Pseudotsuga menziesii (Douglas-fir) is an ideal model system to study the effect of local adaptation and intraspecific variation in transcriptome responses to the environment. Nonetheless, the lack of genomic resources and standardized microarray platforms for gene expression profiling has been a limitation to test the hypothesis on transcriptome organization and variation. Only recently, deep mRNA sequencing has become a promising alternative to overcome the present limitations. However, information on the transcript abundance distribution is needed for unbiased gene expression profiling from mRNA sequencing data. Since this information is not available for adult conifer needle tissue, we inferred the transcript abundance distribution and tested the effect of sequencing depth on the reliable detection and quantification of transcripts from the needle tissue of 50-year-old Douglas-fir trees. We obtained a similar distribution of GO-slim categories in our mRNA-sequencing libraries and in previously published putative unique transcripts (PUTs) for Douglas-fir, that were used as alignment reference. However, the GO-slim distribution in the Douglas-fir libraries and the Douglas-fir PUTs differed from the GO-slim distributions reported from mRNA deep sequencing libraries obtained from Arabidopsis thaliana leaf tissue. Apparently, several highly abundant PUTs associated with proteins involved in photosynthesis were limiting the benefits of increased sequencing depth. Simulations and empirical data indicated that a 3-fold increase from 5 to 15 million aligned reads results in about twice the number of PUTs that surpass the 100 aligned reads threshold that was used for robust transcript quantification.