SRX5626864 GSM3703433 SRP190218 SRS4572405 GSM3703433 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703433 GSM3703433 GEO Accession GSM3703433 SRX5626865 GSM3703434 SRP190218 SRS4572406 GSM3703434 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703434 GSM3703434 GEO Accession GSM3703434 SRX5626866 GSM3703435 SRP190218 SRS4572407 GSM3703435 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703435 GSM3703435 GEO Accession GSM3703435 SRX5626867 GSM3703436 SRP190218 SRS4572408 GSM3703436 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703436 GSM3703436 GEO Accession GSM3703436 SRX5626868 GSM3703437 SRP190218 SRS4572409 GSM3703437 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703437 GSM3703437 GEO Accession GSM3703437 SRX5626869 GSM3703438 SRP190218 SRS4572410 GSM3703438 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703438 GSM3703438 GEO Accession GSM3703438 SRX5626870 GSM3703439 SRP190218 SRS4572411 GSM3703439 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703439 GSM3703439 GEO Accession GSM3703439 SRX5626871 GSM3703440 SRP190218 SRS4572412 GSM3703440 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703440 GSM3703440 GEO Accession GSM3703440 SRX5626872 GSM3703441 SRP190218 SRS4572413 GSM3703441 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703441 GSM3703441 GEO Accession GSM3703441 SRX5626873 GSM3703442 SRP190218 SRS4572414 GSM3703442 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703442 GSM3703442 GEO Accession GSM3703442 SRX5626874 GSM3703443 SRP190218 SRS4572415 GSM3703443 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703443 GSM3703443 GEO Accession GSM3703443 SRX5626875 GSM3703444 SRP190218 SRS4572416 GSM3703444 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703444 GSM3703444 GEO Accession GSM3703444 SRX5626876 GSM3703445 SRP190218 SRS4572417 GSM3703445 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703445 GSM3703445 GEO Accession GSM3703445 SRX5626877 GSM3703446 SRP190218 SRS4572418 GSM3703446 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703446 GSM3703446 GEO Accession GSM3703446 SRX5626878 GSM3703447 SRP190218 SRS4572419 GSM3703447 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703447 GSM3703447 GEO Accession GSM3703447 SRX5626879 GSM3703448 SRP190218 SRS4572420 GSM3703448 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703448 GSM3703448 GEO Accession GSM3703448 SRX5626880 GSM3703449 SRP190218 SRS4572421 GSM3703449 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703449 GSM3703449 GEO Accession GSM3703449 SRX5626881 GSM3703450 SRP190218 SRS4572422 GSM3703450 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703450 GSM3703450 GEO Accession GSM3703450 SRX5626882 GSM3703451 SRP190218 SRS4572423 GSM3703451 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703451 GSM3703451 GEO Accession GSM3703451 SRX5626883 GSM3703452 SRP190218 SRS4572424 GSM3703452 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703452 GSM3703452 GEO Accession GSM3703452 SRX5626884 GSM3703453 SRP190218 SRS4572425 GSM3703453 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703453 GSM3703453 GEO Accession GSM3703453 SRX5626885 GSM3703454 SRP190218 SRS4572426 GSM3703454 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703454 GSM3703454 GEO Accession GSM3703454 SRX5626886 GSM3703455 SRP190218 SRS4572427 GSM3703455 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703455 GSM3703455 GEO Accession GSM3703455 SRX5626887 GSM3703456 SRP190218 SRS4572428 GSM3703456 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703456 GSM3703456 GEO Accession GSM3703456 SRX5626888 GSM3703457 SRP190218 SRS4572429 GSM3703457 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703457 GSM3703457 GEO Accession GSM3703457 SRX5626889 GSM3703458 SRP190218 SRS4572430 GSM3703458 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703458 GSM3703458 GEO Accession GSM3703458 SRX5626890 GSM3703459 SRP190218 SRS4572431 GSM3703459 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703459 GSM3703459 GEO Accession GSM3703459 SRX5626891 GSM3703460 SRP190218 SRS4572433 GSM3703460 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703460 GSM3703460 GEO Accession GSM3703460 SRX5626892 GSM3703461 SRP190218 SRS4572432 GSM3703461 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703461 GSM3703461 GEO Accession GSM3703461 SRX5626893 GSM3703462 SRP190218 SRS4572434 GSM3703462 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703462 