Premise of the study: We present a protocol for the annotation of transcriptome sequence data and the identification of candidate genes therein using the example of the nonmodel conifer Abies alba. •
Methods and results: A normalized cDNA library was built from an A. alba seedling. The sequencing on a 454 platform yielded more than 1.5 million reads that were de novo assembled into 25149 contigs. Two complementary approaches were applied to annotate gene fragments that code for (1) well-known proteins and (2) proteins that are potentially adaptively relevant. Primer development and testing yielded 88 amplicons that could successfully be resequenced from genomic DNA. •
Conclusions: The annotation workflow offers an efficient way to identify potential adaptively relevant genes from the large quantity of transcriptome sequence data. The primer set presented should be prioritized for single-nucleotide polymorphism detection in adaptively relevant genes in A. alba.
Keywords: Abies alba; Pinaceae; adaptation; annotation; candidate genes; de novo sequencing.