CRISPR-Cas9 Gene Editing in Lizards Through Microinjection of Unfertilized Oocytes, bioRxiv, 2019-04-02
AbstractCRISPR-Cas9 mediated gene editing has enabled the direct manipulation of gene function in many species. However, the reproductive biology of reptiles presents unique barriers for the use of this technology, and there are currently no reptiles with effective methods for targeted mutagenesis. Here we present a new approach that enables the efficient production of CRISPR-Cas9 induced mutations in Anolis lizards, an important model for studies of reptile evolution and development.
biorxiv genetics 200-500-users 2019The mutational landscape of a prion-like domain, bioRxiv, 2019-04-02
AbstractSpecific insoluble protein aggregates are the hallmarks of many neurodegenerative diseases1–5. For example, cytoplasmic aggregates of the RNA-binding protein TDP-43 are observed in 97% of cases of Amyotrophic Lateral Sclerosis (ALS)6,7. However, it is still unclear for ALS and other diseases whether it is the insoluble aggregates or other forms of the mutated proteins that cause these diseases that are actually toxic to cells8–13. Here we address this question for TDP-43 by systematically mutating14 the protein and quantifying the effects on cellular toxicity. We generated >50,000 mutations in the intrinsically disordered prion-like domain (PRD) and observed that changes in hydrophobicity and aggregation potential are highly predictive of changes in toxicity. Surprisingly, however, increased hydrophobicity and cytoplasmic aggregation actually reduce cellular toxicity. Mutations have their strongest effects in a central region of the PRD, with variants that increase toxicity promoting the formation of more dynamic liquid-like condensates. The genetic interactions in double mutants reveal that specific structures exist in this ‘unstructured’ region in vivo. Our results demonstrate that deep mutagenesis is a powerful approach for probing the sequence-function relationships of intrinsically disordered proteins as well as their in vivo structural conformations. Moreover, we show that aggregation of TDP-43 is not harmful but actually protects cells, most likely by titrating the protein away from a toxic liquid-like phase.
biorxiv genetics 200-500-users 2019ezTrack An open-source video analysis pipeline for the investigation of animal behavior, bioRxiv, 2019-03-30
AbstractTracking small animal behavior by video is one of the most common tasks in the fields of neuroscience and psychology. Although commercial software exists for the execution of this task, commercial software often presents enormous cost to the researcher, and can also entail purchasing specific hardware setups that are not only expensive but lack adaptability. Moreover, the inaccessibility of the code underlying this software renders them inflexible. Alternatively, available open source options frequently require extensive model training and can be challenging for those inexperienced with programming. Here we present an open source and platform independent set of behavior analysis pipelines using interactive Python (iPythonJupyter Notebook) that researchers with no prior programming experience can use. Two modules are described. One module can be used for the positional analysis of an individual animal across a session (i.e., location tracking), amenable to a wide range of behavioral tasks including conditioned place preference, water maze, light-dark box, open field, and elevated plus maze, to name but a few. A second module is described for the analysis of conditioned freezing behavior. For both modules, a range of interactive plots and visualizations are available to confirm that chosen parameters produce results that conform to the user’s approval. In addition, batch processing tools for the fast analysis of multiple videos is provided, and frame-by-frame output makes aligning the data with neural recording data simple. Lastly, options for cropping video frames to mitigate the influence of fiberopticelectrophysiology cables, analyzing specified portions of time in a video, and defining regions of interest, can be implemented with ease.
biorxiv neuroscience 200-500-users 2019Genetic structure in the paternal lineages of South East Spain revealed by the analysis of 17 Y-STRs, Scientific Reports, 2019-03-26
The genetic data of 17 Y chromosome short tandem repeats in 146 unrelated donor residents in the provinces of Granada, Málaga, and Almería (GMA) were analyzed to determine the genetic legacy of the male inhabitants of the former Kingdom of Granada. A total of 139 unique haplotypes were identified. Observed allele frequencies and haplogroup frequencies were also analyzed. By AMOVA and STRUCTURE analysis, the populations of the 3 provinces could be treated genetically as a single population. The most frequent haplogroup was R1b1b2 (58.22%). By network analysis of all individuals, we observed a distribution according to haplogroup assignment. To improve the characterization of GMA population, it was compared with those of North Africa, the Iberian Peninsula, and southern Europe. In our analysis of allele frequencies and genetic distances, the GMA population lay within the Spanish population group. Further, in the STRUCTURE analysis, there was no African component in the GMA population, confirming that, based on our genetic markers, the GMA population does not reflect any male genetic influence of the North African people. The presence of African haplogroups in the GMA population is irrelevant when their frequency is compared with those in other European populations.
scientific reports genetics 200-500-users 2019A Critique of Pure Learning What Artificial Neural Networks can Learn from Animal Brains, bioRxiv, 2019-03-20
ABSTRACTOver the last decade, artificial neural networks (ANNs), have undergone a revolution, catalyzed in large part by better tools for supervised learning. However, training such networks requires enormous data sets of labeled examples, whereas young animals (including humans) typically learn with few or no labeled examples. This stark contrast with biological learning has led many in the ANN community posit that instead of supervised paradigms, animals must rely instead primarily on unsupervised learning, leading the search for better unsupervised algorithms. Here we argue that much of an animal’s behavioral repertoire is not the result of clever learning algorithms—supervised or unsupervised—but arises instead from behavior programs already present at birth. These programs arise through evolution, are encoded in the genome, and emerge as a consequence of wiring up the brain. Specifically, animals are born with highly structured brain connectivity, which enables them learn very rapidly. Recognizing the importance of the highly structured connectivity suggests a path toward building ANNs capable of rapid learning.
biorxiv neuroscience 200-500-users 2019A Systematic Evaluation of Single Cell RNA-Seq Analysis Pipelines, bioRxiv, 2019-03-20
AbstractThe recent rapid spread of single cell RNA sequencing (scRNA-seq) methods has created a large variety of experimental and computational pipelines for which best practices have not been established, yet. Here, we use simulations based on five scRNA-seq library protocols in combination with nine realistic differential expression (DE) setups to systematically evaluate three mapping, four imputation, seven normalisation and four differential expression testing approaches resulting in ∼ 3,000 pipelines, allowing us to also assess interactions among pipeline steps. We find that choices of normalisation and library preparation protocols have the biggest impact on scRNA-seq analyses. Specifically, we find that library preparation determines the ability to detect symmetric expression differences, while normalisation dominates pipeline performance in asymmetric DE-setups. Finally, we illustrate the importance of informed choices by showing that a good scRNA-seq pipeline can have the same impact on detecting a biological signal as quadrupling the sample size.
biorxiv bioinformatics 200-500-users 2019