Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits

Abstract

A central challenge in evolutionary biology is to identify genes underlying ecologically important traits and describe the fitness consequences of naturally occurring variation at these loci. To address this goal, several novel approaches have been developed, including 'population genomics,' where a large number of molecular markers are scored in individuals from different environments with the goal of identifying markers showing unusual patterns of variation, potentially due to selection at linked sites. Such approaches are appealing because of (1) the increasing ease of generating large numbers of genetic markers, (2) the ability to scan the genome without measuring phenotypes and (3) the simplicity of sampling individuals without knowledge of their breeding history. Although such approaches are inherently applicable to non-model systems, to date these studies have been limited in their ability to uncover functionally relevant genes. By contrast, quantitative genetics has a rich history, and more recently, quantitative trait locus (QTL) mapping has had some success in identifying genes underlying ecologically relevant variation even in novel systems. QTL mapping, however, requires (1) genetic markers that specifically differentiate parental forms, (2) a focus on a particular measurable phenotype and (3) controlled breeding and maintenance of large numbers of progeny. Here we present current advances and suggest future directions that take advantage of population genomics and quantitative genetic approaches -in both model and non-model systems. Specifically, we discuss advantages and limitations of each method and argue that a combination of the two provides a powerful approach to uncovering the molecular mechanisms responsible for adaptation.

Non-random gene flow: an underappreciated force in evolution and ecology

“…A major challenge can be the identification of the relevant genetic variation to study. Most genes in the genome will probably exhibit random gene flow so non-random gene flow, similar to natural selection [62,63], might lead to chromosomal islands of high divergence among populations. Therefore, unless a researcher has strong candidate genes, studies of non-random dispersal might benefit from use of whole genomes or large panels of single nucleotide polymorphisms (SNPs) to identify these regions successfully.…”

“…Such divergent chromosomal regions are typically assumed to be subject to spatially divergent selection [62][63][64]. An alternative interpretation is that genetic markers exhibiting exceptionally high (or low) divergence are linked to genes causing non-random gene flow.…”

Population genomics of the eastern cottonwood (Populus deltoides)

“…In recent years, population genomics has been used to study tree populations, identifying genes under selection involved in local adaptation (Evans et al., 2014; Geraldes et al., 2014; Holliday et al., 2016; Zhou et al., 2014). The great advantage of population genomics studies over smaller‐scale population genetics studies is that the former allow identifying and correcting for genomewide demographic effects, increasing the power to detect locus‐specific effects (Stinchcombe & Hoekstra, 2008). Here, we present the first population genomics study assessing population structure, genetic diversity, LD, population differentiation, and adaptation in P. deltoides , a species lacking this information at a genomewide scale.…”

Admixture as the basis for genetic mapping

“…Population genomics typically refers to the use of many molecular markers with known genomic locations to identify regions under selection, by distinguishing the locus-specific effects of selection from the shared demographic history of the entire genome [18][19][20]. Population genomics can help identify fitness-related genetic variation even without a priori information on the actual phenotypes under selection [21], but it cannot replace experiments to identify and understand the traits targeted by selection [20].…”

“…Population genomics can help identify fitness-related genetic variation even without a priori information on the actual phenotypes under selection [21], but it cannot replace experiments to identify and understand the traits targeted by selection [20].…”