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De novo transcriptomic analysis of Chlorella sorokiniana reveals differential genes expression in photosynthetic carbon fixation and lipid production

View Article: PubMed Central - PubMed

ABSTRACT

Background: Microalgae, which can absorb carbon dioxide and then transform it into lipid, are promising candidates to produce renewable energy, especially biodiesel. The paucity of genomic information, however, limits the development of genome-based genetic modification to improve lipid production in many microalgae. Here, we describe the de novo sequencing, transcriptome assembly, annotation and differential expression analysis for Chlorella sorokiniana cultivated in different conditions to reveal the change of genes expression associated with lipid accumulation and photosynthetic carbon fixation.

Results: Six cultivation conditions were selected to cultivate C. sorokiniana. Lipid content of C. sorokiniana under nitrogen-limited condition was 2.96 times than that under nitrogen-replete condition. When cultivated in light with nitrogen-limited supply, C. sorokiniana can use carbon dioxide to accumulate lipid. Then, transcriptome of C. sorokiniana was sequenced using Illumina paired-end sequencing technology, and 244,291,069 raw reads with length of 100 bp were produced. After preprocessed, these reads were de novo assembled into 63,811 contigs among which 23,528 contigs were found homologous sequences in public databases through Blastx. Gene expression abundance under six conditions were quantified by calculating FPKM value. Ultimately, we found 385 genes at least 2-fold up-regulated while 71 genes at least 2-fold down-regulated in nitrogen-limited condition. Also, 204 genes were at least 2-fold up-regulated in light while 638 genes at least 2-fold down-regulated. Finally, 16 genes were selected to conduct RT-qPCR and 15 genes showed the similar results as those identified by transcriptomic analysis in term of differential expression.

Conclusions: De novo transcriptomic analyses have generated enormous information over C. sorokiniana, revealing a broad overview of genomic information related to lipid accumulation and photosynthetic carbon fixation. The genes with expression change under different conditions are highly likely the potential targets for genetic modification to improve lipid production and CO2 fixation efficiency in oleaginous microalgae.

Electronic supplementary material: The online version of this article (doi:10.1186/s12866-016-0839-8) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

The differentially expressed genes profiles detected by RT-qPCR. C. sorokiniana was cultivated under six different conditions. a: genes involving in lipid accumulation; b: genes involving in Calvin cycle. BC: biotin carboxylase; KAS II: 3-oxoacyl-[acyl-carrier-protein] synthase II; KAS III: 3-oxoacyl-[acyl-carrier-protein] synthase III; KAR: Beta-ketoacyl-ACP reductase; AGPAT: 1-acyl-sn-glycerol-3-phosphate acyltransferase; DGAT: diacylglycerol O-acyltransferase; ACC: acetyl-CoA carboxylase; MAT: malonyltransferase; SS: starch synthase; BE: 1,4-α-glucan branching enzyme; AOx: acyl-CoA oxidase; GPAT: glycerol-3-phosphate O-acyltransferase; RBCL: ribulose-bisphosphate carboxylase large chain; SEBP: sedoheptulose-bisphosphatase; RPE: ribulose-phosphate 3-epimerase; ALDO: fructose-bisphosphate aldolase. Standard error of mean for three technical replicates is represented by the error bars
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Fig6: The differentially expressed genes profiles detected by RT-qPCR. C. sorokiniana was cultivated under six different conditions. a: genes involving in lipid accumulation; b: genes involving in Calvin cycle. BC: biotin carboxylase; KAS II: 3-oxoacyl-[acyl-carrier-protein] synthase II; KAS III: 3-oxoacyl-[acyl-carrier-protein] synthase III; KAR: Beta-ketoacyl-ACP reductase; AGPAT: 1-acyl-sn-glycerol-3-phosphate acyltransferase; DGAT: diacylglycerol O-acyltransferase; ACC: acetyl-CoA carboxylase; MAT: malonyltransferase; SS: starch synthase; BE: 1,4-α-glucan branching enzyme; AOx: acyl-CoA oxidase; GPAT: glycerol-3-phosphate O-acyltransferase; RBCL: ribulose-bisphosphate carboxylase large chain; SEBP: sedoheptulose-bisphosphatase; RPE: ribulose-phosphate 3-epimerase; ALDO: fructose-bisphosphate aldolase. Standard error of mean for three technical replicates is represented by the error bars

Mentions: 16 genes were selected to perform Real-time quantitative PCR (RT-qPCR). In the lipid metabolic pathways (Fig. 6a), 6 genes (biotin carboxylase, BC; 3-oxoacyl-[acyl-carrier-protein] synthase II, KAS II; 3-oxoacyl-[acyl-carrier-protein] synthase II, KAS III; Beta-ketoacyl-[acyl-carrier-protein] reductase, KAR; 1-acyl-sn-glycerol-3-phosphate acyltransferase, AGPAT; diacylglycerol O-acyltransferase, DGAT) showed up-regulation in nitrogen-limited condition, especially BC and KAR. However, 2 genes (acetyl-CoA carboxylase, ACC; malonyltransferase, MAT) were found down-regulated in the nitrogen-limited condition. The down-regulation of ACC and up-regulation of BC under nitrogen-limited condition were also reported in Neochloris oleoabundans [15].Fig. 6


