Striatal activity reflects cortical activity patterns, bioRxiv, 2019-07-16
The dorsal striatum is organized into domains that drive characteristic behaviors1–7, and receive inputs from different parts of the cortex8,9 which modulate similar behaviors10–12. Striatal responses to cortical inputs, however, can be affected by changes in connection strength13–15, local striatal circuitry16,17, and thalamic inputs18,19. Therefore, it is unclear whether the pattern of activity across striatal domains mirrors that across the cortex20–23 or differs from it24–28. Here we use simultaneous large-scale recordings in the cortex and the striatum to show that striatal activity can be accurately predicted by spatiotemporal activity patterns in the cortex. The relationship between activity in the cortex and the striatum was spatially consistent with corticostriatal anatomy, and temporally consistent with a feedforward drive. Each striatal domain exhibited specific sensorimotor responses that predictably followed activity in the associated cortical regions, and the corticostriatal relationship remained unvaried during passive states or performance of a task probing visually guided behavior. However, the task’s visual stimuli and corresponding behavioral responses evoked relatively more activity in the striatum than in associated cortical regions. This increased striatal activity involved an additive offset in firing rate, which was independent of task engagement but only present in animals that had learned the task. Thus, striatal activity largely reflects patterns of cortical activity, deviating from them in a simple additive fashion for learned stimuli or actions.
biorxiv neuroscience 100-200-users 2019Migratory divides coincide with species barriers across replicated avian hybrid zones above the Tibetan Plateau, bioRxiv, 2019-07-12
AbstractMigratory divides are proposed to be catalysts for speciation across a diversity of taxa. However, the relative contribution of migratory behavior to reproductive isolation is difficult to test. Comparing reproductive isolation in hybrid zones with and without migratory divides offers a rare opportunity to directly examine the contribution of divergent migratory behavior to reproductive barriers. We show that across replicate sampling transects of two pairs of barn swallow (Hirundo rustica) subspecies, strong reproductive isolation coincided with an apparent migratory divide spanning 20 degrees of latitude. A third subspecies pair exhibited no evidence for a migratory divide and hybridized extensively. Within migratory divides, migratory phenotype was associated with assortative mating, implicating a central contribution of divergent migratory behavior to reproductive barriers. The remarkable geographic coincidence between migratory divides and genetic breaks supports a longstanding hypothesis that the Tibetan Plateau is a substantial barrier contributing to the diversity of Siberian avifauna.
biorxiv evolutionary-biology 100-200-users 2019VolcanoFinder genomic scans for adaptive introgression, bioRxiv, 2019-07-12
AbstractRecent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method—VolcanoFinder—to detect recent events of adaptive introgression using polymorphism data from the recipient species only.VolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity.Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder.Author summaryThe process by which beneficial alleles are introduced into a species from a closely-related species is termed adaptive introgression. We present an analytically-tractable model for the effects of adaptive introgression on non-adaptive genetic variation in the genomic region surrounding the beneficial allele. The result we describe is a characteristic volcano-shaped pattern of increased variability that arises around the positively-selected site, and we introduce an open-source method VolcanoFinder to detect this signal in genomic data. Importantly, VolcanoFinder is a population-genetic likelihood-based approach, rather than a comparative-genomic approach, and can therefore probe genomic variation data from a single population for footprints of adaptive introgression, even from a priori unknown and possibly extinct donor species.
biorxiv evolutionary-biology 100-200-users 2019A single cell framework for multi-omic analysis of disease identifies malignant regulatory signatures in mixed phenotype acute leukemia, bioRxiv, 2019-07-10
AbstractIn order to identify the molecular determinants of human diseases, such as cancer, that arise from a diverse range of tissue, it is necessary to accurately distinguish normal and pathogenic cellular programs.1–3Here we present a novel approach for single-cell multi-omic deconvolution of healthy and pathological molecular signatures within phenotypically heterogeneous malignant cells. By first creating immunophenotypic, transcriptomic and epigenetic single-cell maps of hematopoietic development from healthy peripheral blood and bone marrow mononuclear cells, we identify cancer-specific transcriptional and chromatin signatures from single cells in a cohort of mixed phenotype acute leukemia (MPAL) clinical samples. MPALs are a high-risk subtype of acute leukemia characterized by a heterogeneous malignant cell population expressing both myeloid and lymphoid lineage-specific markers.4, 5Our results reveal widespread heterogeneity in the pathogenetic gene regulatory and expression programs across patients, yet relatively consistent changes within patients even across malignant cells occupying diverse portions of the hematopoietic lineage. An integrative analysis of transcriptomic and epigenetic maps identifies 91,601 putative gene-regulatory interactions and classifies a number of transcription factors that regulate leukemia specific genes, includingRUNX1-linked regulatory elements proximal toCD69. This work provides a template for integrative, multi-omic analysis for the interpretation of pathogenic molecular signatures in the context of developmental origin.
biorxiv genomics 100-200-users 2019Structures of virus-like capsids formed by the Drosophila neuronal Arc proteins, bioRxiv, 2019-07-10
AbstractThe neuronal protein Arc is a critical mediator of synaptic plasticity. Arc originated in tetrapods and flies through domestication of retrotransposon Gag genes. Recent studies have suggested that Arc mediates intercellular mRNA transfer and like Gag, can form capsid-like structures. Here we report that Drosophila proteins dArc1 and dArc2 assemble virus-like capsids. We determine the capsid structures to 2.8 Å and 3.7 Å resolution, respectively, finding similarity to capsids of retroviruses and retrotransposons. Differences between dArc1 and dArc2 capsids, including the presence of a structured zinc-finger pair in dArc1, are consistent with differential RNA-binding specificity. Our data support a model in which ancestral capsid-forming and RNA-binding properties of Arc remain under positive selection pressure and have been repurposed to function in neuronal signalling.
biorxiv neuroscience 100-200-users 2019Mapping Vector Field of Single Cells, bioRxiv, 2019-07-09
AbstractUnderstanding how gene expression in single cells progress over time is vital for revealing the mechanisms governing cell fate transitions. RNA velocity, which infers immediate changes in gene expression by comparing levels of new (unspliced) versus mature (spliced) transcripts (La Manno et al. 2018), represents an important advance to these efforts. A key question remaining is whether it is possible to predict the most probable cell state backward or forward over arbitrary time-scales. To this end, we introduce an inclusive model (termed Dynamo) capable of predicting cell states over extended time periods, that incorporates promoter state switching, transcription, splicing, translation and RNAprotein degradation by taking advantage of scRNA-seq and the co-assay of transcriptome and proteome. We also implement scSLAM-seq by extending SLAM-seq to plate-based scRNA-seq (Hendriks et al. 2018; Erhard et al. 2019; Cao, Zhou, et al. 2019) and augment the model by explicitly incorporating the metabolic labelling of nascent RNA. We show that through careful design of labelling experiments and an efficient mathematical framework, the entire kinetic behavior of a cell from this model can be robustly and accurately inferred. Aided by the improved framework, we show that it is possible to reconstruct the transcriptomic vector field from sparse and noisy vector samples generated by single cell experiments. The reconstructed vector field further enables global mapping of potential landscapes that reflects the relative stability of a given cell state, and the minimal transition time and most probable paths between any cell states in the state space. This work thus foreshadows the possibility of predicting long-term trajectories of cells during a dynamic process instead of short time velocity estimates. Our methods are implemented as an open source tool, dynamo (<jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsgithub.comaristoteleodynamo-release>httpsgithub.comaristoteleodynamo-release<jatsext-link>).
biorxiv systems-biology 100-200-users 2019