35th NPS abstract book

P5
An ancient trans-kingdom horizontal transfer of Penelope-like retroelements
from insects to conifers
X. LIN 1 , N. FARIDI 1, 2 , C. CASOLA 1
1 Department of Ecosystem Science and Management, Texas A&M University, College Station, TX
77843, USA; 2 USDA Forest Service Southern Research Station, Saucier, MS 77843, USA
Penelope-like elements, or PLEs, represent a class of retroelements represented by two main types:
EN(+)PLEs, which encode the unique combination of a reverse transcriptase (RT) domain and a GIY-
YIG endonuclease (EN) domain; and EN(-)PLEs, encoding only a RT domain. While members of the
second type occur in a variety of eukaryotes, EN(+)PLEs have thus far been detected only in animal
genomes. In this work, we have investigated the evolutionary history of conifers EN(+)PLEs, which
we have named Dryads, recently discovered in loblolly pine. In phylogenies of PLE sequences,
Dryads form a monophyletic group placed within a major animal EN(+)PLE lineage. Furthermore,
Dryads are closely related to a clade of EN(+)PLEs primarily found in insects. Bioinformatics surveys
revealed no EN(+)PLEs in 625 fully sequenced non-metazoan and non-conifer genomes from twelve
major eukaryotic lineages. Additionally, PCR assays indicate that Dryads are absent in non-conifer
gymnosperms, including Ginkgo biloba and several cycads and gnetales. These findings indicate that
Dryads emerged following an ancient horizontal transfer of Penelope-like elements from an insect
group to a common ancestor of conifers in the late Paleozoic, and suggest that retroelements
horizontal transfers might have played an important role in the expansion of the very large conifers
genomes.
P6
Detecting local selection in spatially heterogeneous environments: clues from
simulations and empirical data from a widespread boreal tree, Populus
balsamifera
V. E. CHHATRE 1 , M. C. FITZPATRICK 2 and S. R. KELLER 1
1 Dept. of Plant Biology, University of Vermont, Burlington, VT 05405, USA; 2 Appalachian Laboratory,
University of Maryland Center for Environmental Science, Frostburg, MD 21532, USA
Most widely distributed tree species inhabiting spatially heterogeneous environments experience
varying strengths and types of ecological selection, often giving rise to strong local adaptation.
Frequentist and Bayesian approaches to detect genomic responses to selection along environmental
gradients typically assume linear responses, even though empirical allele frequencies often vary nonlinearly
along environmental gradients. Here, we compare the power of several existing methods in
SNP-environment association analysis (BayeScEnv, Bayenv2 and LFMM), as well as two more recent
biodiversity modelling techniques – Generalized Dissimilarity Modeling (GDM) and Gradient Forests
(GF), at detecting non-linear selection in population genomic datasets. We tested these methods
using two approaches. First, we used spatially explicit simulations of 1000 loci in 30 populations
arrayed in a linear stepping stone model with varying amounts of migration. Selection was applied to
one locus in the form of differential mortality increasing either linearly or non-linearly along the
gradient, and both false positive and false negative rates were calculated across replicate
simulations of each scenario. Second, we compared the performance of the different methods on an
empirical SNP data set from the widely distributed tree Populus balsamifera, consisting of ~1100
trees from 90 populations genotyped at 297 candidate SNPs from the flowering time network
controlling adaptive phenology.
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