Genome-wide diel growth state transitions in the diatom Thalassiosira pseudonana.

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Journal Article
Proceedings of the National Academy of Sciences of the United States of America, 2013, 110 (18), pp. 7518 - 7523
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Marine diatoms are important primary producers that thrive in diverse and dynamic environments. They do so, in theory, by sensing changing conditions and adapting their physiology accordingly. Using the model species Thalassiosira pseudonana, we conducted a detailed physiological and transcriptomic survey to measure the recurrent transcriptional changes that characterize typical diatom growth in batch culture. Roughly 40% of the transcriptome varied significantly and recurrently, reflecting large, reproducible cell-state transitions between four principal states: (i) "dawn," following 12 h of darkness; (ii) "dusk," following 12 h of light; (iii) exponential growth and nutrient repletion; and (iv) stationary phase and nutrient depletion. Increases in expression of thousands of genes at the end of the reoccurring dark periods (dawn), including those involved in photosynthesis (e.g., ribulose-1,5-bisphosphate carboxylase oxygenase genes rbcS and rbcL), imply large-scale anticipatory circadian mechanisms at the level of gene regulation. Repeated shifts in the transcript levels of hundreds of genes encoding sensory, signaling, and regulatory functions accompanied the four cell-state transitions, providing a preliminary map of the highly coordinated gene regulatory program under varying conditions. Several putative light sensing and signaling proteins were associated with recurrent diel transitions, suggesting that these genes may be involved in light-sensitive and circadian regulation of cell state. These results begin to explain, in comprehensive detail, how the diatom gene regulatory program operates under varying environmental conditions. Detailed knowledge of this dynamic molecular process will be invaluable for new hypothesis generation and the interpretation of genetic, environmental, and metatranscriptomic data from field studies.
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