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Browsing Statistics by Author "Allen, Genevera"
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Item A CRISPR toolbox for generating intersectional genetic mouse models for functional, molecular, and anatomical circuit mapping(Springer Nature, 2022) Lusk, Savannah J.; McKinney, Andrew; Hunt, Patrick J.; Fahey, Paul G.; Patel, Jay; Chang, Andersen; Sun, Jenny J.; Martinez, Vena K.; Zhu, Ping Jun; Egbert, Jeremy R.; Allen, Genevera; Jiang, Xiaolong; Arenkiel, Benjamin R.; Tolias, Andreas S.; Costa-Mattioli, Mauro; Ray, Russell S.The functional understanding of genetic interaction networks and cellular mechanisms governing health and disease requires the dissection, and multifaceted study, of discrete cell subtypes in developing and adult animal models. Recombinase-driven expression of transgenic effector alleles represents a significant and powerful approach to delineate cell populations for functional, molecular, and anatomical studies. In addition to single recombinase systems, the expression of two recombinases in distinct, but partially overlapping, populations allows for more defined target expression. Although the application of this method is becoming increasingly popular, its experimental implementation has been broadly restricted to manipulations of a limited set of common alleles that are often commercially produced at great expense, with costs and technical challenges associated with production of intersectional mouse lines hindering customized approaches to many researchers. Here, we present a simplified CRISPR toolkit for rapid, inexpensive, and facile intersectional allele production.Item An automated respiratory data pipeline for waveform characteristic analysis(Wiley, 2023) Lusk, Savannah; Ward, Christopher S.; Chang, Andersen; Twitchell-Heyne, Avery; Fattig, Shaun; Allen, Genevera; Jankowsky, Joanna L.; Ray, Russell S.Comprehensive and accurate analysis of respiratory and metabolic data is crucial to modelling congenital, pathogenic and degenerative diseases converging on autonomic control failure. A lack of tools for high-throughput analysis of respiratory datasets remains a major challenge. We present Breathe Easy, a novel open-source pipeline for processing raw recordings and associated metadata into operative outcomes, publication-worthy graphs and robust statistical analyses including QQ and residual plots for assumption queries and data transformations. This pipeline uses a facile graphical user interface for uploading data files, setting waveform feature thresholds and defining experimental variables. Breathe Easy was validated against manual selection by experts, which represents the current standard in the field. We demonstrate Breathe Easy's utility by examining a 2-year longitudinal study of an Alzheimer's disease mouse model to assess contributions of forebrain pathology in disordered breathing. Whole body plethysmography has become an important experimental outcome measure for a variety of diseases with primary and secondary respiratory indications. Respiratory dysfunction, while not an initial symptom in many of these disorders, often drives disability or death in patient outcomes. Breathe Easy provides an open-source respiratory analysis tool for all respiratory datasets and represents a necessary improvement upon current analytical methods in the field. Key points Respiratory dysfunction is a common endpoint for disability and mortality in many disorders throughout life. Whole body plethysmography in rodents represents a high face-value method for measuring respiratory outcomes in rodent models of these diseases and disorders. Analysis of key respiratory variables remains hindered by manual annotation and analysis that leads to low throughput results that often exclude a majority of the recorded data. Here we present a software suite, Breathe Easy, that automates the process of data selection from raw recordings derived from plethysmography experiments and the analysis of these data into operative outcomes and publication-worthy graphs with statistics. We validate Breathe Easy with a terabyte-scale Alzheimer's dataset that examines the effects of forebrain pathology on respiratory function over 2 years of degeneration.Item Downregulation of glial genes involved in synaptic function mitigates Huntington's disease pathogenesis(eLife, 2021) Onur, Tarik Seref; Laitman, Andrew; Zhao, He; Keyho, Ryan; Kim, Hyemin; Wang, Jennifer; Mair, Megan; Wang, Huilan; Li, Lifang; Perez, Alma; de Haro, Maria; Wan, Ying-Wooi; Allen, Genevera; Lu, Boxun; Al-Ramahi, Ismael; Liu, Zhandong; Botas, JuanMost research on neurodegenerative diseases has focused on neurons, yet glia help form and maintain the synapses whose loss is so prominent in these conditions. To investigate the contributions of glia to Huntington's disease (HD), we profiled the gene expression alterations of Drosophila expressing human mutant Huntingtin (mHTT) in either glia or neurons and compared these changes to what is observed in HD human and HD mice striata. A large portion of conserved genes are concordantly dysregulated across the three species; we tested these genes in a high-throughput behavioral assay and found that downregulation of genes involved in synapse assembly mitigated pathogenesis and behavioral deficits. To our surprise, reducing dNRXN3 function in glia was sufficient to improve the phenotype of flies expressing mHTT in neurons, suggesting that mHTT's toxic effects in glia ramify throughout the brain. This supports a model in which dampening synaptic function is protective because it attenuates the excitotoxicity that characterizes HD.