Estimating scale-specific and localized spatial patterns in allele frequency.

Characterizing spatial patterns in allele frequencies is fundamental to evolutionary biology because these patterns contain evidence of underlying processes. However, the spatial scales at which gene flow, changing selection, and drift act are often unknown. Many of these processes can operate inconsistently across space, causing nonstationary patterns. We present a wavelet approach to characterize spatial pattern in allele frequency that helps solve these problems. We show how our approach can characterize spatial patterns in relatedness at multiple spatial scales, i.e. a multilocus wavelet genetic dissimilarity. We also develop wavelet tests of spatial differentiation in allele frequency and quantitative trait loci (QTL). With simulation, we illustrate these methods under different scenarios. We also apply our approach to natural populations of Arabidopsis thaliana to characterize population structure and identify locally adapted loci across scales. We find, for example, that Arabidopsis flowering time QTL show significantly elevated genetic differentiation at 300-1,300 km scales. Wavelet transforms of allele frequencies offer a flexible way to reveal geographic patterns and underlying evolutionary processes.

Predicting gene expression responses to environment in Arabidopsis thaliana using natural variation in DNA sequence.

The evolution of gene expression responses are a critical component of adaptation to variable environments. Predicting how DNA sequence influences expression is challenging because the genotype to phenotype map is not well resolved for cis regulatory elements, transcription factor binding, regulatory interactions, and epigenetic features, not to mention how these factors respond to environment. We tested if flexible machine learning models could learn some of the underlying cis-regulatory genotype to phenotype map. We tested this approach using cold-responsive transcriptome profiles in 5 diverse Arabidopsis thaliana accessions. We first tested for evidence that cis regulation plays a role in environmental response, finding 14 and 15 motifs that were significantly enriched within the up- and down-stream regions of cold-responsive differentially regulated genes (DEGs). We next applied convolutional neural networks (CNNs), which learn de novo cis-regulatory motifs in DNA sequences to predict expression response to environment. We found that CNNs predicted differential expression with moderate accuracy, with evidence that predictions were hindered by biological complexity of regulation and the large potential regulatory code. Overall, DEGs between specific environments can be predicted based on variation in cis-regulatory sequences, although more information needs to be incorporated and better models may be required.

Long-Term Balancing Selection and the Genetic Load Linked to the Self-Incompatibility Locus in Arabidopsis halleri and A. lyrata.

Balancing selection is a form of natural selection maintaining diversity at the sites it targets and at linked nucleotide sites. Due to selection favoring heterozygosity, it has the potential to facilitate the accumulation of a "sheltered" load of tightly linked recessive deleterious mutations. However, precisely evaluating the extent of these effects has remained challenging. Taking advantage of plant self-incompatibility as one of the best-understood examples of long-term balancing selection, we provide a highly resolved picture of the genomic extent of balancing selection on the sheltered genetic load. We used targeted genome resequencing to reveal polymorphism of the genomic region flanking the self-incompatibility locus in three sample sets in each of the two closely related plant species Arabidopsis halleri and Arabidopsis lyrata, and used 100 control regions from throughout the genome to factor out differences in demographic histories and/or sample structure. Nucleotide polymorphism increased strongly around the S-locus in all sample sets, but only over a limited genomic region, as it became indistinguishable from the genomic background beyond the first 25-30 kb. Genes in this chromosomal interval exhibited no excess of mutations at 0-fold degenerated sites relative to putatively neutral sites, hence revealing no detectable weakening of the efficacy of purifying selection even for these most tightly linked genes. Overall, our results are consistent with the predictions of a narrow genomic influence of linkage to the S-locus and clarify how natural selection in one genomic region affects the evolution of the adjacent genomic regions.

Maintenance of Adaptive Dynamics and No Detectable Load in a Range-Edge Outcrossing Plant Population.

During range expansion, edge populations are expected to face increased genetic drift, which in turn can alter and potentially compromise adaptive dynamics, preventing the removal of deleterious mutations and slowing down adaptation. Here, we contrast populations of the European subspecies Arabidopsis lyrata ssp. petraea, which expanded its Northern range after the last glaciation. We document a sharp decline in effective population size in the range-edge population and observe that nonsynonymous variants segregate at higher frequencies. We detect a 4.9% excess of derived nonsynonymous variants per individual in the range-edge population, suggesting an increase of the genomic burden of deleterious mutations. Inference of the fitness effects of mutations and modeling of allele frequencies under the explicit demographic history of each population predicts a depletion of rare deleterious variants in the range-edge population, but an enrichment for fixed ones, consistent with the bottleneck effect. However, the demographic history of the range-edge population predicts a small net decrease in per-individual fitness. Consistent with this prediction, the range-edge population is not impaired in its growth and survival measured in a common garden experiment. We further observe that the allelic diversity at the self-incompatibility locus, which ensures strict outcrossing and evolves under negative frequency-dependent selection, has remained unchanged. Genomic footprints indicative of selective sweeps are broader in the Northern population but not less frequent. We conclude that the outcrossing species A. lyrata ssp. petraea shows a strong resilience to the effect of range expansion.

Linking genes with ecological strategies in Arabidopsis thaliana.

Arabidopsis thaliana is the most prominent model system in plant molecular biology and genetics. Although its ecology was initially neglected, collections of various genotypes revealed a complex population structure, with high levels of genetic diversity and substantial levels of phenotypic variation. This helped identify the genes and gene pathways mediating phenotypic change. Population genetics studies further demonstrated that this variation generally contributes to local adaptation. Here, we review evidence showing that traits affecting plant life history, growth rate, and stress reactions are not only locally adapted, they also often co-vary. Co-variation between these traits indicates that they evolve as trait syndromes, and reveals the ecological diversification that took place within A. thaliana. We argue that examining traits and the gene that control them within the context of global summary schemes that describe major ecological strategies will contribute to resolve important questions in both molecular biology and ecology.