title: KC_CCR1 KO PanIN

description: 2 female KC;CCR1-/- mice pooled

data_processing:
The University of Michigan Advanced Genomics Core also performed processing and alignment of the raw data using Cell Ranger version 6.1.0 with default settings and an initial expected cell count of 10,000.
Assembly: mm10-2020-A
Supplementary files format and content: raw and filtered Cell Ranger outputs

extract_protocol:
To prepare tissues for sequencing, samples were disrupted to single cell suspension by mechanically mincing the tissue, followed by enzymatic digestion with Collagenase V (1 mg/mL in RPMI, #C9263, Sigma-Aldrich) at 37°C for 30 min under constant shaking. After digestion, suspensions underwent serial filtration through 500 µm, 100 µm, and 40 µm mesh cell strainers. We then enriched for live cells using the MACS Dead Cell Removal Kit (#130-090-101, Miltenyi Biotec). The resulting single cell suspensions were brought to the University of Michigan Advanced Genomics Core for cDNA library preparation and sequencing.
Samples were run using 50-cycle paired-end reads on the NovaSeq 6000 (Illumina) to a depth of 100,000 reads.

treatment_protocol: We induced pancreatitis in 6-week-old KC and KC; Ccr1-/- mice by daily injection of caerulein intraperitoneally at 250 µg/kg over 5 days. Three weeks post caerulein injections we harvested pancreata and performed single-cell RNA sequencing analysis.

value: PanIN pancreas

value: KC; Ccr1-/-


title: KC PanIN

status: Public on Jun 26 2024

type: SRA

city: Ann Arbor

first: Marina

last: Pasca di Magliano

state: MI

address: 1500 E Medical Center Dr

country: USA

institute: University of Michigan Medical School

description: 1 female KC mouse

library_source: transcriptomic single cell

molecule: total RNA

organism: Mus musculus

source_name: PanIN pancreas

tag: tissue

tag: cell line

tag: number of_mice_pooled

tag: genotype

value: KC

tag: cell ranger_version

tag: genome

tag: run date


title: C57BL/6, PBS-T, spleen, biological rep9

city: Seoul

first: Soobin

last: Lee

address: 1, Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea

country: South Korea

institute: Seoul National University

library_source: transcriptomic

data_processing:
Raw paired-end reads were merged using PEAR v0.9.10 in default settings, and quality-filtered using the condition q20p95, retaining reads with a Phred score of 20 or higher in over 95% of base pairs. The products were clustered based on UMI sequences, using Clustal Omega v.1.2.4, excluding singletons in order to extract consensus sequences. Isotypes were annotated by aligning constant regions with the IMGT (International Immunogenetics Information System) constant gene database. V(D)J regions were annotated using IgBLAST v.1.17.1, with reads aligned to IGHV, IGHJ, and CDR1/2/3 regions. Unannotated reads were considered nonfunctional and excluded from analysis, and the remaining reads were identified as productive BCR sequences.
Assembly: mm10
Supplementary files format and content: sequence_id duplicate_count frequency sequence sequence_aa sequence_alignment germline_alignment v_call d_call j_call c_call junction junction_aa cdr1 cdr2 cdr3 cdr1_aa cdr2_aa cdr3_aa rev_comp productive v_cigar d_cigar j_cigar v_alignment_length v_alignment_mutation

source_name: spleen

extract_protocol:
Total RNA was extracted from mouse spleen, LG, and peripheral blood mononuclear cells using TRIzol reagent (Invitrogen, Waltham, MA, USA) following manufacturer’s protocol.
The isolated total RNAs were reverse-transcribed by mouse Heavy chain CH1 domain gene-specific primers, containing unique molecular identifier (UMI) sequences, by using the SuperScript™ IV First-Strand Synthesis System (Invitrogen). After cDNA synthesis, 1.8x volume of SPRI beads (AMPure XP, Beckman Coulter, Brea, CA, USA) were used to purify the cDNA and elute in 35 μL of DW. The purified cDNA was subjected to second-strand synthesis using V gene-specific primers and KAPA biosystems (KAPA HiFi HotStart, Roche, Basel, Switzerland). The PCR conditions were as follows: 95°C for 5 min, 98°C for 1 min, 60°C for 45 secs, and 72°C for 5 min. The synthesized second-stranded DNA was purified using 1x volume of SPRI beads. The purified VH genes were amplified by forward and reverse Illumina adaptor and ligated with Index primers by PCR. The PCR conditions were as follows: 95°C for 5 min; 25 cycles of 98°C for 30 sec, 65°C for 30 sec, and 72°C for 1 min; and 72°C for 5 min. PCR products were subjected to gel electrophoresis in 1.5% agarose gel, then the target amplicons were extracted (NucleoSpin Gel and PCR Clean‑up kit, Macherey-Nagel, Düren, Germany) and purified by 1x volume of SPRI beads as described above. The quality and concentration of the final PCR products were determined using TapeStation 4200 (G2991A, Agilent technologies, Santa Clara, CA, USA) and sequenced by Novaseq 6000 250PE platform (Illumina Inc.).

value: spleen


title: C57BL/6, PBS-T, spleen, biological rep8


title: Spleen, GC, KO4

city: New Haven

first: Anis

last: Barmada

state: CT

address: 300 Cedar Street

department: Department of Immunobiology

institute: Yale University

description:
GCB_Normalized_Counts.txt
KO4_355_222_S277

data_processing:
Sequence reads were run using STAR, mapped to the reference genome (mm10), and read counts were extracted and normalized.
Assembly: mm10
Supplementary files format and content: Normalized counts txt files [counts per million (CPM)]

source_name: Spleen

extract_protocol:
Cells were sorted into complete RPMI based on the markers listed in the sample metadata. Cells were spun down and then RNA was extracted using a Qiagen micro or mini kit.
Library construction was completed by the Yale Center for Genomic Analysis following a standard workflow.

treatment_protocol: Mice were immunized with 100L PBS washed SRBC IP and tissues were harvesed at day 28.

value: Spleen

tag: cell type

value: GC B Cell (CD95+/GL7+)

value: Pik3cg Knockout

tag: treatment

value: SRBC Immunization


title: C57BL/6, PBS-T, lacrimal gland, biological rep8

source_name: lacrimal gland

value: lacrimal gland


title: C57BL/6, PBS-T, spleen, biological rep7


title: C57BL/6, PBS-T, lacrimal gland, biological rep7


title: C57BL/6, PBS-T, lacrimal gland, biological rep6


title: C57BL/6, PBS-T, spleen, biological rep6


title: C57BL/6, PBS-T, spleen, biological rep5


title: LN, Lane 1, GEX

description: 10x Genomics, GEX

data_processing:
The single-cell sequencing data were aligned and processed using 10X CellRanger and CellRanger vdj.
Assembly: mm10 mouse reference genome
Supplementary files format and content: CellRanger output files: gene expression (matrix.mtx.gz, features.tsv.gz, barcodes.tsv.gz) and BCR annotations (filtered_contig_annotations.txt); additionally, table matching cell barcodes to mouse genotype (TotalSeq-CITE-barcodes-to-genotype.csv).

molecule: polyA RNA

source_name: Lymph node

extract_protocol:
Cells from draining lymph nodes were subjected to pan B cell isolation (Stemcell) negative selection kit with supplemental biotin-IgD antibody to enrich for switched B cells. Enriched cells (70% of total) were mixed back to untouched mixture (30% of total). Mixtures were barcoded with mouse TotalSeqTM-C (BioLegend). Cells were submitted to the Yale Center for Genome Analysis for sequencing following standard protocol.
cDNA libraries for gene expression and BCR sequencing were generated according to manufacturer’s instructions (Chromium Next GEM SingleCell V(D)J Reagent Kits). Each library was then sequenced on an Illumina NovaSeq 6000 platform.

value: Lymph node

value: Immune

value: WT & Pik3cg KO


title: LN, Lane 1, BCR

description: 10x Genomics, BCR


title: C57BL/6, PBS-T, lacrimal gland, biological rep3


title: C57BL/6, PBS-T, spleen, biological rep2


title: C57BL/6, PBS-T, spleen, biological rep4


title: bFGF_EGF_0d_rep2

city: Shanghai

first: Sutong

last: Xu

address: No. 500 Zhennan Road, Putuo District

country: China

institute: Tongji university

data_processing:
The quality of the raw reads in fastq format were investigated using fastp (version 0.19.7). Paired-end clean reads were aligned to the mm39 genome using HISAT2 v2.0.5.
featureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. And then FPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene.
Assembly: mm39
Supplementary files format and content: tab-delimited text files include RPKM values for each Sample

source_name: Mouse neural stem cells

growth_protocol: NSCs were isolated from the SVZs of adult C57BL/6 mice (2 female mice and 2 male mice were used for one cell isolation experiment) aged 8-9 weeks after euthanasia, which refer to the protocols described elsewhere (Walker and Kempermann, 2014; Leeman et al., 2018).  And then the cells were maintained in vitro in proliferation medium, which was Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 medium (DMEM/F12, Gibco, 11330032) supplemented with 1% penicillin streptomycin glutamine (P/S, Thermo, 10378016), 2% B27 minus vitamin A (Gibco, 12587-010), and the growth factors EGF and bFGF (R&D Systems, 20 ng/ml each).

extract_protocol:
Total RNA was extracted from samples (1×106 cells for one sample) using Trizol, and then the RNA qualification and qualification was determined by RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA).
RNA was prepared into cDNA and fragmented into 370~420 bp in length. The library fragments were purified with AMPure XP system (Beckman Coulter, Beverly, USA). Final libraries were prepared using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions, and them the library preparations were sequenced on an Illumina NovaSeq 6000 platform (illumine, USA).

