Next-generation sequencing of double stranded RNA is greatly improved by treatment with the inexpensive denaturing reagent DMSO, bioRxiv, 2019-05-21
AbstractDouble stranded RNA (dsRNA) is the genetic material of important viruses and a key component of RNA interference-based immunity in eukaryotes. Previous studies have noted difficulties in determining the sequence of dsRNA molecules that have affected studies of immune function and estimates of viral diversity in nature. Dimethyl sulfoxide (DMSO) has been used to denature dsRNA prior to the reverse transcription stage to improve RT-PCR and Sanger sequencing. We systematically tested the utility of DMSO to improve sequencing yield of a dsRNA virus (Φ6) in a short-read next generation sequencing platform. DMSO treatment improved sequencing read recovery by over two orders of magnitude, even when RNA and cDNA concentrations were below the limit of detection. We also tested the effects of DMSO on a mock eukaryotic viral community and found that dsRNA virus reads increased with DMSO treatment. Furthermore, we provide evidence that DMSO treatment does not adversely affect recovery of reads from a single-stranded RNA viral genome (Influenza ACalifornia072009). We suggest that up to 50% DMSO treatment be used prior to cDNA synthesis when samples of interest are composed of or may contain dsRNA.Data SummarySequence data was deposited in the NCBI Short Read Archive (accession numbers PRJNA527100, PRJNA527101, PRJNA527098). Data and code for analysis is available on GitHub (<jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsgithub.comawilcox83dsRNA-sequencing>httpsgithub.comawilcox83dsRNA-sequencing<jatsext-link>. doi10.5281zenodo.1453423). Protocol for dsRNA sequencing is posted on protocols.io (doi10.17504protocols.io.ugnetve).
biorxiv microbiology 0-100-users 2019Npas1+-Nkx2.1+ Neurons Are an Integral Part of the Cortico-pallido-cortical Loop, bioRxiv, 2019-05-21
AbstractWithin the basal ganglia circuit, the external globus pallidus (GPe) is critically involved in motor control. Aside from Foxp2+ neurons and ChAT+ neurons that have been established as unique neuron types, there is little consensus on the classification of GPe neurons. Properties of the remaining neuron types are poorly-defined. In this study, we leverage new mouse lines, viral tools, and molecular markers to better define GPe neuron subtypes. We found that Sox6 represents a novel, defining marker for GPe neuron subtypes. Lhx6+ neurons that lack the expression of Sox6 were devoid of both parvalbumin and Npas1. This result confirms previous assertions of the existence of a unique Lhx6+ population. Neurons that arise from the Dbx1+ lineage were similarly abundant in the GPe and displayed a heterogeneous makeup. Importantly, tracing experiments revealed that Npas1+-Nkx2.1+ neurons represent the principal non-cholinergic, cortically-projecting neurons. In other words, they form the pallido-cortical arm of the cortico-pallido-cortical loop. Our data further described that pyramidal-tract neurons in the cortex collateralized within the GPe, forming a closed-loop system between the two brain structures. Overall, our findings reconcile some of the discrepancies that arose from differences in techniques or the reliance on pre-existing tools. While spatial distribution and electrophysiological properties of GPe neurons reaffirm the diversification of GPe subtypes, statistical analyses strongly support the notion that these neuron subtypes can be categorized under the two principal neuron classes—i.e., PV+ neurons and Npas1+ neurons.Significance statementThe poor understanding of the neuronal composition in the GPe undermines our ability to interrogate its precise behavioral and disease involvements. In this study, twelve different genetic crosses were used, hundreds of neurons were electrophysiologically-characterized, and over 100,000 neurons were histologically- andor anatomically-profiled. Our current study further establishes the segregation of GPe neuron classes and illustrates the complexity of GPe neurons in adult mice. Our results support the idea that Npas1+-Nkx2.1+ neurons are a distinct GPe neuron subclass. By providing a detailed analysis of the organization of the cortico-pallidal-cortical projection, our findings establish the cellular and circuit substrates that can be important for motor function and dysfunction.
