MODULARITY, NOISE, AND NATURAL SELECTION

Most biological systems are formed by component parts that are to some degree interrelated. Groups of parts that are more associated among themselves and are relatively autonomous from others are called modules. One of the consequences of modularity is that biological systems usually present an unequal distribution of the genetic variation among traits. Estimating the covariance matrix that describes these systems is a difficult problem due to a number of factors such as poor sample sizes and measurement errors. We show that this problem will be exacerbated whenever matrix inversion is required, as in directional selection reconstruction analysis. We explore the consequences of varying degrees of modularity and signal-to-noise ratio on selection reconstruction. We then present and test the efficiency of available methods for controlling noise in matrix estimates. In our simulations, controlling matrices for noise vastly improves the reconstruction of selection gradients. We also perform an analysis of selection gradients reconstruction over a New World Monkeys skull database to illustrate the impact of noise on such analyses. Noise-controlled estimates render far more plausible interpretations that are in full agreement with previous results.

When size makes a difference: allometry, life-history and morphological evolution of capuchins (Cebus) and squirrels (Saimiri) monkeys (Cebinae, Platyrrhini)

Abstract Background How are morphological evolution and developmental changes related? This rather old and intriguing question had a substantial boost after the 70s within the framework of heterochrony (changes in rates or timing of development) and nowadays has the potential to make another major leap forward through the combination of approaches: molecular biology, developmental experimentation, comparative systematic studies, geometric morphometrics and quantitative genetics. Here I take an integrated approach combining life-history comparative analyses, classical and geometric morphometrics applied to ontogenetic series to understand changes in size and shape which happen during the evolution of two New World Monkeys (NWM) sister genera. Results Cebus and Saimiri share the same basic allometric patterns in skull traits, a result robust to sexual and ontogenetic variation. If adults of both genera are compared in the same scale (discounting size differences) most differences are small and not statistically significant. These results are consistent using both approaches, classical and geometric Morphometrics. Cebus is a genus characterized by a number of peramorphic traits (adult-like) while Saimiri is a genus with paedomorphic (child like) traits. Yet, the whole clade Cebinae is characterized by a unique combination of very high pre-natal growth rates and relatively slow post-natal growth rates when compared to the rest of the NWM. Morphologically Cebinae can be considered paedomorphic in relation to the other NWM. Geometric morphometrics allows the precise separation of absolute size, shape variation associated with size (allometry), and shape variation non-associated with size. Interestingly, and despite the fact that they were extracted as independent factors (principal components), evolutionary allometry (those differences in allometric shape associated with intergeneric differences) and ontogenetic allometry (differences in allometric shape associated with ontogenetic variation within genus) are correlated within these two genera. Furthermore, morphological differences produced along these two axes are quite similar. Cebus and Saimiri are aligned along the same evolutionary allometry and have parallel ontogenetic allometry trajectories. Conclusion The evolution of these two Platyrrhini monkeys is basically due to a size differentiation (and consequently to shape changes associated with size). Many life-history changes are correlated or may be the causal agents in such evolution, such as delayed on-set of reproduction in Cebus and larger neonates in Saimiri.

Repeatability and heritability of behavioural types in a social cichlid

Aim. The quantitative genetics underlying correlated behavioural traits (‘‘animal personality’’) have hitherto been studied mainly in domesticated animals. Here we report the repeatability ( ) and heritability ( ) of behavioural types in the highly social cichlid fish Neolamprologus pulcher. Methods. We tested 1779 individuals repeatedly and calculated the of behavioural types by variance components estimation (GLMM REML), using 1327 offspring from 162 broods from 74 pairs. Results. Repeatability of behavioural types was significant and considerable (0.546), but declined from 0.83 between tests conducted on the same day, to 0.19 on tests conducted up to 1201 days apart. All estimates were significant but low (e.g., pair identity SE). Additionally, we found significant variation between broods nested within the parent(s), but these were not related to several environmental factors tested. Conclusions. We conclude that despite a considerable , in this cichlid species is low, and variability in behavioural type appears to be strongly affected by other (non)genetic effects.

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Variance and covariance of actual relationship between relatives at one locus.