treatment_protocol: NSCs obtained after at least three passages were cultured in adherent in the dish treated with poly-L-ornithine (Sigma, P3655) and laminin (Sigma, L2020) in proliferation medium with bFGF/EGF. After 16-18h, the medium were changed into quiescence media (DMEM/F12, 2% B27, 1% P/S, 20ng/ml bFGF (R&D Systems, 3139-FB-025), and 20 ng/ml BMP4 (R&D Systems, 5020-BP-010)) and BMP4-induced media ((DMEM/F12, 2% B27, 1% P/S, and 20ng/ml BMP4 (R&D systems)), and the cells were cultured for another six days

tag: strain

value: Mouse neural stem cells

value: bFGF/EGF

tag: time


title: C57BL/6, PBS-T, lacrimal gland, biological rep1


title: C57BL/6, PBS-T, lacrimal gland, biological rep9


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep8


title: C57BL/6, PBS-T, spleen, biological rep3


title: C57BL/6, NOD-FMT, spleen, biological rep9


title: C57BL/6, NOD-FMT, spleen, biological rep7


title: C57BL/6, NOD-FMT, spleen, biological rep6


title: C57BL/6, PBS-T, lacrimal gland, biological rep4


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep6


title: C57BL/6, NOD-FMT, spleen, biological rep8


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep9


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep7


title: C57BL/6, NOD-FMT, spleen, biological rep5


title: C57BL/6, NOD-FMT, spleen, biological rep4


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep4


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep5


title: C57BL/6, PBS-T, lacrimal gland, biological rep5


title: C57BL/6, NOD-FMT, spleen, biological rep3


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep3


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep2


title: C57BL/6, PBS-T, spleen, biological rep1


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep10


title: C57BL/6, NOD-FMT, spleen, biological rep1


title: C57BL/6, NC1, spleen, biological rep5


title: C57BL/6, NOD-FMT, lacrimal gland, biological rep1


title: C57BL/6, NC1, lacrimal gland, biological rep5


title: C57BL/6, PBS-T, lacrimal gland, biological rep2


title: C57BL/6, NC1, spleen, biological rep4


title: C57BL/6, NC1, spleen, biological rep3


title: C57BL/6, NC1, lacrimal gland, biological rep3


title: C57BL/6, NC1, spleen, biological rep2


title: C57BL/6, NC1, lacrimal gland, biological rep2


title: C57BL/6, NC1, lacrimal gland, biological rep4


title: C57BL/6, NC1, spleen, biological rep1


title: C57BL/6, NOD-FMT, spleen, biological rep10


title: Kidney-UA-Day21-Rep2 [M7]

city: Chengdu

first: Jing

last: Liu

state: Sichuan  SC

address: No.17, Renmin South Rd 3rd Section

institute: West China Hospital of Sichuan University

description: 21-day feeding of adenine and ptassium oxonate

data_processing:
The raw paired end reads were trimmed and quality controlled by SeqPrep (https://github.com/jstjohn/SeqPrep) and Sickle (https://github.com/najoshi/sickle) with default parameters.
Clean reads were separately aligned to reference genome with orientation mode using TopHat (http://tophat.cbcb.umd.edu/, version2.0.0)[1] software.
Sequencing reads should be uniquely matched to the genome allowing up to 2 mismatches, without insertions or deletions.
The region of gene were expanded following depths of sites and the operon was obtained.
The whole genome was split into multiple 15kbp windows that share 5kbp. New transcribed regions were defined as more than 2 consecutive windows without overlapped region of gene, where at least 2 reads mapped per window in the same orientation.
Assembly: mm10
Supplementary files format and content: tab-deliminated text file includes counts for each sample

source_name: kidney

extract_protocol:
Total RNA was extracted from the tissue using TRIzol® Reagent according the manufacturer’s instructions (Invitrogen) and genomic DNA was removed using DNase I (TaKara). Then RNA quality was determined by 2100 Bioanalyser (Agilent) and quantified using the ND-2000 (NanoDrop Technologies). Only high-quality RNA sample (OD260/280=1.8~2.2, OD260/230≥2.0, RIN≥6.5, 28S:18S≥1.0, >2μg) was used to construct sequencing library.
RNA-seq transcriptome librariy was prepared following TruSeqTM RNA sample preparation Kit from Illumina (San Diego, CA) using 1μg of total RNA.  Then the synthesized cDNA was subjected to end-repair, phosphorylation and ‘A’ base addition according to Illumina’s library construction protocol. Libraries were size selected for cDNA target fragments of 200–300 bp on 2% Low Range Ultra Agarose followed by PCR amplified using Phusion DNA polymerase (NEB) for 15 PCR cycles. After quantified by TBS380, paired-end RNA-seq sequencing library was sequenced with the Illumina HiSeq xten/NovaSeq 6000 sequencer (2 × 150bp read length).

value: kidney

value: C57BL/6J, wild type


title: Kidney-Control-Rep1 [C3]

description: control group


title: Kidney-UA-Day21-Rep1 [M3]

value: 21-day feeding of adenine and ptassium oxonate


title: Neuro-2A cells, U4 AMO treated, repeat 2 (3'-Seq)

city: guangzhou

first: chengguo

last: yao

address: No. 74 zhongshan 2rd road

department: school of medicine

institute: sysu

data_processing:
The downstream sequence analysis was performed utilizing our recently published pipeline, QuantifyPoly(A) (QuantifyPoly(A): reshaping alternative polyadenylation landscapes of eukaryotes with weighted density peak clustering. Briefings in bioinformatics22,  (2021); published online EpubNov 5 (10.1093/bib/bbab268).)
Assembly: hg38
Supplementary files format and content: bw files

source_name: Neuro-2A cells

growth_protocol: HeLa and HEK293 cells were obtained from ATCC and cultured in Dulbecco's modified Eagle's medium supplemented with 10% fetal bovine serum (Thermo Scientific).  NIH3T3, and Neuro-2a cells were obtained from iCell Bioscience Inc. (Shanghai, China) and cultured in commercially available medium (Cat. No. iCell-m041-001b; iCell-m040-001b).

extract_protocol:
Total RNA was extracted from cultured cells using the TRIzol (Thermo Scientific).
3'-Seq was conducted using the QuantSeq Rev 3ʹ mRNA-seq library prep kit (Cat. No. 016.24; Lexogen)

treatment_protocol: Electroporation was performed using a Bio-Rad Gene pulser at 960 μF and 280 V. After electroporation, cells were cultured for 12 hours in 6 well plates with 2 ml DMEM.

value: Neuro-2A cells

value: mouse neuroblasts cell line

value: U4 AMO treated


title: C57BL/6, NOD-FMT, spleen, biological rep2

value: spleen


title: Neuro-2A cells, U1 AMO treated, repeat 2 (3'-Seq)

value: U1 AMO treated


title: Kidney-Control-Rep2 [C5]

description: control group


title: Neuro-2A cells, U4 AMO treated, repeat 1 (3'-Seq)


title: Neuro-2A cells, NC AMO treated, repeat 2 (3'-Seq)

value: negative control

value: negative control AMO treated


title: Neuro-2A cells, NC AMO treated, repeat 1 (3'-Seq)


title: Neuro-2A cells, U1 AMO treated, repeat 1 (3'-Seq)


title: NIH-3T3 cells, U4 AMO treated, repeat 2 (3'-Seq)

source_name: NIH-3T3 cells

value: NIH-3T3 cells

value: fibroblast cell line


title: NIH-3T3 cells, NC AMO treated, repeat 2 (3'-Seq)


title: NIH-3T3 cells, U4 AMO treated, repeat 1 (3'-Seq)


title: NIH-3T3 cells, U1 AMO treated, repeat 1 (3'-Seq)


title: NIH-3T3 cells, NC AMO treated, repeat 1 (3'-Seq)


title: Astrocyte, Aged, 12am, rep2

city: Worcester

first: Patrick

last: Sheehan

state: MA

address: 364 Plantation Ave.

department: Neurobiology

institute: University of Massachusetts Medical School

description:
WT89_12am_Female_Aged
Aged_Astrocyte_Counts

data_processing:
RNA-seq reads were aligned and quantitated to the Ensembl release 101 primary assembly with an Illumina DRAGEN Bio-IT on-premise server running version 3.9.3-8 software.
Assembly: Mouse Ensembl release 101 primary assembly
Supplementary files format and content: CSV file contains raw counts for each sample in the specified group.

source_name: Cortex

extract_protocol:
Astrocyte- or microglia-specific RNA were isolated by incubating tissue with anti-GFP or anti-HA coated beads, respectively.  RNA was then purified using the RNA Clean and Concentrator kit (Zymo Research)
Total RNA integrity was determined using Agilent Bioanalyzer or 4200 Tapestation. Library preparation was performed with 10ng of total RNA with a Bioanalyzer RIN score greater than 8.0. ds-cDNA was prepared using the SMARTer Ultra Low RNA kit for Illumina Sequencing (Takara-Clontech) per manufacturer's protocol.

treatment_protocol: Mice were placed in constant darkness 24 hours prior to sacrificing.

value: Cortex

tag: Sex

value: Female

tag: batch

value: Batch 1

value: Astrocyte

value: Aged


title: Astrocyte, Aged, 8pm, rep1

description:
WT86_8pm_Female_Aged
Aged_Astrocyte_Counts


title: NIH-3T3 cells, U1 AMO treated, repeat 2 (3'-Seq)


title: C57BL/6, NC1, lacrimal gland, biological rep1

value: lacrimal gland


title: Kidney-UA-Day21-Rep3 [M9]

value: kidney

value: C57BL/6J, wild type


title: Astrocyte, Aged, 4pm, rep1

description:
WT126_4pm_Female_Aged
Aged_Astrocyte_Counts


title: Astrocyte, Aged, 8am, rep2

description:
WT130_8am_Female_Aged
Aged_Astrocyte_Counts


title: Astrocyte, Aged, 12pm, rep2

description:
WT65_12pm_Female_Aged
Aged_Astrocyte_Counts


title: Astrocyte, Aged, 8am, rep1

description:
WT64_8am_Male_Aged
Aged_Astrocyte_Counts

value: Male


title: Astrocyte, Aged, 12pm, rep1

description:
WT128_12pm_Female_Aged
Aged_Astrocyte_Counts


title: Kidney-Control-Rep3 [C6]

