriched via oligo(dT) magnetic beads (NEB, E7490), followed by cDNA synthesis with random primers and purification using NEBNext Sample Purification Beads (NEB, E7767). Double-stranded cDNA underwent end repair, adapter ligation (with unique barcodes), and PCR amplification.

treatment_protocol: Total RNAs were extracted using the RNeasy plus mini kit following the manufacturer’s instructions. RNA-seq libraries were generated with 500 ng of total RNA using NEB Next Ultra II RNA Library prep kit (NEB, E7770) following the manufacturer’s protocol.

value: Placenta

value: TSC-derived EVT

value: TSC differentiation into EVT


title: Sample 3-4, Sham surgery + Early intervention

description: Library name: Sample 12


title: Sprague-Dawley rat,ARC_212_Input RNA


title: TSC differentiation into EVT, Control, KD, rep2

description: Library name: EVT_Cont_KD_rep2


title: Sample 3-1, Sham surgery + Early intervention

description: Library name: Sample 9


title: s12_Disease

city: Jacksonville

first: Yingxue

last: Ren

state: FL

address: 4500 San Pablo Rd S

institute: Mayo Clinic

description: Library name: s12

data_processing:
Reads were aligned to the human reference genome hg38. Mayo Clinic RNA-Seq analytic pipeline (MAP-RSeq Version 3.1.3) was used to generate raw gene read counts and sequencing quality control metrics. Raw gene counts were corrected for gene length differences, GC bias, and global technical variations through Conditional Quantile Normalization (CQN).
Assembly: hg38
Supplementary files format and content: .tsv file of combined raw gene counts

source_name: iPSC-derived astrocytes

growth_protocol: NPCs from isogenic control and SLOS iPSCs were seeded at 1 ×105 cells/well cultured on Matrigel-coated 6 well-plates in astrocyte differentiation medium composed of astrocyte medium (ScienCell) with CNTF (10 ng/ml; Stem Cell Technologies), BMP4 (10 ng/ml; Stem Cell Technologies), and Heregulin-β1 (10 ng/ml; Stem Cell Technologies) for 1 week.

extract_protocol:
Total RNA was isolated from iPSC-derived astrocytes with RNeasy Mini Kit (Qiagen)
Libraries were constructed according to the manufacturer’s instructions and were sequenced by an Illumina HiSeq 4000

treatment_protocol: The culture medium was switched to astrocyte maintenance medium composed of astrocyte medium with CNTF (20 ng/ml) 1 week after the differentiation. The medium was changed every 2 days, and the cells were passaged every 5–7 days with dissociation using TrypLE Express (Thermo Fisher Scientific). Astrocytes were used for experiments at day 45 after differentiation

value: iPSC-derived astrocytes

tag: group

value: Disease


title: TSC differentiation into EVT, Control, KD, rep1

description: Library name: EVT_Cont_KD_rep1


title: 5_STBRM

value: Forskolin + BRM014


title: 4_STBRM


title: s11_Disease

description: Library name: s11


title: Sample 2-4, UUO surgery + Vehicle

description: Library name: Sample 8

value: UUO surgery + Vehicle


title: TSC differentiation into EVT, ATOH8, KD, rep2

description: Library name: EVT_ATOH8_KD_rep2

value: ATOH8 knockdown


title: s09_Disease

description: Library name: s09


title: Sample 2-2, UUO surgery + Vehicle

description: Library name: Sample 6


title: Sample 2-3, UUO surgery + Vehicle

description: Library name: Sample 7


title: TSC differentiation into EVT, ATOH8, KD, rep3

description: Library name: EVT_ATOH8_KD_rep3


title: 4_SRBRM

value: hTSC


title: 4_SR


title: Sample 2-1, UUO surgery + Vehicle

description: Library name: Sample 5


title: TSC differentiation into EVT, ATOH8, KD, rep1

description: Library name: EVT_ATOH8_KD_rep1


title: 3_STBRM

value: ST


title: Sample 3-2, Sham surgery + Early intervention

description: Library name: Sample 10


title: Sample 1-4, Sham surgery + Vehicle

description: Library name: Sample 4

value: Sham surgery + Vehicle


title: 5_SR

value: WT


title: 4_ST

value: Forskolin


title: 3_ST


title: AML_HSPC_UNC1999_AZA_Rep2, RNA-seq

city: Huddinge

first: Anna

last: Palau

address: Hälsovägen 9

country: Sweden

institute: Karolinska Institutet

data_processing:
Basecalling and demultiplexing were performed using Illumina bcl2fastq (v2.20.0). Sequence data quality was assessed using FastQC (v0.11.8). Counts for each gene were estimated using featureCounts (v1.5.1).
Assembly: Reads were aligned to the Ensembl GRCh38 reference genome using STAR (v2.7.9a).
Supplementary files format and content: tab-delimited text files containing raw read counts (HTSeq)

growth_protocol: control- and AML-iPSCs were differentiated into hematopoietic stem progenitor cells (HSPC) using a 13-day protocol based on Matsubara et al., with two modifications from the original protocol: the addition of IL3 (50 ng/mL) from day 4-13 and that we used clump passaged cells in our system. HSPCs were manually harvested and expanded and drug-treated for 72 hours in SFEMII medium, P/S (1%), SCF (50 ng/mL), IL3 (50 ng/mL), TPO (50 ng/mL), FLT3L (50 ng/mL), IL6 (10 ng/mL).

extract_protocol:
RNA was extracted from cells after drug treatments using AllPrep DNA/RNA Mini Kit (Qiagen), RNA from iPSCs were also collected (day 0).
Illumina stranded mRNA prep ligation sample preparation protocol was used with starting concentration between 25-1000 ng total RNA. The protocol includes mRNA isolation, cDNA synthesis, ligation of adapters and amplification of indexed libraries. The yield and quality of the amplified libraries was analyzed using Qubit by Thermo Fisher and quality was checked by using Agilent Tapestation. The indexed cDNA libraries were normalized and combined, and the pools were sequenced on the Illumina Nextseq 2000 P2 100 cycle sequencing run, generating 58 base paired end reads with dual index.

treatment_protocol: Cells were treated with DMSO as vehicle (1:2000), UNC1999 (2 µM), or UNC1999 (2 µM) + 5-Azacytidine (1 µM).

value: differentiated HSPC from iPSC

tag: time

value: 72 hours


title: s10_Disease

description: Library name: s10


title: 3_SRBRM


title: Sample 1-3, Sham surgery + Vehicle

description: Library name: Sample 3

value: Left kidney

value: Wildtype


title: Sample 1-2, Sham surgery + Vehicle

description: Library name: Sample 2


title: s05_Control

description: Library name: s05

value: Control


title: Sample 1-1, Sham surgery + Vehicle

description: Library name: Sample 1


title: s04_Control

description: Library name: s04


title: AML_HSPC_UNC1999_Rep3, RNA-seq


title: AML_HSPC_UNC1999_AZA_Rep1, RNA-seq


title: AML_HSPC_UNC1999_Rep2, RNA-seq


title: 2_STBRM


title: s06_Control

description: Library name: s06


title: s08_Disease

description: Library name: s08


title: 3_SR

value: TSC


title: WT BMDMs, control, replicate 3

city: Martinsried

first: Assa

last: Yeroslaviz

state: Bavaria

address: Am Klopferspitz 18

department: computational Biology

country: Germany

institute: Max-Planck-Institute for biochemistry

description: Library name: MH_7_S44

data_processing:
Reads were mapped to GRCh38 using STAR
reads were quantified using featureCounts
sample normalization and differential expression analysis was done using DESeq2
Assembly: GRCm38
Supplementary files format and content: tab-delimited file containing raw counts for each sample per column
Supplementary files format and content: tab-delimited file containing DESeq2-normalized counts for each sample per column

source_name: Bone marrow-derived macrophages

growth_protocol: WT and Cas9 bone marrow-derived macrophages (BMDMs) were maintained in DMEM supplemented with 10 % FBS (Biochrome) and 1 % Penicillin-Streptomycin and pullsed with human recombinant CSF1 (50 ng/mL) on day3 and 5.

