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RNA-Seq and transcriptome analysis of nitrogen-deprivation responsive genes in Dunaliella salina TG strain

  • Hexin LvEmail author
  • Qiao-e Wang
  • Bingbing Qi
  • Jiatong He
  • Shiru Jia
Article
  • 27 Downloads

Abstract

Nitrogen is a critical macronutrient for plant growth and development, and Dunaliella salina has various physiological responses to nitrogen deprivation, such as accumulating large amounts of carotenoids in its chloroplasts. However, little is known about the underlying global molecular response of D. salina to nitrogen deprivation. Herein, we used the Illumina platform to interrogate which genes of D. salina respond to nitrogen deprivation. The RNA-seq libraries of D. salina TG cultured under nitrogen-replete and -depleted conditions for 7 days generated 87,160,704 valid reads with an average length of 124.94 bp. De novo assembly produced 73,329 transcripts with an average length of 801 bp and 47,283 unigenes with an average length of 675 bp. 5803 unigenes were assigned to 50 gene ontology (GO) terms belonging to three main categories. A total of 6016 unigenes with 671 enzyme commission numbers were assigned to 251 predicted KEGG metabolic pathways, and 6296 unigenes were categorized into 25 KOG classifications. A total of 27,306 CDS were predicted from the 47,283 unigenes. Analysis of transcription levels revealed that 2380 genes were upregulated and 747 were downregulated during nitrogen deprivation. These nitrogen-deprivation responsive genes and differentially expressed transcriptional regulator genes were identified by GO classification. The transcriptome data may serve as a reference for further analysis of gene expression and functional genomics studies, and will facilitate the study of carotenoid biosynthesis and nitrogen metabolism in chlorophytes at the molecular level.

Keywords

Dunaliella salina Nitrogen deprivation Transcriptome RNA-seq Transcription regulator 

Notes

Acknowledgements

This work is supported by the Open Research Fund Program of Beijing Key Lab of Plant Resource Research and Development, Beijing Technology and Business University and the National Natural Science Foundation of China (No. 31401029).

Author contributions

SJ and HL conceived and designed the project. HL analyzed the data and wrote the paper. BQ performed the cultures materials preparation and qPCR analysis. QW revised the paper and JH provided bioinformatic analysis tools. All authors have read and approved the final manuscript.

Supplementary material

40626_2019_138_MOESM1_ESM.xlsx (4.8 mb)
Supplementary material 1 (XLSX 4909 kb) Supplement Table 1. Statistics of Gene Annotations by Different Databases.
40626_2019_138_MOESM2_ESM.xlsx (360 kb)
Supplementary material 2 (XLSX 359 kb) Supplement Table 2. KEGG Pathway Classifications of Unigenes.
40626_2019_138_MOESM3_ESM.xlsx (218 kb)
Supplementary material 3 (XLSX 218 kb) Supplement Table 3. Differential Expressions of Unigenes of Cells under CM and -N.
40626_2019_138_MOESM4_ESM.xlsx (82 kb)
Supplementary material 4 (XLSX 82 kb) Supplement Table 4. Clusters of DEGs by Hierarchal Analysis.
40626_2019_138_MOESM5_ESM.xlsx (20 kb)
Supplementary material 5 (XLSX 19 kb) Supplement Table 5. Pathway Classifications of DEGs by KEGG. S gene number: Numbers of significantly changed genes in a given KEGG pathway. B gene number: Numbers of annotated genes in a given KEGG pathway.
40626_2019_138_MOESM6_ESM.xlsx (12 kb)
Supplementary material 6 (XLSX 12 kb) Supplement Table 6. Transcription regulators Classified by WEGO analysis.

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Copyright information

© Brazilian Society of Plant Physiology 2019

Authors and Affiliations

  1. 1.Key Laboratory of Industrial Fermentation MicrobiologyMinistry of Education (Tianjin University of Science & Technology)TianjinChina
  2. 2.Beijing Key Lab of Plant Resource Research and DevelopmentBeijing Technology and Business UniversityBeijingChina

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