|
| Status |
Public on Nov 22, 2023 |
| Title |
pankla_nf_rep1 |
| Sample type |
SRA |
| |
|
| Source name |
Primary Neural Crest Cells
|
| Organism |
Gallus gallus |
| Characteristics |
cell type: Primary Neural Crest Cells
Stage: HH9 stage
genotype: wild-type
treatment: embryos developed in ovo until HH9
antibody: PTM Biolabs - PTM-1401 (polyclonal)
|
| Treatment protocol |
The collected embryos were wild-type.
|
| Growth protocol |
Fertilized White Leghorn eggs were purchased from the University of Connecticut (Department of Animal Sciences). The eggs were incubated at 37°C until the embryos reached HH9 (6-7 somites) stage of development.
|
| Extracted molecule |
genomic DNA |
| Extraction protocol |
Neural crest cells were obtained by micro-dissecting dorsal neural folds (NFs) from HH9 embryos (n=5 embryos, n=10 NFs) and pre-somitic mesoderm (PSM) tissue was obtained by dissecting the posterior region of HH9 embryos (n=5 embryos, n=10 PSM strips). A cell suspension was achieved by dissociating embryonic tissue with Accumax (Innovative Cell Technologies, AM105) for 30 min at room temperature under mild agitation and gentle pipetting halfway through the incubation time. The cells were then subjected to the low-salt CUT&RUN protocol (as described in dx.doi.org/10.17504/protocols.io.zcpf2vn and the Methods section of the present study).
DNA libraries for CUT&RUN experiments were performed using the NEBNext Ultra II DNA Library Prep Kit (NEB, E7645) following the manufacturer’s protocol. Quality control of prepared libraries was performed using an Agilent 4200 Tapestation with D5000 Reagents (Agilent Part# 5067-5589) and D500 ScreenTape (Agilent Part# 5067-5588). Libraires were pooled to equimolar concentrations using the NEB Library Quantification Kit (NEB E730S) and sequenced with paired-end 37-bp reads on an Illumina NextSeq 500 instrument.
|
| |
|
| Library strategy |
OTHER |
| Library source |
genomic |
| Library selection |
other |
| Instrument model |
Illumina NextSeq 500 |
| |
|
| Description |
CUT&RUN
|
| Data processing |
Processing the CUT&RUN data involved trimming Illumina adapter sequences from the paired-end reads using Cutadapt (v2.10) (https://doi.org/10.14806/ej.17.1.200) and selecting reads that were at least 25-bp long using the following arguments -a AGATCGGAAGAGCACACGTCTGAACTCCAGTCA -A AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT --minimum-length=25 -j 0.
The reads were then aligned to the reference chicken galGal6 assembly using Bowtie2 (v2.4.2) (https://doi.org/10.1038/nmeth.1923) with the following arguments “--local --very-sensitive-local --no-unal --no-mixed --no-discordant -I 10 -X 1000”. Duplicate reads were then marked by the Picard MarkDuplicates tool (https://github.com/broadinstitute/picard) and BAM files were filtered with SAMtools to discard unmapped reads, reads which were not the primary alignment, reads failing platform/vendor quality checks, and PCR/optical duplicates (-F 1804 -f 2).
MACS2 (https://doi.org/10.1186/gb-2008-9-9-r137) was used to call peaks with a q value cutoff equal to 0.05 with the following arguments “-f BAMPE -g 1218492533 -q 0.05 call-summits”. Consensus peaksets between biological replicates for each assayed histone mark or factor were determined by intersecting the peaksets of each replicate by using the BEDTools (https://doi.org/10.1093/bioinformatics/btq033) intersect function and only keeping peaks that were called in both replicates.
The subread package function featureCounts (https://doi.org/10.1093/bioinformatics/btt656) was used to generate peak count matrices for specific BAM files using the following arguments “--fracOverlap 0.5 --minOverlap 5 -p”. Before analyzing peak matrices, the R package edgeR was employed to first obtain TMM-normalized effective library sizes that were then used to normalize raw peak counts with the cpm() function. Peaks were annotated based on their closest gene using the R package ChIPSeeker (https://doi.org/10.1002/cpz1.585). Tornado and profile plots were generated using the python package DeepTools (https://doi.org/10.1093/nar/gku365). Motif enrichment was performed using HOMER. Reads per genomic content (RPGC) normalized BigWig files, for visualization of normalized read pile-up in a genome browser (IGV v2.13.0) (https://doi.org/10.1038/nbt.1754), were generated with the bamCoverage function of DeeTools using the following arguments “--outFileFormat bigwig --binSize 5 --numberOfProcessors 16 --normalizeUsing RPGC --effectiveGenomeSize 1218492533 --extendReads”.
Assembly: Ensembl galGal6
Supplementary files format and content: bw file
Library strategy: CUT&RUN
|
| |
|
| Submission date |
Mar 27, 2023 |
| Last update date |
Nov 22, 2023 |
| Contact name |
Marcos Simoes-Costa |
| Organization name |
Boston Children's Hospital
|
| Department |
Pathology
|
| Street address |
300 Longwood Ave
|
| City |
Boston |
| State/province |
Massachusetts |
| ZIP/Postal code |
02115 |
| Country |
USA |
| |
|
| Platform ID |
GPL19787 |
| Series (2) |
| GSE228335 |
Histone lactylation couples cellular metabolism with the activation of developmental gene regulatory networks [NCC CUT&RUN] |
| GSE228343 |
Histone lactylation couples cellular metabolism with the activation of developmental gene regulatory networks |
|
| Relations |
| BioSample |
SAMN33942391 |
| SRA |
SRX19788826 |
