Quantitative Genetics, Pleiotropy, and Morphological Integration in the Dentition of Papio hamadryas

Variation in the mammalian dentition is highly informative of adaptations and evolutionary relationships, and consequently has been the focus of considerable research. Much of the current research exploring the genetic underpinnings of dental variation can trace its roots to Olson and Miller's 1958 book Morphological Integration. These authors explored patterns of correlation in the post-canine dentitions of the owl monkey and Hyopsodus, an extinct condylarth from the Eocene. Their results were difficult to interpret, as was even noted by the authors, due to a lack of genetic information through which to view the patterns of correlation. Following in the spirit of Olson and Miller's research, we present a quantitative genetic analysis of dental variation in a pedigreed population of baboons. We identify patterns of genetic correlations that provide insight to the genetic architecture of the baboon dentition. This genetic architecture indicates the presence of at least three modules: an incisor module that is genetically independent of the post-canine dentition, and a premolar module that demonstrates incomplete pleiotropy with the molar module. We then compare this matrix of genetic correlations to matrices of phenotypic correlations between the same measurements made on museum specimens of another baboon subspecies and the Southeast Asian colobine Presbytis. We observe moderate significant correlations between the matrices from these three primate taxa. From these observations we infer similarity in modularity and hypothesize a common pattern of genetic integration across the dental arcade in the Cercopithecoidea

Anatomical Network Comparison of Human Upper and Lower, Newborn and Adult, and Normal and Abnormal Limbs, with Notes on Development, Pathology and Limb Serial Homology vs. Homoplasy

How do the various anatomical parts (modules) of the animal body evolve into very different integrated forms (integration) yet still function properly without decreasing the individual's survival? This long-standing question remains unanswered for multiple reasons, including lack of consensus about conceptual definitions and approaches, as well as a reasonable bias toward the study of hard tissues over soft tissues. A major difficulty concerns the non-trivial technical hurdles of addressing this problem, specifically the lack of quantitative tools to quantify and compare variation across multiple disparate anatomical parts and tissue types. In this paper we apply for the first time a powerful new quantitative tool, Anatomical Network Analysis (AnNA), to examine and compare in detail the musculoskeletal modularity and integration of normal and abnormal human upper and lower limbs. In contrast to other morphological methods, the strength of AnNA is that it allows efficient and direct empirical comparisons among body parts with even vastly different architectures (e.g. upper and lower limbs) and diverse or complex tissue composition (e.g. bones, cartilages and muscles), by quantifying the spatial organization of these parts-their topological patterns relative to each other-using tools borrowed from network theory. Our results reveal similarities between the skeletal networks of the normal newborn/adult upper limb vs. lower limb, with exception to the shoulder vs. pelvis. However, when muscles are included, the overall musculoskeletal network organization of the upper limb is strikingly different from that of the lower limb, particularly that of the more proximal structures of each limb. Importantly, the obtained data provide further evidence to be added to the vast amount of paleontological, gross anatomical, developmental, molecular and embryological data recently obtained that contradicts the long-standing dogma that the upper and lower limbs are serial homologues. In addition, the AnNA of the limbs of a trisomy 18 human fetus strongly supports Pere Alberch's ill-named "logic of monsters" hypothesis, and contradicts the commonly accepted idea that birth defects often lead to lower integration (i.e. more parcellation) of anatomical structures

Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes

Testing for an Unusual Distribution of Rare Variants

Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals

Consequences of epistasis on growth in an erhualian × white duroc pig cross

Epistasis describes an interaction between the effects of loci. We included epistasis in quantitative trait locus (QTL) mapping of growth at a series of ages in a cross of a Chinese pig breed, Erhualian, with a commercial line, White Duroc. Erhualian pigs have much lower growth rates than White Duroc. We improved a method for genomewide testing of epistasis and present a clear analysis workflow. We also suggest a new approach for interpreting epistasis results where significant additive and dominance effects of a locus in specific backgrounds are determined. In total, seventeen QTL were found and eleven showed epistasis. Loci on chromosomes 2, 3, 4 and 7 were highlighted as affecting growth at more than one age or forming an interaction network. Epistasis resulted in both the QTL on chromosomes 3 and 7 having effects in opposite directions. We believe it is the first time for the chromosome 7 locus that an allele from a Chinese breed has been found to decrease growth. The consequences of epistasis were diverse. Results were impacted by using growth rather than body weight as the phenotype and by correcting for an effect of mother. Epistasis made a considerable contribution to growth in this population and modelling epistasis was important for accurately determining QTL effects

Genetic variation in the pleiotropic association between physical activity and body weight in mice

