A transposable element insertion is the switch between alternative life history strategies, bioRxiv, 2018-09-24
Tradeoffs affect resource allocation during development and result in fitness consequences that drive the evolution of life history strategies. Yet despite their importance, we know little about the mechanisms underlying life history tradeoffs in wild populations. Many species of Colias butterflies exhibit an alternative life history strategy (ALHS) where females divert resources from wing pigment synthesis to reproductive and somatic development. Due to this reallocation, a wing color polymorphism is associated with the ALHS individuals have either yelloworange or white wings. Here we map the genetic basis of the ALHS switch in Colias crocea to a transposable element insertion downstream of the Colias homolog of BarH-1, a homeobox transcription factor. Using CRISPRCas9 gene editing, antibody staining, and electron microscopy we find morph-specific specific expression of BarH-1 suppresses the formation of pigment granules in wing scales. Lipid and transcriptome analyses reveal physiological differences associated with the ALHS. These findings characterize a novel mechanism for a female-limited ALHS and show that the switch arises via recruitment of a transcription factor previously known for its function in cell fate determination in pigment cells of the retina.
biorxiv genomics 100-200-users 2018Layer-dependent activity in human prefrontal cortex during working memory, bioRxiv, 2018-09-24
Working memory involves a series of functions encoding a stimulus, maintaining or manipulating its representation over a delay, and finally making a behavioral response. While working memory engages dorsolateral prefrontal cortex (dlPFC), few studies have investigated whether these subfunctions are localized to different cortical depths in this region, and none have done so in humans. Here, we use high-resolution functional MRI to interrogate the layer specificity of neural activity during different epochs of a working memory task in dlPFC. We detect activity timecourses that follow the hypothesized patterns superficial layers are preferentially active during the delay period, while deeper layers are preferentially active during the response. Results demonstrate that layer-specific fMRI can be used in higher-order brain regions to non-invasively map cognitive information processing along cortical circuitry in humans.
biorxiv neuroscience 0-100-users 2018MITO-Tag Mice enable rapid isolation and multimodal profiling of mitochondria from specific cell types in vivo, bioRxiv, 2018-09-24
ABSTRACTMitochondria are metabolic organelles that are essential for mammalian life, but the dynamics of mitochondrial metabolism within mammalian tissues in vivo remains incompletely understood. While whole-tissue metabolite profiling has been useful for studying metabolism in vivo, such an approach lacks resolution at the cellular and subcellular level. In vivo methods for interrogating organellar metabolites in specific cell-types within mammalian tissues have been limited. To address this, we built on prior work in which we exploited a mitochondrially-localized 3XHA epitope-tag (“MITO-Tag”) for the fast isolation of mitochondria from cultured cells to now generate “MITO-Tag Mice.” Affording spatiotemporal control over MITO-Tag expression, these transgenic animals enable the rapid, cell-type-specific immunoisolation of mitochondria from tissues, which we verified using a combination of proteomic and metabolomic approaches. Using MITO-Tag Mice and targeted and untargeted metabolite profiling, we identified changes during fasted and refed conditions in a diverse array of mitochondrial metabolites in hepatocytes and found metabolites that behaved differently at the mitochondrial versus whole-tissue level. MITO-Tag Mice should have utility for studying mitochondrial physiology and our strategy should be generally applicable for studying other mammalian organelles in specific cell-types in vivo.
