Atelier génomique
Denis Puthier and Lydie Pradel
2015-11-23
Atelier génomique (AMU SBBCU22L - AG)
Funding and acknowledgments
We would like to thank all the people that were involved in the preparation of this practical session especially:
- Jean Imbert (TAGC/CoReBio PACA).
- Bertrand Jordan (CoReBio PACA).
- Christian Reil (CoReBio PACA).
- Anne Chorazewiez (ex CoReBio PACA).
- Aurélie Glowacz (AMU).
- and Myriam Ramadour (PGM).
We would like to gratefully acknowledge CoReBio Paca which provided us with the funding to set up this practical session.
Year
2015-2016
Attendees
6 students from the Master BBSG II (Bioinformatique, biochimie structurale et génomique).
Trainers
- Denis Puthier, TAGC
- Lydie Pradel, TAGC
- Beatrice Loriod, TAGC/TGML
- Nicolas Fernandez, TAGC/TGML
About
The aim of this practical session is to provide students with the basic concepts and skills needed to perform Chromatin Immunoprecipitation and Sequencing (ChIP-Seq). Chromatine extracts will be prepared from control and activated cell line. Next, a multiplexed ChIP-Seq library will be produced using the Microplex Library Preparation kit (Diagenode) and validated at each step. Finally, the subsequent library will be sequenced using a NextSeq 500 Illumina sequencer.
After inspecting carefully the reports from the sequencer, downstream analyses are performed using a Galaxy instance deployed on our own server (pedagogix). Reads are quality checked, trimmed and mapped to the reference genome.
Schedule of the course 2015-2016
The practical session will take place from October 12 through October 16, 2015 at the TGML platform hosted in the TAGC laboratory.
Protocols
| Name | link |
|---|---|
| Chromatin preparation and immunoprecipitation | protocole.doc.zip |
| Diagenode Microplex Library Preparation kit | MicroPlex-Libary-Prep-Kit-v2-manual.pdf |
| Agilent BioAnalyzer 6000 RNA_Nano | 0_Agilent_BioAnalyzer_6000_RNA_Nano.pdf |
Tools and files for analysis
- Galaxy server: an open source, web-based platform for data intensive biomedical research.
- Integrative Genomics Viewer (IGV): a high-performance visualization tool for interactive exploration of large, integrated genomic datasets.
- FastQC: A quality control tool for high throughput sequence data;
- sickle - Trimming tool for FASTQ files using quality.
- Bowtie - Read aligner.
- Deeptools - A set of tools to handle bigWigs.
- R: a freely available language and environment for statistical computing and graphics
- RStudio: An interface to R.
Results and additional data
- Lab (2015)
| Type | link |
|---|---|
| Chromatin check (fragment size #1) | Bioanalyzer report |
| Chromatin check (fragment size #2) | Bioanalyzer report |
H3K27Ac-Control_sorted.bw
- Sequencing results (2015)
| Type | link |
|---|---|
| Unstimulated H3K27Ac (fastqc trimmed R1) | H3K27Ac_Control_R1_trim_fastqc.zip |
| Unstimulated H3K27Ac (fastqc trimmed R2) | H3K27Ac_Control_R2_trim_fastqc.zip |
| Stimulated H3K27Ac (fastqc trimmed R1) | H3K27Ac_Treated_R1_trim_fastqc.zip |
