Search bioRxiv⌕ Search

Biology subjects

Braun, R. E.

Publications and source records attributed to Braun, R. E..

8 recordsLinked to original sources

DISCOVERY AND VALIDATION OF GENES DRIVING DRUG-INTAKE AND RELATED BEHAVIORAL TRAITS IN MICE

Substance use disorders (SUDs) are heritable disorders characterized by compulsive drug use, but the biological mechanisms driving addiction remain largely unknown. Genetic correlations reveal that predisposing drug-naive phenotypes, including anxiety, depression, novelty preference, and sensation seeking, are predictive of drug-use phenotypes, implicating shared genetic mechanisms. Because of this relationship, high-throughput behavioral screening of predictive phenotypes in knockout (KO) mice allows efficient discovery of genes likely to be involved in drug use. We used this strategy in two rounds of screening in which we identified 33 drug-use candidate genes and ultimately validated the perturbation of 22 of these genes as causal drivers of substance intake. In our initial round of screening, we employed the two-bottle-choice paradigms to assess alcohol, methamphetamine, and nicotine intake. We identified 19 KO strains that were extreme responders on at least one predictive phenotype. Thirteen of the 19 gene deletions (68%) significantly affected alcohol use three methamphetamine use, and two both. In the second round of screening, we employed a multivariate approach to identify outliers and performed validation using methamphetamine two-bottle choice and ethanol drinking-in-the-dark protocols. We identified 15 KO strains that were extreme responders across the predisposing drug-naive phenotypes. Eight of the 15 gene deletions (53%) significantly affected intake or preference for three alcohol, eight methamphetamine or three both (3). We observed multiple relations between predisposing behaviors and drug intake, revealing many distinct biobehavioral processes underlying these relationships. The set of mouse models identified in this study can be used to characterize these addiction-related processes further.

genetics↗

The production of 4,182 mouse lines identifies experimental and biological variables impacting Cas9-mediated mutant mouse line production

The International Mouse Phenotyping Consortium (IMPC) systematically produces and phenotypes mouse lines with presumptive null mutations to provide insight into gene function. The IMPC now uses the programmable RNA-guided nuclease Cas9 for its increased capacity and flexibility to efficiently generate null alleles in the C57BL/6N strain. In addition to being a valuable novel and accessible research resource, the production of 3,313 knockout mouse lines using comparable protocols provides a rich dataset to analyze experimental and biological variables affecting in vivo gene engineering with Cas9. Mouse line production has two critical steps - generation of founders with the desired allele and germline transmission (GLT) of that allele from founders to offspring. A systematic evaluation of the variables impacting success rates identified gene essentiality as the primary factor influencing successful production of null alleles. Collectively, our findings provide best practice recommendations for using Cas9 to generate alleles in mouse essential genes, many of which are orthologs of genes linked to human disease.

genetics↗

Whole genome analysis for 163 guide RNAs in Cas9 edited mice reveals minimal off-target activity

Introductory ParagraphThe Knockout Mouse Phenotyping Program (KOMP2) uses CRISRPR/Cas9 for high-throughput mouse line production to generate null alleles in the inbred C57BL/6N strain for broad-based in vivo phenotyping. In order to assess the risk of spurious S. pyogenes Cas9-induced off-target mutagenesis, we applied whole genome sequencing to compare the genomes of 50 Cas9-derived founder mice representing 163 different gRNAs to 28 untreated inbred control mice. Our analysis pipeline detected 28 off-target sequence variants associated with 21 guides. These potential off-targets were identified in 18/50 (36%) founders with 9/28 (32%) independently validated corresponding to 8 founder animals. In total, only 4.9% (8/163) of all guides exhibited off-target activity resulting in a rate of 0.16 Cas9 off-target mutations per founder analyzed. In comparison, we observed ~1225 unique variants in each mouse regardless of whether or not it was exposed to Cas9. These findings indicate that Cas9-mediated off-target mutagenesis is rare in founder knockout mice generated using guide RNAs designed to minimize off-target risk. Overall, bona fide off-target variants comprise a small fraction of the genetic heterogeneity found in carefully maintained colonies of inbred strains.

genetics↗

Human and mouse essentiality screens as a resource for disease gene discovery

Although genomic sequencing has been transformative in the study of rare genetic diseases, identifying causal variants remains a considerable challenge that can be addressed in part by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from the comprehensive viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and from human cell line essentiality screens. We propose a novel, cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing characteristics in the biological processes they regulate, tissue expression levels and human mutation rates. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented in the developmental lethal category, representing genes not essential for cell survival but required for organism development. Exploiting this finding, we have screened developmental disorder cases from three independent disease sequencing consortia and identified potentially pathogenic, de novo variants shared in different patients for several developmental lethal genes that have not previously been associated with rare disease. We therefore propose FUSIL as an efficient resource for disease gene discovery.

genomics↗

Noninvasive sleep monitoring in large-scale screening of knock-out mice reveals novel sleep-related genes