biorxiv molecular-biology 100-200-users 2018How to make a rodent giant Genomic basis and tradeoffs of gigantism in the capybara, the world’s largest rodent, bioRxiv, 2018-09-23
AbstractGigantism is the result of one lineage within a clade evolving extremely large body size relative to its small-bodied ancestors, a phenomenon observed numerous times in animals. Theory predicts that the evolution of giants should be constrained by two tradeoffs. First, because body size is negatively correlated with population size, purifying selection is expected to be less efficient in species of large body size, leading to a genome-wide elevation of the ratio of non-synonymous to synonymous substitution rates (dNdS) or mutation load. Second, gigantism is achieved through higher number of cells and higher rates of cell proliferation, thus increasing the likelihood of cancer. However, the incidence of cancer in gigantic animals is lower than the theoretical expectation, a phenomenon referred to as Peto’s Paradox. To explore the genetic basis of gigantism in rodents and uncover genomic signatures of gigantism-related tradeoffs, we sequenced the genome of the capybara, the world’s largest living rodent. We found that dNdS is elevated genome wide in the capybara, relative to other rodents, implying a higher mutation load. Conversely, a genome-wide scan for adaptive protein evolution in the capybara highlighted several genes involved in growth regulation by the insulininsulin-like growth factor signaling (IIS) pathway. Capybara-specific gene-family expansions included a putative novel anticancer adaptation that involves T cell-mediated tumor suppression, offering a potential resolution to Peto’s Paradox in this lineage. Gene interaction network analyses also revealed that size regulators function simultaneously as growth factors and oncogenes, creating an evolutionary conflict. Based on our findings, we hypothesize that gigantism in the capybara likely involved three evolutionary steps 1) Increase in body size by cell proliferation through the ISS pathway, 2) coupled evolution of growth-regulatory and cancer-suppression mechanisms, possibly driven by intragenomic conflict, and 3) establishment of the T cell-mediated tumor suppression pathway as an anticancer adaptation. Interestingly, increased mutation load appears to be an inevitable outcome of an increase in body size.Author SummaryThe existence of gigantic animals presents an evolutionary puzzle. Larger animals have more cells and undergo exponentially more cell divisions, thus, they should have enormous rates of cancer. Moreover, large animals also have smaller populations making them vulnerable to extinction. So, how do gigantic animals such as elephants and blue whales protect themselves from cancer, and what are the consequences of evolving a large size on the ‘genetic health’ of a species? To address these questions we sequenced the genome of the capybara, the world’s largest rodent, and performed comparative genomic analyses to identify the genes and pathways involved in growth regulation and cancer suppression. We found that the insulin-signaling pathway was involved in the evolution of gigantism in the capybara. We also found a putative novel anticancer mechanism mediated by the detection of tumors by T-cells, offering a potential solution to how capybaras mitigated the tradeoff imposed by cancer. Furthermore, we show that capybara genome harbors a higher proportion of slightly deleterious mutations relative to all other rodent genomes. Overall, this study provides insights at the genomic level into the evolution of a complex and extreme phenotype, and offers a detailed picture of how the evolution of a giant body size in the capybara has shaped its genome.
biorxiv evolutionary-biology 100-200-users 2018Parliament2 Fast Structural Variant Calling Using Optimized Combinations of Callers, bioRxiv, 2018-09-23
AbstractHere we present Parliament2 – a structural variant caller which combines multiple best-in-class structural variant callers to create a highly accurate callset. This captures more events than the individual callers achieve independently. Parliament2 uses a call-overlap-genotype approach that is highly extensible to new methods and presents users the choice to run some or all of Breakdancer, Breakseq, CNVnator, Delly, Lumpy, and Manta to run. Parliament2 applies an additional parallelization framework to speed certain callers and executes these in parallel, taking advantage of the different resource requirements to complete structural variant calling much faster than running the programs individually. Parliament2 is available as a Docker container, which pre-installs all required dependencies. This allows users to run any caller with easy installation and execution. This Docker container can easily be deployed in cloud or local environments and is available as an app on DNAnexus.
biorxiv bioinformatics 0-100-users 2018Revealing multi-scale population structure in large cohorts, bioRxiv, 2018-09-23
Genetic structure in large cohorts results from technical, sampling and demographic variation. Visualisation is therefore a first step in most genomic analyses. However, existing data exploration methods struggle with unbalanced sampling and the many scales of population structure. We investigate an approach to dimension reduction of genomic data that combines principal components analysis (PCA) with uniform manifold approximation and projection (UMAP) to succinctly illustrate population structure in large cohorts and capture their relationships on local and global scales. Using data from large-scale genomic datasets, we demonstrate that PCA-UMAP effectively clusters closely related individuals while placing them in a global continuum of genetic variation. This approach reveals previously overlooked subpopulations within the American Hispanic population and fine-scale relationships between geography, genotypes, and phenotypes in the UK population. This opens new lines of investigation for demographic research and statistical genetics. Given its small computational cost, PCA-UMAP also provides a general-purpose approach to exploratory analysis in population-scale datasets.
biorxiv genomics 100-200-users 2018