The relationship between pairs of individuals is an important topic in many areas of population and quantitative genetics. It is usually measured as the proportion of thegenome identical by descent shared by the pair and it can be inferred from pedigree information. But there is a variance in actual relationships as a consequence of Mendelian sampling, whose general formula has not been developed. The goal of this work is to develop this general formula for the one-locus situation,. We provide simple expressions for the variances and covariances of all actual relationships in an arbitrary complex pedigree. The proposed method relies on the use of the nine identity coefficients and the generalized relationship coefficients; formulas have been checked by computer simulation. Finally two examples for a short pedigree of dogs and a long pedigree of sheep are given.

Integração morfológica e modularidade em crânios das espécies do grupo Rhinella granulosa

Os conceitos e métodos provindos das teorias de integração morfológica e de genética quantitativa formam o arcabouço teórico para o estudo da evolução de estruturas complexas, compostas de múltiplos caracteres que interagem entre si. Nesse trabalho, utilizamos o crânio como modelo de estrutura complexa e estudamos sua diversificação nas espécies de sapo do grupo Rhinella granulosa. As perguntas do trabalho foram: (1) A organização da (co)variação é similar entre as espécies?; (2) A organização da (co)variação é modular nas espécies, conforme expectativas baseadas em desenvolvimento ou função?; (3) Fatores externos, como filogenia e clima, estruturam a similaridade no padrão de covariação entre as espécies?; (4) A diversificação da morfologia média do crânio se deu por deriva ou seleção natural?; (5) A divergência na morfologia média do crânio está associada à variação climática entre as espécies?; e finalmente (6) Restrições evolutivas atuaram na divergência entre as espécies? Os espécimes foram escaneados e validamos o uso de imagens 3D para a mensuração de 21 distâncias lineares. Os crânios das espécies foram representados como matrizes fenotípicas (P) de covariância e de correlação entre as distâncias. A similaridade entre as P das espécies é alta. As P de todas as espécies se conformam a um padrão modular compatível com interações funcionais entre ossos. As diferenças entre as P concentram-se no rostro e são associadas a diferenças no clima entre as espécies. Detectamos sinal de seleção natural nos nós mais basais da filogenia e variação local no crânio está associada à variação na sazonalidade da chuva entre as espécies. Restrições evolutivas atuaram na diversificação do crânio das espécies, defletindo as respostas evolutivas para tamanho. Concluímos que tanto seleção estabilizadora e direcional, conectadas à variação climática, quanto restrições evolutivas atuaram na diversificação do crânio das espécies

Effects of Interspecific Gene Flow on the Phenotypic Variance-Covariance Matrix in Lake Victoria Cichlids

Quantitative genetics theory predicts adaptive evolution to be constrained along evolutionary lines of least resistance. In theory, hybridization and subsequent interspecific gene flow may however rapidly change the evolutionary constraints of a population and eventually change its evolutionary potential, but empirical evidence is still scarce. Using closely related species pairs of Lake Victoria cichlids sampled from four different islands with different levels of interspecific gene flow, we tested for potential effects of introgressive hybridization on phenotypic evolution in wild populations. We found that these effects differed among our study species. Constraints measured as the eccentricity of phenotypic variance-covariance matrices declined significantly with increasing gene flow in the less abundant species for matrices that have a diverged line of least resistance. In contrast we find no such decline for the more abundant species. Overall our results suggest that hybridization can change the underlying phenotypic variance-covariance matrix, potentially increasing the adaptive potential of such populations.