description: control group


title: Astrocyte, Aged, 4am, rep1

description:
WT125_4am_Female_Aged
Aged_Astrocyte_Counts


title: Microglia, Aged, 12am, rep2

description:
WT42_12am_Female_Aged
Aged_Microglia_Counts

value: Microglia


title: Microglia, Aged, 12am, rep1

description:
WT51_12am_Male_Aged
Aged_Microglia_Counts


title: Microglia, Aged, 4pm, rep2

description:
WT6_4pm_Female_Aged
Aged_Microglia_Counts


title: Microglia, Aged, 8pm, rep1

description:
WT53_8pm_Male_Aged
Aged_Microglia_Counts


title: Microglia, Aged, 12pm, rep2

description:
WT5_12pm_Male_Aged
Aged_Microglia_Counts


title: Microglia, Aged, 4pm, rep1

description:
WT54_4pm_Female_Aged
Aged_Microglia_Counts


title: Microglia, Aged, 8am, rep1

description:
WT56_8am_Female_Aged
Aged_Microglia_Counts


title: Microglia, Aged, 8am, rep2

description:
WT2_8am_Male_Aged
Aged_Microglia_Counts


title: Microglia, Aged, 12pm, rep1

description:
WT55_12pm_Female_Aged
Aged_Microglia_Counts


title: Bulk, WT, 12am, rep2

description:
WT178_12am_Female_batch2
WT_Bulk_Counts

value: Batch 2

value: Bulk

value: WT


title: Astrocyte, Aged, 12am, rep1

description:
WT120_12am_Male_Aged
Aged_Astrocyte_Counts


title: Bulk, WT, 8pm, rep2

description:
WT153_8pm_Female_batch2
WT_Bulk_Counts


title: Bulk, WT, 10pm, rep2

description:
WT168_10pm_Female_batch2
WT_Bulk_Counts


title: Astrocyte, Aged, 4pm, rep2

description:
WT78_4pm_Female_Aged
Aged_Astrocyte_Counts


title: Bulk, WT, 4pm, rep2

description:
WT148_4pm_Female_batch2
WT_Bulk_Counts


title: Bulk, WT, 2pm, rep2

description:
WT147_2pm_Female_batch2
WT_Bulk_Counts


title: Bulk, WT, 10am, rep2

description:
WT131_10am_Female_batch2
WT_Bulk_Counts


title: Bulk, WT, 12pm, rep2

description:
WT165_12pm_Male_batch2
WT_Bulk_Counts


title: Bulk, WT, 8am, rep2

description:
WT176_8am_Female_batch2
WT_Bulk_Counts


title: Bulk, WT, 6am, rep2

description:
WT175_6am_Female_batch2
WT_Bulk_Counts


title: Bulk, WT, 4am, rep2

description:
WT129_4am_Male_batch2
WT_Bulk_Counts


title: Microglia, Aged, 4am, rep2

description:
WT43_4am_Female_Aged
Aged_Microglia_Counts


title: Astrocyte, Aged, 4am, rep2

description:
WT101_4am_Male_Aged
Aged_Astrocyte_Counts


title: Bulk, WT, 2am, rep2

description:
WT174_2am_Female_batch2
WT_Bulk_Counts


title: Bulk, APP, 8pm, rep2

description:
APP154_8pm_Female_batch2
APP_Bulk_Counts

value: APP


title: Bulk, APP, 4pm, rep2

description:
APP136_4pm_Female_batch2
APP_Bulk_Counts


title: Bulk, APP, 8am, rep2

description:
APP103_8am_Male_batch2
APP_Bulk_Counts


title: Bulk, APP, 6pm, rep2

description:
APP122_6pm_Male_batch2
APP_Bulk_Counts


title: Bulk, APP, 6am, rep2

description:
APP156_6am_Female_batch2
APP_Bulk_Counts


title: Bulk, APP, 10am, rep2

description:
APP113_10am_Male_batch2
APP_Bulk_Counts


title: Bulk, WT, 12am, rep1

description:
WT32_12am_Male_batch1
WT_Bulk_Counts


title: Bulk, APP, 4am, rep2

description:
APP100_4am_Male_batch2
APP_Bulk_Counts


title: Bulk, WT, 8pm, rep1

description:
WT24_8pm_Male_batch1
WT_Bulk_Counts


title: Bulk, WT, 6pm, rep1

description:
WT20_6pm_Male_batch1
WT_Bulk_Counts


title: Microglia, Aged, 4am, rep1

description:
WT49_4am_Female_Aged
Aged_Microglia_Counts


title: Bulk, WT, 4pm, rep1

description:
WT16_4pm_Male_batch1
WT_Bulk_Counts


title: Bulk, WT, 12pm, rep1

description:
WT132_12pm_Female_batch2
WT_Bulk_Counts


title: Bulk, APP, 10pm, rep2

description:
APP95_10pm_Male_batch2
APP_Bulk_Counts


title: Bulk, WT, 8am, rep1

description:
WT6_8am_Male_batch1
WT_Bulk_Counts


title: Bulk, WT, 2pm, rep1

description:
WT10_2pm_Male_batch1
WT_Bulk_Counts


title: Bulk, APP, 2am, rep2

description:
APP96_2am_Male_batch2
APP_Bulk_Counts


title: Bulk, WT, 6am, rep1

description:
WT55_6am_Male_batch1
WT_Bulk_Counts


title: Bulk, WT, 4am, rep1

description:
WT47_4am_Female_batch1
WT_Bulk_Counts


title: Bulk, APP, 12am, rep2

description:
APP155_12am_Female_batch2
APP_Bulk_Counts


title: Bulk, WT, 2am, rep1

description:
WT37_2am_Male_batch1
WT_Bulk_Counts


title: Bulk, APP, 2pm, rep2

description:
APP157_2pm_Female_batch2
APP_Bulk_Counts


title: Bulk, APP, 10pm, rep1

description:
APP31_10pm_Female_batch1
APP_Bulk_Counts


title: Bulk, APP, 8pm, rep1

description:
APP29_8pm_Male_batch1
APP_Bulk_Counts


title: Bulk, APP, 6pm, rep1

description:
APP28_6pm_Female_batch1
APP_Bulk_Counts


title: Bulk, APP, 12am, rep1

description:
APP33_12am_Male_batch1
APP_Bulk_Counts


title: Bulk, APP, 12pm, rep2

description:
APP121_12pm_Female_batch2
APP_Bulk_Counts


title: Bulk, APP, 2pm, rep1

description:
APP25_2pm_Male_batch1
APP_Bulk_Counts


title: Bulk, APP, 4pm, rep1

description:
APP26_4pm_Male_batch1
APP_Bulk_Counts


title: Bulk, APP, 12pm, rep1

description:
APP23_12pm_Male_batch1
APP_Bulk_Counts


title: Bulk, WT, 10pm, rep1

description:
WT30_10pm_Male_batch1
WT_Bulk_Counts


title: Bulk, APP, 6am, rep1

description:
APP36_6am_Male_batch1
APP_Bulk_Counts


title: Bulk, APP, 10am, rep1

description:
APP21_10am_Female_batch1
APP_Bulk_Counts


title: Bulk, APP, 8am, rep1

description:
APP19_8am_Female_batch1
APP_Bulk_Counts


title: Astrocyte, WT, 10pm, rep2

description:
WT168_10pm_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, WT, 6pm, rep2

description:
WT152_6pm_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, WT, 8pm, rep2

description:
WT153_8pm_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, WT, 2pm, rep2

description:
WT147_2pm_Female_batch2
WT_Astrocyte_Counts


title: Bulk, WT, 10am, rep1

description:
WT7_10am_Male_batch1
WT_Bulk_Counts


title: Astrocyte, WT, 4pm, rep2

description:
WT148_4pm_Female_batch2
WT_Astrocyte_Counts


title: Bulk, APP, 4am, rep1

description:
APP35_4am_Female_batch1
APP_Bulk_Counts


title: Astrocyte, WT, 12pm, rep2

description:
WT165_12pm_Male_batch2
WT_Astrocyte_Counts


title: Astrocyte, WT, 8am, rep2

description:
WT176_8am_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, APP, 12am, rep2

description:
APP155_12am_Female_batch2
APP_Astrocyte_Counts


title: Astrocyte, WT, 2am, rep2

description:
WT174_2am_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, WT, 10am, rep2

description:
WT131_10am_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, APP, 10pm, rep2

description:
APP95_10pm_Male_batch2
APP_Astrocyte_Counts


title: Astrocyte, APP, 6pm, rep2

description:
APP122_6pm_Male_batch2
APP_Astrocyte_Counts


title: Astrocyte, WT, 4am, rep2

description:
WT129_4am_Male_batch2
WT_Astrocyte_Counts


title: Astrocyte, APP, 4pm, rep2

description:
APP136_4pm_Female_batch2
APP_Astrocyte_Counts


title: Astrocyte, WT, 6am, rep2

description:
WT175_6am_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, APP, 10am, rep2

description:
APP113_10am_Male_batch2
APP_Astrocyte_Counts


title: Astrocyte, APP, 2pm, rep2

description:
APP157_2pm_Female_batch2
APP_Astrocyte_Counts


title: Astrocyte, APP, 8pm, rep2

description:
APP154_8pm_Female_batch2
APP_Astrocyte_Counts


title: Astrocyte, APP, 6am, rep2

description:
APP156_6am_Female_batch2
APP_Astrocyte_Counts


title: Astrocyte, APP, 12pm, rep2

description:
APP121_12pm_Female_batch2
APP_Astrocyte_Counts


title: Bulk, APP, 2am, rep1

description:
APP34_2am_Female_batch1
APP_Bulk_Counts


title: Astrocyte, APP, 2am, rep2

description:
APP96_2am_Male_batch2
APP_Astrocyte_Counts


title: Astrocyte, WT, 10pm, rep1

description:
WT30_10pm_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, WT, 12am, rep1

description:
WT32_12am_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, APP, 4am, rep2

description:
APP100_4am_Male_batch2
APP_Astrocyte_Counts


title: Astrocyte, WT, 8pm, rep1

description:
WT24_8pm_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, WT, 12am, rep2

description:
WT178_12am_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, WT, 2pm, rep1

description:
WT10_2pm_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, WT, 10am, rep1

description:
WT7_10am_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, WT, 4pm, rep1

description:
WT16_4pm_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, WT, 6am, rep1

description:
WT55_6am_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, WT, 12pm, rep1

description:
WT132_12pm_Female_batch2
WT_Astrocyte_Counts


title: Astrocyte, WT, 2am, rep1

description:
WT37_2am_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, APP, 12am, rep1