<p>Abstract</p> <p>Background</p> <p>A sedentary lifestyle is often assumed to lead to increases in body weight and potentially obesity and related diseases but in fact little is known about the genetic association between physical activity and body weight. We tested for such an association between body weight and the distance, duration, and speed voluntarily run by 310 mice from the F₂generation produced from an intercross of two inbred lines that differed dramatically in their physical activity levels.</p> <p>Methods</p> <p>We used a conventional interval mapping approach with SNP markers to search for QTLs that affected both body weight and activity traits. We also conducted a genome scan to search for relationship QTLs (<it>rel</it>QTLs), or chromosomal regions that affected an activity trait variably depending on the phenotypic value of body weight.</p> <p>Results</p> <p>We uncovered seven quantitative trait loci (QTLs) affecting body weight, but only one co-localized with another QTL previously found for activity traits. We discovered 19 <it>rel</it>QTLs that provided evidence for a genetic (pleiotropic) association of physical activity and body weight. The three genotypes at each of these loci typically exhibited a combination of negative, zero, and positive regressions of the activity traits on body weight, the net effect of which was to produce overall independence of body weight from physical activity. We also demonstrated that the <it>rel</it>QTLs produced these varying associations through differential epistatic interactions with a number of other epistatic QTLs throughout the genome.</p> <p>Conclusion</p> <p>It was concluded that individuals with specific combinations of genotypes at the <it>rel</it>QTLs and <it>epi</it>QTLs might account for some of the variation typically seen in plots of the association of physical activity with body weight.</p

Effects of thymic selection of the T cell repertoire on HLA-class I associated control of HIV infection

Without therapy, most people infected with human immunodeficiency virus (HIV) ultimately progress to AIDS. Rare individuals (‘elite controllers’) maintain very low levels of HIV RNA without therapy, thereby making disease progression and transmission unlikely. Certain HLA class I alleles are markedly enriched in elite controllers, with the highest association observed for HLA-B57 (ref. 1). Because HLA molecules present viral peptides that activate CD8+ T cells, an immune-mediated mechanism is probably responsible for superior control of HIV. Here we describe how the peptide-binding characteristics of HLA-B57 molecules affect thymic development such that, compared to other HLA-restricted T cells, a larger fraction of the naive repertoire of B57-restricted clones recognizes a viral epitope, and these T cells are more cross-reactive to mutants of targeted epitopes. Our calculations predict that such a T-cell repertoire imposes strong immune pressure on immunodominant HIV epitopes and emergent mutants, thereby promoting efficient control of the virus. Supporting these predictions, in a large cohort of HLA-typed individuals, our experiments show that the relative ability of HLA-B alleles to control HIV correlates with their peptide-binding characteristics that affect thymic development. Our results provide a conceptual framework that unifies diverse empirical observations, and have implications for vaccination strategies.Mark and Lisa Schwartz FoundationNational Institutes of Health (U.S.) (Director’s Pioneer award)Philip T. and Susan M. Ragon FoundationJane Coffin Childs Memorial Fund for Medical ResearchBill & Melinda Gates FoundationNational Institute of Allergy and Infectious Diseases (U.S.)National Institutes of Health (U.S.) (contract no. HHSN261200800001E)National Institutes of Health (U.S.). Intramural Research ProgramNational Cancer Institute (U.S.)Center for Cancer Research (National Cancer Institute (U.S.)

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

Contribution of genetic effects to genetic variance components with epistasis and linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Cockerham genetic models are commonly used in quantitative trait loci (QTL) analysis with a special feature of partitioning genotypic variances into various genetic variance components, while the F_∞genetic models are widely used in genetic association studies. Over years, there have been some confusion about the relationship between these two type of models. A link between the additive, dominance and epistatic effects in an F_∞model and the additive, dominance and epistatic variance components in a Cockerham model has not been well established, especially when there are multiple QTL in presence of epistasis and linkage disequilibrium (LD).</p> <p>Results</p> <p>In this paper, we further explore the differences and links between the F_∞and Cockerham models. First, we show that the Cockerham type models are allelic based models with a special modification to correct a confounding problem. Several important moment functions, which are useful for partition of variance components in Cockerham models, are also derived. Next, we discuss properties of the F_∞models in partition of genotypic variances. Its difference from that of the Cockerham models is addressed. Finally, for a two-locus biallelic QTL model with epistasis and LD between the loci, we present detailed formulas for calculation of the genetic variance components in terms of the additive, dominant and epistatic effects in an F_∞model. A new way of linking the Cockerham and F_∞model parameters through their coding variables of genotypes is also proposed, which is especially useful when reduced F_∞models are applied.</p> <p>Conclusion</p> <p>The Cockerham type models are allele-based models with a focus on partition of genotypic variances into various genetic variance components, which are contributed by allelic effects and their interactions. By contrast, the F_∞regression models are genotype-based models focusing on modeling and testing of within-locus genotypic effects and locus-by-locus genotypic interactions. When there is no need to distinguish the paternal and maternal allelic effects, these two types of models are transferable. Transformation between an F_∞model's parameters and its corresponding Cockerham model's parameters can be established through a relationship between their coding variables of genotypes. Genetic variance components in terms of the additive, dominance and epistatic genetic effects in an F_∞model can then be calculated by translating formulas derived for the Cockerham models.</p