How does cold change gene expression in Arabidopsis?

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Abiotic stresses such as low temperature limit plant productivity and geographical distribution, motivating research into how plants adapt. Because cold exposure causes a wide range of physiological, biochemical and molecular changes, the researchers sought a robust, global view of the response. They used Serial Analysis of Gene Expression (SAGE) to track transcriptome changes in Arabidopsis thaliana during low-temperature stress.

They generated five SAGE libraries from A. thaliana leaf tissue collected between 30 minutes and one week of treatment at 4°C. More than 240,000 high-quality SAGE tags, corresponding to 16,629 annotated genes, surveyed transcriptome changes from stress perception through the acquisition of freezing tolerance. Representing the SAGE data by gene identifier supported more robust statistical analysis, cross-platform comparisons and identification of genes with shared expression profiles.

Simultaneous statistical analysis of all five libraries identified 920 low-temperature-responsive genes; only 24% overlapped with an earlier global expression analysis using microarrays, although similar functional categories were affected. Clustering differentially regulated genes helped identify previously unrecognized loci correlated with the development of freezing tolerance. Analysis of their promoter sequences revealed subsets of genes independent of CBF and ABA regulation that could help elucidate complementary signaling pathways. The SAGE data also showed increased alternative pre-mRNA processing at low temperatures and repression of antisense transcription, emphasizing the complexity of the plant response.

The authors concluded that alternative transcript processing appears important for increasing the flexibility of the stress-induced transcriptome. They identified novel genes and cis-acting sequences as promising targets for manipulating plants' ability to protect themselves against low-temperature stress. They also presented their analyses as a framework for interpreting quantitative sequence-tag-based transcriptome analysis as next-generation sequencing technology is applied.