PRJNA174770, RNA-seq, nitrogen depletion, PRJNA174770

Analysis NamePRJNA174770
Organism NameNannochloropsis gaditana (N. gaditana B-31)
Methodnf-core/rnaseq (nf-core/rnaseq v1.2)
SourceRNA-seq, nitrogen depletion, PRJNA174770
Date performed2019-07-03


Transcriptome profiling in nitrogen depletion

This dataset was downloaded from NCBI under bioproject: PRJNA174770.

Below detailed description was retreived from Reference: Corteggiani Carpinelli E et al., "Chromosome scale genome assembly and transcriptome profiling of Nannochloropsis gaditana in nitrogen depletion.", Mol Plant, 2014 Feb;7(2):323-35.


DNA and RNA Purification

Nucleic acids were purified from N. gaditana as previously described (La Claire and Herrin, 1997) with minor variations: rupture of microalgal cells was helped by the addition of quartz powder; DNA obtained after precipitation was not further processed through CsCl gradient purification as reported in the published protocol. Total RNA obtained after purification was enriched in mRNA using Dynabeads Oligo (dT)25 (Invitrogen).

Gene Expression Analysis

For each experiment, we calculated the number of unique reads mapping on each gene using the htseq-count program (HTSeq v0.5.3p7, available online at The raw counts were normalized to account for distributional differences between samples due to different sequencing depth using median normalization implemented in the EDASeq package (Risso et al., 2011). All the genes having an average number of reads lower than 10 across all six experiments were excluded from further analysis. Differentially expressed genes were identified using the edgeR package (Robinson et al., 2010). We compared nitrogen-depleted and nitrogen-sufficient samples collected 3 d after re-suspension. Since the experiments had two replicates, we calculated the variability among them using edgeR function estimateCommonDisp. We also compared nitrogen-depleted and nitrogen-sufficient samples collected 6 d after re-suspension. We assumed that the variability of the samples was similar to the previous one and therefore we set the dispersion parameter to the same value (0.03507416). The differentially expressed genes were calculated using the exactTest function, which is based on a negative-binomial model. The p-value was set to 0.05 after FDR correction.


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Feature Expression

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