Using RNAseq to characterize gene expression in lodgepole pine and interior spruce

S. Yeaman, K.A. Hodgins, K. Nurkowski, H. Suren, J.A. Holliday, L.H. Rieseberg, and S.N. Aitken

Understanding the genomic basis of how forest trees adapt to climate will be important to making management decisions to prepare for climate change. The AdapTree project aims to characterize the genomic basis of local adaptation to climate in Pinus contorta (lodgepole pine) and Picea glauca, Picea engelmanii and their hybrids (interior spruce), which are key species of economic importance in British Columbia and Alberta. Plasticity is one important component of how species cope with variable environments, and studying gene expression provides one approach to characterize which genes are most involved in responding to climate. Here, we explore how gene expression varies among 48 accessions of lodgepole pine and 41 accessions of interior spruce, each from a single population. Each individual in the experiment was grown under one of seven treatments in growth chambers, representing a range of moisture, temperature, and light regimes. We then used RNAseq methods to sequence RNA extracted from root, stem, and leaf tissue, yielding approximately 3.8 Gb of data per library. To assemble a reference transcriptome for each species, we combined one library from each of the seven treatments and ran the combined data on Trinity. We used RSEM and EdgeR to estimate expression levels for each gene in our transcriptome, and used WGCNA to group these genes into clusters based on similarity of expression profiles. We identified 8894 and 11618 differentially expressed genes in spruce and pine, respectively, at an FDR = 0.01. Our cluster analysis identified 13 groups, which correspond to genes that have similar patterns of expression across the different treatments. These characterizations of gene expression will provide a basis to test hypotheses about the importance of plasticity in adaptation. Subsequent work in the AdapTree project aims to characterize which genes are involved in local adaptation to climate. Using this data, it will be possible to test whether the most plastic genes also tend to be the most or least likely to be involved in local adaptation.