The Populus genus is one of the major plant model systems, but genomic resources have thus far primarily been available for poplar species, and primarily Populus trichocarpa (Torr. & Gray), which was the first tree with a whole-genome assembly. To further advance evolutionary and functional genomic analyses in Populus, we produced genome assemblies and population genetics resources of two aspen species, Populus tremula L. and Populus tremuloides Michx. The two aspen species have distributions spanning the Northern Hemisphere, where they are keystone species supporting a wide variety of dependent communities and produce a diverse array of secondary metabolites. Our analyses show that the two aspens share a similar genome structure and a highly conserved gene content with P. trichocarpa but display substantially higher levels of heterozygosity. Based on population resequencing data, we observed widespread positive and negative selection acting on both coding and noncoding regions. Furthermore, patterns of genetic diversity and molecular evolution in aspen are influenced by a number of features, such as expression level, coexpression network connectivity, and regulatory variation. To maximize the community utility of these resources, we have integrated all presented data within the PopGenIE web resource (PopGenIE.org).

With the rapid advancement of high throughput sequencing, large numbers of genetic markers can be readily and cheaply acquired, but most current software packages for genetic map construction cannot handle such dense input. Modern computer architectures and server farms represent untapped resources that can be used to enable higher marker densities to be processed in tractable time. Here we present a pipeline using a modified version of OneMap that parallelizes over bottleneck functions and achieves substantial speedups for producing a high density linkage map (N = 20,000). Using simulated data we show that the outcome is as accurate as the traditional pipeline. We further demonstrate that there is a direct relationship between the number of markers used and the level of deviation between true and estimated order, which in turn impacts the final size of a genetic map.

Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome‐wide association study (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA‐Seq data that we used to perform gene co‐expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population‐wide co‐expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small‐effect variations in gene expression. Genes associated with shape variation were peripheral within the population‐wide co‐expression network, were not highly connected within the leaf development co‐expression network, and exhibited signatures of relaxed selection. As such, our results are consistent with the omnigenic model.