A catalogue of putative unique transcripts from Douglas-fir (Pseudotsuga menziesii) based on 454 transcriptome sequencing of genetically diverse, drought stressed seedlings

Abstract

BackgroundDouglas-fir (Pseudotsuga menziesii) extends over a wide range of contrasting environmental conditions, reflecting substantial local adaptation. For this reason, it is an interesting model species to study plant adaptation and the effects of global climate change such as increased temperatures and significant periods of drought on individual trees and the forest landscape in general. However, genomic data and tools for studying genetic variation in natural populations to understand the genetic and physiological mechanisms of adaptation are currently missing for Douglas-fir. This study represents a first step towards characterizing the Douglas-fir transcriptome based on 454 sequencing of twelve cDNA libraries. The libraries were constructed from needle and wood tissue of coastal and interior provenances subjected to drought stress experiments.ResultsThe 454 sequencing of twelve normalized cDNA libraries resulted in 3.6 million reads from which a set of 170,859 putative unique transcripts (PUTs) was assembled. Functional annotation by BLAST searches and Gene Ontology mapping showed that the composition of functional classes is very similar to other plant transcriptomes and demonstrated that a large fraction of the Douglas-fir transcriptome is tagged by the PUTs. Based on evolutionary conservation, we identified about 1,000 candidate genes related to drought stress. A total number of 187,653 single nucleotide polymorphisms (SNPs) were detected by three SNP detection tools. However, only 27,688 SNPs were identified by all three methods, indicating that SNP detection depends on the particular method used. The two alleles of about 60% of the 27,688 SNPs are segregating simultaneously in both coastal and interior provenances, which indicates a high proportion of ancestral shared polymorphisms or a high level of gene flow between these two ecologically and phenotypically different varieties.ConclusionsWe established a catalogue of PUTs and large SNP database for Douglas-fir. Both will serve as a useful resource for the further characterization of the genome and transcriptome of Douglas-fir and for the analysis of genetic variation using genotyping or resequencing methods.

De novo assembly of maritime pine transcriptome: implications for forest breeding and biotechnology

“…Our study reveals a strong influence of the SNP calling algorithm on the number of detected SNPs. Such variability in the number of called SNPs between SNP detection software has been already reported in another conifer species (Muller et al ., ) and indicates that results should be interpreted with caution, especially if based on a single detection approach. In our case, using a set of already validated SNPs, we show that CLCBio was able to detect true SNPs at a rate that was ten times higher than the most stringent criteria implemented in GigaBayes.…”

An Axiom SNP genotyping array for Douglas-fir

“…We developed and tested an Axiom genotyping array designed to genotype 55,766 SNPs. First, we created a combined dataset of SNPs described by Howe et al [17] and Müller et al [32] (i.e., the OSU and UH datasets, Fig. 1).…”

“…This is an average of 17,555 SNPs across both populations, and Flow chart of steps used to select SNPs for the Axiom genotyping array. SNPs on the Axiom array were selected from the Oregon State University (OSU) dataset described by Howe et al [17] and the University of Hohenheim (UH) dataset described by Müller et al [32]. 'Discovered SNPs' are the starting SNPs and isotigs from each dataset.…”

“…The Affymetrix Recommendation variable is based on bins of pConvert. We excluded the 'not possible' category, and except for the SNPs that [17] or putative transcripts [32] used for SNP discovery. v0.5 is version 0.5 of the Douglas-fir reference genome.…”

“…v0.5 is version 0.5 of the Douglas-fir reference genome. UH SNPs were those detected by Müller et al [32], whereas OSU SNPs were those detected by Howe et al [17] b For the categorical variables, percentages and numbers of probesets are reported for each category and means are absent. All differences among categories were highly significant (P < 0.0001) using a likelihood ratio chi-square test c For the ranks and continuous variables, means are reported in bold, and percentages and numbers of probesets are reported for the upper (Q3) and lower (Q1) quartiles.…”