High-throughput mapping of mesoscale connectomes in individual mice, bioRxiv, 2018-09-20
AbstractBrain function is determined by connectivity among brain areas, and disruption of this connectivity leads to neuropsychiatric disorders. Understanding connectivity is essential to modern neuroscience, but mesoscale connectivity atlases are currently slow and expensive to generate, exist for few model systems, and require pooling across many brains. Here we present a method, muMAPseq (multisource Multiplexed Analysis of Projections by sequencing), which leverages barcoding and high-throughput sequencing to generate atlases from single animals rapidly and at low cost. We apply muMAPseq to tracing the neocortical connectome of individual mice, and demonstrate high reproducibility, and accuracy. Applying muMAPseq to the mutant BTBR mouse strain, which lacks a corpus callosum, we recapitulate its known connectopathies, and also uncover novel deficits. muMAPseq allows individual laboratories to generate atlases tailored to individuals, disease models, and new model species, and will facilitate quantitative comparative connectomics, permitting examination of how age, sex, environment, genetics and species affect neuronal wiring.
biorxiv neuroscience 100-200-users 2018A non-spatial account of place and grid cells based on clustering models of concept learning, bioRxiv, 2018-09-19
ABSTRACTOne view is that conceptual knowledge is organized using the circuitry in the medial temporal lobe (MTL) that supports spatial processing and navigation. In contrast, we find that a domain-general learning algorithm explains key findings in both spatial and conceptual domains. When the clustering model is applied to spatial navigation tasks, so called place and grid cell-like representations emerge because of the relatively uniform distribution of possible inputs in these tasks. The same mechanism applied to conceptual tasks, where the overall space can be higher-dimensional and sampling sparser, leads to representations more aligned with human conceptual knowledge. Although the types of memory supported by the MTL are superficially dissimilar, the information processing steps appear shared. Our account suggests that the MTL uses a general-purpose algorithm to learn and organize context-relevant information in a useful format, rather than relying on navigation-specific neural circuitry.
biorxiv neuroscience 100-200-users 2018Integrin-mediated attachment of the blastoderm to the vitelline envelope impacts gastrulation of insects, bioRxiv, 2018-09-19
AbstractDuring gastrulation, physical forces reshape the simple embryonic tissue to form a complex body plan of multicellular organisms1. These forces often cause large-scale asymmetric movements of the embryonic tissue2,3. In many embryos, the tissue undergoing gastrulation movements is surrounded by a rigid protective shell4,5. While it is well recognized that gastrulation movements depend on forces generated by tissue-intrinsic contractility6,7, it is not known if interactions between the tissue and the protective shell provide additional forces that impact gastrulation. Here we show that a particular part of the blastoderm tissue of the red flour beetle Tribolium castaneum tightly adheres in a temporally coordinated manner to the vitelline envelope surrounding the embryo. This attachment generates an additional force that counteracts the tissue-intrinsic contractile forces to create asymmetric tissue movements. Furthermore, this localized attachment is mediated by a specific integrin, and its knock-down leads to a gastrulation phenotype consistent with complete loss of attachment. Moreover, analysis of another integrin in the fruit fly Drosophila melanogaster suggests that gastrulation in this organism also relies on adhesion between the blastoderm and the vitelline. Together, our findings reveal a conserved mechanism whereby the spatiotemporal pattern of tissue adhesion to the vitelline envelope provides controllable counter-forces that shape gastrulation movements in insects.
biorxiv developmental-biology 100-200-users 2018Polygenicity of complex traits is explained by negative selection, bioRxiv, 2018-09-19
Complex traits and common disease are highly polygenic thousands of common variants are causal, and their effect sizes are almost always small. Polygenicity could be explained by negative selection, which constrains common-variant effect sizes and may reshape their distribution across the genome. We refer to this phenomenon as flattening, as genetic signal is flattened relative to the underlying biology. We introduce a mathematical definition of polygenicity, the effective number of associated SNPs, and a robust statistical method to estimate it. This definition of polygenicity differs from the number of causal SNPs, a standard definition; it depends strongly on SNPs with large effects. In analyses of 33 complex traits (average N=361k), we determined that common variants are ∼4x more polygenic than low-frequency variants, consistent with pervasive flattening. Moreover, functionally important regions of the genome have increased polygenicity in proportion to their increased heritability, implying that heritability enrichment reflects differences in the number of associations rather than their magnitude (which is constrained by selection). We conclude that negative selection constrains the genetic signal of biologically important regions and genes, reshaping genetic architecture.
biorxiv genetics 100-200-users 2018RELION-3 new tools for automated high-resolution cryo-EM structure determination, bioRxiv, 2018-09-19
AbstractHere, we describe the third major release of relion. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D-classification. Perparticle refinement of CTF parameters and correction of estimated beam tilt provides higher-resolution reconstructions when particles are at different heights in the ice, andor coma-free alignment has not been optimal. Ewald sphere curvature correction improves resolution for large particles. We illustrate these developments with publicly available data sets together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 0.2-0.7 Å compared to previous relion versions.
biorxiv biophysics 100-200-users 2018Genomic prediction of cognitive traits in childhood and adolescence, bioRxiv, 2018-09-18
AbstractRecent advances in genomics are producing powerful DNA predictors of complex traits, especially cognitive abilities. Here, we leveraged summary statistics from the most recent genome-wide association studies of intelligence and educational attainment to build prediction models of general cognitive ability and educational achievement. To this end, we compared the performances of multi-trait genomic and polygenic scoring methods. In a representative UK sample of 7,026 children at age 12 and 16, we show that we can now predict up to 11 percent of the variance in intelligence and 16 percent in educational achievement. We also show that predictive power increases from age 12 to age 16 and that genomic predictions do not differ for girls and boys. Multivariate genomic methods were effective in boosting predictive power and, even though prediction accuracy varied across polygenic scores approaches, results were similar using different multivariate and polygenic score methods. Polygenic scores for educational attainment and intelligence are the most powerful predictors in the behavioural sciences and exceed predictions that can be made from parental phenotypes such as educational attainment and occupational status.
biorxiv genomics 100-200-users 2018