extract_protocol:
For RNA extraction, cells were dissolved in 1 mL TRIzol™ reagent transferred into a 1.5 mL tube, and frozen at -80 °C overnight. The following day, samples were thawed on ice, and 200 µL chloroform was added. Samples were mixed and centrifuged at 18.000 g at 4 °C for 10 minutes before the colorless phase was transferred into a fresh 1.5 mL tube containing 500 µL 100 % isopropanol. After RNA precipitation at -20 °C overnight, samples were centrifuged, and the RNA pellets were washed with 70 % ethanol. Following the last centrifugation step and ethanol removal, pellets were air dried for ~ 5 min before 25 µL of nuclease-free was added.
Bulk mRNA sequencing libraries were prepared with 250ng of total RNA of each sample using the NEBNext Ultra™ II Directional RNA Library Prep Kit for Illumina® (E7760, NEB) with NEBNext® Poly(A) mRNA Magnetic Isolation Module (E7490, NEB), according to standard manufacturer’s protocol. Total RNA and the final library quality controls were performed using Qubit™ Flex Fluorometer (Q33327, Thermo Fisher Scientific) and 4200 TapeStation System (G2991BA, Agilent) before and after library preparation. The libraries were sequenced on Illumina NovaSeq 6000 SP flow cell (2 x 60 bp) and demultiplexed by bcl2fastq Conversion Software (Illumina).

treatment_protocol: After CSF1 differentiation cells were activated with either LPS + IFNg, IL4 + IL13, or a media control on day 7.

value: Bone marrow-derived macrophages

value: control

value: female


title: AML_HSPC_UNC1999_AZA_Rep3, RNA-seq


title: s07_Disease

description: Library name: s07

value: iPSC-derived astrocytes

value: Disease


title: Cas9 BMDMs, IL4_IL13, replicate 3

description: Library name: MH_52_S49


title: AML_HSPC_UNC1999_Rep1, RNA-seq


title: s02_Control

description: Library name: s02


title: 2_SRBRM


title: 2_ST


title: AML_HSPC_DMSO_Rep3, RNA-seq

value: DMSO


title: s01_Control

description: Library name: s01


title: Cas9 BMDMs, IL4_IL13, replicate 2

description: Library name: MH_49_S28


title: 2_SR

value: hTSC


title: Cas9 BMDMs, IL4_IL13, replicate 1

description: Library name: MH_46_S29


title: Ngn2_CD19_SETD1A_fs_mutant, rep3

city: New Brunswick

first: Zhiping

last: Pang

state: New Jersey

address: 89 French Street Floor 3, Room 3233

department: Child Health Institute of New Jersey

institute: Rutgers University

data_processing:
Raw fastq sequencing files were aligned with human reference genome (hg38) using HISAT2 for patient-specific mutation and STAR for frameshif mutation.
Raw counts of expressed genes were extracted using featureCounts from the Rsubread package.
Assembly: hg38
Supplementary files format and content: Samples x genes, raw counts

growth_protocol: Ngn2-iN cultures are fed with Neurobasal medium with 5%FBS and three growth factors (BDNF, GDNF and NT3).

extract_protocol:
Total RNA was prepared using Qiagen Rneasy kits, followed by poly(A) selection using oligo-dT magnetic beads.
Illumina TruSeq 3' RNA Library kits were used.

value: SETD1A heterozygous mutant c.4596_4597insG(p. Leu1533fs)


title: AML_HSPC_DMSO_Rep2, RNA-seq


title: AML_HSPC_DMSO_Rep1, RNA-seq


title: WT BMDMs, IL4_IL13, replicate 3

description: Library name: MH_43_S34


title: 1_STBRM

value: ST

value: Forskolin + BRM014


title: Ngn2_CD19_SETD1A_fs_mutant, rep2


title: WT BMDMs, IL4_IL13, replicate 2

description: Library name: MH_40_S30

value: WT


title: Ngn2_CD19_SETD1A_fs_control, rep2


title: 1_SRBRM


title: s03_Control

description: Library name: s03


title: 1_ST

value: Forskolin


title: AML_iPSC_Rep2, RNA-seq

value: iPSC


title: Ngn2_CD19_SETD1A_fs_control, rep1


title: WT BMDMs, control, replicate 2

description: Library name: MH_4_S41


title: AML_iPSC_Rep3, RNA-seq


title: Ngn2_CD15_SETD1A_fs_mutant, rep3


title: 1_SR


title: WT BMDMs, IL4_IL13, replicate 1

description: Library name: MH_37_S53


title: AML_iPSC_Rep1, RNA-seq


title: vCTB_BRM_P3

data_processing:
adapter trimming; bbduk
UMI extraction, UMItools
alignment; STAR (2.7.3c)
UMI collapsing; UMItools
Read count; htseq (version 0.11.2)
Assembly: GENCODE V38
Supplementary files format and content: count table of each submitted sample

extract_protocol:
RNA extraction was carried out using RNeasy mini/micro and DNAse I kit (all from QIAGEN) according to the manufacturer’s instruction. RNA quantification was carried out by Nanodrop (ThermoFisher) or RNA broad range QUBIT assay kit (ThermoFisher, Q10211).
Libraries were prepared using QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina - Dual Indexing, 96 UDI (Workflow B), Set B1 (Lexogen) following the manufacturer’s instructions.

value: placenta

value: vCTB


title: Cas9 BMDMs, LPS_IFNg, replicate 3

description: Library name: MH_34_S55


title: Ngn2_CD15_SETD1A_fs_mutant, rep2


title: control_HSPC_UNC1999_AZA_Rep2, RNA-seq

value: differentiated HSPC from iPSC

value: 72 hours


title: Ngn2_CD15_SETD1A_fs_control, rep3

value: Control


title: Cas9 BMDMs, LPS_IFNg, replicate 2

description: Library name: MH_31_S2

value: Bone marrow-derived macrophages


title: control_HSPC_UNC1999_AZA_Rep1, RNA-seq


title: Ngn2_CD15_SETD1A_fs_control, rep2


title: control_HSPC_UNC1999_Rep3, RNA-seq


title: vCTB_P3


title: vCTB_P2


title: WT BMDMs, LPS_IFNg, replicate 3

description: Library name: MH_25_S25

value: female


title: WT BMDMs, LPS_IFNg, replicate 2

description: Library name: MH_22_S19


title: Ngn2_CD07_SETD1A_fs_mutant, rep2


title: vCTB_P1


title: control_HSPC_UNC1999_Rep2, RNA-seq


title: control_HSPC_UNC1999_AZA_Rep3, RNA-seq


title: CT30_BRM2_P3


title: control_HSPC_UNC1999_Rep1, RNA-seq


title: control_HSPC_DMSO_Rep3, RNA-seq


title: Cas9 BMDMs, control, replicate 3

description: Library name: MH_16_S31

value: control


title: Ngn2_CD07_SETD1A_fs_mutant, rep1


title: CT30_BRM2_P2


title: Ngn2_CD07_SETD1A_fs_control, rep3


title: control_HSPC_DMSO_Rep2, RNA-seq


title: vCTB_BRM_P2


title: vCTB_BRM_P1


title: Cas9 BMDMs, control, replicate 2

description: Library name: MH_13_S36


title: CT30_BRM2_P1


title: Cas9 BMDMs, LPS_IFNg, replicate 1

description: Library name: MH_28_S52


title: control_HSPC_DMSO_Rep1, RNA-seq


title: Ngn2_CD07_SETD1A_fs_mutant, rep3


title: Cas9 BMDMs, control, replicate 1

description: Library name: MH_10_S40


title: Ngn2_CD07_SETD1A_fs_control, rep1


title: CT30_2_P3


title: WT BMDMs, control, replicate 1

description: Library name: MH_1_S48


title: control_iPSC_Rep3, RNA-seq


title: control_iPSC_Rep2, RNA-seq


title: CT30_2_P2


title: MLO_WT_batch2_manual_150

city: Singapore

first: Matas

last: Vitkauskas

address: 60 Biopolis St.

