Chips and tags suggest plant-environment interactions differ for two alpine Pachycladon species

芯片和标签表明,两种高山厚叶草属植物的植物-环境相互作用存在差异。

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Abstract

BACKGROUND: Expression profiling has been proposed as a means for screening non-model organisms in their natural environments to identify genes potentially important in adaptive diversification. Tag profiling using high throughput sequencing is a relatively low cost means of expression profiling with deep coverage. However the extent to which very short cDNA sequences can be effectively used in screening for candidate genes is unclear. Here we investigate this question using an evolutionarily distant as well as a closely related transcriptome for referencing tags. We do this by comparing differentially expressed genes and processes between two closely related allopolyploid species of Pachycladon which have distinct altitudinal preferences in the New Zealand Southern Alps. We validate biological inferences against earlier microarray analyses. RESULTS: Statistical and gene annotation enrichment analyses of tag profiles identified more differentially expressed genes of potential adaptive significance than previous analyses of array-based expression profiles. These include genes involved in glucosinolate metabolism, flowering time, and response to cold, desiccation, fungi and oxidation. In addition, despite the short length of 20mer tags, we were able to infer patterns of homeologous gene expression for 700 genes in our reference library of 7,128 full-length Pachycladon ESTs. We also demonstrate that there is significant information loss when mapping tags to the non-conspecific reference transcriptome of A. thaliana as opposed to P. fastigiatum ESTs but also describe mapping strategies by which the larger collection of A. thaliana ESTs can be used as a reference. CONCLUSION: When coupled with a reference transcriptome generated using RNA-seq, tag sequencing offers a promising approach for screening natural populations and identifying candidate genes of potential adaptive significance. We identify computational issues important for the successful application of tag profiling in a non-model allopolyploid plant species.

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