description:
APP33_12am_Male_batch1
APP_Astrocyte_Counts


title: Astrocyte, APP, 6pm, rep1

description:
APP28_6pm_Female_batch1
APP_Astrocyte_Counts


title: Astrocyte, WT, 8am, rep1

description:
WT6_8am_Male_batch1
WT_Astrocyte_Counts


title: Astrocyte, APP, 10pm, rep1

description:
APP31_10pm_Female_batch1
APP_Astrocyte_Counts


title: Astrocyte, APP, 8pm, rep1

description:
APP29_8pm_Male_batch1
APP_Astrocyte_Counts


title: Astrocyte, APP, 8am, rep2

description:
APP103_8am_Male_batch2
APP_Astrocyte_Counts


title: Astrocyte, APP, 10am, rep1

description:
APP21_10am_Female_batch1
APP_Astrocyte_Counts


title: Astrocyte, WT, 4am, rep1

description:
WT47_4am_Female_batch1
WT_Astrocyte_Counts


title: Astrocyte, APP, 2pm, rep1

description:
APP25_2pm_Male_batch1
APP_Astrocyte_Counts


title: Astrocyte, APP, 4pm, rep1

description:
APP26_4pm_Male_batch1
APP_Astrocyte_Counts


title: Astrocyte, APP, 8am, rep1

description:
APP19_8am_Female_batch1
APP_Astrocyte_Counts


title: Astrocyte, APP, 12pm, rep1

description:
APP23_12pm_Male_batch1
APP_Astrocyte_Counts


title: Astrocyte, APP, 6am, rep1

description:
APP36_6am_Male_batch1
APP_Astrocyte_Counts


title: Microglia, WT, 12am, rep2

description:
WT8_12am_Female_batch2
WT_Microglia_Counts


title: Astrocyte, APP, 4am, rep1

description:
APP35_4am_Female_batch1
APP_Astrocyte_Counts


title: Astrocyte, WT, 6pm, rep1

description:
WT20_6pm_Male_batch1
WT_Astrocyte_Counts


title: Microglia, WT, 10pm, rep1

description:
WT74_10pm_Female_batch2
WT_Microglia_Counts


title: Microglia, WT, 2pm, rep2

description:
WT194_2pm_Male_batch3
WT_Microglia_Counts

value: Batch 3


title: Microglia, WT, 8pm, rep2

description:
WT262_8pm_Female_batch3
WT_Microglia_Counts


title: Microglia, WT, 4pm, rep2

description:
WT260_4pm_Female_batch3
WT_Microglia_Counts


title: Microglia, WT, 10am, rep2

description:
WT76_10am_Male_batch2
WT_Microglia_Counts


title: Microglia, WT, 8am, rep2

description:
WT80_8am_Male_batch2
WT_Microglia_Counts


title: Microglia, WT, 6am, rep2

description:
WT72_6am_Male_batch2
WT_Microglia_Counts


title: Microglia, WT, 4am, rep2

description:
WT18_4am_Female_batch2
WT_Microglia_Counts


title: Microglia, APP, 8pm, rep2

description:
APP45_8pm_Male_batch2
APP_Microglia_Counts


title: Microglia, WT, 2am, rep2

description:
WT15_2am_Male_batch2
WT_Microglia_Counts


title: Microglia, APP, 12am, rep2

description:
APP46_12am_Male_batch2
APP_Microglia_Counts


title: Microglia, APP, 10pm, rep2

description:
APP64_10pm_Female_batch2
APP_Microglia_Counts


title: Microglia, APP, 2pm, rep2

description:
APP41_2pm_Male_batch2
APP_Microglia_Counts


title: Microglia, APP, 6pm, rep2

description:
APP60_6pm_Female_batch2
APP_Microglia_Counts


title: Microglia, APP, 12pm, rep2

description:
APP39_12pm_Male_batch2
APP_Microglia_Counts


title: Astrocyte, APP, 2am, rep1

description:
APP34_2am_Female_batch1
APP_Astrocyte_Counts


title: Microglia, APP, 8am, rep2

description:
APP176_8am_Male_batch3
APP_Microglia_Counts


title: Microglia, APP, 6am, rep2

description:
APP50_6am_Male_batch2
APP_Microglia_Counts


title: Microglia, APP, 4pm, rep2

description:
APP59_4pm_Female_batch2
APP_Microglia_Counts


title: Microglia, WT, 6pm, rep1

description:
WT7_6pm_Male_batch1
WT_Microglia_Counts


title: Microglia, APP, 2am, rep2

description:
APP66_2am_Female_batch2
APP_Microglia_Counts


title: Microglia, WT, 4pm, rep1

description:
WT6_4pm_Male_batch1
WT_Microglia_Counts


title: Microglia, WT, 12pm, rep2

description:
WT265_12pm_Female_batch3
WT_Microglia_Counts


title: Microglia, WT, 8pm, rep1

description:
WT8_8pm_Male_batch1
WT_Microglia_Counts


title: Microglia, WT, 12pm, rep1

description:
WT3_12pm_Female_batch1
WT_Microglia_Counts


title: Microglia, WT, 10am, rep1

description:
WT40_10am_Female_batch1
WT_Microglia_Counts


title: Microglia, WT, 4am, rep1

description:
WT26_4am_Male_batch1
WT_Microglia_Counts


title: Microglia, WT, 8am, rep1

description:
WT29_8am_Female_batch1
WT_Microglia_Counts


title: Microglia, WT, 6am, rep1

description:
WT28_6am_Female_batch1
WT_Microglia_Counts


title: Microglia, APP, 4am, rep2

description:
APP170_4am_Male_batch3
APP_Microglia_Counts


title: Microglia, WT, 2pm, rep1

description:
WT5_2pm_Male_batch1
WT_Microglia_Counts


title: Microglia, APP, 12am, rep1

description:
APP15_12am_Female_batch1
APP_Microglia_Counts


title: Microglia, WT, 2am, rep1

description:
WT25_2am_Female_batch1
WT_Microglia_Counts


title: Microglia, APP, 8pm, rep1

description:
APP12_8pm_Female_batch1
APP_Microglia_Counts


title: Microglia, APP, 10pm, rep1

description:
APP13_10pm_Male_batch1
APP_Microglia_Counts


title: Microglia, APP, 10am, rep2

description:
APP35_10am_Female_batch2
APP_Microglia_Counts


title: Microglia, APP, 6pm, rep1

description:
APP11_6pm_Male_batch1
APP_Microglia_Counts


title: Microglia, APP, 12pm, rep1

description:
APP1_12pm_Female_batch1
APP_Microglia_Counts


title: Microglia, APP, 10am, rep1

description:
APP24_10am_Male_batch1
APP_Microglia_Counts


title: Microglia, WT, 12am, rep1

description:
WT14_12am_Male_batch1
WT_Microglia_Counts


title: Microglia, APP, 8am, rep1

description:
APP20_8am_Female_batch1
APP_Microglia_Counts


title: Microglia, APP, 2am, rep1

description:
APP16_2am_Male_batch1
APP_Microglia_Counts


title: Microglia, APP, 2pm, rep1

description:
APP2_2pm_Female_batch1
APP_Microglia_Counts


title: Microglia, APP, 6am, rep1

description:
APP19_6am_Female_batch1
APP_Microglia_Counts


title: Microglia, APP, 4am, rep1

description:
APP18_4am_Female_batch1
APP_Microglia_Counts


title: Microglia, APP, 4pm, rep1

description:
APP10_4pm_Male_batch1
APP_Microglia_Counts


title: 5_Pod_RARRES1_WT

city: New York

first: Zeguo

last: Sun

address: 1468 Madison Avenue

institute: Ichan School of Medicine at Mount Sinai

data_processing:
Raw fastq files were aligned with mm10 by cellranger/7.1.0 with default parameters.Ambient RNAs was cleaned by soupX with default parameters.
Gene-cell QC was performed by Seurat 4. Genes expressed in less than 3 cells were removed and Cells expressing less than 200 genes were removed. Potential doublets were identified and removed with DoubletFinder.
Assembly: mm10
Supplementary files format and content: Sparse matrix of gene-cell expression after ambient RNA cleaned by soupX.

source_name: Kidney cortex

extract_protocol:
Decapsulated whole kidneys were minced and dissociated in 2 mL of digestion buffer at 37°C for 17 min. The digested tissue was gently resuspended in RPMI medium supplemented with 10% FBS and filtered through a 70-micron cell strainer (Falcon) on ice and pelleted by centrifugation (200g for 5 min), and repeated. The pellet was resuspended in HBSS and further filtered through a 40-micron cell strainer (Falcon) to obtain single cells. After centrifugation, the cell pellets were incubated with 5 mL of RBC lysis buffer (eBioscience, 00-4333-57) to remove any remaining red blood cells on ice for 5 min. Finally, the cells were washed and resuspended in RPMI medium twice to remove any debris or cell aggregates. Cell viability and number were determined using a Countess II Automated Cell Counter (Invitrogen, C10227) after staining with trypan blue.
Sequencing libraries were constructed according to 10x standard protocol by following the steps cDNA fragmentation, end repair and A-tailing, size selection by SPRIselect beads (Beckman Coulter), adaptor ligation, sample index PCR amplification, and repeat SPRIselect beads size selection. The final constructed single-cell libraries were sequenced by Illumina Novaseq machine with total reads per cell targeted for a minimum of 50,000.

value: Kidney cortex

value: Nphs1-rtTA; TRE-hRARRES1WT transgenes


title: 4_WT_control

value: Control


title: 3_WT_control


title: 6_Pod_RARRES1_WT


title: IMs .control, in vivo, rep1

city: new york

first: David

last: Lyden

state: NY

address: 413 East 69th Street, Room BB1228

department: Pediatrics

institute: Weill Cornell medical College

data_processing:
The raw sequencing reads in BCL format were processed through bcl2fastq 2.19 (Illumina) for FASTQ conversion and demultiplexing.
RNA reads were aligned and mapped to the mm9 mouse reference genome by TopHat2 (version 2.0.11) (http://ccb.jhu.edu/software/tophat/index.shtml), and transcriptome reconstruction was performed by Cufflinks (version 2.1.1) (http://cole-trapnell-lab.github.io/cufflinks/).
The abundance of transcripts was measured with Cufflinks in fragments per kilobase of exon model per million mapped reads (FPKM).
Gene expression profiles were constructed for differential expression, clustering, and principal component analyses using the DESeq2 package (https://bioconductor.org/packages/release/bioc/html/DESeq2.html).
For differential expression analysis, pairwise comparisons between two or more groups were performed using parametric tests where read counts follow a negative binomial distribution with a gene-specific dispersion parameter. CorrectedP-values were calculated based on the Benjamini–Hochberg method to adjust for multiple testing.
Assembly: mm9
Supplementary files format and content: Excel Files containg raw count for each sample

source_name: lung tissue

extract_protocol:
Ttizol + RNeasy Micro Kit
SMART-Seq v4 Ultra Low Input RNA plus Nextera XT DNA Sample Preparation

treatment_protocol: EVPs were labled eith pkh67, and retro-orbitally administreted to mice. After 1h the lung was harvasted, digested and subjected to sorting by flow-cytometery.

value: lung tissue

value: interstitial macrophages

value: PBS


title: IMs .B16F10 EVP, in vivo, rep3

value: B16F10 EVPs


title: IMs ,B16F10 EVP, in vivo, rep2


title: IMs .control, in vivo, rep2


title: IMs .control, in vivo, rep3


title: IMs ,B16F10 EVP, in vivo, rep1


title: IMs .control, rep2

growth_protocol: After FACS sorting, cell were cultured with RPMI with 10% FBS, GM-CSF (20ng/ml), 1 mM Sodium Pyruvate, and 1x penicillin/streptomycin for 24h, and subjected to EVPs treatment.

extract_protocol:
Trizol
SMART-Seq v4 Ultra Low Input RNA plus Nextera XT DNA Sample Preparation