department: Genome Institute of Singapore

country: Singapore

institute: A*star research entities

library_source: transcriptomic single cell

data_processing:
Datasets were analyzed using the nf-core/RNA-Seq pipeline version 1.4.2. In brief, reads were quality-checked using FASTQC to ensure sequencing quality, then processed for adaptor and low read quality trimming (TrimGalore v0.6.4). Alignment to human transcriptome NCBI_GRCh38 was carried out with STAR v2.6.1. Gene feature counting was performed using tximport package (Soneson, Love, & Robinson, 2015) that quantifies transcript abundance of different reads.
Digital count matrices were generated from 10X Genomics output and aligned to the GRch38 genome as reference, with intron mode on CellRanger 7.0.1. We removed low sequencing depth cells with less than 1000 genes per cell, but not more than 10000 as well as damaged cells using a cutoff of 10% cell genome mapping to the mitochondrial genome as well as a cutoff of 1% mitochondrial gene expression to remove single nuclei. The gene-cell matrix was further filtered by iteratively clustering and removing clusters associated with cell types that are non-physiological for hMLOs. Cortically misdifferentiated cells were removed based on expression of cortical markers FOXG1 (Miyoshi & Fishell, 2012) (Cargnin, et al., 2018) and PAX6 (Muzio, et al., 2002) (Quinn, et al., 2007) and vascular leptomeningeal cells based on expression of COL1A1 and COL1A3 genes (Tiklová, et al., 2020). Choroid plexus cells were removed based on expression of TTR, TRPM3 and AQP1 (Herbert, Cavallaro, & Dwork, 1990) (Johansson, et al., 2005) (Oberwinkler, Lis, Giehl, Flockerzi, & Philipp, 2005). Lastly, through iterative clustering, we also removed uninterpretable clusters with lower number of genes per cell in relation to other clusters, and no clear cell-type identity markers expected of cells in the midbrain (defined as expression of FOXA2, LMX1A, and clear expression of neurotransmission markers – GAD2, or TH).
Assembly: hg38 (GRCh38)
Supplementary files format and content: Processed files are .RDS that were compressed using gzip. Raw files are fastq files.

source_name: Midbrain -like Organoid (MLO)

growth_protocol: hMLOs were generated as previously published (Jo, et al., 2016) (Jo, et al., 2021). In brief, TrypLE-Express-dissociated hPSCs were seeded into a V-bottom 96-well culture plate (Sumitomo Bakelite) in neuronal induction media with the ROCK inhibitor thiazovivin, which was removed after 24 h. Neuronal induction medium, used for the first three days, contained DMEM/F12:Neurobasal (1:1), N2 supplement (1:100), B27 without vitamin A (1:50), GlutaMAX (1%), minimum essential media-nonessential amino acid (1%), and β-mercaptoethanol (0.1%) (all Invitrogen) supplemented with 1 μg/ml heparin (Sigma-Aldrich), 10 μM SB431542 (Stemgent), 200 ng/ml Noggin (Prospec), and 0.8 μM CHIR99021 (Reagents Direct). On day 3, 100 ng/ml SHH-C25II and 100 ng/ml FGF8 (both R&D Systems), along with 0.5 μM purmorphamine (Stemgent), were added for midbrain patterning. On day 7, media was completely removed and organoids were embedded in reduced growth factor Matrigel and left to solidify in a 37°C incubator for 30 min, then grown in tissue growth induction medium containing Neurobasal, 1:100 N2 supplement, 1:50 B27 without vitamin A, 1% GlutaMAX, 1% minimum essential media-nonessential amino acid, and 0.1% β-mercaptoethanol supplemented with 2.5 μg/ml insulin (Sigma-Aldrich), 200 ng/ml laminin (Sigma-Aldrich), 100 ng/ml SHH-C25II, and 100 ng/ml FGF8. On day 8, hMLOs were transferred using a wide-bore pipette tip into low-attachment 6-well-plates (Costar) in final differentiation media, consisting of Neurobasal medium, N2 supplement (1:100), B27 without vitamin A (1:50), GlutaMAX (1%), minimum essential media-nonessential amino acid (1%), β-mercaptoethanol (0.1%), 10ng/ml BDNF (Peprotech), 10 ng/ml GDNF (Peprotech), 100 μM ascorbic acid (Sigma-Aldrich), and 125 μM db-cAMP (Sigma-Aldrich), and were cultured on orbital shakers for maintenance.

extract_protocol:
Following manufacturer’s protocol, 50 units of papain enzyme (Worthington) was activated with 1 mM L-cysteine and 0.5 μM EDTA in Earle's Balanced Salt Solution (EBSS) (Thermo Fisher), and DNase I (Worthington) added. hMLOs were finely chopped with a scalpel and then resuspended in papain enzyme mix. The slurry was incubated at 37°C, 5% CO2 for 45 min on a rotator, and then triturated. Cells were spun down at 300xg for 5 min and washed twice in EBSS containing ovalbumin (Worthington) and BSA.
Library preparation for RNA-seq was performed by Novogene AIT Singapore or using Chromium Single Cell 3ʹ GEM kit.

value: Midbrain -like Organoid (MLO)

tag: sequencing batch

tag: library preparation_method

value: manual

tag: age (days)


title: CT30_2_P1

value: hTSC


title: MLO_DJ1KO_batch2_manual_120


title: E16.5-CSB-scRNAseq-Tcf4cKO

first: lanhui

last: zeng

address: Yixueyuan Road, Xuhui

department: Institutes of Brain Science

institute: Fudan University

description: Library name: Sample2

data_processing:
The demultiplexing, barcoded processing, gene counting and aggregation were made using the Cell Ranger software v2.1.1 (https://support.10xgenomics.com/single-cell-gene- expression/software/pipelines/latest/what-is-cell-ranger)
Assembly: mouse mm10
Supplementary files format and content: control_barcodes.tsv,control_features.tsv,control_matrix.mtx
Supplementary files format and content: mut_barcodes.tsv,mut_features.tsv,mut_matrix.mtx

source_name: mouse brain corticoseptal boundary tissue

extract_protocol:
Prepare and oxygenate ACSF on ice, then make 3% low-melt agarose in ACSF (47°C). Prepare 1× HBSS with 0.04% BSA (Ca²⁺/Mg²⁺-free) and chill, along with Miltenyi tissue digestion solution (37°C). Embed brain tissue in agarose, section at 300 μm, and collect slices in ice-cold ACSF. After washing slices 3× with HBSS to remove divalent cations, isolate CSB tissue, digest in 500 μL enzyme solution (37°C, 15 min with intermittent pipetting), then quench with HBSS and filter. Centrifuge the filtrate (600 rcf, 5 min, 4°C), resuspend cells in 100 μL HBSS, and assess viability via trypan blue before proceeding with 10x Genomics single-cell RNA sequencing.
Library was performed according to the manufacter's instructions (single cell 3'v1 protocol, 10xGenomics).Briefly, GCs were resuspended in the master mix and loaded together with partitioning oil and gel beads into the chip to generate the gel bead-in-emulsion(GEM).The poly-ARNA from the cell lysate contained in every single GEM was retrotranscripted to cDNA,which contains an llumina R1 primer sequence, Unique Molecular Identifier (UMI) and the 10x Barcode.The pooled barcoded cDNA was then cleaned up with Silane DynaBeads, amplified by PCR and the apropiated sized fragments were selected with SPRI select reagent for subsequent library construction.


title: S7_decidualization oocktail + ET-1-1

description: Library name: S7

value: HESC

value: endometrial stromal


title: WT BMDMs, LPS_IFNg, replicate 1

description: Library name: MH_19_S17


title: E16.5-CSB-scRNAseq-WT

description: Library name: Sample1

value: mouse brain corticoseptal boundary tissue


title: Jej_vilcre_ndi1_plus_veh5

city: Chicago

first: Zachary

middle: Lee

last: Sebo

address: 303 E Superior St

institute: Northwestern University

description: Library name: Sample 10

data_processing:
Data was processed via the publicly available nf-core/RNAseq pipeline v3.12.0 implemented in Nextflow v23.04.3 using Singularity v3.8.1
Assembly: GRCm38
Supplementary files format and content: normalized_gene_counts.csv

source_name: jejunum

extract_protocol:
RNA was extracted using the Direct-zol RNA miniprep kit from Zymo Research (cat. # R2051)
NEBNext Ultra DNA Library Prep Kit for Illumina (NEB E7370L)

