Evidence for rapid phenotypic and behavioral change in a recently established cavefish population, bioRxiv, 2019-05-28
AbstractSubstantial morphological and behavioral shifts often accompany rapid environmental change, yet, little is known about the early stages of cave colonization. Relative to surface streams, caves are extreme environments with perpetual darkness and low nutrient availability. The Mexican tetra (Astyanax mexicanus), has repeatedly colonized caves throughout Mexico, suggesting an ability to adapt to these conditions. Here, we survey for phenotypic and behavioral differences between a surface population and a cave population of A. mexicanus that has recently colonized Honey Creek Cave, Comal County, Texas, likely within the last century. We found that fish from Honey Creek Cave and fish from Honey Creek surface populations differ significantly in morphological traits including length, coloration, body condition, eye size, and dorsal fin placement. Cavefish also exhibit an increased number of superficial neuromasts relative to surface fish. Behaviorally, cavefish consume fewer worms when trials are performed in both lighted and darkened conditions. Cavefish are more aggressive than surface fish and exhibit fewer behaviors associated with stress. Further in contrast to surface fish, cavefish prefer the edges to the center of an arena and are qualitatively more likely to investigate a novel object placed in the tank. While cavefish and surface fish were wild-caught and developmental environment likely play a role in shaping these differences, our work demonstrates morphological and behavioral shifts for Texas cavefish and offers an exciting opportunity for future work to explore the genetic and environmental contributions to early cave colonization.
biorxiv animal-behavior-and-cognition 0-100-users 2019Fate mapping via Ms4a3 expression history traces monocyte-derived cells, bioRxiv, 2019-05-28
SUMMARYMost tissue-resident macrophage (RTM) populations are seeded by waves of embryonic hematopoiesis and are self-maintained independently of a bone-marrow contribution during adulthood. A proportion of RTMs, however, is constantly replaced by blood monocytes and their functions compared to embryonic RTM remains unclear. The kinetics and extent of the contribution of circulating monocytes to RTM replacement during homeostasis, inflammation and disease is highly debated. Here, we identified Ms4a3 as a specific marker expressed by granulocyte-monocyte progenitors (GMPs) and subsequently generated Ms4a3TdT reporter and Ms4a3Cre-RosaTdT fate mapper models to follow monocytes and their progenies. Our Ms4a3Cre-RosaTdT model traced efficiently blood monocytes (97%) and granulocytes (100%), but no lymphocytes or tissue dendritic cells. Using this model, we precisely quantified the contribution of monocytes to the RTM pool during homeostasis and inflammation. The unambiguous identification of monocyte-derived cells will permit future studies of their function under any condition.
biorxiv immunology 0-100-users 2019RNASeqR an R package for automated two-group RNA-Seq analysis workflow, bioRxiv, 2019-05-28
RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the underlying biological impact of transcription. RNA-Seq analysis requires multiple processing steps and huge computational capabilities. There are many well-developed R packages for individual steps; however, there are few RBioconductor packages that integrate existing software tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end results in pure R environment so that researchers can quickly and easily get fundamental information in big sequencing data. To address this need, we have developed the open source RBioconductor package, RNASeqR. It allows users to run an automated RNA-Seq analysis with only six steps, producing essential tabular and graphical results for further biological interpretation. The features of RNASeqR include six-step analysis, comprehensive visualization, background execution version, and the integration of both R and command-line software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis pipeline in pure R environment. It allows users to efficiently utilize popular software tools, including both RBioconductor and command-line tools, without predefining the resources or environments. RNASeqR is freely available for Linux and macOS operating systems from Bioconductor (httpsbioconductor.orgpackagesreleasebiochtmlRNASeqR.html).
biorxiv bioinformatics 100-200-users 2019Rock the Chalk A five-year comparative analysis of a large microbiology lecture course reveals improved outcomes of chalk-talk compared to PowerPoint, bioRxiv, 2019-05-28
AbstractThe rise of electronic assisted presentation programs such as PowerPoint in undergraduate large lecture biology classes has displaced more traditional hand-drawn lectures such as the blackboard or overhead projectors, referred here as “chalk-talk” approaches. But which method is more effective in a large lecture microbiology classroom is unclear. Here I present data from a large microbial genetics lecture course taken during a five-year span comparing PowerPoint to chalk-talk lecturing methods. The results indicate that the chalk-talk approach was preferred by the students and rated higher in all measured metrics including course enjoyment, learning of key concepts, and course outcomes.
biorxiv scientific-communication-and-education 200-500-users 2019An Algorithmic Barrier to Neural Circuit Understanding, bioRxiv, 2019-05-27
AbstractNeuroscience is witnessing extraordinary progress in experimental techniques, especially at the neural circuit level. These advances are largely aimed at enabling us to understand how neural circuit computations mechanistically cause behavior. Here, using techniques from Theoretical Computer Science, we examine how many experiments are needed to obtain such an empirical understanding. It is proved, mathematically, that establishing the most extensive notions of understanding need exponentially-many experiments in the number of neurons, in general, unless a widely-posited hypothesis about computation is false. Worse still, the feasible experimental regime is one where the number of experiments scales sub-linearly in the number of neurons, suggesting a fundamental impediment to such an understanding. Determining which notions of understanding are algorithmically tractable, thus, becomes an important new endeavor in Neuroscience.
biorxiv neuroscience 100-200-users 2019