Diversification of the ruminant skull along an evolutionary line of least resistance.

Clarifying how microevolutionary processes scale to macroevolutionary patterns is a fundamental goal in evolutionary biology, but these analyses, requiring comparative datasets of population-level variation, are limited. By analyzing a previously published dataset of 2859 ruminant crania, we find that variation within and between ruminant species is biased by a highly conserved mammalian-wide allometric pattern, CREA (craniofacial evolutionary allometry), where larger species have proportionally longer faces. Species with higher morphological integration and species more biased toward CREA have diverged farther from their ancestors, and Ruminantia as a clade diversified farther than expected in the direction of CREA. Our analyses indicate that CREA acts as an evolutionary line of least resistance and facilitates morphological diversification due to its alignment with the browser-grazer continuum. Together, our results demonstrate that constraints at the population level can produce highly directional patterns of phenotypic evolution at the macroevolutionary scale. Further research is needed to explore how CREA has been exploited in other mammalian clades

Transcriptomic stratification of late-onset Alzheimer\u27s cases reveals novel genetic modifiers of disease pathology.

Late-Onset Alzheimer\u27s disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, and two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value \u3c 5×10-8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways

Transfer learning-trained convolutional neural networks identify novel MRI biomarkers of Alzheimer\u27s disease progression.

Introduction: Genome-wide association studies (GWAS) for late onset Alzheimer\u27s disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity. Methods: We use a transfer learning technique to train three-dimensional convolutional neural network (CNN) models based on structural magnetic resonance imaging (MRI) from the screening stage in the Alzheimer\u27s Disease Neuroimaging Initiative consortium to derive image features that reflect AD progression. Results: CNN-derived image phenotypes are significantly associated with fasting metabolites related to early lipid metabolic changes as well as insulin resistance and with genetic variants mapped to candidate genes enriched for amyloid beta degradation, tau phosphorylation, calcium ion binding-dependent synaptic loss, Discussion: This is the first attempt to show that non-invasive MRI biomarkers are linked to AD progression characteristics, reinforcing their use in early AD diagnosis and monitoring

Bridging the rodent to human translational gap: Marmosets as model systems for the study of Alzheimer\u27s disease.

INTRODUCTION: Our limited understanding of the mechanisms that trigger the emergence of Alzheimer\u27s disease (AD) has contributed to the lack of interventions that stop, prevent, or fully treat this disease. We believe that the development of a non-human primate model of AD will be an essential step toward overcoming limitations of other model systems and is crucial for investigating primate-specific mechanisms underlying the cellular and molecular root causes of the pathogenesis and progression of AD. METHODS: A new consortium has been established with funding support from the National Institute on Aging aimed at the generation, characterization, and validation of Marmosets As Research Models of AD (MARMO-AD). This consortium will study gene-edited marmoset models carrying genetic risk for AD and wild-type genetically diverse aging marmosets from birth throughout their lifespan, using non-invasive longitudinal assessments. These include characterizing the genetic, molecular, functional, behavioral, cognitive, and pathological features of aging and AD. RESULTS: The consortium successfully generated viable founders carrying DISCUSSION: By establishing marmoset models of AD, we will be able to investigate primate-specific cellular and molecular root causes that underlie the pathogenesis and progression of AD, overcome limitations of other model organisms, and support future translational studies to accelerate the pace of bringing therapies to patients

Variation in histone configurations correlates with gene expression across nine inbred strains of mice.

The diversity outbred (DO) mice and their inbred founders are widely used models of human disease. However, although the genetic diversity of these mice has been well documented, their epigenetic diversity has not. Epigenetic modifications, such as histone modifications and DNA methylation, are important regulators of gene expression, and as such are a critical mechanistic link between genotype and phenotype. Therefore, creating a map of epigenetic modifications in the DO mice and their founders is an important step toward understanding mechanisms of gene regulation and the link to disease in this widely used resource. To this end, we performed a strain survey of epigenetic modifications in hepatocytes of the DO founders. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), and DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represented a distinct combination of the four histone modifications. We found that the epigenetic landscape was highly variable across the DO founders and was associated with variation in gene expression across strains. We found that epigenetic state imputed into a population of DO mice recapitulated the association with gene expression seen in the founders suggesting that both histone modifications and DNA methylation are highly heritable mechanisms of gene expression regulation. We illustrate how DO gene expression can be aligned with inbred epigenetic states to identify putative cis-regulatory regions. Finally, we provide a data resource that documents strain-specific variation in chromatin state and DNA methylation in hepatocytes across nine widely used strains of laboratory mice

Data from: The evolution of morphological integration in the ruminant skull

Patterns of morphological integration have the potential to influence evolutionary trajectories. However, this influence depends on the stability of the integration pattern relative to the rate of evolutionary change. Studying the evolution of integration over large phylogenetic scales is complicated by its multivariate nature and the need to have both large sample sizes and a comprehensive taxon coverage. As a result, the question of how integration evolves over long time scales is still poorly understood. In this study I examined the evolution of integration across the phylogeny of extant ruminants, as reflected in their within-population covariation structure. I analyzed interlandmark distances from 2,054 skulls, representing 47 out of the 200 extant species of ruminants, including all major subfamilies of bovids and cervids. I estimated the within-population covariance matrix for each species, and compared them using multidimensional scaling and phylogenetic comparative methods. Results show that closely-related taxa differ substantially from each other in their integration pattern. However, the differences among higher-level clades still reflect their history of common descent. Differences between bovids and cervids involve mainly the oral and nasal regions, in accord with their different feeding and locomotion adaptations. Thus, the effect of both natural selection and phylogenetic history can be detected in the ruminant skull even though integration varies considerably among closely-related species

Data package

This data package includes raw data, R code and other information required to reproduce all results in the paper. Raw data and specimen information are provided as both tab-limited text file and R object. Phylogenetic trees are provided as both R object of class "phylo" (package ape). Other information is provided as R objects. A detailed README file is also include

EvoOfInt_EvoBio

This data package includes raw data, as well as R code and other information required to reproduce all results in the paper. Raw data and specimen information are provided as both tab-limited text file and R object. Phylogenetic trees are provided as both R object and a nexus file. Other information is provided as R objects. A detailed README file is also include

Data from: Disintegrating the fly: a mutational perspective on phenotypic integration and covariation

The structure of environmentally induced phenotypic covariation can influence the effective strength and magnitude of natural selection. Yet our understanding of the factors that contribute to and influence the evolutionary lability of such covariation is poor. Most studies have either examined environmental variation without accounting for covariation, or examined phenotypic and genetic covariation without distinguishing the environmental component. In this study we examined the effect of mutational perturbations on different properties of environmental covariation, as well as mean shape. We use strains of Drosophila melanogaster bearing well-characterized mutations known to influence wing shape, as well as naturally-derived strains, all reared under carefully-controlled conditions and with the same genetic background. We find that mean shape changes more freely than the covariance structure, and that different properties of the covariance matrix change independently from each other. The perturbations affect matrix orientation more than they affect matrix eccentricity or total variance. Yet, mutational effects on matrix orientation do not cluster according to the developmental pathway that they target. These results suggest that it might be useful to consider a more general concept of ‘decanalization’, involving all aspects of variation and covariation

Data and R code

Raw data, R code, and other information required to reproduce the analyses, figures, and tables in Haber and Dworkin 2016: "Dis-integrating the fly: A mutational perspective on phenotypic integration and covariation.