value: jejunum


title: MeRIP-seq IP, NC with LPS treatment Replicate 2

city: shenzhen

first: Xiaona

state: China

address: No. 113 Baohe Road, Longgang District, Shenzhen

institute: Southern University of Science and Technology

description: Library name: LPS-2-m6A-IP

data_processing:
RNA-seq: Reads were aligned to the mouse Ensemble genome GRCm38 using Hisat2 aligner (v2.1.0) under parameters: “--rna-strandness RF”. The reads mapped the genome were calculated using featureCounts (v1.6.3). Differential gene expression analysis was performed using the DESeq2 R-package. MeRIP-seq: Cutadapt (v2.5) was used to trim adapters and filter for sequences, remaining reads were then aligned to the mouse Ensemble genome GRCm38 using Hisat2 aligner (v2.1.0) under parameters: “--rna-strandness RF”. m6A peaks were identified using exomePeak R package (v2.13.2) under parameters: “PEAK_CUTOFF_PVALUE=0.05,PEAK_CUTOFF_FDR=NA,FRAGMENT_LENGTH=200”. Differential m6A peak were identified using exomePeak R package under parameters: “PEAK_CUTOFF_PVALUE=NA,PEAK_CUTOFF_FDR=0.05,FRAGMENT_LENGTH=200” . GO and KEGG analysis were performed using clusterProfiler R package (v3.6.0). m6A-RNA-related genomic features were visualized using Guitar R package (v1.16.0). Identified m6A peaks which p value <0.05 were chosen for the de novo motif analysis using homer (v4.10.4) under parameters:”-len 6 -rna”. Ribo-seq: Adapter sequences were removed from raw sequencing data using cutadapt software. Meanwhile, reads with length between 25 and 35 nt were kept for downstream analysis. Then reads were aligned to rRNA and tRNA sequences so as to remove rRNA and tRNA reads using bowtie software, remaining reads were used to align to reference genome and transcriptome (Ensembl Version 91) using hisat2 and bowtie software separately. The trinucleotide periodicity of ribosomes and codon usage frequency were estimated using revised riboWaltz package. Read counts were calculated using featureCounts software. Raw counts were further normalized as FPKM values using fpkm function in DESeq2 package.
Assembly: GRCm38
Supplementary files format and content: RNA-seq: read counts table and FPKM table; MeRIP-seq: peak files; Ribo-seq: read counts table and FPKM table;

extract_protocol:
Total RNA was extracted using TRIzol™ Reagent (Invitrogen, 15596018).
RNA-seq: VAHTS Stranded mRNA-seq Library Prep Kit for Illumina V2 (Vazyme Biotech, NR612-02) was used for library preparation according to the instructions. MeRIP-seq: 10 μg total RNA was fragmented into 100-200 nt RNA fragments using 10X RNA Fragmentation Buffer (100 mM Tris-HCl, 100 mM ZnCl2 in nuclease-free H2O). The reaction was stopped by adding 10X EDTA (0.5M EDTA). Methylated RNA immunoprecipitation was performed using EpiTM m6A immunoprecipitation kit (Epibiotek, R1804). Briefly, the fragmented RNA was incubated with anti-m6A monoclonal antibody (abcam,ab208577) for 3 h at 4℃ and then with protein A/G magnetic beads (Invitrogen, 8880210002D/10004D) at 4 ℃ for an additional 2 h to obtain immunoprecipitated RNA fragments. The m6A-enriched RNA was purified using TRIzol™ Reagent (Invitrogen, 15596018). The library was prepared by smart-seq method. Ribo-seq: A total of 10^7 cells were prepared for cell lysis. Then, the cell medium was discarded, and the cells were washed twice with ice-cold PBS containing 100 μg/mL cycloheximide (Adooq, 66-81-9). Ribosome profiling was performed using Epi™ Ribosome Profiling Kit (Epibiotek, R1814). Subsquently, RPFs (ribosome-protected RNA fragments) was extracted using RNA clean&ConcentratorTM-5 kit (ZYMO, R1016). EpiTM RiboRNA Depletion Kit (Human/Mouse/Rat) (Epibiotek, R1805) was used for rRNA depletion. Sequencing libraries were constructed using QIAseq miRNA Library kit (QIAGEN, 1103679).

value: cell line

value: Macrophage; Abelson murine leukemia virus transformed

value: overexpressed control

value: with LPS treatment for 12h


title: control_iPSC_Rep1, RNA-seq

value: iPSC


title: CT27_BRM_P2

value: placenta

value: WT


title: Jej_vilcre_ndi1_plus_veh4

description: Library name: Sample 9


title: MLO_WT_batch2_manual_120


title: Ngn2_CD07_SETD1A_fs_control, rep2

value: Control


title: CT27_BRM_P1


title: Jej_vilcre_ndi1_plus_veh3

description: Library name: Sample 8


title: MLO_DJ1KO_batch2_manual_90


title: MeRIP-seq IP, NC with LPS treatment Replicate 1

description: Library name: LPS-1-m6A-IP


title: MLO_DJ1KO_batch2_manual_150


title: CT27_P3


title: Jej_vilcre_ndi1_plus_veh2

description: Library name: Sample 7


title: MLO_WT_batch2_manual_90


title: MeRIP-seq input, NC with LPS treatment Replicate 1

description: Library name: LPS-1-m6A-input


title: MLO_DJ1KO_batch2_manual_70


title: Jej_vilcre_ndi1_plus_veh1

description: Library name: Sample 6


title: MeRIP-seq IP, NC without LPS treatment Replicate 2

description: Library name: NC-2-m6A-IP

value: without LPS treatment


title: CT27_BRM_P3


title: MLO_WT_batch2_manual_70


title: CT27_P1


title: Jej_vilcre_plus_veh5

description: Library name: Sample 5

value: Vil-Cre


title: MeRIP-seq input, NC without LPS treatment Replicate 2

description: Library name: NC-2-m6A-Input


title: MLO_WT_batch1_manual_156

value: Midbrain -like Organoid (MLO)


title: MeRIP-seq input, NC with LPS treatment Replicate 2

description: Library name: LPS-2-m6A-Input


title: CT30_BRM_P2


title: Sample 4-4, UUO surgery + Early intervention

description: Library name: Sample 16

value: Left kidney

value: Wildtype

value: UUO surgery + Early intervention


title: MLO_WT_batch1_robot_126

value: robot


title: MeRIP-seq IP, NC without LPS treatment Replicate 1

description: Library name: NC-1-m6A-IP


title: CT30_BRM_P3

value: hTSC


title: MeRIP-seq input, NC without LPS treatment Replicate 1

description: Library name: NC-1-m6A-Input


title: MLO_WT_batch1_manual_120

value: manual


title: Jej_vilcre_plus_veh3

description: Library name: Sample 3

value: jejunum


title: Jej_vilcre_plus_veh2

description: Library name: Sample 2


title: RNA-seq, NC with LPS treatment Replicate 2

description: Library name: LPS-2-mR

value: cell line

value: Macrophage; Abelson murine leukemia virus transformed


title: MLO_WT_batch1_manual_126


title: CT30_BRM_P1


title: Jej_vilcre_plus_veh1

description: Library name: Sample 1


title: CT30_P3


title: RNA-seq, NC with LPS treatment Replicate 1

description: Library name: LPS-1-mR

value: overexpressed control

value: with LPS treatment for 12h


title: CT30_P2

value: placenta


title: Cerebellum, Wt-DMSO, 431

city: Albany

first: Cara

middle: T

last: Pager

state: NY

address: 1400 Washington Avenue

institute: University at Albany, State University of New York

data_processing:
After sequencing the quality of the fastq files were checked using the program FastQC (version 0.11.9).
Both paired-end files for samples 409, 422, 425, and 426 were downsampled using Seqtk (version 1.4) to either ~65 or 70 million reads per file to more closely match the read depth of the other samples in the dataset.
STAR (version 2.7.10a) was used to align the fastq files to the GRcm39/mm39 genome with the --quantModeGeneCounts option added to count the reads per gene.
Assembly: GRCm39/mm39
Supplementary files format and content: Tab-delimited text files contain the raw read count abundances for each sample.

