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Among the estimated ~23,000 protein encoding human genes, the class of ‘druggable genes’– defined by their ability to bind drug-like compounds– represents an enticing collection of targets for clinical intervention. Yet many if not most of these genes remain poorly understood and understudied. Here we evaluate three major classes of druggable genes (GPCRs, ion channels, and kinases) and found that a third of these remain largely ignored yet display significant mouse phenotypes upon genetic ablation. We show that both well-studied and understudied druggable genes share a similar number and spectrum of phenotypes. Moreover, many of the mouse phenotypes arising from the ablation of both well-studied and understudied druggable genes show similarities with symptoms in rare human diseases. Collectively these data diminish the notion that most poorly studied genes may not be especially ‘important’ and highlight therapeutic opportunities and potential disease models among poorly characterized druggable genes.

The International Mouse Phenotyping Consortium (IMPC) is generating and phenotyping null mutations for every protein-coding gene in the mouse1,2. The IMPC now uses Cas9, a programmable RNA-guided nuclease that has revolutionized mouse genome editing3 and 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 >3,300 knockout mouse lines using comparable protocols provides a rich dataset to analyze experimental and biological variables affecting in vivo null allele 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. Our analysis identified that whether a gene is essential for viability was the primary factor influencing successful production of null alleles. Collectively, our findings provide best practice recommendations for generating null alleles in mice using Cas9; these recommendations may be applicable to other allele types and species.

PurposeArap1 is an Arf-directed GTPase-activating protein (GAP) shown to modulate actin cytoskeletal dynamics by regulating Arf and Rho family members. We have previously shown that Arap1-/- mice develop photoreceptor degeneration similar to the human condition retinitis pigmentosa (RP), corroborated by fundus examination, histopathology, and ERG analysis. However, Arap1 expression was not detected in photoreceptors, but in Müller Glia and retinal pigment epithelium (RPE), suggesting a non-cell-autonomous mechanism for degeneration. The aim of this study was to elucidate the role of retinal Arap1 in photoreceptor maintenance.MethodsAlbino Arap1-/- mice were generated via breeding pigmented Arap1-/- mice onto a Tyr-/- C57BL/6J background. Conditional knockout (cKO) mice were generated for Müller Glia/RPE, Müller Glia, and RPE via targeting Cralbp, Glast, and Vmd2 promoters, respectively, to drive Cre recombinase expression to knock out Arap1. Mice were analyzed by fundus photography, optical coherence tomography (OCT), histology, and immunohistochemistry. Arap1 binding partners were assayed by affinity purification mass spectrometry.ResultsVmd2-Cre Arap1tm1c/tm1c and Cralbp-Cre Arap1tm1c/tm1c mice, but not Glast-Cre Arap1tm1c/tm1c mice, recapitulated the photoreceptor degeneration phenotype originally observed in germline Arap1−/− mice. These findings were corroborated by fundus exam, OCT, and histological analysis. Mass spectrometry analysis of ARAP1 co-immunoprecipitation identified putative binding partners of ARAP1, revealing numerous interactants involved in phagocytosis, cytoskeletal composition, intracellular trafficking, and endocytosis. Quantification of rod outer segment (OS) phagocytosis in vivo demonstrated a clear phagocytic defect in Arap1−/− mice compared to Arap1+/+ littermate controls while cone phagocytosis was preserved.ConclusionsArap1 expression, specifically in RPE, is necessary for photoreceptor survival due to its indispensable function in RPE phagocytosis. We propose a model in which Arap1 regulates G-protein function for nonmuscle myosin II targeting during phagocytosis. This novel role of Arap1 is important for further understanding of both the diversity of its functions and the complex molecular regulation of RPE phagocytosis.

Author(s): Rajderkar, Sudha; Barozzi, Iros; Zhu, Yiwen; Hu, Rong; Zhang, Yanxiao; Li, Bin; Fukuda-Yuzawa, Yoko; Kelman, Guy; Akeza, Adyam; Blow, Matthew; Pham, Quan; Harrington, Anne; Godoy, Janeth; Meky, Eman; von Maydell, Kianna; Novak, Catherine; Plajzer-Frick, Ingrid; Afzal, Veena; Tran, Stella; Talkowski, Michael; Kent Lloyd, KC; Ren, Bing; Dickel, Diane; Visel, Axel; Pennacchio, Len | Abstract: Summary Topologically associating domain (TAD) boundaries are thought to partition the genome into distinct regulatory territories. Anecdotal evidence suggests that their disruption may interfere with normal gene expression and cause disease phenotype 1–3 , but the overall extent to which this occurs remains unknown. Here we show that TAD boundary deletions commonly disrupt normal genome function in vivo . We used CRISPR genome editing in mice to individually delete eight TAD boundaries (11-80kb in size) from the genome in mice. All deletions examined resulted in at least one detectable molecular or organismal phenotype, which included altered chromatin interactions or gene expression, reduced viability, and anatomical phenotypes. For 5 of 8 (62%) loci examined, boundary deletions were associated with increased embryonic lethality or other developmental phenotypes. For example, a TAD boundary deletion near Smad3/Smad6 caused complete embryonic lethality, while a deletion near Tbx5/Lhx5 resulted in a severe lung malformation. Our findings demonstrate the importance of TAD boundary sequences for in vivo genome function and suggest that noncoding deletions affecting TAD boundaries should be carefully considered for potential pathogenicity in clinical genetics screening.

