The contribution of mutation and selection to multivariate quantitative genetic variance in an outbred population of Drosophila serrata

Genetic variance is not equal for all multivariate combinations of traits. This inequality, in which some combinations of traits have abundant genetic variation while others have very little, biases the rate and direction of multivariate phenotypic evolution. However, we still understand little about what causes genetic variance to differ among trait combinations. Here, we investigate the relative roles of mutation and selection in determining the genetic variance of multivariate phenotypes. We accumulated mutations in an outbred population of Drosophila serrata and analyzed wing shape and size traits for over 35,000 flies to simultaneously estimate the additive genetic and additive mutational (co)variances. This experimental design allowed us to gain insight into the phenotypic effects of mutation as they arise and come under selection in naturally outbred populations. Multivariate phenotypes associated with more (less) genetic variance were also associated with more (less) mutational variance, suggesting that differences in mutational input contribute to differences in genetic variance. However, mutational correlations between traits were stronger than genetic correlations, and most mutational variance was associated with only one multivariate trait combination, while genetic variance was relatively more equal across multivariate traits. Therefore, selection is implicated in breaking down trait covariance and resulting in a different pattern of genetic variance among multivariate combinations of traits than that predicted by mutation and drift. Overall, while low mutational input might slow evolution of some multivariate phenotypes, stabilizing selection appears to reduce the strength of evolutionary bias introduced by pleiotropic mutation.

Associating Multivariate Traits with Genetic Variants Using Collapsing and Kernel Methods with Pedigree- or Population-Based Studies

In genetic association analysis, several relevant phenotypes or multivariate traits with different types of components are usually collected to study complex or multifactorial diseases. Over the past few years, jointly testing for association between multivariate traits and multiple genetic variants has become more popular because it can increase statistical power to identify causal genes in pedigree- or population-based studies. However, most of the existing methods mainly focus on testing genetic variants associated with multiple continuous phenotypes. In this investigation, we develop a framework for identifying the pleiotropic effects of genetic variants on multivariate traits by using collapsing and kernel methods with pedigree- or population-structured data. The proposed framework is applicable to the burden test, the kernel test, and the omnibus test for autosomes and the X chromosome. The proposed multivariate trait association methods can accommodate continuous phenotypes or binary phenotypes and further can adjust for covariates. Simulation studies show that the performance of our methods is satisfactory with respect to the empirical type I error rates and power rates in comparison with the existing methods.

Flexible multivariate linear mixed models for structured multiple traits

Many genetic studies collect structured multivariate traits that have rich information about the traits encoded in trait covariates, in addition to the genotype and covariate information on individuals. Examples of such data include gene-environment studies where the same genotype/clone is measured in multiple enviroments, and longitudinal studies where a measurement is taken at multiple time points. We present a flexible multivariate linear mixed model (fMulti-LMM) suitable for genetic analysis of structured multivariate traits. Our model can incorporate low- and high-dimensional trait covariates to test the genetic association across structured multiple traits while capturing the correlations due to individual-to-individual similarity measured by genome-wide markers and trait-to-trait similarity measured by trait covariates.

Sperm quality and quantity evolve through different selective processes in the Phasianidae

Sperm competition is often considered the primary selective force underlying the rapid and diversifying evolution of ejaculate traits. Yet, several recent studies have drawn attention to other forms of selection with the potential of exceeding the effects of sperm competition. Since ejaculates are complex, multivariate traits, it seems plausible that different ejaculate components vary in their responses to different selective pressures. Such information, however, is generally lacking as individual ejaculate traits tend to be studied in isolation. Here, we studied the macroevolutionary patterns of ejaculate volume, sperm number, sperm length and the proportion of viable normal sperm in response to varying levels of sperm competition, body size and the duration of female sperm storage in pheasants and allies (Phasianidae). Ejaculate volume, sperm number and sperm viability were all relatively higher in polygamous than in monogamous mating systems. However, whereas ejaculate volume additionally covaried with body size, sperm number instead increased with the female sperm-storage duration, in conjunction with a decrease in sperm length. Overall, our results revealed important details on how different forms of selection can jointly shape ejaculates as complex, composite traits.

Comparative analyses of phenotypic sequences using phylogenetic trees

Phenotypic sequences are a type of multivariate trait organized structurally, such as teeth distributed along the dental arch, or temporally, such as the stages of an ontogenetic series. However, unlike other multivariate traits, the elements of a phenotypic sequence are arranged along a vector, which allows for distinct evolutionary patterns between neighboring and distant positions. In fact, sequence traits share many characteristics with molecular sequences. We implement an approach to estimate rates of trait evolution that explicitly incorporates the sequence organization of traits. We apply models to study the temporal pattern evolution of cricket calling songs. We test whether songs show autocorrelation of rates (i.e., neighboring positions along a phenotypic sequence have correlated rates of evolution), or if they are best described by rate variation independent of sequence position. Our results show that models perform well when used with sequence phenotypes even under small sample sizes. We also show that silent regions of the songs evolve faster than chirp regions, which suggests that macroevolutionary changes are faster when associated with axes of variation less constrained by multiple sources of selection. Our approach is flexible and can be applied to any multivariate trait with units organized in a sequence-like structure.

Multi-character approach reveals a discordant pattern of phenotypic variation during ontogeny in Culex pipiens biotypes (Diptera: Culicidae)

Culex (Culex) pipiens s.l. (Diptera: Culicidae) comprises two distinct biotypes, pipiens (‘rural’) and molestus (‘urban’), both of which are thought to have differing capacities due to different host preferences. To better understand West Nile encephalitis epidemiology and improve risk assessment, local distinction between these forms is essential. This study assesses phenotypic variation at larval and adult stages of ‘urban’ and ‘rural’ biotypes of the species by complementary use of meristic, univariate and multivariate traits analyzed by traditional and geometric morphometrics. Third- and fourth-instar larvae from a broad area of the city of Novi Sad (Serbia) were collected and reared in the laboratory. After adult eclosion, the sex of each larva was recorded based on the sex of the corresponding adult. Examination of the association between variations of larval traits revealed contrasting variations regarding pecten spines vs. siphonal size and siphonal shape in the ‘rural’ biotype. Siphons of larvae collected in marshes and forest ecosystems outside urban areas were found to be the largest, but possessed the smallest number of pecten spines. In addition, statistically significant female-biased sexual dimorphism was observed in siphonal size, wing size and wing shape. Finally, we propose that an integrative approach is essential in delimitation of Cx. pipiens s.l. biotypes, since their differentiation was not possible based solely on larval and adult traits. Our findings shed light on the phenotypic plasticity important for population persistence in the changing environment of these medically important taxa.