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Predicting adaptive phenotypes from multilocus genotypes in Sitka spruce (Picea sitchensis) using random forest.

ABSTRACT: Climate is the primary driver of the distribution of tree species worldwide, and the potential for adaptive evolution will be an important factor determining the response of forests to anthropogenic climate change. Although association mapping has the potential to improve our understanding of the genomic underpinnings of climatically relevant traits, the utility of adaptive polymorphisms uncovered by such studies would be greatly enhanced by the development of integrated models that account for the phenotypic effects of multiple single-nucleotide polymorphisms (SNPs) and their interactions simultaneously. We previously reported the results of association mapping in the widespread conifer Sitka spruce (Picea sitchensis). In the current study we used the recursive partitioning algorithm 'Random Forest' to identify optimized combinations of SNPs to predict adaptive phenotypes. After adjusting for population structure, we were able to explain 37% and 30% of the phenotypic variation, respectively, in two locally adaptive traits--autumn budset timing and cold hardiness. For each trait, the leading five SNPs captured much of the phenotypic variation. To determine the role of epistasis in shaping these phenotypes, we also used a novel approach to quantify the strength and direction of pairwise interactions between SNPs and found such interactions to be common. Our results demonstrate the power of Random Forest to identify subsets of markers that are most important to climatic adaptation, and suggest that interactions among these loci may be widespread.

SUBMITTER: Holliday JA

PROVIDER: S-EPMC3429923 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMembers of the pine family (Pinaceae), especially species of spruce (Picea spp.) and pine (Pinus spp.), dominate many of the world's temperate and boreal forests. These conifer forests are of critical importance for global ecosystem stability and biodiversity. They also provide the majority of the world's wood and fiber supply and serve as a renewable resource for other industrial biomaterials. In contrast to angiosperms, functional and comparative genomics research on conifers, or other gymnosperms, is limited by the lack of a relevant reference genome sequence. Sequence-finished full-length (FL)cDNAs and large collections of expressed sequence tags (ESTs) are essential for gene discovery, functional genomics, and for future efforts of conifer genome annotation.ResultsAs part of a conifer genomics program to characterize defense against insects and adaptation to local environments, and to discover genes for the production of biomaterials, we developed 20 standard, normalized or full-length enriched cDNA libraries from Sitka spruce (P. sitchensis), white spruce (P. glauca), and interior spruce (P. glauca-engelmannii complex). We sequenced and analyzed 206,875 3'- or 5'-end ESTs from these libraries, and developed a resource of 6,464 high-quality sequence-finished FLcDNAs from Sitka spruce. Clustering and assembly of 147,146 3'-end ESTs resulted in 19,941 contigs and 26,804 singletons, representing 46,745 putative unique transcripts (PUTs). The 6,464 FLcDNAs were all obtained from a single Sitka spruce genotype and represent 5,718 PUTs.ConclusionThis paper provides detailed annotation and quality assessment of a large EST and FLcDNA resource for spruce. The 6,464 Sitka spruce FLcDNAs represent the third largest sequence-verified FLcDNA resource for any plant species, behind only rice (Oryza sativa) and Arabidopsis (Arabidopsis thaliana), and the only substantial FLcDNA resource for a gymnosperm. Our emphasis on capturing FLcDNAs and ESTs from cDNA libraries representing herbivore-, wound- or elicitor-treated induced spruce tissues, along with incorporating normalization to capture rare transcripts, resulted in a rich resource for functional genomics and proteomics studies. Sequence comparisons against five plant genomes and the non-redundant GenBank protein database revealed that a substantial number of spruce transcripts have no obvious similarity to known angiosperm gene sequences. Opportunities for future applications of the sequence and clone resources for comparative and functional genomics are discussed.

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Predicting adaptive phenotypes from multilocus genotypes in Sitka spruce (Picea sitchensis) using random forest.

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