source_name: Cerebellum

extract_protocol:
RNA forwild-type and SCA1 KI mice was extracted using TRIzol (Ambion, Life Technologies),following the manufacturers protocol and aDNA digestion was performed usingthe TURBO DNA-free Kit (Invitrogen). The Qubit RNA high sensitivity assay wasused to obtain RNA concentrations(Thermo Fisher Scientific). RNA quality waschecked via capillary electrophoresis on a 5300 fragment analyzer (AgilentBioanalyzer) using the RNA AnalysisDNF-471 RNA kit (Agilent).
The NEBNext Ultra IIDirectional RNA Library Prep Kit (Illumina) with NEBNext rRNA Depletion Kit(New EnglandBiolabs) was used to prepare RNA-seq libraries, with a total of500 ng input RNA from each sample. The manufacturer’sprotocols were followed,with the following exceptions: 40× adaptor dilutions were used, and 13 cyclesof libraryamplification were performed. The resulting libraries were pooled inequimolar amounts, quantified using the NEBNextLibrary Quant Kit for Illumina(New England Biolabs), quality checked via capillary electrophoresis on the5300fragment analyzer (Agilent Bioanalzyer) using the DNF-474 HS NGS kit(Agilent). Libraries with sufficient quantitywere loaded into P2 flow cell1000/2000 by Illumina and were sequenced using paired-end, 100 base pairsequencing onthe Illumina NextSeq 2000 sequencer at the University at AlbanyRNA Institute. All datasets had total read depths greaterthan 40 million paired-end reads.

treatment_protocol: Starting at 18 weeks ofage, WT and Atxn1154Q/2Q mice were treated with 25mg/ml Hit 2 dissolved in DMSO or DMSO alone (DMSO<4ml/kg) via intraperitoneal (IP) injection daily for 5 days, followed by tworest days and an additional 5 days of IPinjection. All injections were performedbetween 8 and 9am in the morning and on the final day of injections (20 weeksofage), after 3pm, mice were anesthetised using urethane in saline (1.2-1.5 g/kg)followed by a double thoracotomy andperfusion through the ascending aorta with20 mLs 1x PBS. Cerebellum was removed and stored at -70°C.

value: Cerebellum

value: Wt

value: DMSO


title: MLO_WT_manual_batch1_105

value: WT


title: CT27_P2

first: Andreas

last: Lackner

address: Schwarzspanierstrasse 17

institute: Medical University of Vienna


title: CT30_P1


title: RNA-seq, NC without LPS treatment Replicate 2

description: Library name: NC-2-mR

value: without LPS treatment


title: MLO_WT_batch1_manual_60

value: Midbrain -like Organoid (MLO)


title: Cerebellum, Het-DMSO, 429

value: Het


title: Cerebellum, Het-Hit2, 430


title: 3_V281_ST

value: ST


title: Jej_vilcre_plus_veh4

description: Library name: Sample 4

value: Vil-Cre


title: S14_decidualization oocktail + ET-1-2

description: Library name: S14

value: HESC

value: endometrial stromal


title: FTO _LPS_rep_3

description: Library name: FTO _LPS_3

data_processing:
RNA-seq: Reads were aligned to the mouse Ensemble genome GRCm39 using Hisat2 aligner (v2.2.1). The reads mapped the genome were calculated using StringTie (v2.1.6). Differential gene expression analysis was performed using the DESeq2 R-package.
Assembly: GRCm39
Supplementary files format and content: read counts table and FPKM table

extract_protocol:
Total RNA was extracted using TRIzol™ Reagent (Invitrogen, 15596018).
dUTP method was used for library preparation.

value: overexpressed FTO

value: with LPS treatment for 6h


title: 3_V278_ST


title: FTO _LPS_rep_2

description: Library name: FTO _LPS_2

value: cell line

value: Macrophage; Abelson murine leukemia virus transformed


title: 3_V188_ST

value: shNeg


title: RNA-seq, NC without LPS treatment Replicate 1

description: Library name: NC-1-mR

value: overexpressed control


title: Cerebellum, Wt-DMSO, 425

value: Cerebellum


title: scSTAMP-MAT-seq_Plate4_Lib1_Genome_Methylation_Accessibility

city: Santa Barbara

first: Robert

middle: Anthony

last: Piscopio

state: CA

address: 2002 BioEngineering Bldg, CNTR for Bioengineering

institute: University of California, Santa Barbara

description: Method is detailed in Piscopio et al.

data_processing:
Supplementary files format and content: text file where each row is a mapped read, and column 1 indicates cell number, column 2 contains chromosome number, column 3 contains genomic location, and column 4 indicates sense and antisense strands of DNA.
scSTAMP-seq data processing and gene expression analysis. Sequencing FASTQ data files were processed using custom Perl scripts on a Linux high performance computing (HPC) cluster at the University of California, Santa Barbara. Sequencing data was post-processed and analyzed using Seurat (version 4.3.0) in R (version 4.2.2) and RStudio (version 2022.12.0+353). Representative figures were generated in RStudio and compiled in Adobe Illustrator (version 26.5).  scSTAMP-seq barcode processing and analysis. A custom Perl script was written to evaluate the spatial barcode portion of the sequencing library. For PHO spatial barcode sequences, read 1 was used to determine cell barcode/UMI. Read 2 was used to distinguish ‘inner’ and ‘outer’ sequence reads by identifying unique ‘inner’ and ‘outer’ primer sequences as well as the downstream spatial barcode/UMI sequence. MPO barcode counts were determined similarly, but an additional multiplex identifier sequence from read 2 was used to distinguish multiplex from spatial barcodes. Unique counts for each molecule were defined as reads containing a unique combination of the UMI on read 1 and on read 2.  Plate-based scSTAMP-seq data processing. For plate-based sequencing, read 2 of the paired-end read was aligned in the sense direction using BWA (version 0.7.15-r1140) to the RefSeq gene model based on the human genome release hg19, incorporating a collection of 92 ERCC spike-in molecules. In cases where a read aligned to multiple locations, it was evenly distributed across those locations. Gene isoforms were consolidated into a single gene count, and the unique molecular identifiers (UMIs) were used to remove duplicate reads and generate transcript counts at the single-molecule level for each gene within individual cells. Genes that were not detected in at least one cell were excluded from subsequent analyses.  Droplet-based scSTAMP-seq data processing. For droplet-based sequencing, read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to hg19 using the gene annotation file from Ensembl. Transcripts with the same UMI were deduplicated and genes that were not detected in at least one cell were removed from any downstream analysis.  scSTAMP-seq gene expression analysis. The standard analysis pipeline in Seurat (version 4.3.0) was used for single-cell RNA expression normalization and analysis36. For plate-based sequencing experiments, cells containing more than 1000 genes and more than 1000 unique transcripts, as well as less than 20% ERCC spike-ins, were used for downstream analysis. For the droplet-based sequencing experiment, cells containing more than 200 genes and more than 200 unique transcripts, as well as less than 5% mitochondrial counts, were used for downstream analysis. The default NormalizeData function was used to log normalize the data. Principal components were obtained from the 2,000 most variable genes and the elbow method was used to determine the optimal number of principal components used in clustering. UMAP based clustering was performed by running the following functions, FindNeighbors, FindClusters, and RunUMAP. After clustering, cell types were assigned to groups using known expression markers, spatial barcode counts, and multiplex barcode counts, where stated.
scSTAMP-MAT-seq genome-wide DNA accessibility and 5mC analysis. The scSTAMP-MAT-seq analysis pipeline for DNA accessibility and 5mC was performed as described in the scMAT-seq methods by Chialastri et al.31. DNase I hypersensitivity sites for Hela cells were downloaded from the UCSC table browser and sites were grouped based on detection scores35. To compare across datasets, the data was normalized to counts per million and a 75 base pair moving average was plotted for region of interest. When comparing differing genomic regions within a sample, each region was further normalized by methylated cytosines that were detected when MspJI-seq was performed on bulk Hela gDNA that had been GpC methylated after stripping off chromatin. Bulk Hela gDNA isolation, chromatin stripping, and processing was performed as described previously by Chialastri et al.31. For clustering, DNA accessibility and 5mC were quantified within 5 kb bins and then converted to binary scores. Pseudobulk profiles were generated using the assigned cell type from the transcriptome. For comparison between Hela and U2OS cells, the top 2% most variable bins between groups were retained. After removal of bins with low variance, principal component analysis was used to assign clusters. Cluster identification was performed through comparison to transcriptome derived cell types, where high similarity was observed between cluster calling for all 3 measurements. A threshold minimum of 15,000 was applied to the data shown in Supplementary Figure 14a,b.
Assembly: hg19
Library strategy: scSTAMP-MAT-seq

source_name: Hela, U2OS

growth_protocol: Cell culture. Hela and U2OS cells were cultured and maintained on tissue cultured treated plastic flasks (Thermo Scientific, 156367) or 6-well plates (Corning, 3516) in DMEM with high glucose, GlutaMAX and sodium pyruvate (Gibco, 10569044), supplemented with 10% fetal bovine serum (FBS) (Gibco, 10569044) and 1% Pen-Strep (Gibco, 15140122). All mammalian cell cultures were maintained in incubators at 37°C and 5% CO2. Cells were routinely passaged 1:6 after 70-80% confluence was reached using 0.25% trypsin-EDTA (Gibco, 25200056). For microscopy imaging, cells were seeded onto glass 96 well glass bottom plates (Cellvis, P96-1.5H-N) or 35 mm dishes with glass coverslips (MATTEK, P35G-1.5-20-C) coated with fibronectin (Advanced Biomatrix, 5050). For the combinatorial barcoding experiment, cells were seeded on a custom protein patterned 96-well plate (CYTOO, 20-950-00) treated with fibronectin.