biorxiv neuroscience 0-100-users 2019Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data, bioRxiv, 2019-05-20
AbstractWe present a comprehensive evaluation of state-of-the-art algorithms for inferring gene regulatory networks (GRNs) from single-cell gene expression data. We develop a systematic framework called BEELINE for this purpose. We use synthetic networks with predictable cellular trajectories as well as curated Boolean models to serve as the ground truth for evaluating the accuracy of GRN inference algorithms. We develop a strategy to simulate single-cell gene expression data from these two types of networks that avoids the pitfalls of previously-used methods. We selected 12 representative GRN inference algorithms. We found that the accuracy of these methods (measured in terms of AUROC and AUPRC) was moderate, by and large, although the methods were better in recovering interactions in the synthetic networks than the Boolean models. Techniques that did not require pseudotime-ordered cells were more accurate, in general. The observation that the endpoints of many false positive edges were connected by paths of length two in the Boolean models suggested that indirect effects may be predominant in the outputs of the algorithms we tested. The predicted networks were considerably inconsistent with each other, indicating that combining GRN inference algorithms using ensembles is likely to be challenging. Based on the results, we present some recommendations to users of GRN inference algorithms, including suggestions on how to create simulated gene expression datasets for testing them. BEELINE, which is available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpgithub.commurali-groupBEELINE>httpgithub.commurali-groupBEELINE<jatsext-link> under an open-source license, will aid in the future development of GRN inference algorithms for single-cell transcriptomic data.
biorxiv bioinformatics 0-100-users 2019Benchmarking principal component analysis for large-scale single-cell RNA-sequencing, bioRxiv, 2019-05-20
Principal component analysis (PCA) is an essential method for analyzing single-cell RNA-seq (scRNA-seq) dataset but for large-scale scRNA-seq datasets, the computation consumes a long time and large memory space. In this work, we review the existing fast and memory-efficient PCA algorithms and implementations and evaluate their practical application to large-scale scRNA-seq dataset. Our benchmark showed that some PCA algorithms based on Krylov subspace and randomized singular value decomposition are fast, memory-efficient, and accurate than the other algorithms. Considering the difference of computational environment of users and developers, we also developed the guideline to select the appropriate PCA implementations.
biorxiv bioinformatics 100-200-users 2019DeepFly3D A deep learning-based approach for 3D limb and appendage tracking in tethered, adult Drosophila, bioRxiv, 2019-05-20
AbstractStudying how neural circuits orchestrate limbed behaviors requires the precise measurement of the positions of each appendage in 3-dimensional (3D) space. Deep neural networks can estimate 2-dimensional (2D) pose in freely behaving and tethered animals. However, the unique challenges associated with transforming these 2D measurements into reliable and precise 3D poses have not been addressed for small animals including the fly, Drosophila melanogaster. Here we present DeepFly3D, a software that infers the 3D pose of tethered, adult Drosophila—or other animals—using multiple camera images. DeepFly3D does not require manual calibration, uses pictorial structures to automatically detect and correct pose estimation errors, and uses active learning to iteratively improve performance. We demonstrate more accurate unsupervised behavioral embedding using 3D joint angles rather than commonly used 2D pose data. Thus, DeepFly3D enables the automated acquisition of behavioral measurements at an unprecedented level of resolution for a variety of biological applications.
biorxiv animal-behavior-and-cognition 100-200-users 2019Single-cell transcriptomics reveals expansion of cytotoxic CD4 T-cells in supercentenarians, bioRxiv, 2019-05-20
AbstractSupercentenarians, people who have reached 110 years of age, are a great model of healthy aging. Their characteristics of delayed onset of age-related diseases and compression of morbidity imply that their immune system remains functional. Here we performed single-cell transcriptome analysis of 61,202 peripheral blood mononuclear cells (PBMCs), derived from seven supercentenarians and five younger controls. We identified a marked increase of cytotoxic CD4 T-cells (CD4 CTLs) coupled with a substantial reduction of B-cells as a novel signature of supercentenarians. Furthermore, single-cell T-cell receptor sequencing of two supercentenarians revealed that CD4 CTLs had accumulated through massive clonal expansion, with the most frequent clonotypes accounting for 15% to 35% of the entire CD4 T-cell population. The CD4 CTLs exhibited substantial heterogeneity in their degree of cytotoxicity as well as a nearly identical transcriptome to that of CD8 CTLs. This indicates that CD4 CTLs utilize the transcriptional program of the CD8 lineage while retaining CD4 expression. Our study reveals that supercentenarians have unique characteristics in their circulating lymphocytes, which may represent an essential adaptation to achieve exceptional longevity by sustaining immune responses to infections and diseases.SignificanceExceptionally long-lived people such as supercentenarians tend to spend their entire lives in good health, implying that their immune system remains active to protect against infections and tumors. However, their immunological condition has been largely unexplored. We profiled thousands of circulating immune cells from supercentenarians at single-cell resolution, and identified a large number of CD4 T-cells that have cytotoxic features. This characteristic is very unique to supercentenarians, because generally CD4 T-cells have helper, but not cytotoxic, functions under physiological conditions. We further profiled their T-cell receptors, and revealed that the cytotoxic CD4 T-cells were accumulated through clonal expansion. The conversion of helper CD4 T-cells to a cytotoxic variety might be an adaptation to the late stage of aging.
biorxiv immunology 100-200-users 2019