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Background R2R3-MYB transcription factors are regulatory genes that have been linked to key aspects of plant development and secondary metabolism. They have been implicated in the transcriptional control of phenylpropanoid, and flavonoid metabolic pathways in model plant systems. However, in trees, knowledge is still limited about the role of R2R3-MYBs in such processes. Microarray transcript profiles (9K custom cDNA array) obtained from comparison between wild type and transgenic spruces that constitutively overexpressed Pinus taeda MYB1, MYB8 [1], and MYB14 [2] identified putative targets in flavonoid and phenylpropanoid metabolism. Cross-comparison of these data sets identified 70 sequences that were common to the three transgenic backgrounds: interestingly, 66 of these 70 sequences were co-expressed between PtMYB1 and PtMYB8 transgenics but produced opposite profiles with PtMYB14 transgenics. Pairwise comparisons between these transgenic data sets identified 121 additional sequences showing opposite profiles. Predicted annotations and KEGG classification showed that many of the sequences were linked to the metabolism of amino acids and carbohydrates as well as flavonoids, phenylpropanoids, and terpenoids.It was hypothesized that MYB1/MYB8 and MYB14 may be part of competing transcriptional networks for the regulation of primary metabolism and secondary metabolism. The opposite transcriptional responses might also support structural or defensive oriented response, respectively. Material and methods A qPCR based experimental approach was used to test these hypotheses by evaluating transcript profile of the negatively co-expressed sequences together with MYB1, MYB8 and MYB14. Transcript levels were monitored during a diurnal cycle in three year-old wild type spruces, based on the fact that some genes associated to phenylpropanoid metabolism [3] and stress [4] were reported to follow a diurnal transcript variation. Our analysis also included a set of 10 additional MYBs putatively linked to secondary cell wall deposition [1] and stress oriented response [2]. A Spearman correlation rank test was used to estimate significant correlation (adjusted P val ≤ 0.01, FDR 1%) between MYB transcript profiles and selected co-expressed sequences. A functional assay system developed in embryogenic spruce cells was used to screen for possible interactions between transcription factors and promoters of putative target genes.

Background Connecting phenotype with genotype is the basis for developing forest genetic applications such as marker assisted selection (MAS). Quantitative Trait Locus (QTL) mapping and genetic association mapping (or linkage disequilibrium (LD) are two major approaches to find genes that control phenotypes of interest in forest trees. Quantitative trait loci (QTL) and association mapping experiments in white spruce (Picea glauca [Moench] Voss) aimed to identify genes linked to or associated with growth, adaptation, and wood property traits. Gene mapping in conifer trees presents us with specific challenges, including very large genome sizes, low level of linkage disequilibrium, and large effective size in breeding populations. Therefore, association mapping experiments have relied on testing candidate gene targets rather than genome-wide association scans. We have explored different approaches to utilize gene expression and SNP outlier data to identify candidate genes, to help to explain the findings of gene mapping experiments and provide a broader understanding of observed phenotypic variations. Results Growth and phenology

Background Modern forest management relies on extensive breeding and reforestation programs to sustain forest productivity and conservation of natural forests. Plantation forestry, with its increased productivity and improved wood quality, is likely to become an important source of wood products in the future. Vegetative propagation of superior coniferous forest trees through tissue culture has the potential to deliver a stable supply of superior seedlings for forest plantation. To clone adult (mature) conifer trees by means of tissue culture has been a cherished goal for the last several decades. The benefits derived from improving the genetic make-up of planting stock would be significant if such clonal propagation could be achieved at a high efficiency and without growth abnormalities of regenerated plants. Although, somatic embryogenesis (SE) technology has worked well for many conifer species using zygotic embryos as starting material, attempts to achieve the same in adult conifers have failed. The basis of this failure is not exactly understood.

Background Genetic variation can cause changes in gene expression (mRNA abundance) among individuals. This so-called heritable variation in gene expression is affected by genetic variants that are co-segregating with the gene locus (local/cis effects) and/or segregating independently from it (distant/trans effects). Genetic variation in gene expression can be measured to estimate the extant of variation in gene expression within a population, and to determine to what degree expression alleles of different genes are connected within regulatory networks. Furthermore, determining whether variation in the expression of a gene is linked to local or distant effects allows us to make inferences about how heritable variation may change depending on gene function, the number of interacting partners, genetic architecture and evolutionary history [1,2]. Detecting heritable variation in gene expression can be a challenging task in diploid organisms, mainly because of tissue-specificity and dominance effects of allelic expression. For example, up to 70% of gene expression alleles in Drosophila may be masked by dominance [3]. We developed an experimental system to overcome these obstacles by utilizing the conifer seed’s maternally derived haploid tissue, the megagametophyte. Analyzing a set of sibling megagametophytes allows us to first, measure separately the expression each of the two alleles in the maternal genome in the absence of dominance and second, identify genes whose expression levels are co-segregating. In addition, the megagametophyte allows us to categorize the underlying genetic variants into local or distant with a simple co-segregation assay.