extract_protocol:
For FACS sorting, a single-cell suspension was made by dissociating cells using 0.25% trypsin-EDTA and inactivated using DMEM containing serum. Afterwards, cells were washed and resuspended in 1 mL of cold 1x DPBS-/- (without calcium or magnesium) (Gibco, 14040133) before being passed through a 35 µm nylon mesh cell strainer into a 5 mL round bottom polystyrene tube (Corning, 352235) that was then kept on ice. For plate-based single-cell capture, cell suspensions were FACS sorted for single cells into 384-well plates (Bio-Rad, HSP3801). For droplet-based single-cell capture, cell suspensions were processed for single cells by a 10X Genomics Chromium Controller following the workflow of the 10X Genomics Chromium Next GEM Single Cell 3’ LT Kit v3.1 (10X Genomics, 1000325).
scSTAMP-seq plate-based library preparation. 4 µL of Vapor-Lock (QIAGEN, 981611) was dispensed into each well of a 384-well plate using a 12-channel pipette. All downstream dispensing into 384-well plates was performed using a Nanodrop II liquid handling robot (BioNex Solutions). To each well, 100 nL of uniquely barcoded 7.5 ng/µL reverse transcription primers containing 6-nucleotide UMI was added. The reverse transcription primers used here have been described by Grün et al.33. Next, 100 nL of lysis buffer (0.175% IGEPAL CA-630, 1.75 mM dNTPs, 1:1,250,000 ERCC RNA spike-in mix (Ambion, 4456740), 0.19 U RNase inhibitor (Clontech, 2313A)) was added to each well. Single cells were sorted into individual wells of a 384-well plate using FACS. After sorting, plates were heated to 65°C for 3 minutes and returned to ice. Reverse transcription was conducted next by adding 150 nL of reverse transcription mix (0.7 U RNase OUT (Invitrogen, 10777-019), 2.34x first strand buffer (Invitrogen, 10777-019), 23.34 mM DTT (Invitrogen, 10777-019), 3.5 U Superscript II (Invitrogen, 18064-071)) to each well and the plates were incubated at 42°C for 1 hour and 15 minutes, 4°C for 5 minutes, 70°C for 10 minutes, and then held at 4°C. Next, second strand synthesis was carried out by adding 1.75 µL of second strand synthesis mix (1.74x second strand buffer (Invitrogen, 10812-014), 0.35 mM dNTP (Invitrogen, 10812-014), 0.14 U E. coli DNA Ligase (Invitrogen, 18052-019), 0.56 U E. coli DNA Polymerase I (Invitrogen, 18010-025), 0.03 U RNase H (Invitrogen 18021-071)) to each well and the plates were incubated at 16°C for 2 hours and then held at 4°C. 1 µL of nuclease-free water was added into each well to minimize losses during downstream pooling. The PHO, MPO, and endogenous mRNA molecules in a well now all contain the same RNA capture barcode, indicating a unique cell, which allows for pooling. Reaction wells receiving different barcodes were pooled using a multichannel pipette, and the oil phase was discarded. The small molecule spatial barcode portion was separated from endogenous transcript cDNA using a 3.2x SPRI bead cleanup with 1.8x 100% isopropanol in 2 steps. First, 0.7x AMPure XP beads (Beckman Coulter, A63881) were added and incubated at room temp for 15 minutes. At this step, it is critical to not dispose of the supernatant, as the spatial barcode library portion is found in the supernatant and the endogenous cDNA is bound to SPRI beads. The supernatant containing the spatial barcode fragments was then transferred to a fresh Eppendorf tube. The endogenous cDNA portion was prepared as described previously by Chialastri et al.31. Second, to the spatial barcode sample, an additional 2.5x beads and 1.8x 100% isopropanol (of the original pre-cleanup sample volume) were added and incubated at room temp for 15 minutes. The samples were placed on a magnetic stand for 5 minutes. The supernatant was removed and beads were washed twice with 80% ethanol. The sample was then eluted in 30 µL of nuclease-free water. The sample was then concentrated to 15 µL using an Eppendorf Vacufuge plus. Next, samples were prepared for PCR amplification by mixing 15 µL of the concentrated elute from the previous step, 25 µL of 2x PCR master mix (NEB, M0541S), 2 µL Illumina RPI primer (10 µM), 2 µL each of an ‘inner’ and ‘outer’ PCR primer (10 µM), and nuclease-free water up to 50 µL. This first PCR was performed at 94°C for 10 seconds, 60°C for 30 seconds, and 72°C for 30 seconds, for 10 cycles. A subsequent ExoSAP-IT treatment was then applied to cleanup the PCR product as follows. 2 µL of ExoSAP-IT (Applied Biosystems, 78200.200.UL) was added to 5 µL of sample from the previous PCR (for a total volume of 7 µL) and incubated at 37°C for 15 minutes. Another PCR was performed by mixing 7 µL of the cleaned-up PCR with 22.5 µL 2x PCR master mix, 2 µL Illumina RPI primer, 2 µL Illumina sample index primer, and nuclease-free water up to 45 µL. This second PCR was performed at 94°C for 10 seconds, 60°C for 30 seconds, and 72°C for 30 seconds, for 6-12 cycles.  Another ExoSAP-IT treatment was then applied to the 45 µL reaction by adding 5 µL of ExoSAP-IT to the previous PCR (for 50 µL total) and incubated at 37°C for 15 minutes. Finally, a 1.2x double-sided selection (0.90x left/0.30x right) was used to purify the spatial library, and a final ethanol wash was performed twice. The product was then eluted in 20 µL of nuclease-free water. Library fragment size distribution was determined using a 2100 Bioanalyzer. A schematic depicting each step of this process can be found in Supplementary Figure 1.  scSTAMP-seq droplet-based library preparation. Sequencing libraries were prepared using a custom protocol based on the 10X Genomics Chromium Next GEM Single Cell 3’ LT Kit v3.1 (10X Genomics, 1000325) adapted from McGinnis et al.29. The 10X workflow was followed until cDNA amplification. We designed custom ‘inner’ and ‘outer’ PHO handle primers that allow scSTAMP-seq to be adapted for the 10X workflow (Supplementary Table 1). The scSTAMP-seq 10X ‘inner’ and ‘outer’ PHO primers were mixed to a working concentration of 2.5 µM. Next, the following cDNA amplification master-mix was made: 50 µL 10X amplification master mix, 15 µL 10X cDNA primer mix, 1 µL scSTAMP-seq 10X primers. Then, cDNA amplification was performed and an SPRI size selection was performed by incubating samples for 30 minutes with 0.6x AMPure XP beads to separate spatial and endogenous cDNA fractions. Next, the small molecule spatial barcode fraction was separated from endogenous transcript cDNA using the same strategy as described in the plate-based library preparation method above. The endogenous cDNA portion was then processed to generate Illumina libraries according to the 10X workflow and the spatial portion was processed to generate Illumina libraries as described in the plate-based library preparation workflow. A schematic depicting each step of this process can be found in Supplementary Figure 10.  scSTAMP-MAT-seq multiomic library preparation. The DNA accessibility and 5mC sequencing pipeline was performed as described previously in the scMAT-seq methods by Chialastri et al.31 up to the first SPRI bead clean up. At this step, the small molecule spatial barcode portion was separated from endogenous molecules using the same strategy as described in the plate-based library preparation workflow. The transcriptomic and epigenomic libraries were processed to generate Illumina libraries as described in scMAT-seq by Chialastri et al.31 and the spatial portion was processed to generate Illumina libraries as described in the plate-based library preparation workflow above. A schematic depicting each step of this process can be found in Supplementary Fig. 12.  Library sequencing was performed by Novogene on an Illumina HiSeq 4000 platform or at the Biological Nanostructures Laboratory (BNL) in the California NanoSystems Institute (CNSI) at the University of California Santa Barbara (UCSB) on an Illumina NextSeq 500 platform.