Gasterosteus aculeatus egg traits and fish lengths vs. experiment setup

1) Our study addresses the role of non-genetic and genetic inheritance in shaping the adaptive potential of populations under a warming ocean scenario. We used a combined experimental approach (transgenerational plasticity and quantitative genetics) to partition the relative contribution of maternal vs. paternal (additive genetic) effects to offspring body size (a key component of fitness), and investigated a potential physiological mechanism (mitochondrial respiration capacities) underlying whole organism growth/size responses. 2) In very early stages of growth (up to 30 days), offspring body size of marine sticklebacks benefited from maternal transgenerational plasticity (TGP): offspring of mothers acclimated to17°C were larger when reared at 17°C, and offspring of mothers acclimated to 21°C were larger when reared at 21°C. The benefits of maternal TGP on body size were stronger and persisted longer (up to 60 days) for offspring reared in the warmer (21°C) environment, suggesting that maternal effects will be highly relevant for climate change scenarios in this system. 3) Mitochondrial respiration capacities measured on mature offspring (F1 adults) matched the pattern of TGP for juvenile body size, providing an intuitive mechanistic basis for the maternal acclimation persisting into adulthood. Size differences between temperatures seen at early growth stages remained in the F1 adults, linking offspring body size to maternal inheritance of mitochondria. 4) Lower maternal variance components in the warmer environment were mostly driven by mothers acclimated to ambient (colder) conditions, further supporting our tenet that maternal effects were stronger at elevated temperature. Importantly, all parent-offspring temperature combination groups showed genotype x environment (GxE) interactions, suggesting that reaction norms have the potential to evolve. 5) To summarise, transgenerational plasticity and genotype x environment interactions work in concert to mediate impacts of ocean warming on metabolic capacity and early growth of marine sticklebacks. TGP can buffer short-term detrimental effects of climate warming and may buy time for genetic adaptation to catch up, therefore markedly contributing to the evolutionary potential and persistence of populations under climate change.

The genetic covariance among clinal environments after adaptation to an environmental gradient in Drosophila serrata

We examined the genetic basis of clinal adaptation by determining the evolutionary response of life-history traits to laboratory natural selection along a gradient of thermal stress in Drosophila serrata. A gradient of heat stress was created by exposing larvae to a heat stress of 36degrees for 4 hr for 0, 1, 2, 3, 4, or 5 days of larval development, with the remainder of development taking place at 25degrees. Replicated lines were exposed to each level of this stress every second generation for 30 generations. At the end of selection, we conducted a complete reciprocal transfer experiment where all populations were raised in all environments, to estimate the realized additive genetic covariance matrix among clinal environments in three life-history traits. Visualization of the genetic covariance functions of the life-history traits revealed that the genetic correlation between environments generally declined as environments became more different and even became negative between the most different environments in some cases. One exception to this general pattern was a life-history trait representing the classic trade-off between development time and body size, which responded to selection in a similar genetic fashion across all environments. Adaptation to clinal environments may involve a number of distinct genetic effects along the length of the cline, the complexity of which may not be fully revealed by focusing primarily on populations at the ends of the cline.

Orientation of the genetic variance-covariance matrix and the fitness surface for multiple male sexually selected traits

Stabilizing selection has been predicted to change genetic variances and covariances so that the orientation of the genetic variance-covariance matrix (G) becomes aligned with the orientation of the fitness surface, but it is less clear how directional selection may change G. Here we develop statistical approaches to the comparison of G with vectors of linear and nonlinear selection. We apply these approaches to a set of male sexually selected cuticular hydrocarbons (CHCs) of Drosophila serrata. Even though male CHCs displayed substantial additive genetic variance, more than 99% of the genetic variance was orientated 74.9degrees away from the vector of linear sexual selection, suggesting that open-ended female preferences may greatly reduce genetic variation in male display traits. Although the orientation of G and the fitness surface were found to differ significantly, the similarity present in eigenstructure was a consequence of traits under weak linear selection and strong nonlinear ( convex) selection. Associating the eigenstructure of G with vectors of linear and nonlinear selection may provide a way of determining what long-term changes in G may be generated by the processes of natural and sexual selection.

Constraints on muscular performance: trade-offs between power output and fatigue resistance

An important functional and evolutionary constraint on the physical performance of vertebrates is believed to be the trade-off between speed and endurance capacity. However, despite the pervasiveness of physiological arguments, most studies have found no evidence of the trade-off when tested at the whole-animal level. We investigated the existence of this trade-off at the whole-muscle level, the presumed site of this physiological conflict, by examining inter-individual variation in both maximum power output and fatigue resistance for mouse extensor digitorum longus (EDL) muscle using the work-loop technique. We found negative correlations between several measures of in vitro maximum power output and force production with fatigue resistance for individual mouse EDL muscles, indicating functional trade-offs between these performance parameters. We suggest that this trade-off detected at the whole-muscle level has imposed an important constraint on the evolution of vertebrate physical performance.

