- Triplicates (2x15cm dishes = 30 milion cells per replicate), splited 5 days before 1:2
- Starved for 24 hours at 0.5 mM glucose, then 0.5 hours at 20 mM for HIGH glucose while 0.5 mM for LOW glucose
Polysome profiling 13 fractions divided in:
- Monosomes: 5-6
- Light polysomes: 7-9
- Heavy polysomes: 10-13
- Total RNA for each replicate
| Raw_reads | Monosomes | Light Poly | Heavy Poly |
|---|---|---|---|
| Low_glucose rep1 | 10814918 | 9745454 | 12051978 |
| Low_glucose rep2 | 10578664 | 13997704 | 9749807 |
| Low_glucose rep3 | 13326344 | 11453671 | 7871513 |
| High_glucose rep1 | 12416163 | 10723806 | 8476376 |
| High_glucose rep2 | 10948574 | 11572776 | 8985906 |
| High_glucose rep3 | 10855263 | 8762845 | 13196915 |
run_dirty_STAR.sh
- Mapping: STAR 2.5.4b; parameters: --outFilterMultimapNmax 20 --outSAMprimaryFlag AllBestScore --outSAMtype BAM SortedByCoordinate --quantMode TranscriptomeSAM GeneCounts --outStd Log --seedSearchStartLmaxOverLread 0.5 --winAnchorMultimapNmax 36 --outFilterScoreMinOverLread 0.5 --outFilterMatchNminOverLread 0.5
| Unique mapped | Monosomes | Light Poly | Heavy Poly | Total RNA |
|---|---|---|---|---|
| Low_glucose rep1 | 61.24% | 75.83% | 74.58% | 79.24% |
| Low_glucose rep2 | 56.84% | 76.06% | 74.69% | 78.81% |
| Low_glucose rep3 | 50.12% | 68.52% | 73.96% | 77.56% |
| High_glucose rep1 | 60.37% | 73.56% | 73.78% | 78.71% |
| High_glucose rep2 | 58.57% | 69.51% | 80.24% | 79.24% |
| High_glucose rep3 | 64.97% | 68.10% | 77.64% | 78.40% |
-
TPM quantification: RSEM (used) and STRINGTIE (just tried)
-
Filtering of the files for protein coding genes
diffAnal_GOenrich_Clustering_Bcells.R
R code to performe all the downstream analysis starting from the read counts and/or the TPM tables after the RNA-seq analysis.
The script is performing the following families of analysis.
- Differential analysis using Limma.
- Quality control using R PCA packages (and for visualisation).
- Enrichment analysis using clusterProfiler. 4 Cluster analysis using various R clustering methods (hierarchical, k-means, mclust).
...
The RNA features extraction software can be found at the following GitHub repository: RNA_Features_Extraction