treatment_protocol: PHO labeling of cell membranes. First, cell culture media was removed, and cells were washed three times with cold DPBS+/+ (with calcium and magnesium) (Gibco, 14040133). Hybridized PHO/CMO-anchor at 500 nM was then incubated with live-cell samples over ice for 15 minutes. Next, cells were washed again three times with cold DPBS+/+. After washing, CMO co-anchors were incubated with live-cell samples over ice for 15 minutes. Cells were then washed again three times with cold DPBS+/+. This subsequent two-step anchor/co-anchor incubation is optimal for oligo embedding rate and retention time, as described previously by Weber et al.28. Cells were then imaged and illuminated with UV light. After illumination, cells were either processed for single cell sorting, or the labeling procedure was repeated for experiments that utilized iterative rounds of unique spatial barcode labeling. For experiments that incorporated MPOs, both PHOs and MPOs were incubated simultaneously.  Microscopy and photomask illumination. All microscopy was performed using a Nikon Ti-2 inverted confocal microscope equipped with a Yokogawa CSU-W1 SoRa spinning disk and an Andor iXon Life 888 EMCCD camera. Images were captured with a Nikon CFI S Plan Fluor ELWD 20x objective lens and a Nikon CFI Plan Apo Lambda 10x objective lens. For fluorescence confocal imaging, 488 nm, 561 nm, and 640 nm lasers at 100% power were delivered through liquid light guides for FAM, Cy3, and Cy5 fluorophores, respectively. Digital light processing (DLP) patterned light projection was done using a Mightex Polygon400-G digital micromirror device (DMD) coupled with an Excelitas X-Cite 360-380 nm UVA liquid light guide-coupled LED, or a 365 nm 50W LED flood light (Everbeam, B08635F9CX) with an acrylic light diffusion film and custom 3D printed plate stand for consistent and uniform illumination.

value: Hela, U2OS

value: Hela and U2OS cell samples were labeled with PHO1. Hela and U2OS cell samples then received 0 and 1 minutes of UV flood light illumination.


title: scSTAMP-MAT-seq_Plate4_Lib1_Spatial

description: Method is detailed in Piscopio et al.

library_source: other

data_processing:
Supplementary files format and content: text file for PHO barcodes where each row contains counts for inner and outer spatial barcodes.
scSTAMP-seq data processing and gene expression analysis. Sequencing FASTQ data files were processed using custom Perl scripts on a Linux high performance computing (HPC) cluster at the University of California, Santa Barbara. Sequencing data was post-processed and analyzed using Seurat (version 4.3.0) in R (version 4.2.2) and RStudio (version 2022.12.0+353). Representative figures were generated in RStudio and compiled in Adobe Illustrator (version 26.5).  scSTAMP-seq barcode processing and analysis. A custom Perl script was written to evaluate the spatial barcode portion of the sequencing library. For PHO spatial barcode sequences, read 1 was used to determine cell barcode/UMI. Read 2 was used to distinguish ‘inner’ and ‘outer’ sequence reads by identifying unique ‘inner’ and ‘outer’ primer sequences as well as the downstream spatial barcode/UMI sequence. MPO barcode counts were determined similarly, but an additional multiplex identifier sequence from read 2 was used to distinguish multiplex from spatial barcodes. Unique counts for each molecule were defined as reads containing a unique combination of the UMI on read 1 and on read 2.  Plate-based scSTAMP-seq data processing. For plate-based sequencing, read 2 of the paired-end read was aligned in the sense direction using BWA (version 0.7.15-r1140) to the RefSeq gene model based on the human genome release hg19, incorporating a collection of 92 ERCC spike-in molecules. In cases where a read aligned to multiple locations, it was evenly distributed across those locations. Gene isoforms were consolidated into a single gene count, and the unique molecular identifiers (UMIs) were used to remove duplicate reads and generate transcript counts at the single-molecule level for each gene within individual cells. Genes that were not detected in at least one cell were excluded from subsequent analyses.  Droplet-based scSTAMP-seq data processing. For droplet-based sequencing, read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to hg19 using the gene annotation file from Ensembl. Transcripts with the same UMI were deduplicated and genes that were not detected in at least one cell were removed from any downstream analysis.  scSTAMP-seq gene expression analysis. The standard analysis pipeline in Seurat (version 4.3.0) was used for single-cell RNA expression normalization and analysis36. For plate-based sequencing experiments, cells containing more than 1000 genes and more than 1000 unique transcripts, as well as less than 20% ERCC spike-ins, were used for downstream analysis. For the droplet-based sequencing experiment, cells containing more than 200 genes and more than 200 unique transcripts, as well as less than 5% mitochondrial counts, were used for downstream analysis. The default NormalizeData function was used to log normalize the data. Principal components were obtained from the 2,000 most variable genes and the elbow method was used to determine the optimal number of principal components used in clustering. UMAP based clustering was performed by running the following functions, FindNeighbors, FindClusters, and RunUMAP. After clustering, cell types were assigned to groups using known expression markers, spatial barcode counts, and multiplex barcode counts, where stated.
scSTAMP-MAT-seq genome-wide DNA accessibility and 5mC analysis. The scSTAMP-MAT-seq analysis pipeline for DNA accessibility and 5mC was performed as described in the scMAT-seq methods by Chialastri et al.31. DNase I hypersensitivity sites for Hela cells were downloaded from the UCSC table browser and sites were grouped based on detection scores35. To compare across datasets, the data was normalized to counts per million and a 75 base pair moving average was plotted for region of interest. When comparing differing genomic regions within a sample, each region was further normalized by methylated cytosines that were detected when MspJI-seq was performed on bulk Hela gDNA that had been GpC methylated after stripping off chromatin. Bulk Hela gDNA isolation, chromatin stripping, and processing was performed as described previously by Chialastri et al.31. For clustering, DNA accessibility and 5mC were quantified within 5 kb bins and then converted to binary scores. Pseudobulk profiles were generated using the assigned cell type from the transcriptome. For comparison between Hela and U2OS cells, the top 2% most variable bins between groups were retained. After removal of bins with low variance, principal component analysis was used to assign clusters. Cluster identification was performed through comparison to transcriptome derived cell types, where high similarity was observed between cluster calling for all 3 measurements. A threshold minimum of 15,000 was applied to the data shown in Supplementary Figure 14a,b.
Assembly: hg19
Library strategy: scSTAMP-MAT-seq

molecule: other


title: FTO _LPS_rep_1

last: Chen

description: Library name: FTO _LPS_1


title: scSTAMP-MAT-seq_Plate4_Lib1_Transcriptome

description: Method is detailed in Piscopio et al.

