Molecular recording of mammalian embryogenesis, bioRxiv, 2018-08-03
Understanding the emergence of complex multicellular organisms from single totipotent cells, or ontogenesis, represents a foundational question in biology. The study of mammalian development is particularly challenging due to the difficulty of monitoring embryos in utero, the variability of progenitor field sizes, and the indeterminate relationship between the generation of uncommitted progenitors and their progression to subsequent stages. Here, we present a flexible, high information, multi-channel molecular recorder with a single cell (sc) readout and apply it as an evolving lineage tracer to define a mouse cell fate map from fertilization through gastrulation. By combining lineage information with scRNA-seq profiles, we recapitulate canonical developmental relationships between different tissue types and reveal an unexpected transcriptional convergence of endodermal cells from extra-embryonic and embryonic origins, illustrating how lineage information complements scRNA-seq to define cell types. Finally, we apply our cell fate map to estimate the number of embryonic progenitor cells and the degree of asymmetric partitioning within the pluripotent epiblast during specification. Our approach enables massively parallel, high-resolution recording of lineage and other information in mammalian systems to facilitate a quantitative framework for describing developmental processes.
biorxiv developmental-biology 0-100-users 2018Pooled optical screens in human cells, bioRxiv, 2018-08-03
Large-scale genetic screens play a key role in the systematic discovery of genes underlying cellular phenotypes. Pooling of genetic perturbations greatly increases screening throughput, but has so far been limited to screens of enrichments defined by cell fitness and flow cytometry, or to comparatively low-throughput single cell gene expression profiles. Although microscopy is a rich source of spatial and temporal information about mammalian cells, high-content imaging screens have been restricted to much less efficient arrayed formats. Here, we introduce an optical method to link perturbations and their phenotypic outcomes at the single-cell level in a pooled setting. Barcoded perturbations are read out by targeted in situ sequencing following image-based phenotyping. We apply this technology to screen a focused set of 952 genes across >3 million cells for involvement in NF-κB activation by imaging the translocation of RelA (p65) to the nucleus, recovering 20 known pathway components and 3 novel candidate positive regulators of IL-1β and TNFα-stimulated immune responses.
biorxiv genomics 200-500-users 2018Reaction times and other skewed distributions problems with the mean and the median, bioRxiv, 2018-08-03
ABSTRACTTo summarise skewed (asymmetric) distributions, such as reaction times, typically the mean or the median are used as measures of central tendency. Using the mean might seem surprising, given that it provides a poor measure of central tendency for skewed distributions, whereas the median provides a better indication of the location of the bulk of the observations. However, the sample median is biased with small sample sizes, it tends to overestimate the population median. This is not the case for the mean. Based on this observation, Miller (1988) concluded that “sample medians must not be used to compare reaction times across experimental conditions when there are unequal numbers of trials in the conditions.” Here we replicate and extend Miller (1988), and demonstrate that his conclusion was ill-advised for several reasons. First, the median’s bias can be corrected using a percentile bootstrap bias correction. Second, a careful examination of the sampling distributions reveals that the sample median is median unbiased, whereas the mean is median biased when dealing with skewed distributions. That is, on average the sample mean estimates the population mean, but typically this is not the case. In addition, simulations of false and true positives in various situations show that no method dominates. Crucially, neither the mean nor the median are sufficient or even necessary to compare skewed distributions. Different questions require different methods and it would be unwise to use the mean or the median in all situations. Better tools are available to get a deeper understanding of how distributions differ we illustrate a powerful alternative that relies on quantile estimation. All the code and data to reproduce the figures and analyses in the article are available online.
biorxiv neuroscience 100-200-users 2018MemBright a Family of Fluorescent Membrane Probes for Advanced Cellular Imaging and Neuroscience, bioRxiv, 2018-07-30
AbstractThe proper staining of the plasma membrane (PM) is critical in bioimaging as it delimits the cell. Herein, we developed MemBright a family of six cyanine-based fluorescent turn-on PM probes that emit from orange to near-infrared when reaching the PM, and enable homogeneous and selective PM staining with excellent contrast in mono and two-photon microscopy. These probes are compatible with long-term live cell imaging and immunostaining. Moreover, MemBright label neurons in a brighter manner than surrounding cells allowing identification of neurons in acute brain tissue section and neuromuscular-junctions without any use of transfection or transgenic animals. At last, MemBright were used in super-resolution imaging to unravel the dendritic spines’ neck. 3D multicolor dSTORM in combination with immunostaining revealed en-passant synapse displaying endogenous glutamate receptors clustered at the axonal-dendritic contact site. MemBright probes thus constitute a universal toolkit for cell biology and neuroscience biomembrane imaging with a variety of microscopy techniques.
biorxiv neuroscience 0-100-users 2018Clonal evolution and genome stability in a 2,500-year-old fungal individual, bioRxiv, 2018-07-26
AbstractIn the late 1980s, a genetic individual of the fungus Armillaria gallica that extended over at least 37 hectares of forest floor and encompassed hundreds of tree root systems was discovered on the Upper Peninsula of Michigan. Based on observed growth rates, the individual was estimated to be at least 1500 years old with a mass of more than 105 kg. Nearly three decades on, we returned to the site of individual for new sampling. We report here that the same genetic individual of A. gallica is still alive on its original site, but we estimated that it is older and larger than originally estimated, at least 2,500 years and 4 × 105 kg, respectively. We also show that mutation has occurred within the somatic cells of the individual, reflecting its historical pattern of growth from a single point. The overall rate of mutation, however, was extremely low. The large individual of A. gallica has been remarkably resistant to genomic change as it has persisted in place.
biorxiv evolutionary-biology 0-100-users 2018Moving beyond P values Everyday data analysis with estimation plots, bioRxiv, 2018-07-26
Over the past 75 years, a number of statisticians have advised that the data-analysis method known as null-hypothesis significance testing (NHST) should be deprecated (Berkson, 1942; Halsey et al., 2015; Wasserstein et al., 2019). The limitations of NHST have been extensively discussed, with a broad consensus that current statistical practice in the biological sciences needs reform. However, there is less agreement on reform’s specific nature, with vigorous debate surrounding what would constitute a suitable alternative (Altman et al., 2000; Benjamin et al., 2017; Cumming and Calin-Jageman, 2016). An emerging view is that a more complete analytic technique would use statistical graphics to estimate effect sizes and evaluate their uncertainty (Cohen, 1994; Cumming and Calin-Jageman, 2016). As these estimation methods require only minimal statistical retraining, they have great potential to shift the current data-analysis culture away from dichotomous thinking towards quantitative reasoning (Claridge-Chang and Assam, 2016). The evolution of statistics has been inextricably linked to the development of quantitative displays that support complex visual reasoning (Tufte, 2001). We consider that the graphic we describe here as estimation plot is the most intuitive way to display the complete statistical information about experimental data sets. However, a major obstacle to adopting estimation plots is accessibility to suitable software. To lower this hurdle, we have developed free software that makes high-quality estimation plotting available to all. Here, we explain the rationale for estimation plots by contrasting them with conventional charts used to display data with NHST results, and describe how the use of these graphs affords five major analytical advantages.
biorxiv bioinformatics 500+-users 2018