title: IMs ,K7M2 ITGA5 KO EVP, rep1

value: K7M2 ITGA5 KO EVP


title: IMs ,K7M2 ITGA5 KO EVP, rep2


title: IMs .control, rep1


title: IMs ,B16F10 ITGA5 KO EVP, rep2

value: B16F10 ITGA5 KO EVP


title: IMs ,K7M2 CON KO EVP, rep1

value: K7M2 CON KO EVP


title: IMs ,K7M2 CON KO EVP, rep2


title: IMs ,B16F10 CON KO EVP, rep2

value: B16F10 CON KO EVP


title: IMs ,B16F10 ITGA5 KO EVP, rep1


title: IMs ,B16F10 CON KO EVP, rep1


title: LNP-Ctrl, scRNA-seq-TCR

city: Houston

first: Dafei

last: Chai

state: Texas

address: Alkek Building One Baylor Plaza

institute: Baylor College of Medicine

description: 10× Genomics

data_processing:
TCR Raw gene expression matrices were derived using the Count v7.1.0 pipeline (10x genomics Cloud) with mouse GRCm38/mm10 as the reference.
Raw sequence reads in the FASTQ formats were aligned to the mouse reference genome using CellRanger Count v7.1.0 pipeline (https://cloud.10xgenomics.com) with the default settings for alignment, barcode assignment, and UMI counting of the raw sequencing data with genome reference Mouse (mm10) 2020-A. BCR and TCR Raw gene expression matrices were generated by CellRanger count pipeline with default parameters and mouse GRCm38/mm10 as the reference genome.  The doublet cells were eliminated using the R package scDblFinder (1.14.0)[PMID: 35814628], and additional processing was performed using the R package Seurat (v4.4.0). Filtered cells were those with >10% mitochondrial, nFeature RNA >7500, or <200 identified genes.  The highly variable genes were determined using the "vst" selection method in Seurat and the FindVariableFeatures tool after log-normalization. The ScaleData function in Seurat was used to scale the data. The RunHarmony function from the R package harmony (1.01)[PMID: 31740819] was used to combine multiple data after PCA analysis. Using Seurat's FindNeighbors FindClusters function and a resolution of 0.5, neighbors and clusters were defined. RunUMAP was used to calculate the UMAP dimensionality reduction with default parameters utilizing the top 30 principal components (PCs) and harmony reduction. For the analysis focusing on T cells, B cells, NK cells and NK like cells which subset from the annotation cell types, data were re-run from NormalizeData function following Seurat pipeline. To assist with the annotation of the T cell subcluster, we utilize the R packages STACAS (2.1.3)[PMID: 32845323] and ProjecTILs (3.2.0)[PMID: 34017005].
DEGs between clusters were obtained with a Wilcoxon followed by Bonferroni correction using the FindAllMarkers function in Seurat. For GO and KEGG enrichment analysis, Clusterprofiler (4.8.3)[PMID: 34557778] was used to examine DEG of cell clusters. The AddModuleScore function was recruited to evaluate the gene set score of T cells’ Transcription factors, Memory markers, Cytotoxic markers as well as Checkpoint markers. For plotting specific genes or gene set score of interest, FeaturePlot function in Seurat and plot_density function in Nebulosa (1.10.0)[PMID: 33459785] was used to show the genes or gene set score distribution on cells. UMAP and heatmap plot modification was done using scRNAtoolVis (0.0.7).
scVDJ and scRNA seq analysis was performed by combining Seurat and scRepertoire (1.11.0) [ PMID: 32789006] packages. In brief, scVDJ analysis is carried out when the T cells and B cells subcluster are combine with TCR and BCR data, respectively, using the combine TCR or combine BCR function in scRepertoire, the downstream process adheres scRepertoire protocol. For the motif sequence of TRAV and TRAB, we hired the python module CoNGA to calculate and show the TCR motif of subcluster of T cells.
Pesudotime analysis was performed via two different methods. We use R package FitDevo (1.2.1) [PMID: 35870444] to analyze the developmental trajectories of T cells, B cells, NK cells, and NKL, and also infer the CD8+ and CD4+ T cell starting cell populations through global cell differentiation. R package Slingshot (2.8.0)[PMID: 29914354] is used to infer the differentiation paths of CD8+T cells and CD4+T cells. By combining the UMAP dimensionality reduction results in Seurat and the starting trajectory of FitDevo analysis, we use the slingPseudotime function to predict the cell differentiation path. Then the potential developmental pathways in each cell group were obtained.
The CellChatR toolkit (2.2) [PMID: 33597522] was used to explore cellular interactions different between control and treatment groups. Communication probabilities were calculated based on the CellChatDB database of literature and PPI supported ligand–receptor interactions in mouse datasets. We first filter the incoming and outgoing parameters for each sample group using the selectK function, and then we aggregate the data from the two cell groups using the mergeCellChat function. The official Cellchat protocol "Comparison analysis of multiple datasets using CellChat" is used to analyze the merged data items.
Assembly: mm10
Supplementary files format and content: h5 or gz

source_name: Tumor

growth_protocol: C57BL/6J micewere injected subcutaneously with 3x106 MC38-p53KO/E285K tumors.  On day 10 post-tumor inoculation, when the tumors were palpable (~50-100mm3),  treatment was initiated.

extract_protocol:
Tumors were harvested 14 days lfollowing LNP-pE285K-mAb or LNP-Ctrl treatment, single cell suspensions were prepared and stained with APC-Cy7-conjugated anti-mouse CD45 antibody. Briefly, dead cells were excluded by staining with DAPI viability dye  and Fc receptors were blocked prior to the addition of PE-conjugated anti-mouse CD45  antibody. 1,0000 CD45+ live cells were sorted from each tumor sample using a FACSAria IIIu instrument. Equal numbers of sorted CD45+ cells from 5 mice per group were pooled, pelleted and resuspended concentrated by centrifugation, and resuspended at a density of 1 × 103 cells/μl in RPMI1640 medium containing 10% FBS. Approximately 10000 cells were allocated for the 10 × Genomics 5′ v 2 single-cell assay. TCR/BCR libraries were prepared using the Chromium™ single cell V(D)J enrichment kit (10× Genomics). Reverse transcription, cDNA amplification and library preparation were executed following the manufacturer’s protocol.
Approximately 10,000 cells were allocated for the 10 × Genomics 5′ v2 single-cell assay. TCR/BCR libraries were prepared using the Chromium™ single cell V(D)J enrichment kit (10× Genomics). Reverse transcription, cDNA amplification and library preparation were executed following the manufacturer’s protocol.

treatment_protocol: A syngeneic mouse colon cancer model was established by inoculating MC38-p53KO/E285K cells (3 × 105 cells/mouse) subcutaneously. On day 10 post-tumor inoculation, when the tumors were palpable (~50-100mm3), a single-dose treatment of LNP-Ctrl plasmid (40 μg/mouse) was administered intratumorally.

tag: age

value: 6–8 weeks old

value: Tumor

value: control group (LNP-Ctrl)

value: A syngeneic mouse colon cancer model was established by inoculating MC38-p53KO/E285K cells (3 × 10^5 cells/mouse) subcutaneously. On day 10 post-tumor inoculation, when the tumors were palpable (~50-100mm3), a single-dose treatment of LNP-Ctrl plasmid (40 μg/mouse) was administered intratumorally.

value: CD45+ cells


title: LNP-pE285K-mAb, scRNA-seq-TCR

description: 10× Genomics

value: experimental group (LNP-pE285K-mAb)


title: LNP-pE285K-mAb, scRNA-seq

description: 10× Genomics

data_processing:
Raw sequence reads in the FASTQ format were aligned to the mouse reference genome using Cell Ranger Count v7.1.0 pipeline (10x genomics Cloud) with the default settings for alignment, barcode assignment, and unique molecular identifiers (UMI) counting against the Mouse (mm10) 2020-A genome reference.
Raw sequence reads in the FASTQ formats were aligned to the mouse reference genome using CellRanger Count v7.1.0 pipeline (https://cloud.10xgenomics.com) with the default settings for alignment, barcode assignment, and UMI counting of the raw sequencing data with genome reference Mouse (mm10) 2020-A. BCR and TCR Raw gene expression matrices were generated by CellRanger count pipeline with default parameters and mouse GRCm38/mm10 as the reference genome.  The doublet cells were eliminated using the R package scDblFinder (1.14.0)[PMID: 35814628], and additional processing was performed using the R package Seurat (v4.4.0). Filtered cells were those with >10% mitochondrial, nFeature RNA >7500, or <200 identified genes.  The highly variable genes were determined using the "vst" selection method in Seurat and the FindVariableFeatures tool after log-normalization. The ScaleData function in Seurat was used to scale the data. The RunHarmony function from the R package harmony (1.01)[PMID: 31740819] was used to combine multiple data after PCA analysis. Using Seurat's FindNeighbors FindClusters function and a resolution of 0.5, neighbors and clusters were defined. RunUMAP was used to calculate the UMAP dimensionality reduction with default parameters utilizing the top 30 principal components (PCs) and harmony reduction. For the analysis focusing on T cells, B cells, NK cells and NK like cells which subset from the annotation cell types, data were re-run from NormalizeData function following Seurat pipeline. To assist with the annotation of the T cell subcluster, we utilize the R packages STACAS (2.1.3)[PMID: 32845323] and ProjecTILs (3.2.0)[PMID: 34017005].
DEGs between clusters were obtained with a Wilcoxon followed by Bonferroni correction using the FindAllMarkers function in Seurat. For GO and KEGG enrichment analysis, Clusterprofiler (4.8.3)[PMID: 34557778] was used to examine DEG of cell clusters. The AddModuleScore function was recruited to evaluate the gene set score of T cells’ Transcription factors, Memory markers, Cytotoxic markers as well as Checkpoint markers. For plotting specific genes or gene set score of interest, FeaturePlot function in Seurat and plot_density function in Nebulosa (1.10.0)[PMID: 33459785] was used to show the genes or gene set score distribution on cells. UMAP and heatmap plot modification was done using scRNAtoolVis (0.0.7).
scVDJ and scRNA seq analysis was performed by combining Seurat and scRepertoire (1.11.0) [ PMID: 32789006] packages. In brief, scVDJ analysis is carried out when the T cells and B cells subcluster are combine with TCR and BCR data, respectively, using the combine TCR or combine BCR function in scRepertoire, the downstream process adheres scRepertoire protocol. For the motif sequence of TRAV and TRAB, we hired the python module CoNGA to calculate and show the TCR motif of subcluster of T cells.
Pesudotime analysis was performed via two different methods. We use R package FitDevo (1.2.1) [PMID: 35870444] to analyze the developmental trajectories of T cells, B cells, NK cells, and NKL, and also infer the CD8+ and CD4+ T cell starting cell populations through global cell differentiation. R package Slingshot (2.8.0)[PMID: 29914354] is used to infer the differentiation paths of CD8+T cells and CD4+T cells. By combining the UMAP dimensionality reduction results in Seurat and the starting trajectory of FitDevo analysis, we use the slingPseudotime function to predict the cell differentiation path. Then the potential developmental pathways in each cell group were obtained.
The CellChatR toolkit (2.2) [PMID: 33597522] was used to explore cellular interactions different between control and treatment groups. Communication probabilities were calculated based on the CellChatDB database of literature and PPI supported ligand–receptor interactions in mouse datasets. We first filter the incoming and outgoing parameters for each sample group using the selectK function, and then we aggregate the data from the two cell groups using the mergeCellChat function. The official Cellchat protocol "Comparison analysis of multiple datasets using CellChat" is used to analyze the merged data items.
Assembly: mm10
Supplementary files format and content: h5 or gz