| Stimulated H3K27Ac (fastqc trimmed R2) | H3K27Ac_Treated_R2_trim_fastqc.zip |
| Unstimulated H3K27Me3 (fastqc trimmed R1) | H3K27Me3-Contr_R1_trim_fastqc.zip |
| Unstimulated H3K27Me3 (fastqc trimmed R2) | H3K27Me3-Contr_R2_trim_fastqc.zip |
| Stimulated H3K27Me3 (fastqc trimmed R1) | H3K27Me3_Treated_R1_trim_fastqc.zip |
| Stimulated H3K27Me3 (fastqc trimmed R2) | H3K27Me3_Treated_R2_trim_fastqc.zip |
| Unstimulated H3K27Ac (bigwig) | H3K27Ac-Control_sorted_2015.bw.zip |
| Stimulated H3K27Ac (bigwig) | H3K27Ac_Treated_sorted_2015.bw.zip |
| Unstimulated H3K27me3 (bigwig) | H3K27Me3-Contr_sorted_2015.bw.zip |
| Stimulated H3K27me3 (bigwig) | H3K27Me3_Treated_sorted_2015.bw.zip |
| Unstimulated H3K27Ac (signal around promoters) | H3K27Ac-Control_prom1k1k_2015.txt.zip |
| Stimulated H3K27Ac (signal around promoters) | H3K27Ac_Treated_prom1k1k_2015.txt.zip |
| Unstimulated H3K27Me3 (signal around promoters) | H3K27Me3-Contr_prom1k1k_2015.txt.zip |
| Stimulated H3K27Me3 (signal around promoters) | H3K27Me3_Treated_prom1k1k_2015.txt.zip |
| Unstimulated H3K27Ac (peaks bed format) | H3K27Ac_Control_peaks.bed.zip |
| Unstimulated H3K27Ac (peaks xls format) | H3K27Ac_Control_peaks.xls.zip |
| Stimulated H3K27Ac (peaks bed format) | H3K27Ac_Treated_peaks.bed.zip |
| Stimulated H3K27Ac (peaks xls format) | H3K27Ac_Treated_peaks.xls.zip |
| Unstimulated H3K27me3 (peaks bed format) | H3K27Me3_Control__peaks.bed.zip |
| Unstimulated H3K27me3 (peaks xls format) | H3K27Me3_Control__peaks.xls.zip |
| Stimulated H3K27me3 (peaks bed format) | H3K27Me3_Treated_peaks.bed.zip |
| Unstimulated H3K27me3 (peaks xls format) | H3K27Me3_Treated_peaks.xls.zip |
- Sequencing results (2014)
| Type | link |
|---|---|
| Input (bigwig) | NS-S_Input.bw.zip |
| Unstimulated H3K27Ac (bigwig) | NS_H3K27Ac.bw |
| Unstimulated H3K27Ac(signal around promoters) | NS_H3K27Ac_prom1k1k.txt |
| Unstimulated H3K4me3 (bigwig) | NS_H3K4me3.bw |
| Unstimulated H3K4me3(signal around promoters) | NS_H3K4me3_prom1k1k.txt |
| Stimulated H3K4me3 (bigwig) | S_H3K4me3.bw |
| Stimulated H3K4me3(signal around promoters) | S_H3K4me3_prom1k1k.txt |
| Unstimulated H3K27Ac (peaks) | NS_H3K27Ac_peaks.bed |
| Unstimulated H3K4me3 (peaks) | NS_H3K4me3_peaks.bed |
| Stimulated H3K4me3 (peaks) | S_H3K4me3_peaks.bed |
| Unstimulated H3K27Ac (bam index chr19) | NS_H3K27Ac_chr19.bam.bai |
| Unstimulated H3K27Ac (bam chr19) | NS_H3K27Ac_chr19.bam.bai |
- Sequencing results (others)
| Type | link |
|---|---|
| RNA-Seq (counts, gene) | counts.txt |
| RNA-Seq (counts, transcript) | counts.txt |
| Unstimulated H3K4me1 (bigwig) | NS_H3K4me1.bw |
| Unstimulated H3K4me2 (bigwig) | NS_H3K4me2.bw |
| Unstimulated PolII (bigwig) | NS_PolII.bw |
| Unstimulated RNA-Seq (bigwig minus strand) | NS_RNA_min.bw |
| Unstimulated RNA-Seq (bigwig plus strand) | NS_RNA_plus.bw |
| Stimulated H3K4me3 (signal around promoters) | H3K4me3-S_prom1k1k.tsv |
| Stimulated RNA-Seq (bigwig minus strand) | S_RNA_min.bw |
| Stimulated RNA-Seq (bigwig plus strand) | S_RNA_plus.bw |