Interindividual variation of isolated muscle performance and fibre-type composition in the toad Bufo viridus

Interindividual analyses of physiological performance represent one of the most powerful tools for identifying functional positive and negative linkages between various performance traits. In this study we investigated functional linkages in the whole-gastrocnemius performance of juvenile Bufo viridis by examining interindividual variation in in vitro muscle performance and muscle fibre-type composition. We used the work-loop technique to investigate the maximum in vitro power output and fatigue resistance of the gastrocnemius muscle during repeated sets of three cycles at the cycle frequency of 5 Hz, simulating an intermittent style of locomotion. We found several significant correlations between different measures of in vitro muscle performance, including a negative correlation between maximum net power output and fatigue resistance of power, indicating functional trade-offs between these performance traits. We also investigated the extent of individual variation in the proportions of different fibre types, and tested for correlations between individual variation in muscle fibre-type composition and the previously measured isolated muscle performance. Fast glycolytic fibres represented 84.0+/-3.4% of the muscle, while the combined slow oxidative and fast oxidative-glycolytic fibres represented 16+/-3.4%. We found no significant correlations between measures of in vitro muscle performance and the proportion of different fibre types in the gastrocnemius muscle. However, despite this lack of correlation between whole-muscle performance and muscle fibre-type composition data, we suggest the functional linkages detected between different measures of in vitro muscular performance have important ecological and evolutionary consequences.

Genetic diversity revealed in the apomictic fruit species Garcinia mangostana L. (mangosteen)

The novel molecular marker technique Randomly Amplified DNA Fingerprinting (RAF) was used to survey genetic relationships between 37 accessions of the tropical fruit G. mangostana (mangosteen) and among 11 accessions from eight other Garcinia species. Although mangosteen is believed to reproduce exclusively through apomixis, our results show that considerable genetic diversity exists within G. mangostana and between other Garcinia species. Among the 37 G. mangostana accessions examined, nine different genotypes were identified which clustered into three distinct groups based on correspondence analysis (reciprocal averaging). For 26 (70%) of the accessions no marker variation was detected over 530 loci screened. A further eight (22%) accessions exhibited very low levels of variation (0.2-1%) suggesting at least one well conservedm angosteen genotype. The remaining three accessions (8%) showed extensive variation (22-31%) compared with the majority of accessions. The three mangosteen groups were 63-70% dissimilar to the other Garcinia species investigated. The genetic diversity identified in this research will assist in the conservation of Garcinia germplasm and provides a valuable framework for the genetic improvement of mangosteen.

Simulating the effects of dominance and epistasis on selection response in the CIMMYT wheat breeding program using QuCim

Plant breeders use many different breeding methods to develop superior cultivars. However, it is difficult, cumbersome, and expensive to evaluate the performance of a breeding method or to compare the efficiencies of different breeding methods within an ongoing breeding program. To facilitate comparisons, we developed a QU-GENE module called QuCim that can simulate a large number of breeding strategies for self-pollinated species. The wheat breeding strategy Selected Bulk used by CIMMYT's wheat breeding program was defined in QuCim as an example of how this is done. This selection method was simulated in QuCim to investigate the effects of deviations from the additive genetic model, in the form of dominance and epistasis, on selection outcomes. The simulation results indicate that the partial dominance model does not greatly influence genetic advance compared with the pure additive model. Genetic advance in genetic systems with overdominance and epistasis are slower than when gene effects are purely additive or partially dominant. The additive gene effect is an appropriate indicator of the change in gene frequency following selection when epistasis is absent. In the absence of epistasis, the additive variance decreases rapidly with selection. However, after several cycles of selection it remains relatively fixed when epistasis is present. The variance from partial dominance is relatively small and therefore hard to detect by the covariance among half sibs and the covariance among full sibs. The dominance variance from the overdominance model can be identified successfully, but it does not change significantly, which confirms that overdominance cannot be utilized by an inbred breeding program. QuCim is an effective tool to compare selection strategies and to validate some theories in quantitative genetics.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.