title: LNP-pE285K-mAb, scRNA-seq-BCR

description: 10× Genomics

data_processing:
BCR Raw gene expression matrices were derived using the Count v7.1.0 pipeline (10x genomics Cloud) with mouse GRCm38/mm10 as the reference.
Raw sequence reads in the FASTQ formats were aligned to the mouse reference genome using CellRanger Count v7.1.0 pipeline (https://cloud.10xgenomics.com) with the default settings for alignment, barcode assignment, and UMI counting of the raw sequencing data with genome reference Mouse (mm10) 2020-A. BCR and TCR Raw gene expression matrices were generated by CellRanger count pipeline with default parameters and mouse GRCm38/mm10 as the reference genome.  The doublet cells were eliminated using the R package scDblFinder (1.14.0)[PMID: 35814628], and additional processing was performed using the R package Seurat (v4.4.0). Filtered cells were those with >10% mitochondrial, nFeature RNA >7500, or <200 identified genes.  The highly variable genes were determined using the "vst" selection method in Seurat and the FindVariableFeatures tool after log-normalization. The ScaleData function in Seurat was used to scale the data. The RunHarmony function from the R package harmony (1.01)[PMID: 31740819] was used to combine multiple data after PCA analysis. Using Seurat's FindNeighbors FindClusters function and a resolution of 0.5, neighbors and clusters were defined. RunUMAP was used to calculate the UMAP dimensionality reduction with default parameters utilizing the top 30 principal components (PCs) and harmony reduction. For the analysis focusing on T cells, B cells, NK cells and NK like cells which subset from the annotation cell types, data were re-run from NormalizeData function following Seurat pipeline. To assist with the annotation of the T cell subcluster, we utilize the R packages STACAS (2.1.3)[PMID: 32845323] and ProjecTILs (3.2.0)[PMID: 34017005].
DEGs between clusters were obtained with a Wilcoxon followed by Bonferroni correction using the FindAllMarkers function in Seurat. For GO and KEGG enrichment analysis, Clusterprofiler (4.8.3)[PMID: 34557778] was used to examine DEG of cell clusters. The AddModuleScore function was recruited to evaluate the gene set score of T cells’ Transcription factors, Memory markers, Cytotoxic markers as well as Checkpoint markers. For plotting specific genes or gene set score of interest, FeaturePlot function in Seurat and plot_density function in Nebulosa (1.10.0)[PMID: 33459785] was used to show the genes or gene set score distribution on cells. UMAP and heatmap plot modification was done using scRNAtoolVis (0.0.7).
scVDJ and scRNA seq analysis was performed by combining Seurat and scRepertoire (1.11.0) [ PMID: 32789006] packages. In brief, scVDJ analysis is carried out when the T cells and B cells subcluster are combine with TCR and BCR data, respectively, using the combine TCR or combine BCR function in scRepertoire, the downstream process adheres scRepertoire protocol. For the motif sequence of TRAV and TRAB, we hired the python module CoNGA to calculate and show the TCR motif of subcluster of T cells.
Pesudotime analysis was performed via two different methods. We use R package FitDevo (1.2.1) [PMID: 35870444] to analyze the developmental trajectories of T cells, B cells, NK cells, and NKL, and also infer the CD8+ and CD4+ T cell starting cell populations through global cell differentiation. R package Slingshot (2.8.0)[PMID: 29914354] is used to infer the differentiation paths of CD8+T cells and CD4+T cells. By combining the UMAP dimensionality reduction results in Seurat and the starting trajectory of FitDevo analysis, we use the slingPseudotime function to predict the cell differentiation path. Then the potential developmental pathways in each cell group were obtained.
The CellChatR toolkit (2.2) [PMID: 33597522] was used to explore cellular interactions different between control and treatment groups. Communication probabilities were calculated based on the CellChatDB database of literature and PPI supported ligand–receptor interactions in mouse datasets. We first filter the incoming and outgoing parameters for each sample group using the selectK function, and then we aggregate the data from the two cell groups using the mergeCellChat function. The official Cellchat protocol "Comparison analysis of multiple datasets using CellChat" is used to analyze the merged data items.
Assembly: mm10
Supplementary files format and content: h5 or gz


title: LNP-Ctrl, scRNA-seq-BCR

description: 10× Genomics


title: LNP-Ctrl, scRNA-seq

description: 10× Genomics


title: REG_203

city: Portland

first: Zheng

last: Xia

state: Oregon

address: 2720 S. Moody Avenue

institute: OREGON HEALTH & SCIENCE UNIVERSITY

data_processing:
Sequence reads were mapped to mm10 using STAR_2.6.1a.
Read counts extraction and normalization were performed using RSEM_v1.3.1.
Assembly: GRCm38.89
Supplementary files format and content: .genes.results.txt (raw counts and TPM)

source_name: Liver

extract_protocol:
Trizol
NEBNext Ultra RNA Library Prep

value: Liver

value: Balb/C

value: 4-weeks post-wean (regressed).


title: REG_239


title: NUL_226

value: non-pregnant (nulliparous)


title: NUL_221


title: REG_214


title: NUL_227


title: NUL_220


title: REG_234


title: LAC_240

value: lactation day 10


title: LAC_213


title: ID8_98b

description: Involution Day8_98b

value: Involution Day8


title: LAC_200


title: ID6_218

description: Involution Day6_218

value: Involution Day6


title: ID8_14

description: Involution Day8_14


title: ID8_101b

description: Involution Day8_101b


title: ID6_232

description: Involution Day6_232


title: ID6_209

description: Involution Day6_209


title: ID6_216

description: Involution Day6_216


title: ID4_15

description: Involution Day4_15

value: Involution Day4


title: ID4_211

description: Involution Day4_211


title: ID4_13

description: Involution Day4_13


title: ID6_201

description: Involution Day6_201


title: ID2_39

description: Involution Day2_39

value: Involution Day2


title: ID4_215

description: Involution Day4_215


title: ID2_31

description: Involution Day2_31


title: ID2_224

description: Involution Day2_224


title: Brain, wildtype male 1

city: Indianapolis

first: Luke

middle: Child

last: Dabin

state: Indiana

department: Medical and Molecular Genetics

institute: Indiana University

data_processing:
Processing of the sequencing data was performed with the cellranger pipeline (v4.0.0, 10X Genomics)
Assembly: mm10
Supplementary files format and content: cellranger output, including raw and processed tab-separated values files and matrix files

source_name: Right brain hemisphere, minus cerebellum and olfactory bulb

extract_protocol:
Each mouse was anesthetised, transcardially perfused with sterile cold PBS, and then the brain was collected. After removing the cerebellum and olfactory bulb, the right hemisphere was immediately finely minced on ice and transferred to a polypropylene tube containing 10 ml ice-cold Accutase (Gibco, A11105-01). Tissue was incubated with rocking at 4oC for 30 minutes and then pelleted through centrifugation at 300 g for 5 minutes at 4oC. Supernatant was aspirated and samples were resuspended in 5 ml ice-cold wash buffer [1X HBSS (Gibco, 14175095), 0.04% BSA (Miltenyi, 130-091-376)] and gently dissociated through trituration using a 5 ml serological pipette. 70 µm and 40 µm cell-strainers (Corning, 352350 & 352340) were moistened with 5 ml ice-cold wash buffer and samples were sequentially strained through into fresh polypropylene tubes, each filter was rinsed with an additional 5 ml of ice-cold wash buffer. Cell suspensions were pelleted through centrifugation at 300 g for 10 min at 4oC. The supernatant was aspirated, and cells were resuspended in 1080 µl of degassed MACS Myelin Removal Buffer (1X DPS (Gibco 14190250), 0.5% BSA (Miltenyi, 130-091-376)) and transferred to 2 ml DNA LoBind tubes (Eppendorf, 022431048). 120 µl of myelin removal beads (Miltenyi, 130-096-733) were added to each sample and mixed thoroughly by pipetting. Samples and beads were incubated for 15 min at 4oC with rotating. Samples were transferred to 15 ml polypropylene tubes and washed with 10 ml myelin removal buffer, then pelleted through centrifugation at 300 g for 10 min at 4oC. Supernatant was aspirated and samples were resuspended in 2ml myelin removal buffer. LS columns (Miltenyi, 130-042-401) were loaded into a QuadroMACS separator on a MACS MultiStand with Tube Rack (Miltenyi, 130-090-976 & 130-042-303 & 130-091-052). Columns were equilibrated with three successive 1 ml volumes of myelin removal buffer which were collected in 15 ml polypropylene tubes. Cell suspensions were loaded onto columns and myelin-depleted cell suspensions were washed through using four successive 1 ml volumes of myelin removal buffer. Effluent was made up to 10 ml total volume and cells were pelleted through centrifugation at 300 g for 5 min at 4oC. Supernatant was aspirated to a residual volume of 200 µl and cells were gently resuspended using a pipette. Cells were then pelleted through centrifugation at 300 g for 5 min at 4oC before resuspension in 200 µl resuspension buffer (1X DPS (Gibco 14190250); 0.04% BSA (Miltenyi, 130-091-376)), another centrifugation step using the same settings and finally resuspension in 50 µl resuspension buffer. An aliquot of cells was stained with trypan blue, and the cell concentration and viability were determined by manual counting using a disposable hemocytometer slide (C-Chip, SKC, Inc., Covington, GA) and the 40X objective of an EVOS XL Core microscope
Single cell suspensions were mixed with single cell master mix containing lysis buffer and reverse transcription reagents, following the Chromium Next GEM Single Cell 3’ Reagent Kits User v3.1 (Dual Index) Guide, CG000315 Rev A (10X Genomics, Pleasanton, CA). Each single cell mix was then loaded into a single well of a Single Cell Chip G and run on the Chromium Controller for GEM generation and barcoding. Sample processing and library preparation were performed according to the manufacturer’s instructions using the Chromium Next GEM Single Cell 3’ v3.1 dual index kit (10X Genomics, Inc.) and SPRIselect paramagnetic bead-based chemistry (Beckman Coulter Life Sciences, Indianapolis, IN). The cDNA and library quality were assessed using the Agilent 2100 Bioanalyzer and a High Sensitivity DNA kit (Agilent Technologies, Santa Clara, CA) and the final library concentration was determined using a Qubit Fluorometer and the dsDNA HS assay kit (Thermo Fisher Scientific, Waltham, MA). Sequencing was carried out on a NovaSeq 6000 v1.5 S2 100 cycle chip (Illumina) with 28-10-10-91 read setup.

value: Inpp5d +/+

value: male


title: Brain, wildtype male 2

value: Right brain hemisphere, minus cerebellum and olfactory bulb


title: Brain, wildtype female 2

value: female


title: Brain, homozygous knockout female 1

value: Inpp5d -/-


title: Brain, heterozygous knockout female 2


title: Brain, heterozygous knockout female 1


title: Brain, wildtype female 1


title: Brain, homozygous knockout male 1


title: Brain, homozygous knockout male 2


title: Brain, homozygous knockout female 2


title: OTX2-dTAG_DE1_HA_Rep2

first: Ly-sha

last: Ee

address: 413 E 69th Street

institute: Weill Cornell Medicine

description:
OTX2_DE_HApeaks.txt
CnR_DE_MERGE.bw
DE_CnR_Peaks_merge50bp.bed

library_source: genomic

data_processing:
Reads were trimmed using bbmap (v38.95) with parameters ktrim=r ref=adapters rcomp=t tpe=t tbo=t hdist=1 mink=11.
Trimmed reads were aligned to the mm10 reference genome using Bowtie2 (v2.3.5.1) with parameters --local --very-sensitive-local --no-mixed --no-discordant --phred33 -I 5 -X 999 (Langmead and Salzberg, 2012)
Reads with a MAPQ score less than 5 were removed with samtools (v1.14) (Li, et al., 2009).
PCR duplicates were removed with Picard (v2.26.10) using parameter VALIDATION_STRINGENCY=LENIENT. Fragments between 20 and 120bp were isolated using a custom awk script
Bigwigs were generated from bam files using bedtools (v2.30) normalizing to sequencing depth using the formula: (effective_genome_size / read_count * read_length) with 1870000000 as the effective genome size (Quinlan and Hall, 2010)
Bam files were converted to bed files with bedtools (v2.30) with parameter -bedpe. MACS (v2.2.6) was used to call peaks on individual and merged replicates using parameters -g 1870000000 --nomodel --seed 123 –keep-dup all (Zhang, et al., 2008)
Assembly: mm10
Supplementary files format and content: BigWig, narrowPeak
Supplementary files format and content: txt
Library strategy: CUT&RUN

molecule: genomic DNA

source_name: 7H OTX2-dTAG-EGFP

growth_protocol: All cells cultured at 37C, 5% CO2. EpiSCs are grown in N2B27, 20ng/ml Activin A, 12.5ng/ml FGF2, 175nM NVP. DE are differentiated in CDM, 40ng/ml Activin A, 3uM CHIR for 16hrs followed by 100ng/ml Activin A, 100nM LDN for 24hrs

