bioRxiv preprint doi: https://doi.org/10.1101/203307; this version posted December 23, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 The genomics of local adaptation in trees: 2 Are we out of the woods yet? † 3 Brandon M. Lind*, Mitra Menon*, Constance E. Bolte* , † † 4 Trevor M. Faske , and Andrew J. Eckert * 5 Integrative Life Sciences, Virginia Commonwealth University, Richmond, Virginia 23284 USA † 6 Department of Biology, Virginia Commonwealth University, Richmond, Virginia 23284 USA 7 Dec 22, 2017 8 Running Title: Are we out of the woods yet? 9 Keywords: 10 trees, GWAS, genetic architecture, polygenic local adaptation bioRxiv preprint doi: https://doi.org/10.1101/203307; this version posted December 23, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Lind et al: Are we out of the woods yet? 11 Abstract 12 There is substantial interest in uncovering the genetic basis of the traits underlying adaptive 13 responses in tree species, as this information will ultimately aid conservation and industrial 14 endeavors across populations, generations, and environments. Fundamentally, the 15 characterization of such genetic bases is within the context of a genetic architecture, which 16 describes the mutlidimensional relationship between genotype and phenotype through the 17 identification of causative variants, their relative location within a genome, expression, 18 pleiotropic effect, environmental influence, and degree of dominance, epistasis, and additivity. 19 Here, we review theory related to polygenic local adaptation and contextualize these 20 expectations with methods often used to uncover the genetic basis of traits important to tree 21 conservation and industry. A broad literature survey suggests that most tree traits generally 22 exhibit considerable heritability, that underlying quantitative genetic variation (�"#) is structured 23 more so across populations than neutral expectations (�"#) in 69% of comparisons across the 24 literature, and that single-locus associations often exhibit small estimated per-locus effects. 25 Together, these results suggest differential selection across populations often acts on tree 26 phenotypes underlain by polygenic architectures consisting of numerous small to moderate 27 effect loci. Using this synthesis, we highlight the limits of using solely single-locus approaches to 28 describe underlying genetic architectures and close by addressing hurdles and promising 29 alternatives towards such goals, remark upon the current state of tree genomics, and identify 30 future directions for this field. Importantly, we argue, the success of future endeavors should not 31 be predicated on the shortcomings of past studies and will instead be dependent upon the 32 application of theory to empiricism, standardized reporting, centralized open-access databases, 33 and continual input and review of the community’s research. ii bioRxiv preprint doi: https://doi.org/10.1101/203307; this version posted December 23, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Lind et al: Are we out of the woods yet? 34 Table Of Contents 35 The genomics of local adaptation in trees: Are we out of the woods yet? ......................................... i 36 Keywords: ......................................................................................................................................... i 37 Abstract ............................................................................................................................................... ii 38 Introduction .........................................................................................................................................1 39 Identifying heritable phenotypic variation .......................................................................................4 40 Expectations for the loci underlying quantitative traits ................................................................10 41 Gene action .....................................................................................................................................12 42 Negative selection ...........................................................................................................................17 43 Positive selection ............................................................................................................................19 44 Gene flow ........................................................................................................................................22 45 Summary .........................................................................................................................................24 46 The genomics of local adaptation in trees .......................................................................................25 47 Common approaches used to identify adaptive loci .......................................................................25 48 Current progress in trees .................................................................................................................26 49 Are we out of the woods yet? .........................................................................................................27 50 The Path Forward .............................................................................................................................30 51 Stepping off the path – what’s in our pack? ...................................................................................30 52 At the trail junction – where to next? .............................................................................................34 53 Concluding Remarks ........................................................................................................................43 54 Acknowledgements ............................................................................................................................43 55 References ..........................................................................................................................................45 56 Author Contributions .......................................................................................................................74 57 Figures ................................................................................................................................................75 58 Figure 1 ...........................................................................................................................................75 59 Figure 2 ...........................................................................................................................................76 60 Figure 3A ........................................................................................................................................77 61 Figure 3B ........................................................................................................................................78 62 Tables .................................................................................................................................................79 63 Table 1. Where to next? The Path Forward identifies meaningful ways in which we can progress 64 our understanding of the architecture underlying complex traits in trees. Here we outline some 65 questions that can be used to guide future inquiry as the number of markers and sequence length 66 increase, and annotation becomes more precise and specific to tree biology. ................................79 67 Boxes ...................................................................................................................................................80 68 Box 1: A step in the right direction: Synergism between GWAS and Genomic Selection ............80 69 SUPPLEMENTAL INFORMATION .................................................................................................................81 70 Supplemental Figures .......................................................................................................................82 71 Figure S1 .........................................................................................................................................82 72 Figure S2 .........................................................................................................................................83 73 Figure S3 .........................................................................................................................................84 74 Figure S4 .........................................................................................................................................85 75 Figure S5 .........................................................................................................................................86 76 Supplemental Tables .........................................................................................................................87