Sequence capture as a tool to understand the genomic basis for adaptation in angiosperm and gymnosperm trees

TR Number



Journal Title

Journal ISSN

Volume Title


Virginia Tech


Forest trees represent a unique group of organisms combined with ecological and economic importance. Owing to their random mating system and widespread geographical distribution, they harbor abundance genetic variation both within and among populations. Despite their importance, research in forest trees has been underrepresented majorly due to their large and complex genome and scarce funding. However, recent climate change and other associated problems such as insect outbreaks, diseases and stress related damages have urged scientists to focus more on trees. Furthermore, the advent in high-throughput sequencing technologies have allowed trees to be sequenced and used as reference genome, which provided deeper understanding between genotype and environment. Whole genome sequencing is still not possible for organisms having large genomes including most tree species, and it is still not feasible economically for population genomic studies which require sequencing hundreds of samples. To get around this problem, genomic reduction is required. Sequence capture has been one of the genomic reduction techniques enabled studying the subset of the DNA of interest. In this paper, our primary goal is to outline challenges, provide guidance about the utility of sequence capture in trees, and to leverage such data in genome-wide association analyses to find the genetic variants that underlie complex, adaptive traits in spruce and pine, as well as poplar. Results of this research will facilitate bridging the genomic information gap between trees and other organisms. Moreover, it will provide better understanding how genetic variation governs phenotype in trees, which will facilitate both marker assisted selection for improved traits as well as provide guidance to determine forest management strategies for reforestation to mitigate the effects of climate change.



Forest trees, sequence capture, adaptation, next-generation sequencing