extract_protocol:
CUT&RUN on OTX2-HA was performed on 500,000 EpiSCs or DE cells per sample using BioMag Plus Concanavalin A beads (ConA beads, PolySciences NC1358578), 1:100 anti-HA (CST C29F4 #3724) or anti-IgG (EpiCypher 130042), and ProteinA/G MNase (EpiCypher). Fragmented DNA was isolated by phenolchloroform extraction and EtOH precipitation
CUT&RUN libraries were constructed using the Takara Thruplex Library Prep and Unique Dual Index kits. Cycles for PCR amplification were determined individually for each sample by qPCR. Libraries were size selected using SPRI beads (Beckman Coulter)

treatment_protocol: Live DE cells were sorted for CUT&RUN with DAPI on BD-Influx

value: 7H OTX2-dTAG-EGFP

value: Definitive Endoderm

value: BL6/129 hybrid

tag: chip antibody

value: HA


title: ID6_230

description: Involution Day6_230

value: Liver

value: Balb/C


title: Brain, heterozygous knockout male 2


title: OTX2-dTAG_DE1_IgG

description:
DE_CnR_Peaks_merge50bp.bed
CnR_DE_MERGE.bw

value: IgG


title: Parental_DE1_IgG

description: wt_de1_noTrt_aIgG_rep1_mm10_trim_q5_dupsRem_20to120_rpgcNorm.bw


title: Parental_DE1_HA

description:
wt_de1_noTrt_aHA_rep1_mm10_trim_q5_dupsRem_20to120_rpgcNorm.bw
wt_de1_noTrt_aHA_rep1_mm10_trim_q5_dupsRem_20to120_peaks.narrowPeak


title: OTX2-dTAG_EpiSC_HA_Rep2

description:
OTX2_Epi_HApeaks.txt
CnR_EpiSCs_MERGE.bw
DE_CnR_Peaks_merge50bp.bed

value: Epiblast stem cells


title: OTX2-dTAG_EpiSC_HA_Rep1

description:
OTX2_Epi_HApeaks.txt
CnR_EpiSCs_MERGE.bw
EpiSCs_CnR_Peaks_merge50bp.bed


title: OTX2-dTAG_EpiSC_IgG_Rep2


title: OTX2-dTAG_EpiSC_IgG_Rep1


title: OTX2-dTAG_DE_ATAC_dTAG_Rep3

description:
ATAC_DE_allpeaks.txt
dTAG_ALL.bw
dTAG_ALL.mm10.macs2_peaks.bed
ATAC_DE_DMSOenrich_peaks.txt
ATAC_DE_dTAGenrich_peaks.txt

data_processing:
Raw ATAC-seq reads were trimmed using fastp to remove low-quality bases from reads (quality<20) and adapter sequences. The trimmed reads were aligned using Bowtie2 (Langmead and Salzberg, 2012) to UCSC genome assembly mm10. Duplicate reads were removed using Sambamba.
Peaks were identified with MACS2 (Gaspar, 2018) and those overlapping with satellite repeat regions were discarded.
Peak intensity for each sample was counted using featureCounts (Liao, et al., 2014). HOMER (v4.11) (Heinz, et al., 2010) was used for motif analyses. To associate peaks with nearby genes and genomic location, ChipSeeker (Yu, et al., 2015) was used
For further analyses, a union peak atlas was created from the MACS2 files
Assembly: mm10
Supplementary files format and content: BigWig, bed
Supplementary files format and content: txt

growth_protocol: All cells cultured at 37C, 5% CO2. DE are differentiated in CDM, 40ng/ml Activin A, 3uM CHIR for 16hrs followed by 100ng/ml Activin A, 100nM LDN for 24hrs

extract_protocol:
ATACseq was performed on 50,000 DE cells per sample using the Nextera DNA library preparation kit (Illumina FC121103) according to the manufacturer's instructions
Libraries were constructed using the Nextera DNA library preparation kit (Illumina FC121103) and NEBNext High-Fidelity 2X PCR Master Mix (NEB M0541) according to the manufacturer's instructions. Cycles for PCR amplification were determined individually for each sample by qPCR Libraries were size selected (0.55–1.5x) using SPRI beads (Beckman Coulter)

treatment_protocol: dTAG13 or DMSO vehicle added at primitive streak (PS) stage for 24hrs to deplete OTX2. Live DE cells were sorted for ATACseq with DAPI on BD-Influx


title: OTX2-dTAG_DE_ATAC_DMSO_Rep1

description:
ATAC_DE_allpeaks.txt
DMSO_ALL.bw
DMSO_ALL.mm10.macs2_peaks.bed
ATAC_DE_DMSOenrich_peaks.txt
ATAC_DE_dTAGenrich_peaks.txt

value: DMSO


title: OTX2-dTAG_DE_ATAC_DMSO_Rep3


title: OTX2-dTAG_DE_ATAC_dTAG_Rep2


title: OTX2-dTAG_DE_ATAC_dTAG_Rep1


title: Epi_DE_dTAG_at_PS pool

data_processing:
Fastq files were processed using CellRanger (10x genomics cloud).
Raw h5 files were processed using CellBender to eliminate background reads, empty beads, and other artifacts (Fleming, et al., 2022). Scanpy (Wolf, et al., 2018) was used for downstream analyses. Cell clusters with high percentage of mitochondrial reads or a relatively low number of reads were eliminated.
Palantir (Setty, et al., 2019) was used for pseudo-time analyses
For differential expression analyses, Wilcoxon testing was performed and only genes with padj<0.05 and log2 fold-change>1 were considered as differentially expressed genes (DEGs). The scores/ranking per gene given by the scanpy.get.rank_genes_groups_df function were used.
Assembly: mm10
Supplementary files format and content: h5ad, txt

growth_protocol: All cells cultured at 37C, 5% CO2. EpiSCs are grown in N2B27, 20ng/ml Activin A, 12.5ng/ml FGF2, 175nM NVP. DE are differentiated in CDM, 40ng/ml Activin A, 3uM CHIR for 16hrs followed by 100ng/ml Activin A, 100nM LDN for 48hrs

extract_protocol:
Cells at indicated stages were dissociated using Accutase to single-cell suspension inPBS-/- with 0.04% BSA. Samples were labeled with Cell Multiplexing Oligos (10x GenomicsChromium Next GEM Single Cell 3ʹ Reagent Kit v3.1 Dual Index) and live cells sorted using DAPI on a BD Influx Cell Sorter.
Two pools were created for multiplexing inPBS-/- with 0.04% BSA (targeting 10,000 cells/sample)- EpiSCs, DE with DMSO or dTAG13 added at PS stage; and DE with DMSO or dTAG13 added at 24hrs DE differentiation. Single-cell libraries were generated according to the manufacturer's instructions (10x GenomicsChromium Single Cell Gene Expression - Cell Multiplexing).
scRNA-seq (10x Genomics, multiplexed pooling)

treatment_protocol: dTAG13 or DMSO vehicle added at primitive streak (PS) or 24hrs DE stage to deplete OTX2

value: Epiblast stem cells, Definitive Endoderm

value: DMSO_dTAG at primitive streak


title: OTX2-dTAG_DE_ATAC_DMSO_Rep2


title: BMDMs, Treat rep3, 6h

first: Zhuoxuan

last: Jia

state: Shanghai

institute: Shanghai 9th People’s  Hospital, Shanghai Jiao Tong University School of Medicine

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 STAR (--twopassMode Basic|--outSAMstrandField intronMotif|--alignSJstitchMismatchNmax 5 -1 5 5) 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 ≥ 1.2 were considered differentially expressed genes. Differentially expressed genes were then subjected to enrichment analysis of GO functions and KEGG pathways.
Assembly: mm10
Supplementary files format and content: tab-delimited text files include FPKM values for each Sample

source_name: Bone marrow

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: Bone marrow

value: BMDMs

value: WT

value: LPS+IFN-γ+Annexin A5


title: BMDMs, Treat rep2, 6h


title: Brain, heterozygous knockout male 1

value: Right brain hemisphere, minus cerebellum and olfactory bulb

value: male


title: BMDMs, Treat rep1, 6h


title: OTX2-dTAG_DE1_HA_Rep1

value: 7H OTX2-dTAG-EGFP


title: BMDMs, Control rep3, 6h

value: Normal


title: BMDMs, Model rep3, 6h

value: LPS+IFN-γ


title: BMDMs, Control rep2, 6h


title: BMDMs, Model rep1, 6h


title: BMDMs, Control rep1, 6h


title: lung epithelia, IL13,MAV, donor2

city: Iowa city

first: Alejandro

middle: Pezzulo

last: Colmenares

state: Iowa

address: 169 Newton Road

department: Internal medicine

institute: University of Iowa

data_processing:
Base cells were demultiplexed and converted to FASTQ format by the University of Iowa Genomics core.
The processed fastq files were pseudo aligned to mouse reference
Mapped raw reads were reported in transcripts per million (TPM) by Kallisto. For downstream analysis, output from Kallisto was summarized into gene-level estimates using tximport v1.10.1 in R v3.5.1.
Differential gene expression was performed using iDEP v0.92
Assembly: mm10, accession: GCF_000001635.27 and SARS-CoV-2 reference (accession: GCA_009937905.1)

source_name: airway epithelial cells

extract_protocol:
Total RNA was extracted and purified from harvested mice lungs using RNeasy plus mini kit from QIAGEN.
cDNA library was prepared using Illumina TruSeq strannded mRNA protocol
The pooled library was sequenced on 1 lane of Illumina NovaSeq 6000 SP Flowcell instrument.

treatment_protocol: 6-10-week BALB/c mice (n=4) were intranasally infected by 1,000PFU of SARS2-N501YMA30 after a 4-day pretreatment of 2.5 μg/day intranasal IL-13 or vehicle

value: airway epithelial cells

tag: donor


title: lung epithelia, IL13,MAV, donor4


title: lung epithelia, IL13,MAV, donor3


title: OTX2-dTAG_EpiSC_IgG_Rep3

value: BL6/129 hybrid


title: lung epithelia, vehicle,MAV, donor2

value: Vehicle, 1000 MAV


title: lung epithelia, vehicle,MAV, donor3


title: lung epithelia, vehicle,MAV, donor1


title: lung epithelia, IL13, noMAV, donor2

value: IL13, noMAV


title: lung epithelia, vehicle,MAV, donor4


title: lung epithelia, IL13, noMAV, donor4


title: lung epithelia, IL13, noMAV, donor3


title: lung epithelia, vehicle, noMAV, donor4

value: vehicle,noMAV


title: lung epithelia, IL13, noMAV, donor1


title: lung epithelia, vehicle, noMAV, donor3


title: lung epithelia, vehicle, noMAV, donor1


title: lung epithelia, vehicle, noMAV, donor2


title: Deferiprone_12h_4

city: New York City

first: Tito Alejandro

middle: A

last: Sandoval Medina

email: tas2037@med.cornell.edu, tito@wustl.edu

state: New York

address: 1300 York Avenue E907

department: OBGyN

institute: Weill Cornell Medine

data_processing: none provided

source_name: cell culture

extract_protocol: none provided

value: cell culture

value: Ovarian Cancer

value: Deferiprone 12h


title: Deferiprone_12h_3


title: BMDMs, Model rep2, 6h

value: Bone marrow


title: Deferiprone_12h_2


title: Deferiprone_12h_1


title: Vehicle_2

value: Vehicle


title: lung epithelia, IL13,MAV, donor1

value: WT


title: Vehicle_1


title: 2283545_NEJF10-3D-Hyp-01

city: Memphis

first: Hongjian

last: Jin

state: TN

address: 262 Danny Thomas Place

department: Center for Applied Bioinformatics

institute: St Jude Children's Research Hospital

data_processing:
Total stranded RNA sequencing data were processed by  the internal AutoMapper pipeline.First the raw reads were firs trimmed (Trim-Galore version 0.60) and mapped to mouse reference gennome(STAR v2.7).
The gene level expression values were quantified (RSEM v1.31) based on GENCODE annotation (M22).
Assembly: GRCm38(mm10)
Supplementary files format and content: gene-level RSEM raw count, TPM, FPKM txt files

growth_protocol: NEJF10 cells were cultured in DMEM supplemented with 10% Fetal Bovine Serum, 1% L-Glutamine, and 1% Penicillin/Streptomycin at 37 °C in an atmosphere of 5% CO2 with 21% oxygen or 1% oxygen.

