Gene expression profile analysis in astaxanthin-induced Haematococcus pluvialis using a cDNA microarray

Hyunsuk Eom, Choul Gyun Lee, Eon Seon Jin

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

The unicellular green alga Haematococcus pluvialis (Volvocales) is known for the ketocarotenoid astaxanthin (3, 3′-dihydroxy-β, β-carotene-4, 4′-dione) accumulation, which is induced under unfavorable culture conditions. In this work, we used cDNA microarray analysis to screen differentially expressed genes in H. pluvialis under astaxanthin-inductive culture conditions, such as combination of cell exposure to high irradiance and nutrient deprivation. Among the 965 genes in the cDNA array, there are 144 genes exhibiting differential expression (twofold changes) under these conditions. A significant decrease in the expression of photosynthesis-related genes was shown in astaxanthin-accumulating cells (red cells). Defenseor stress-related genes and signal transduction genes were also induced in the red cells. A comparison of microarray and real-time PCR analysis showed good correlation between the differentially expressed genes by the two methods. Our results indicate that the cDNA microarray approach, as employed in this work, can be relied upon and used to monitor gene expression profiles in H. pluvialis. In addition, the genes that were differentially expressed during astaxanthin induction are suitable candidates for further study and can be used as tools for dissecting the molecular mechanism of this unique pigment accumulation process in the green alga H. pluvialis.

Original languageEnglish
Pages (from-to)1231-1242
Number of pages12
JournalPlanta
Volume223
Issue number6
DOIs
StatePublished - May 2006

Bibliographical note

Funding Information:
Acknowledgements This work was supported by 21C Frontier Microbial Genomics and Application Center grant (MG05-0308-5-0) from the Ministry of Science and Technology.

Keywords

  • Astaxanthin
  • DNA microarray
  • Haematococcus pluvialis
  • Real-time PCR
  • Transcript profiling

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