Simple Summary Collar-mounted activity monitors using battery-powered accelerometers can continuously and accurately analyze specific canine behaviors and activity levels. These include normal behaviors and those that are indicators of disease conditions such as scratching, inappetence, excessive weight, or osteoarthritis. Algorithms used to analyze activity data are validated by video recordings of specific canine behaviors, which were used to label accelerometer data. The study described here was noteworthy for the large volume of data collected from more than 2500 dogs in clinical and real-world home settings. The accelerometer data were analyzed by a machine learning methodology, whereby algorithms were continually updated as additional data were acquired. The study determined that algorithms from the accelerometer data detected eating and drinking behaviors with a high degree of accuracy. Accurate detection of other behaviors such as licking, petting, rubbing, scratching, and sniffing was also demonstrated. The study confirmed that activity monitors using validated algorithms can accurately detect important health-related canine behaviors via a collar-mounted accelerometer. The validated algorithms have widespread practical benefits when used in commercially available canine activity monitors. Abstract Collar-mounted canine activity monitors can use accelerometer data to estimate dog activity levels, step counts, and distance traveled. With recent advances in machine learning and embedded computing, much more nuanced and accurate behavior classification has become possible, giving these affordable consumer devices the potential to improve the efficiency and effectiveness of pet healthcare. Here, we describe a novel deep learning algorithm that classifies dog behavior at sub-second resolution using commercial pet activity monitors. We built machine learning training databases from more than 5000 videos of more than 2500 dogs and ran the algorithms in production on more than 11 million days of device data. We then surveyed project participants representing 10,550 dogs, which provided 163,110 event responses to validate real-world detection of eating and drinking behavior. The resultant algorithm displayed a sensitivity and specificity for detecting drinking behavior (0.949 and 0.999, respectively) and eating behavior (0.988, 0.983). We also demonstrated detection of licking (0.772, 0.990), petting (0.305, 0.991), rubbing (0.729, 0.996), scratching (0.870, 0.997), and sniffing (0.610, 0.968). We show that the devices’ position on the collar had no measurable impact on performance. In production, users reported a true positive rate of 95.3% for eating (among 1514 users), and of 94.9% for drinking (among 1491 users). The study demonstrates the accurate detection of important health-related canine behaviors using a collar-mounted accelerometer. We trained and validated our algorithms on a large and realistic training dataset, and we assessed and confirmed accuracy in production via user validation.

CRISPR-Cas9 gene editing technology has considerably facilitated the generation of mouse knockout alleles, relieving many of the cumbersome and time-consuming steps of traditional mouse embryonic stem cell technology. However, the generation of conditional knockout alleles remains an important challenge. An earlier study reported up to 16% efficiency in generating conditional knockout alleles in mice using 2 single guide RNAs (sgRNA) and 2 single-stranded oligonucleotides (ssODN) (2sgRNA-2ssODN). We re-evaluated this method from a large data set generated from a consortium consisting of 17 transgenic core facilities or laboratories or programs across the world. The dataset constituted 17,887 microinjected or electroporated zygotes and 1,718 live born mice, of which only 15 (0.87%) mice harbored 2 correct LoxP insertions in cis configuration indicating a very low efficiency of the method. To determine the factors required to successfully generate conditional alleles using the 2sgRNA-2ssODN approach, we performed a generalized linear regression model. We show that factors such as the concentration of the sgRNA, Cas9 protein or the distance between the placement of LoxP insertions were not predictive for the success of this technique. The major predictor affecting the method’s success was the probability of simultaneously inserting intact proximal and distal LoxP sequences, without the loss of the DNA segment between the two sgRNA cleavage sites. Our analysis of a large data set indicates that the 2sgRNA–2ssODN method generates a large number of undesired alleles (>99%), and a very small number of desired alleles (