Sleep is a critical process that is well-conserved across mammalian species, and perhaps most animals, yet its functions and underlying mechanisms remain poorly understood. Identification of genes and pathways that can influence sleep may shed new light on these functions. Genomic screens enable the detection of previously unsuspected molecular processes that influence sleep. In this study, we report results from a large-scale phenotyping study of sleep-wake parameters for a population of single-gene knockout mice. Sleep-wake parameters were measured using a high throughput, non-invasive piezoelectric system called PiezoSleep. Knockout mice generated on a C57BL6/N (B6N) background were monitored for sleep and wake parameters for five days. By analyzing data from over 6000 mice representing 343 single gene knockout lines, we identified 122 genes influencing traits like sleep duration and bout length that have not been previously implicated in sleep, including those that affect sleep only during a specific circadian phase. PiezoSleep also allows assessment of breath rates during sleep and this was integrated as a supplemental tool in identifying aberrant physiology in these knockout lines. Sex differences were evident in both normal and altered sleep behavior. Through a combination of genetic and phenotypic associations, and known QTLs for sleep, we propose a set of candidate genes playing specific roles in sleep. The high \"hit rate\" demonstrates that many genes can alter normal sleep behaviors through a variety of mechanisms. Further investigation of these genes may provide insight into the pathways regulating sleep, functional aspects of sleep, or indirect potentially pathological processes that alter normal sleep.

neuroscience↗

Identification of slow-cycling germline stem cells and their regulation by PLZF

Long-term maintenance of spermatogenesis in mammals is supported by GDNF, an essential growth factor required for spermatogonial stem cell (SSC) self-renewal. Exploiting a transgenic GDNF overexpression model, which expands and normalizes the pool of undifferentiated spermatogonia between Plzf+/+ and Plzflu/lu mice, we used RNAseq to identify a rare subpopulation of cells that express EOMES, a T-box transcription factor. Lineage tracing and busulfan challenge show that these are long-term SSCs that contribute to steady state spermatogenesis as well as regeneration following chemical injury. EOMES+ SSCs have a lower proliferation index than EOMES- GFRA1+ spermatogonia in wild-type but not in Plzflu/lu mice. This comparison demonstrates that PLZF regulates their proliferative activity and suggests that EOMES+ SSCs are lost through proliferative exhaustion in Plzflu/lu mice. Single cell RNA sequencing of EOMES+ cells from Plzf+/+ and Plzflu/lu mice support a hierarchical model of both slow- and rapid-cycling SSCs.

developmental biology↗

Robust Mouse Tracking in Complex Environments using Neural Networks

The ability to track animals accurately is critical for behavioral experiments. For video-based assays, this is often accomplished by manipulating environmental conditions to increase contrast between the animal and the background, in order to achieve proper foreground/background detection (segmentation). However, as behavioral paradigms become more sophisticated with ethologically relevant environments, the approach of modifying environmental conditions offers diminishing returns, particularly for scalable experiments. Currently, there is a need for methods to monitor behaviors over long periods of time, under dynamic environmental conditions, and in animals that are genetically and behaviorally heterogeneous. To address this need, we developed a state-of-the-art neural network-based tracker for mice, using modern machine vision techniques. We test three different neural network architectures to determine their performance on genetically diverse mice under varying environmental conditions. We find that an encoder-decoder segmentation neural network achieves high accuracy and speed with minimal training data. Furthermore, we provide a labeling interface, labeled training data, tuned hyperparameters, and a pre-trained network for the mouse behavior and neuroscience communities. This general-purpose neural network tracker can be easily extended to other experimental paradigms and even to other animals, through transfer learning, thus providing a robust, generalizable solution for biobehavioral research.

animal behavior and cognition↗

Large-scale discovery of mouse transgenic integration sites reveals frequent structural variation and insertional mutagenesis

Transgenesis has been a mainstay of mouse genetics for over 30 years, providing numerous models of human disease and critical genetic tools in widespread use today. Generated through the random integration of DNA fragments into the host genome, transgenesis can lead to insertional mutagenesis if a coding gene or essential element is disrupted, and there is evidence that larger scale structural variation can accompany the integration. The insertion sites of only a tiny fraction of the thousands of transgenic lines in existence have been discovered and reported due in part to limitations in the discovery tools. Targeted Locus Amplification (TLA) provides a robust and efficient means to identify both the insertion site and content of transgenes through deep sequencing of genomic loci linked to specific known transgene cassettes. Here, we report the first large-scale analysis of transgene insertion sites from 40 highly used transgenic mouse lines. We show that the transgenes disrupt the coding sequence of endogenous genes in half of the lines, frequently involving large deletions and/or structural variations at the insertion site. Furthermore, we identify a number of unexpected sequences in some of the transgenes, including undocumented cassettes and contaminating DNA fragments. We demonstrate that these transgene insertions can have phenotypic consequences, which could confound certain experiments, emphasizing the need for careful attention to control strategies. Together, these data show that transgenic alleles display a high rate of potentially confounding genetic events, and highlight the need for careful characterization of each line to assure interpretable and reproducible experiments.

genetics↗