extract_protocol:
Total RNA extraction from cells and tumor tissues was performed using the RNeasy Mini Kit (74106, Qiagen) according to the manufacturer’s instructions.
RNA libraries were prepared for sequencing using standard Illumina protocols at the St. Jude Hartwell Center.

treatment_protocol: NEJF10 cells were cultured in 21% and 1% oxygen in monolayer, or 21% oxygen in 3D spheroid.

value: HB

value: 3D Culture with 1% O2


title: 2283544_NEJF10-3D-Nor-02

value: 3D Culture with 21% O2


title: NEJF10-2D-Hyp-02

value: Culture with 1% O2


title: NEJF10-2D-Nor-02

value: Culture with 21% O2


title: NEJF10-2D-Hyp-01


title: SRSF1_KO

first: Yuan

middle: Ning

last: Yang

address: 320 Yueyang Road

institute: Shanghai Institute of Nutrition and Health,CAS

description: 10x Genomics

data_processing:
The 10×Genomics Cell Ranger software suite (version 5.0.0) was employed for demultiplexing cellular barcodes, mapping reads to the genome and transcriptome, and down-sampling reads to create normalized aggregate data across samples. Subsequently, a matrix of gene counts versus cells was generated. The unique molecular identifier (UMI) count matrix was further analyzed using the R package Seurat (version 3.1.1).
To eliminate low-quality cells or potential multiplet captures, we applied a set of criteria as follows: Cells were excluded if their UMI/gene counts fell beyond the mean value +/- 2 fold of standard deviations, assuming a Gaussian distribution for each cell's UMI/gene counts. Additionally, cells were further removed if more than 10% of their gene counts belonged to mitochondrial genes.
The DoubletFinder package  (version 2.0.2) was utilized to identify potential doublets.
The NormalizeData function in Seurat was employed for library size normalization, resulting in the acquisition of normalized counts.
The gene expression measurements for each cell were normalized by the total expression using the "LogNormalize" method, a global-scaling normalization approach. The normalized values were then multiplied by a default scaling factor (10,000) and log-transformed to obtain the final results.
Assembly: mm10
Supplementary files format and content: Matrix table with raw gene counts for every gene and every cell

source_name: brown adipose tissue

extract_protocol:
The preparation of nucleus suspensions for experiments was conducted under constant ice-cold conditions. Interscapular brown adipose tissue was harvested from 8-week-old control and adipose tissue-specific Srsf1-knockout mice for experiment. Fresh tissue samples were cut and lysed in 1 ml of nucleus lysis solution (NST) (Supplementary Table 2) on ice for 7 minutes. Once complete nucleus lysis was confirmed, 1 mL of ST Wash buffer (Supplementary Table 2) was added to resuspend the nuclei. Subsequently, the resuspension was filtered through a 40µm cell sieve (BD), and the resulting filtrate was transferred to a 15mL centrifuge tube. The cell sieve was washed with an appropriate amount of ST Wash buffer, and the wash buffer was combined with the nuclei filtrate. To ensure proper resuspension, the nuclei were resuspended. Nuclei were resuspended in PBS+1% BSA at a concentration of 700-1200/µl. Finally, the nuclei were stained with Tissue Blue and counted through microscopic examination.Then nuclei  were used for single-nucleus  sequencing.
cDNA library amplification and DNA library construction were performed using the 10× Genomics Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1  and the Chromium™ Single Cell 3’/5’ Library Construction Kit , respectively, following the manufacturer’s instructions.

value: brown adipose tissue

value: mixed cell types

value: single nucleus

value: 8-week-old; gene knock out


title: 2283543_NEJF10-3D-Nor-01


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-38

city: Seattle

first: John

middle: Kenneth

last: Mich

state: WA

address: 615 Westlake Ave N

institute: Allen Institute for Brain Science

data_processing:
Base-calling using standard Illumina software.
Alignment with STAR (https://github.com/alexdobin/STAR)
Transformed by counts per million.
Assembly: mm10
Supplementary files format and content: Processed data in counts per million (CPM) format.

source_name: MB/HB

extract_protocol:
Single SYFP2-expressing cells from mouse brain were flow sorted into individual tubes in SMARTerv4 collection buffer.
SMARTerv4

value: MB/HB


title: DE_dTAG_at_DE pool

value: 7H OTX2-dTAG-EGFP

value: Definitive Endoderm

value: BL6/129 hybrid

value: DMSO_dTAG at 24hrs DE


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-43


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-39


title: WT

description: 10x Genomics

value: wild type


title: NEJF10-2D-Nor-01


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-37


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-36


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-41


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-42


title: Vehicle_4

value: cell culture

value: Ovarian Cancer

value: Vehicle


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-38


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-39


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-35


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-40


title: 2283546_NEJF10-3D-Hyp-02

value: HB

value: 3D Culture with 1% O2


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-37


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-35


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-34


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-33


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-31


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-30


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-29


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-28


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-27


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-33


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-34


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-30


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-31


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-29


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-28


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-27


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-36


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-26


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-26


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-25


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-25


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-19


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-24


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-22


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-20


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-18


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-32


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-17


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-14


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-12


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-16


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-15


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-11


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-32


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-13


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-10


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-24


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-23


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-8


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-22


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-23


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-21


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-19


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-7


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-21


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-18


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-13


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-14


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-17


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-10


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-15


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-20


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-16


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-11


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-12


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-8


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-7


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-6


title: BrainCell_Enhancer-GFAP_promoter_MouseID-651226_Cell-45

source_name: VISp

value: VISp


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-44


title: BrainCell_Enhancer-MGT_E160m_MouseID-651228_Cell-9


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-43


title: BrainCell_Enhancer-eHGT_390h_MouseID-651220_Cell-45


title: BrainCell_Enhancer-eHGT_390h_MouseID-651220_Cell-44


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-40


title: BrainCell_Enhancer-eHGT_409h_MouseID-641433_Cell-44


title: BrainCell_Enhancer-eHGT_385m_MouseID-615515_Cell-34


title: BrainCell_Enhancer-eHGT_381h_MouseID-615516_Cell-48


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-46


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-47


title: BrainCell_Enhancer-eHGT_375m_MouseID-651221_Cell-38

source_name: CBX

value: CBX


title: BrainCell_Enhancer-eHGT_376h_MouseID-614199_Cell-40


title: BrainCell_Enhancer-eHGT_380h_MouseID-651225_Cell-46


title: BrainCell_Enhancer-eHGT_390h_MouseID-651220_Cell-43


title: BrainCell_Enhancer-3xCore2(390m)_MouseID-630480_Cell-47


title: BrainCell_Enhancer-eHGT_380h_MouseID-651225_Cell-47


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-9


title: BrainCell_Enhancer-eHGT_385m_MouseID-651224_Cell-46


title: BrainCell_Enhancer-MGT_E160m_MouseID-651229_Cell-5


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-36


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-37


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-42


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-34


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-35


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-33


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-32


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-38


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-39


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-41


title: BrainCell_Enhancer-eHGT_381h_MouseID-651222_Cell-31


title: BrainCell_Enhancer-GFAP_promoter_MouseID-651226_Cell-44


title: BrainCell_Enhancer-eHGT_387m_MouseID-593373_Cell-48


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-47


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-45


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-43


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-46


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-44


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-42


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-39


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-41


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-37


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-36


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-35


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-38


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-40


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-34


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-32


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-33


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-28


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-27


title: Vehicle_3


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-26


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-30


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-31


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-48


title: BrainCell_Enhancer-GFAP_promoter_MouseID-630479_Cell-45


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-24


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-25


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-22


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-23


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-17


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-16


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-21


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-15


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-13


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-19


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-20


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-14


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-11


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-10


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-8


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-29


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-45


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-9


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-44


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-43


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-41


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-42


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-40


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-36


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-37


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-38


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-35


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-18


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-34


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-32


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-33


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-31


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-29


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-26


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-27


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-28


title: BrainCell_Enhancer-eHGT_641m_MouseID-601543_Cell-12


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-25


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-24


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-22


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-23


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-18


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-19


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-21


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-17


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-13


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-15


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-12


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-39


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-14


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-16


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-46


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-43


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-30


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-45


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-44


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-11


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-41


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-40


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-39


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-42


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-38


title: BrainCell_Enhancer-eHGT_405m_MouseID-601542_Cell-20


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-37


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-33


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-32


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-35


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-36


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-29


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-27


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-34


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-31


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-30


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-25


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-26


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-24


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-28


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-22


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-23


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-20


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-21


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-19


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-17


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-16


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-14


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-18


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-12


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-8


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-13


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-11


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-5


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-7


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-6


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-44


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-10


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-9


title: BrainCell_Enhancer-eHGT_400m_MouseID-601541_Cell-15


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-42


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-39


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-40


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-41


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-36


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-35


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-43


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-34


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-37


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-33


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-38


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-32


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-31


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-30


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-28


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-29


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-26


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-24


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-25


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-23


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-22


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-21


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-17


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-16


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-20


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-15


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-18


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-13


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-12


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-48


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-14


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-47


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-44


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-45


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-46


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-41


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-27


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-40


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-43


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-39


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-42


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-36


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-37


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-35


title: BrainCell_Enhancer-eHGT_396m_MouseID-601540_Cell-19


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-34


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-30


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-29


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-33


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-28


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-31


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-26


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-23


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-32


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-25


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-24


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-22


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-27


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-21


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-20


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-19


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-38


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-16


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-15


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-14


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-11


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-9


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-8


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-13


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-7


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-12


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-6


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-5


title: BrainCell_Enhancer-eHGT_395h_MouseID-562430_Cell-10


title: BrainCell_Enhancer-eHGT_410m_MouseID-556486_Cell-48


title: BrainCell_Enhancer-eHGT_410m_MouseID-556486_Cell-44


title: BrainCell_Enhancer-eHGT_410m_MouseID-556486_Cell-45


title: BrainCell_Enhancer-eHGT_410m_MouseID-556486_Cell-39


title: BrainCell_Enhancer-eHGT_410m_MouseID-556486_Cell-43