Mapping quantitative trait loci onto a phylogenetic tree

Integrating natural history collections and comparative genomics to study the genetic architecture of convergent evolution

Evolutionary convergence has been long considered primary evidence of adaptation driven by natural selection and provides opportunities to explore evolutionary repeatability and predictability. In recent years, there has been increased interest in exploring the genetic mechanisms underlying convergent evolution, in part, owing to the advent of genomic techniques. However, the current 'genomics gold rush' in studies of convergence has overshadowed the reality that most trait classifications are quite broadly defined, resulting in incomplete or potentially biased interpretations of results. Genomic studies of convergence would be greatly improved by integrating deep 'vertical', natural history knowledge with 'horizontal' knowledge focusing on the breadth of taxonomic diversity. Natural history collections have and continue to be best positioned for increasing our comprehensive understanding of phenotypic diversity, with modern practices of digitization and databasing of morphological traits providing exciting improvements in our ability to evaluate the degree of morphological convergence. Combining more detailed phenotypic data with the well-established field of genomics will enable scientists to make progress on an important goal in biology: to understand the degree to which genetic or molecular convergence is associated with phenotypic convergence. Although the fields of comparative biology or comparative genomics alone can separately reveal important insights into convergent evolution, here we suggest that the synergistic and complementary roles of natural history collection-derived phenomic data and comparative genomics methods can be particularly powerful in together elucidating the genomic basis of convergent evolution among higher taxa. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

The Pace of Hybrid Incompatibility Evolution in House Mice

Hybrids between species are often sterile or inviable. This form of reproductive isolation is thought to evolve via the accumulation of mutations that interact to reduce fitness when combined in hybrids. Mathematical formulations of this "Dobzhansky-Muller model" predict an accelerating buildup of hybrid incompatibilities with divergence time (the "snowball effect"). Although the Dobzhansky-Muller model is widely accepted, the snowball effect has only been tested in two species groups. We evaluated evidence for the snowball effect in the evolution of hybrid male sterility among subspecies of house mice, a recently diverged group that shows partial reproductive isolation. We compared the history of subspecies divergence with patterns of quantitative trait loci (QTL) detected in F2 intercrosses between two pairs of subspecies (Mus musculus domesticus with M. m. musculus and M. m. domesticus with M. m. castaneus). We used a recently developed phylogenetic comparative method to statistically measure the fit of these data to the snowball prediction. To apply this method, QTL were partitioned as either shared or unshared in the two crosses. A heuristic partitioning based on the overlap of QTL confidence intervals produced unambiguous support for the snowball effect. An alternative approach combining data among crosses favored the snowball effect for the autosomes, but a linear accumulation of incompatibilities for the X chromosome. Reasoning that the X chromosome analyses are complicated by low mapping resolution, we conclude that hybrid male sterility loci have snowballed in house mice. Our study illustrates the power of comparative genetic mapping for understanding mechanisms of speciation.

A model framework for identifying genes that guide the evolution of heterochrony

Heterochrony, the phylogenic change in the time of developmental events or rate of development, has been thought to play an important role in producing phenotypic novelty during evolution. Increasing evidence suggests that specific genes are implicated in heterochrony, guiding the process of developmental divergence, but no quantitative models have been instrumented to map such heterochrony genes. Here, we present a computational framework for genetic mapping by which to characterize and locate quantitative trait loci (QTLs) that govern heterochrony described by four parameters, the timing of the inflection point, the timing of maximum acceleration of growth, the timing of maximum deceleration of growth, and the length of linear growth. The framework was developed from functional mapping, a dynamic model derived to map QTLs for the overall process and pattern of development. By integrating an optimality algorithm, the framework allows the so-called heterochrony QTLs (hQTLs) to be tested and quantified. Specific pipelines are given for testing how hQTLs control the onset and offset of developmental events, the rate of development, and duration of a particular developmental stage. Computer simulation was performed to examine the statistical properties of the model and demonstrate its utility to characterize the effect of hQTLs on population diversification due to heterochrony. By analyzing a genetic mapping data in rice, the framework identified an hQTL that controls the timing of maximum growth rate and duration of linear growth stage in plant height growth. The framework provides a tool to study how genetic variation translates into phenotypic innovation, leading a lineage to evolve, through heterochrony.

Challenges and prospects in genome-wide quantitative trait loci mapping of standing genetic variation in natural populations

A considerable challenge in evolutionary genetics is to understand the genetic mechanisms that facilitate or impede evolutionary adaptation in natural populations. For this, we must understand the genetic loci contributing to trait variation and the selective forces acting on them. The decreased costs and increased feasibility of obtaining genotypic data on a large number of individuals have greatly facilitated gene mapping in natural populations, particularly because organisms whose genetics have been historically difficult to study are now within reach. Here we review the methods available to evolutionary ecologists interested in dissecting the genetic basis of traits in natural populations. Our focus lies on standing genetic variation in outbred populations. We present an overview of the current state of research in the field, covering studies on both plants and animals. We also draw attention to particular challenges associated with the discovery of quantitative trait loci and discuss parallels to studies on crops, livestock, and humans. Finally, we point to some likely future developments in genetic mapping studies.

Heritability and coefficient of genetic variation analyses of phenotypic traits provide strong basis for high-resolution QTL mapping in the Collaborative Cross mouse genetic reference population

Most biological traits of human importance are complex in nature; their manifestation controlled by the cumulative effect of many genetic factors interacting with one another and with the individual's life history. Because of this, mouse genetic reference populations (GRPs) consisting of collections of inbred lines or recombinant inbred lines (RIL) derived from crosses between inbred lines are of particular value in analysis of complex traits, since massive amounts of data can be accumulated on the individual lines. However, existing mouse GRPs are derived from inbred lines that share a common history, resulting in limited genetic diversity, and reduced mapping precision due to long-range gametic disequilibrium. To overcome these limitations, the Collaborative Cross (CC) a genetically highly diverse collection of mouse RIL was established. The CC, now in advanced stages of development, will eventually consist of about 500 RIL derived from reciprocal crosses of eight divergent founder strains of mice, including three wild subspecies. Previous studies have shown that the CC indeed contains enormous diversity at the DNA level, that founder haplotypes are inherited in expected frequency, and that long-range gametic disequilibrium is not present. We here present data, primarily from our own laboratory, documenting extensive genetic variation among CC lines as expressed in broad-sense heritability (H(2)) and by the well-known "coefficient of genetic variation," demonstrating the ability of the CC resource to provide unprecedented mapping precision leading to identification of strong candidate genes.

The evolution of hybrid incompatibilities along a phylogeny

The Dobzhansky-Muller model of speciation posits that defects in hybrids between species are the result of negative epistatic interactions between alleles that arose in independent genetic backgrounds. Tests of one important prediction from this model, that incompatibilities "snowball," have relied on comparisons of the number of incompatibilities between closely related pairs of species separated by different divergence times. How incompatibilities accumulate along phylogenies, however, remains poorly understood. We extend the Dobzhansky-Muller model to multispecies clades to describe the mathematical relationship between tree topology and the number of shared incompatibilities among related pairs of species. We use these results to develop a statistical test that distinguishes between the snowball and alternative incompatibility accumulation models, including nonepistatic and multilocus incompatibility models, in a phylogenetic context. We further demonstrate that patterns of incompatibility sharing across species pairs can be used to estimate the relative frequencies of different types of incompatibilities, including derived-derived versus derived-ancestral incompatibilities. Our results and statistical methods should motivate comparative genetic mapping of hybrid incompatibilities to evaluate competing models of speciation.