data_processing:
Supplementary files format and content: text file where column 1 contains gene names and columns 2-97 contain gene counts for 96 single cells.
scSTAMP-seq data processing and gene expression analysis. Sequencing FASTQ data files were processed using custom Perl scripts on a Linux high performance computing (HPC) cluster at the University of California, Santa Barbara. Sequencing data was post-processed and analyzed using Seurat (version 4.3.0) in R (version 4.2.2) and RStudio (version 2022.12.0+353). Representative figures were generated in RStudio and compiled in Adobe Illustrator (version 26.5).  scSTAMP-seq barcode processing and analysis. A custom Perl script was written to evaluate the spatial barcode portion of the sequencing library. For PHO spatial barcode sequences, read 1 was used to determine cell barcode/UMI. Read 2 was used to distinguish ‘inner’ and ‘outer’ sequence reads by identifying unique ‘inner’ and ‘outer’ primer sequences as well as the downstream spatial barcode/UMI sequence. MPO barcode counts were determined similarly, but an additional multiplex identifier sequence from read 2 was used to distinguish multiplex from spatial barcodes. Unique counts for each molecule were defined as reads containing a unique combination of the UMI on read 1 and on read 2.  Plate-based scSTAMP-seq data processing. For plate-based sequencing, read 2 of the paired-end read was aligned in the sense direction using BWA (version 0.7.15-r1140) to the RefSeq gene model based on the human genome release hg19, incorporating a collection of 92 ERCC spike-in molecules. In cases where a read aligned to multiple locations, it was evenly distributed across those locations. Gene isoforms were consolidated into a single gene count, and the unique molecular identifiers (UMIs) were used to remove duplicate reads and generate transcript counts at the single-molecule level for each gene within individual cells. Genes that were not detected in at least one cell were excluded from subsequent analyses.  Droplet-based scSTAMP-seq data processing. For droplet-based sequencing, read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to hg19 using the gene annotation file from Ensembl. Transcripts with the same UMI were deduplicated and genes that were not detected in at least one cell were removed from any downstream analysis.  scSTAMP-seq gene expression analysis. The standard analysis pipeline in Seurat (version 4.3.0) was used for single-cell RNA expression normalization and analysis36. For plate-based sequencing experiments, cells containing more than 1000 genes and more than 1000 unique transcripts, as well as less than 20% ERCC spike-ins, were used for downstream analysis. For the droplet-based sequencing experiment, cells containing more than 200 genes and more than 200 unique transcripts, as well as less than 5% mitochondrial counts, were used for downstream analysis. The default NormalizeData function was used to log normalize the data. Principal components were obtained from the 2,000 most variable genes and the elbow method was used to determine the optimal number of principal components used in clustering. UMAP based clustering was performed by running the following functions, FindNeighbors, FindClusters, and RunUMAP. After clustering, cell types were assigned to groups using known expression markers, spatial barcode counts, and multiplex barcode counts, where stated.
scSTAMP-MAT-seq genome-wide DNA accessibility and 5mC analysis. The scSTAMP-MAT-seq analysis pipeline for DNA accessibility and 5mC was performed as described in the scMAT-seq methods by Chialastri et al.31. DNase I hypersensitivity sites for Hela cells were downloaded from the UCSC table browser and sites were grouped based on detection scores35. To compare across datasets, the data was normalized to counts per million and a 75 base pair moving average was plotted for region of interest. When comparing differing genomic regions within a sample, each region was further normalized by methylated cytosines that were detected when MspJI-seq was performed on bulk Hela gDNA that had been GpC methylated after stripping off chromatin. Bulk Hela gDNA isolation, chromatin stripping, and processing was performed as described previously by Chialastri et al.31. For clustering, DNA accessibility and 5mC were quantified within 5 kb bins and then converted to binary scores. Pseudobulk profiles were generated using the assigned cell type from the transcriptome. For comparison between Hela and U2OS cells, the top 2% most variable bins between groups were retained. After removal of bins with low variance, principal component analysis was used to assign clusters. Cluster identification was performed through comparison to transcriptome derived cell types, where high similarity was observed between cluster calling for all 3 measurements. A threshold minimum of 15,000 was applied to the data shown in Supplementary Figure 14a,b.
Assembly: hg19
Library strategy: scSTAMP-MAT-seq


title: 3_V281_SR

city: Vienna

source_name: placenta

value: placenta

value: hTSC

value: WT


title: Cerebellum, Wt-DMSO, 426

value: Wt

value: DMSO


title: Cerebellum, Het-Hit2, 422

value: Het


title: LPS_rep_3

description: Library name: LPS_3


title: MLO_WT_batch1_manual_99

value: Midbrain -like Organoid (MLO)

value: manual


title: 3_V278_SR


title: Cerebellum, Het-Hit2, 421


title: LPS_rep_2

description: Library name: LPS_2


title: Cerebellum, Het-DMSO, 420


title: LPS_rep_1

description: Library name: LPS_1


title: 2_V281_ST

value: ST


title: scSTAMP-seq_CombinatorialBarcoding_Plate1_Lib4_Spatial

description: Method is detailed in Piscopio et al.

data_processing:
Supplementary files format and content: text file for PHO barcodes where each row contains counts for inner and outer spatial barcodes.
scSTAMP-seq data processing and gene expression analysis. Sequencing FASTQ data files were processed using custom Perl scripts on a Linux high performance computing (HPC) cluster at the University of California, Santa Barbara. Sequencing data was post-processed and analyzed using Seurat (version 4.3.0) in R (version 4.2.2) and RStudio (version 2022.12.0+353). Representative figures were generated in RStudio and compiled in Adobe Illustrator (version 26.5).  scSTAMP-seq barcode processing and analysis. A custom Perl script was written to evaluate the spatial barcode portion of the sequencing library. For PHO spatial barcode sequences, read 1 was used to determine cell barcode/UMI. Read 2 was used to distinguish ‘inner’ and ‘outer’ sequence reads by identifying unique ‘inner’ and ‘outer’ primer sequences as well as the downstream spatial barcode/UMI sequence. MPO barcode counts were determined similarly, but an additional multiplex identifier sequence from read 2 was used to distinguish multiplex from spatial barcodes. Unique counts for each molecule were defined as reads containing a unique combination of the UMI on read 1 and on read 2.  Plate-based scSTAMP-seq data processing. For plate-based sequencing, read 2 of the paired-end read was aligned in the sense direction using BWA (version 0.7.15-r1140) to the RefSeq gene model based on the human genome release hg19, incorporating a collection of 92 ERCC spike-in molecules. In cases where a read aligned to multiple locations, it was evenly distributed across those locations. Gene isoforms were consolidated into a single gene count, and the unique molecular identifiers (UMIs) were used to remove duplicate reads and generate transcript counts at the single-molecule level for each gene within individual cells. Genes that were not detected in at least one cell were excluded from subsequent analyses.  Droplet-based scSTAMP-seq data processing. For droplet-based sequencing, read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to hg19 using the gene annotation file from Ensembl. Transcripts with the same UMI were deduplicated and genes that were not detected in at least one cell were removed from any downstream analysis.  scSTAMP-seq gene expression analysis. The standard analysis pipeline in Seurat (version 4.3.0) was used for single-cell RNA expression normalization and analysis36. For plate-based sequencing experiments, cells containing more than 1000 genes and more than 1000 unique transcripts, as well as less than 20% ERCC spike-ins, were used for downstream analysis. For the droplet-based sequencing experiment, cells containing more than 200 genes and more than 200 unique transcripts, as well as less than 5% mitochondrial counts, were used for downstream analysis. The default NormalizeData function was used to log normalize the data. Principal components were obtained from the 2,000 most variable genes and the elbow method was used to determine the optimal number of principal components used in clustering. UMAP based clustering was performed by running the following functions, FindNeighbors, FindClusters, and RunUMAP. After clustering, cell types were assigned to groups using known expression markers, spatial barcode counts, and multiplex barcode counts, where stated.
scSTAMP-MAT-seq genome-wide DNA accessibility and 5mC analysis. The scSTAMP-MAT-seq analysis pipeline for DNA accessibility and 5mC was performed as described in the scMAT-seq methods by Chialastri et al.31. DNase I hypersensitivity sites for Hela cells were downloaded from the UCSC table browser and sites were grouped based on detection scores35. To compare across datasets, the data was normalized to counts per million and a 75 base pair moving average was plotted for region of interest. When comparing differing genomic regions within a sample, each region was further normalized by methylated cytosines that were detected when MspJI-seq was performed on bulk Hela gDNA that had been GpC methylated after stripping off chromatin. Bulk Hela gDNA isolation, chromatin stripping, and processing was performed as described previously by Chialastri et al.31. For clustering, DNA accessibility and 5mC were quantified within 5 kb bins and then converted to binary scores. Pseudobulk profiles were generated using the assigned cell type from the transcriptome. For comparison between Hela and U2OS cells, the top 2% most variable bins between groups were retained. After removal of bins with low variance, principal component analysis was used to assign clusters. Cluster identification was performed through comparison to transcriptome derived cell types, where high similarity was observed between cluster calling for all 3 measurements. A threshold minimum of 15,000 was applied to the data shown in Supplementary Figure 14a,b.
Assembly: hg19
Library strategy: scSTAMP-seq

source_name: Hela

value: Hela

value: Hela cell samples were labeled with PHO1, PHO2, and PHO3. Hela cell samples then received 60 seconds of UV DLP light illumination. After PHO1 labeling, Hela cell samples received 60 seconds of a three quarters area UV DLP light illumination photomask. After PHO2 labeling, Hela cell samples received 60 seconds of a one half area UV DLP light illumination photomask. After PHO3 labeling, Hela cell samples received 60 seconds of a one quarter area UV DLP light illumination photomask.


title: Cerebellum, Wt-DMSO, 413