De novo transcriptomic analysis of Chlorella sorokiniana reveals differential genes expression in photosynthetic carbon fixation and lipid production
The differentially expressed genes profiles detected by RT-qPCR. C. sorokiniana was cultivated under six different conditions. a: genes involving in lipid accumulation; b: genes involving in Calvin cycle. BC: biotin carboxylase; KAS II: 3-oxoacyl-[acyl-carrier-protein] synthase II; KAS III: 3-oxoacyl-[acyl-carrier-protein] synthase III; KAR: Beta-ketoacyl-ACP reductase; AGPAT: 1-acyl-sn-glycerol-3-phosphate acyltransferase; DGAT: diacylglycerol O-acyltransferase; ACC: acetyl-CoA carboxylase; MAT: malonyltransferase; SS: starch synthase; BE: 1,4-α-glucan branching enzyme; AOx: acyl-CoA oxidase; GPAT: glycerol-3-phosphate O-acyltransferase; RBCL: ribulose-bisphosphate carboxylase large chain; SEBP: sedoheptulose-bisphosphatase; RPE: ribulose-phosphate 3-epimerase; ALDO: fructose-bisphosphate aldolase. Standard error of mean for three technical replicates is represented by the error bars
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC5037625&req=5

Fig6: The differentially expressed genes profiles detected by RT-qPCR. C. sorokiniana was cultivated under six different conditions. a: genes involving in lipid accumulation; b: genes involving in Calvin cycle. BC: biotin carboxylase; KAS II: 3-oxoacyl-[acyl-carrier-protein] synthase II; KAS III: 3-oxoacyl-[acyl-carrier-protein] synthase III; KAR: Beta-ketoacyl-ACP reductase; AGPAT: 1-acyl-sn-glycerol-3-phosphate acyltransferase; DGAT: diacylglycerol O-acyltransferase; ACC: acetyl-CoA carboxylase; MAT: malonyltransferase; SS: starch synthase; BE: 1,4-α-glucan branching enzyme; AOx: acyl-CoA oxidase; GPAT: glycerol-3-phosphate O-acyltransferase; RBCL: ribulose-bisphosphate carboxylase large chain; SEBP: sedoheptulose-bisphosphatase; RPE: ribulose-phosphate 3-epimerase; ALDO: fructose-bisphosphate aldolase. Standard error of mean for three technical replicates is represented by the error bars
Mentions: 16 genes were selected to perform Real-time quantitative PCR (RT-qPCR). In the lipid metabolic pathways (Fig. 6a), 6 genes (biotin carboxylase, BC; 3-oxoacyl-[acyl-carrier-protein] synthase II, KAS II; 3-oxoacyl-[acyl-carrier-protein] synthase II, KAS III; Beta-ketoacyl-[acyl-carrier-protein] reductase, KAR; 1-acyl-sn-glycerol-3-phosphate acyltransferase, AGPAT; diacylglycerol O-acyltransferase, DGAT) showed up-regulation in nitrogen-limited condition, especially BC and KAR. However, 2 genes (acetyl-CoA carboxylase, ACC; malonyltransferase, MAT) were found down-regulated in the nitrogen-limited condition. The down-regulation of ACC and up-regulation of BC under nitrogen-limited condition were also reported in Neochloris oleoabundans [15].Fig. 6

View Article: PubMed Central - PubMed

ABSTRACT

Background: Microalgae, which can absorb carbon dioxide and then transform it into lipid, are promising candidates to produce renewable energy, especially biodiesel. The paucity of genomic information, however, limits the development of genome-based genetic modification to improve lipid production in many microalgae. Here, we describe the de novo sequencing, transcriptome assembly, annotation and differential expression analysis for Chlorella sorokiniana cultivated in different conditions to reveal the change of genes expression associated with lipid accumulation and photosynthetic carbon fixation.

Results: Six cultivation conditions were selected to cultivate C. sorokiniana. Lipid content of C. sorokiniana under nitrogen-limited condition was 2.96 times than that under nitrogen-replete condition. When cultivated in light with nitrogen-limited supply, C. sorokiniana can use carbon dioxide to accumulate lipid. Then, transcriptome of C. sorokiniana was sequenced using Illumina paired-end sequencing technology, and 244,291,069 raw reads with length of 100 bp were produced. After preprocessed, these reads were de novo assembled into 63,811 contigs among which 23,528 contigs were found homologous sequences in public databases through Blastx. Gene expression abundance under six conditions were quantified by calculating FPKM value. Ultimately, we found 385 genes at least 2-fold up-regulated while 71 genes at least 2-fold down-regulated in nitrogen-limited condition. Also, 204 genes were at least 2-fold up-regulated in light while 638 genes at least 2-fold down-regulated. Finally, 16 genes were selected to conduct RT-qPCR and 15 genes showed the similar results as those identified by transcriptomic analysis in term of differential expression.

Conclusions: De novo transcriptomic analyses have generated enormous information over C. sorokiniana, revealing a broad overview of genomic information related to lipid accumulation and photosynthetic carbon fixation. The genes with expression change under different conditions are highly likely the potential targets for genetic modification to improve lipid production and CO2 fixation efficiency in oleaginous microalgae.

Electronic supplementary material: The online version of this article (doi:10.1186/s12866-016-0839-8) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus