Ciliary ARL13B inhibits developmental kidney cystogenesis in mouse.

ARL13B is a small GTPase enriched in cilia. Deletion of Arl13b in mouse kidney results in renal cysts and an associated absence of primary cilia. Similarly, ablation of cilia leads to kidney cysts. To investigate whether ARL13B functions from within cilia to direct kidney development, we examined kidneys of mice expressing an engineered cilia-excluded ARL13B variant, ARL13BV358A. These mice retained renal cilia and developed cystic kidneys. Because ARL13B functions as a guanine nucleotide exchange factor (GEF) for ARL3, we examined kidneys of mice expressing an ARL13B variant that lacks ARL3 GEF activity, ARL13BR79Q. We found normal kidney development with no evidence of cysts in these mice. Taken together, our results show that ARL13B functions within cilia to inhibit renal cystogenesis during mouse development, and that this function does not depend on its role as a GEF for ARL3.

GRK2 Kinases in the Primary Cilium Initiate SMOOTHENED-PKA Signaling in the Hedgehog Cascade.

During Hedgehog (Hh) signal transduction in development and disease, the atypical G protein-coupled receptor (GPCR) SMOOTHENED (SMO) communicates with GLI transcription factors by binding the protein kinase A catalytic subunit (PKA-C) and physically blocking its enzymatic activity. Here we show that GPCR kinase 2 (GRK2) orchestrates this process during endogenous Hh pathway activation in the primary cilium. Upon SMO activation, GRK2 rapidly relocalizes from the ciliary base to the shaft, triggering SMO phosphorylation and PKA-C interaction. Reconstitution studies reveal that GRK2 phosphorylation enables active SMO to bind PKA-C directly. Lastly, the SMO-GRK2-PKA pathway underlies Hh signal transduction in a range of cellular and in vivo models. Thus, GRK2 phosphorylation of ciliary SMO, and the ensuing PKA-C binding and inactivation, are critical initiating events for the intracellular steps in Hh signaling. More broadly, our study suggests an expanded role for GRKs in enabling direct GPCR interactions with diverse intracellular effectors.

Ciliary ARL13B inhibits developmental kidney cystogenesis in mouse.

ARL13B is a small GTPase enriched in cilia. Deletion of Arl13b in mouse kidney results in renal cysts and an associated absence of primary cilia. Similarly, ablation of cilia leads to kidney cysts. To investigate whether ARL13B functions from within cilia to direct kidney development, we examined kidneys of mice expressing an engineered cilia-excluded ARL13B variant, ARL13BV358A. These mice retained renal cilia and developed cystic kidneys. Because ARL13B functions as a guanine nucleotide exchange factor (GEF) for ARL3, we examined kidneys of mice expressing an ARL13B variant that lacks ARL3 GEF activity, ARL13BR79Q. We found normal kidney development with no evidence of cysts in these mice. Taken together, our results show that ARL13B functions within cilia to inhibit renal cystogenesis during mouse development, and that this function does not depend on its role as a GEF for ARL3.

Zebrafish, Danio rerio, Skin Mucus Harbors a Distinct Bacterial Community Dominated by Actinobacteria.

The skin mucus of teleost fish harbors a complex microbial community that is continually interacting with the aquatic environment. Despite zebrafish, Danio rerio, serving as a model organism in a myriad of research fields, very little is known about the composition and role of the skin mucus microbiome. The purpose of this study was to determine a simple sampling method for the skin mucus microbiome, identify prominent bacterial members, and compare its composition to the microbial community of the surrounding environment. Next-generation sequencing of the V3-V4 region of the 16S rRNA gene was performed on skin mucus and filtered tank water samples. Results show that prominent bacterial members of the skin mucus in zebrafish include Actinobacteria (Mycobacteriaceae) and Gammaproteobacteria (Aeromonadaceae), followed by Alphaproteobacteria and Betaproteobacteria. The tank water contained much higher bacterial diversity and was clearly different from the skin mucus microbiome, despite continuous interaction. This study identifies a straightforward sampling method for the zebrafish skin mucus microbiome, enabling hypothesis generation on the role of ectosymbionts on host and microbiome health.

Smoothened and ARL13B are critical in mouse for superior cerebellar peduncle targeting.

Patients with the ciliopathy Joubert syndrome present with physical anomalies, intellectual disability, and a hindbrain malformation described as the "molar tooth sign" due to its appearance on an MRI. This radiological abnormality results from a combination of hypoplasia of the cerebellar vermis and inappropriate targeting of the white matter tracts of the superior cerebellar peduncles. ARL13B is a cilia-enriched regulatory GTPase established to regulate cell fate, cell proliferation, and axon guidance through vertebrate Hedgehog signaling. In patients, mutations in ARL13B cause Joubert syndrome. To understand the etiology of the molar tooth sign, we used mouse models to investigate the role of ARL13B during cerebellar development. We found that ARL13B regulates superior cerebellar peduncle targeting and these fiber tracts require Hedgehog signaling for proper guidance. However, in mouse, the Joubert-causing R79Q mutation in ARL13B does not disrupt Hedgehog signaling nor does it impact tract targeting. We found a small cerebellar vermis in mice lacking ARL13B function but no cerebellar vermis hypoplasia in mice expressing the Joubert-causing R79Q mutation. In addition, mice expressing a cilia-excluded variant of ARL13B that transduces Hedgehog normally showed normal tract targeting and vermis width. Taken together, our data indicate that ARL13B is critical for the control of cerebellar vermis width as well as superior cerebellar peduncle axon guidance, likely via Hedgehog signaling. Thus, our work highlights the complexity of ARL13B in molar tooth sign etiology.

Radiologist observations of computed tomography (CT) images predict treatment outcome in TB Portals, a real-world database of tuberculosis (TB) cases.

The TB Portals program provides a publicly accessible repository of TB case data containing multi-modal information such as case clinical characteristics, pathogen genomics, and radiomics. The real-world resource contains over 3400 TB cases, primarily drug resistant cases, and CT images with radiologist annotations are available for many of these cases. The breadth of data collected offers a patient-centric view into the etiology of the disease including the temporal context of the available imaging information. Here, we analyze a cohort of new TB cases with available radiologist observations of CTs taken around the time of initial registration of the case into the database and with available follow up to treatment outcome of cured or died. Follow up ranged from 5 weeks to a little over 2 years consistent with the longest treatment regimens for drug resistant TB and cases were registered within the years 2008 to 2019. The radiologist observations were incorporated into machine learning pipelines to test various class balancing strategies on the performance of predictive models. The modeling results support that the radiologist observations are predictive of treatment outcome. Moreover, inferential statistical analysis identifies markers of TB disease spread as having an association with poor treatment outcome including presence of radiologist observations in both lungs, swollen lymph nodes, multiple cavities, and large cavities. While the initial results are promising, further data collection is needed to incorporate methods to mitigate potential confounding such as including additional model covariates or matching cohorts on covariates of interest (e.g. demographics, BMI, comorbidity, TB subtype, etc.). Nonetheless, the preliminary results highlight the utility of the resource for hypothesis generation and exploration of potential biomarkers of TB disease severity and support these additional data collection efforts.

The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration.

OBJECTIVE: Clinical research informatics tools are necessary to support comprehensive studies of infectious diseases. The National Institute of Allergy and Infectious Diseases (NIAID) developed the publicly accessible Tuberculosis Data Exploration Portal (TB DEPOT) to address the complex etiology of tuberculosis (TB). MATERIALS AND METHODS: TB DEPOT displays deidentified patient case data and facilitates analyses across a wide range of clinical, socioeconomic, genomic, and radiological factors. The solution is built using Amazon Web Services cloud-based infrastructure, .NET Core, Angular, Highcharts, R, PLINK, and other custom-developed services. Structured patient data, pathogen genomic variants, and medical images are integrated into the solution to allow seamless filtering across data domains. RESULTS: Researchers can use TB DEPOT to query TB patient cases, create and save patient cohorts, and execute comparative statistical analyses on demand. The tool supports user-driven data exploration and fulfills the National Institute of Health's Findable, Accessible, Interoperable, and Reusable (FAIR) principles. DISCUSSION: TB DEPOT is the first tool of its kind in the field of TB research to integrate multidimensional data from TB patient cases. Its scalable and flexible architectural design has accommodated growth in the data, organizations, types of data, feature requests, and usage. Use of client-side technologies over server-side technologies and prioritizing maintenance have been important lessons learned. Future directions are dynamically prioritized and key functionality is shared through an application programming interface. CONCLUSION: This paper describes the platform development methodology, resulting functionality, benefits, and technical considerations of a clinical research informatics application to support increased understanding of TB.

Performance of Qure.ai automatic classifiers against a large annotated database of patients with diverse forms of tuberculosis.

Availability of trained radiologists for fast processing of CXRs in regions burdened with tuberculosis always has been a challenge, affecting both timely diagnosis and patient monitoring. The paucity of annotated images of lungs of TB patients hampers attempts to apply data-oriented algorithms for research and clinical practices. The TB Portals Program database (TBPP, https://TBPortals.niaid.nih.gov) is a global collaboration curating a large collection of the most dangerous, hard-to-cure drug-resistant tuberculosis (DR-TB) patient cases. TBPP, with 1,179 (83%) DR-TB patient cases, is a unique collection that is well positioned as a testing ground for deep learning classifiers. As of January 2019, the TBPP database contains 1,538 CXRs, of which 346 (22.5%) are annotated by a radiologist and 104 (6.7%) by a pulmonologist-leaving 1,088 (70.7%) CXRs without annotations. The Qure.ai qXR artificial intelligence automated CXR interpretation tool, was blind-tested on the 346 radiologist-annotated CXRs from the TBPP database. Qure.ai qXR CXR predictions for cavity, nodule, pleural effusion, hilar lymphadenopathy was successfully matching human expert annotations. In addition, we tested the 12 Qure.ai classifiers to find whether they correlate with treatment success (information provided by treating physicians). Ten descriptors were found as significant: abnormal CXR (p = 0.0005), pleural effusion (p = 0.048), nodule (p = 0.0004), hilar lymphadenopathy (p = 0.0038), cavity (p = 0.0002), opacity (p = 0.0006), atelectasis (p = 0.0074), consolidation (p = 0.0004), indicator of TB disease (p = < .0001), and fibrosis (p = < .0001). We conclude that applying fully automated Qure.ai CXR analysis tool is useful for fast, accurate, uniform, large-scale CXR annotation assistance, as it performed well even for DR-TB cases that were not used for initial training. Testing artificial intelligence algorithms (encapsulating both machine learning and deep learning classifiers) on diverse data collections, such as TBPP, is critically important toward progressing to clinically adopted automatic assistants for medical data analysis.

A retrospective genomic analysis of drug-resistant strains of M. tuberculosis in a high-burden setting, with an emphasis on comparative diagnostics and reactivation and reinfection status.

BACKGROUND: Recurrence of drug-resistant tuberculosis (DR-TB) after treatment occurs through relapse of the initial infection or reinfection by a new drug-resistant strain. Outbreaks of DR-TB in high burden regions present unique challenges in determining recurrence status for effective disease management and treatment. In the Republic of Moldova the burden of DR-TB is exceptionally high, with many cases presenting as recurrent. METHODS: We performed a retrospective analysis of Mycobacterium tuberculosis from Moldova to better understand the genomic basis of drug resistance and its effect on the determination of recurrence status in a high DR-burden environment. To do this we analyzed genomes from 278 isolates collected from 189 patients, including 87 patients with longitudinal samples. These pathogen genomes were sequenced using Illumina technology, and SNP panels were generated for each sample for use in phylogenetic and network analysis. Discordance between genomic resistance profiles and clinical drug-resistance test results was examined in detail to assess the possibility of mixed infection. RESULTS: There were clusters of multiple patients with 10 or fewer differences among DR-TB samples, which is evidence of person-to-person transmission of DR-TB. Analysis of longitudinally collected isolates revealed that many infections exhibited little change over time, though 35 patients demonstrated reinfection by divergent (number of differences > 10) lineages. Additionally, several same-lineage sample pairs were found to be more divergent than expected for a relapsed infection. Network analysis of the H3/4.2.1 clade found very close relationships among 61 of these samples, making differentiation of reactivation and reinfection difficult. There was discordance between genomic profile and clinical drug sensitivity test results in twelve samples, and four of these had low level (but not statistically significant) variation at DR SNPs suggesting low-level mixed infections. CONCLUSIONS: Whole-genome sequencing provided a detailed view of the genealogical structure of the DR-TB epidemic in Moldova, showing that reinfection may be more prevalent than currently recognized. We also found increased evidence of mixed infection, which could be more robustly characterized with deeper levels of genomic sequencing.

The ciliary phosphatidylinositol phosphatase Inpp5e plays positive and negative regulatory roles in Shh signaling.

Sonic hedgehog (Shh) signal transduction specifies ventral cell fates in the neural tube and is mediated by the Gli transcription factors that play both activator (GliA) and repressor (GliR) roles. Cilia are essential for Shh signal transduction and the ciliary phosphatidylinositol phosphatase Inpp5e is linked to Shh regulation. In the course of a forward genetic screen for recessive mouse mutants, we identified a functional null allele of inositol polyphosphate-5-phosphatase E (Inpp5e), ridge top (rdg), with expanded ventral neural cell fates at E10.5. By E12.5, Inpp5erdg/rdg embryos displayed normal neural patterning and this correction over time required Gli3, the predominant repressor in neural patterning. Inpp5erdg function largely depended on the presence of cilia and on smoothened, the obligate transducer of Shh signaling, indicating that Inpp5e functions within the cilium to regulate the pathway. These data indicate that Inpp5e plays a more complicated role in Shh signaling than previously appreciated. We propose that Inpp5e attenuates Shh signaling in the neural tube through regulation of the relative timing of GliA and GliR production, which is important in understanding how the duration of Shh signaling regulates neural tube patterning.

Comparative analysis of genomic variability for drug-resistant strains of Mycobacterium tuberculosis: The special case of Belarus.

Mycobacterium tuberculosis (M.tb) is the leading cause of death from an infectious disease. Drug resistant tuberculosis (DR-TB) threatens to exacerbate challenges in diagnostics and treatment. It is important to monitor strains circulating in countries with heavy burden of DR-TB, to make informed decisions about treatment, and because in these countries there is an elevated probability that DR-TB may advance to the totally drug resistant form. The TB Portals Program (TBPP, https://TBPortals.niaid.nih.gov) formed a global network of participating institutions and hospitals collecting and analyzing de-identified clinical, imaging and socioeconomic data, augmenting these with genomic sequencing results. TB Portals database includes complete M.tb genomes, with the information about spoligotypes, strains, and genomic variants related to drug resistance. Within the framework of TB Portals, we created Data Exploration Portal (DEPOT), to facilitate visualization and statistical analysis of user-defined cohorts from the entire TB Portals database. A continuing TB Portals research objective is to actively monitor and examine genomic variability that may account for observed differences in DR-TB incident rates and/or difficulties with diagnosis and treatment. Our analysis identified that several genomic variants implicated in drug resistance or improved fitness of the pathogen, were significantly more frequent in M.tb strains circulating in Belarus in comparison with other countries. Further studies are necessary to reveal whether the corresponding genomic variants may explain unusually high burden of drug-resistant M.tb in Belarus and suggest improvements for diagnostic and drug therapies.

TB DEPOT (Data Exploration Portal): A multi-domain tuberculosis data analysis resource.

The NIAID TB Portals Program (TBPP) established a unique and growing database repository of socioeconomic, geographic, clinical, laboratory, radiological, and genomic data from patient cases of drug-resistant tuberculosis (DR-TB). Currently, there are 2,428 total cases from nine country sites (Azerbaijan, Belarus, Moldova, Georgia, Romania, China, India, Kazakhstan, and South Africa), 1,611 (66%) of which are multidrug- or extensively-drug resistant and 1,185 (49%), 863 (36%), and 952 (39%) of which contain X-ray, computed tomography (CT) scan, and genomic data, respectively. We introduce the Data Exploration Portal (TB DEPOT, https://depot.tbportals.niaid.nih.gov) to visualize and analyze these multi-domain data. The TB DEPOT leverages the TBPP integration of clinical, socioeconomic, genomic, and imaging data into standardized formats and enables user-driven, repeatable, and reproducible analyses. It furthers the TBPP goals to provide a web-enabled analytics platform to countries with a high burden of multidrug-resistant TB (MDR-TB) but limited IT resources and inaccessible data, and enables the reusability of data, in conformity with the NIH's Findable, Accessible, Interoperable, and Reusable (FAIR) principles. TB DEPOT provides access to "analysis-ready" data and the ability to generate and test complex clinically-oriented hypotheses instantaneously with minimal statistical background and data processing skills. TB DEPOT is also promising for enhancing medical training and furnishing well annotated, hard to find, MDR-TB patient cases. TB DEPOT, as part of TBPP, further fosters collaborative research efforts to better understand drug-resistant tuberculosis and aid in the development of novel diagnostics and personalized treatment regimens.

Hypomorphic Smo mutant with inefficient ciliary enrichment disrupts the highest level of vertebrate Hedgehog response.

Smoothened (Smo) is the essential transducer of Sonic hedgehog (Shh) signaling, which regulates cell fate and proliferation during embryogenesis. We identified a novel mouse mutant, cabbie (cbb), and found that its cause is a missense mutation in Smo. We showed the Smocbb mutation is insensitive to the Shh agonist SAG, perhaps due to the disruption of SAG binding. We characterized Smocbb for defects in craniofacial and skeletal development, as well as neural tube patterning, and revealed Smocbb affected processes that require the highest levels of Shh activity. Smo is normally enriched in cilia upon Shh stimulation; however, we detected inefficient enrichment of Smo in Smocbb mutants whether we stimulated with Shh or SAG. Taken together, our data suggest that the highest levels of vertebrate Hedgehog signaling activity require efficient Smo ciliary enrichment.

Disruption of the ciliary GTPase Arl13b suppresses Sonic hedgehog overactivation and inhibits medulloblastoma formation.

Medulloblastoma (MB) is the most common malignant pediatric brain tumor, and overactivation of the Sonic Hedgehog (Shh) signaling pathway, which requires the primary cilium, causes 30% of MBs. Current treatments have known negative side effects or resistance mechanisms, so new treatments are necessary. Shh signaling mutations, like those that remove Patched1 (Ptch1) or activate Smoothened (Smo), cause tumors dependent on the presence of cilia. Genetic ablation of cilia prevents these tumors by removing Gli activator, but cilia are a poor therapeutic target since they support many biological processes. A more appropriate strategy would be to identify a protein that functionally disentangles Gli activation and ciliogenesis. Our mechanistic understanding of the ciliary GTPase Arl13b predicts that it could be such a target. Arl13b mutants retain short cilia, and loss of Arl13b results in ligand-independent, constitutive, low-level pathway activation but prevents maximal signaling without disrupting Gli repressor. Here, we show that deletion of Arl13b reduced Shh signaling levels in the presence of oncogenic SmoA1, suggesting Arl13b acts downstream of known tumor resistance mechanisms. Knockdown of ARL13B in human MB cell lines and in primary mouse MB cell culture decreased proliferation. Importantly, loss of Arl13b in a Ptch1-deleted mouse model of MB inhibited tumor formation. Postnatal depletion of Arl13b does not lead to any overt phenotypes in the epidermis, liver, or cerebellum. Thus, our in vivo and in vitro studies demonstrate that disruption of Arl13b inhibits cilia-dependent oncogenic Shh overactivation.

A novel homozygous ARL13B variant in patients with Joubert syndrome impairs its guanine nucleotide-exchange factor activity.

ARL13B encodes for the ADP-ribosylation factor-like 13B GTPase, which is required for normal cilia structure and Sonic hedgehog (Shh) signaling. Disruptions in cilia structure or function lead to a class of human disorders called ciliopathies. Joubert syndrome is characterized by a wide spectrum of symptoms, including a variable degree of intellectual disability, ataxia, and ocular abnormalities. Here we report a novel homozygous missense variant c.[223G>A] (p.(Gly75Arg) in the ARL13B gene, which was identified by whole-exome sequencing of a trio from a consanguineous family with multiple-affected individuals suffering from intellectual disability, ataxia, ocular defects, and epilepsy. The same variant was also identified in a second family. We saw a striking difference in the severity of ataxia between affected male and female individuals in both families. Both ARL13B and ARL13B-c.[223G>A] (p.(Gly75Arg) expression rescued the cilia length and Shh defects displayed by Arl13b hennin (null) cells, indicating that the variant did not disrupt either ARL13B function. In contrast, ARL13B-c.[223G>A] (p.(Gly75Arg) displayed a marked loss of ARL3 guanine nucleotide-exchange factor activity, with retention of its GTPase activities, highlighting the correlation between its loss of function as an ARL3 guanine nucleotide-exchange factor and Joubert syndrome.

The TB Portals: an Open-Access, Web-Based Platform for Global Drug-Resistant-Tuberculosis Data Sharing and Analysis.

The TB Portals program is an international consortium of physicians, radiologists, and microbiologists from countries with a heavy burden of drug-resistant tuberculosis working with data scientists and information technology professionals. Together, we have built the TB Portals, a repository of socioeconomic/geographic, clinical, laboratory, radiological, and genomic data from patient cases of drug-resistant tuberculosis backed by shareable, physical samples. Currently, there are 1,299 total cases from five country sites (Azerbaijan, Belarus, Moldova, Georgia, and Romania), 976 (75.1%) of which are multidrug or extensively drug resistant and 38.2%, 51.9%, and 36.3% of which contain X-ray, computed tomography (CT) scan, and genomic data, respectively. The top Mycobacterium tuberculosis lineages represented among collected samples are Beijing, T1, and H3, and single nucleotide polymorphisms (SNPs) that confer resistance to isoniazid, rifampin, ofloxacin, and moxifloxacin occur the most frequently. These data and samples have promoted drug discovery efforts and research into genomics and quantitative image analysis to improve diagnostics while also serving as a valuable resource for researchers and clinical providers. The TB Portals database and associated projects are continually growing, and we invite new partners and collaborations to our initiative. The TB Portals data and their associated analytical and statistical tools are freely available at https://tbportals.niaid.nih.gov/.

Mutation of murine Sox4 untranslated regions results in partially penetrant perinatal lethality.

BACKGROUND: Sox4 is an essential gene, and genetic deletion results in embryonic lethality. In an effort to develop mice with tissue-specific deletion, we bred conditional knockout mice bearing LoxP recombination sites flanking the Sox4 gene, with the LoxP sites located in the Sox4 5'UTR and 3'UTR. RESULTS: The number of mice homozygous for this LoxP-flanked conditional knockout allele was far below the expected number, suggesting embryonic lethality with reduced penetrance. From over 200 animals bred, only 11% were homozygous Sox4(flox/flox) mice, compared to the expected Mendelian ratio of 25% (p<0.001). Moreover, there was a significant reduction in the number of female Sox4(flox/flox) mice (26%) relative to male Sox4(flox/flox) mice (p=0.0371). Reduced Sox4 expression in homozygous embryos was confirmed by in-situ hybridization and Quantitative real-time polymerase chain reaction (QPCR). CONCLUSION: LoxP sites in the 5' and 3' UTR of both alleles of Sox4 resulted in reduced, but variable expression of Sox4 message.

Defective Nodal and Cerl2 expression in the Arl13b(hnn) mutant node underlie its heterotaxia.

Specification of the left-right axis during embryonic development is critical for the morphogenesis of asymmetric organs such as the heart, lungs, and stomach. The first known left-right asymmetry to occur in the mouse embryo is a leftward fluid flow in the node that is created by rotating cilia on the node surface. This flow is followed by asymmetric expression of Nodal and its inhibitor Cerl2 in the node. Defects in cilia and/or fluid flow in the node lead to defective Nodal and Cerl2 expression and therefore incorrect visceral organ situs. Here we show the cilia protein Arl13b is required for left right axis specification as its absence results in heterotaxia. We find the defect originates in the node where Cerl2 is not downregulated and asymmetric expression of Nodal is not maintained resulting in symmetric expression of both genes. Subsequently, Nodal expression is delayed in the lateral plate mesoderm (LPM). Symmetric Nodal and Cerl2 in the node could result from defects in either the generation and/ or the detection of Nodal flow, which would account for the subsequent defects in the LPM and organ positioning.

Multiplex Chromosomal Exome Sequencing Accelerates Identification of ENU-Induced Mutations in the Mouse.

Forward genetic screens in Mus musculus have proved powerfully informative by revealing unsuspected mechanisms governing basic biological processes. This approach uses potent chemical mutagens, such as N-ethyl-N-nitrosourea (ENU), to randomly induce mutations in mice, which are then bred and phenotypically screened to identify lines that disrupt a specific biological process of interest. Although identifying a mutation using the rich resources of mouse genetics is straightforward, it is unfortunately neither fast nor cheap. Here we show that detecting newly induced causal variants in a forward genetic screen can be accelerated dramatically using a methodology that combines multiplex chromosome-specific exome capture, next-generation sequencing, rapid mapping, sequence annotation, and variation filtering. The key innovation of our method is multiplex capture and sequence that allows the simultaneous survey of both mutant, parental, and background strains in a single experiment. By comparing variants identified in mutant offspring with those found in dbSNP, the unmutagenized background strains, and parental lines, induced causative mutations can be distinguished immediately from preexisting variation or experimental artifact. Here we demonstrate this approach to find the causative mutations induced in four novel ENU lines identified from a recent ENU screen. In all four cases, after applying our method, we found six or fewer putative mutations (and sometimes only a single one). Determining the causative variant was then easily achieved through standard segregation approaches. We have developed this process into a community resource that will speed up individual labs' ability to identify the genetic lesion in mutant mouse lines; all of our reagents and software tools are open source and available to the broader scientific community.