GSM3703462 GEO Accession GSM3703462 SRX5626894 GSM3703463 SRP190218 SRS4572435 GSM3703463 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703463 GSM3703463 GEO Accession GSM3703463 SRX5626895 GSM3703464 SRP190218 SRS4572436 GSM3703464 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703464 GSM3703464 GEO Accession GSM3703464 SRX5626896 GSM3703465 SRP190218 SRS4572437 GSM3703465 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703465 GSM3703465 GEO Accession GSM3703465 SRX5626897 GSM3703466 SRP190218 SRS4572438 GSM3703466 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703466 GSM3703466 GEO Accession GSM3703466 SRX5626898 GSM3703467 SRP190218 SRS4572439 GSM3703467 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703467 GSM3703467 GEO Accession GSM3703467 SRX5626899 GSM3703468 SRP190218 SRS4572441 GSM3703468 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703468 GSM3703468 GEO Accession GSM3703468 SRX5626900 GSM3703469 SRP190218 SRS4572440 GSM3703469 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703469 GSM3703469 GEO Accession GSM3703469 SRX5626901 GSM3703470 SRP190218 SRS4572442 GSM3703470 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703470 GSM3703470 GEO Accession GSM3703470 SRX5626902 GSM3703471 SRP190218 SRS4572443 GSM3703471 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703471 GSM3703471 GEO Accession GSM3703471 SRX5626903 GSM3703472 SRP190218 SRS4572444 GSM3703472 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703472 GSM3703472 GEO Accession GSM3703472 SRX5626904 GSM3703473 SRP190218 SRS4572445 GSM3703473 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703473 GSM3703473 GEO Accession GSM3703473 SRX5626905 GSM3703474 SRP190218 SRS4572446 GSM3703474 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703474 GSM3703474 GEO Accession GSM3703474 SRX5626906 GSM3703475 SRP190218 SRS4572447 GSM3703475 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703475 GSM3703475 GEO Accession GSM3703475 SRX5626907 GSM3703476 SRP190218 SRS4572448 GSM3703476 RNA-Seq TRANSCRIPTOMIC cDNA Cultured cells (50 ml per sample) were harvested for RNA isolation after N- or NR treatments at 6, 12, 24, 48 and 72 h. For each time point two biological replicates were harvested by centrifugation (4000 x g, 10 min, 22°C). Cells were flash-frozen in liquid N and ground using TissueLyser II (Qiagen). RNA was extracted using the E.Z.N.A® Plant RNA kit (OMEGA) according to the manufacturer's instructions. RNA quality was verified using the Bioanalyzer (Agilent). Single-end, 50 bp nucleotide sequences were acquired for each sample using an Illumina HiSeq 2500 (MSU-Research Technology Support Facility). RNA-Seq reads were trimmed using Trimmomatic (v0.32) (Bolger et al., 2014) with removal of leading and trailing low quality bases (below quality score 10 with a 4-base wide sliding window) as well as TruSeq Single End adaptors. The resulting reads were aligned to the N. oceanica CCMP1779 genome assembly (GSE36959) (Vieler et al., 2012) using STAR (2.3.0e) (Dobin et al., 2013) by only allowing unique mapping, a maximum of 4 mismatches per pair and a maximum intron length of 10,000 bp. The HTSeq (0.6.1) (Anders et al., 2015) was used to generate a count table for all genes using the exon as the feature type as well as the intersect-nonempty mode so that only reads that were completely aligned to two genes are considered ambiguous. HTSeq count tables were used for differential expression analysis using DEseq2 (Love et al., 2014). Differential gene expression was examined using DESeq2 (Love et al., 2014). A generalized linear model was fit, and we tested on condition (deprivation or recovery) and the time:condition interaction with log2-fold changes greater than 1. Significant differentially expressed genes with p-values less than 0.01 were identified after Benjamini-Hochberg (BH) multiple testing correction. Differentially expressed genes were clustered based on expression using K-means clustering (k = 4) with the Pearsons correlation distance metric within MeV (4.8.1) (Saeed et al., 2003). References: Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166-169 Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378 Vieler A et al. (2012) Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779. PLoS Genet 8: e1003064 RNA libraries were prepared for sequencing using standard Illumina protocols Illumina HiSeq 2500 gds 303703476 GSM3703476 GEO Accession GSM3703476