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Significance Acute myeloid leukemia (AML) is the most common acute leukemia in adults, with a 5-y survival of 29%. Immunotherapy is based on the premise that tumors suppress the immune system. We investigated the status of T cell immunity in AML at the time of diagnosis. We found a significant association between T cell percentage in the bone marrow and overall survival in newly diagnosed AML patients. When we evaluated the T cells from the bone marrow of patients with AML, one-third displayed profound functional impairment. Most of these compromised T cells, however, could be rescued using checkpoint inhibitors. Our results support the development of immune checkpoint therapy to combat this deadly disease., Acute myeloid leukemia (AML) is the most common acute leukemia in adults, with approximately four new cases per 100,000 persons per year. Standard treatment for AML consists of induction chemotherapy with remission achieved in 50 to 75% of cases. Unfortunately, most patients will relapse and die from their disease, as 5-y survival is roughly 29%. Therefore, other treatment options are urgently needed. In recent years, immune-based therapies have led to unprecedented rates of survival among patients with some advanced cancers. Suppression of T cell function in the tumor microenvironment is commonly observed and may play a role in AML. We found that there is a significant association between T cell infiltration in the bone marrow microenvironment of newly diagnosed patients with AML and increased overall survival. Functional studies aimed at establishing the degree of T cell suppression in patients with AML revealed impaired T cell function in many patients. In most cases, T cell proliferation could be restored by blocking the immune checkpoint molecules PD-1, CTLA-4, or TIM3. Our data demonstrate that AML establishes an immune suppressive environment in the bone marrow, in part through T cell checkpoint function.

Inherited predisposition to myeloid malignancies is more common than previously appreciated. We analyzed the whole-exome sequencing data of paired leukemia and skin biopsy samples from 391 adult patients from the Beat AML 1.0 consortium. Using the 2015 American College of Medical Genetics and Genomics (ACMG) guidelines for variant interpretation, we curated 1547 unique variants from 228 genes. The pathogenic/likely pathogenic (P/LP) germline variants were identified in 53 acute myeloid leukemia (AML) patients (13.6%) in 34 genes, including 6.39% (25/391) of patients harboring P/LP variants in genes considered clinically actionable (tier 1). 41.5% of the 53 patients with P/LP variants were in genes associated with the DNA damage response. The most frequently mutated genes were CHEK2 (8 patients) and DDX41 (7 patients). Pathogenic germline variants were also found in new candidate genes (DNAH5, DNAH9, DNMT3A, and SUZ12). No strong correlation was found between the germline mutational rate and age of AML onset. Among 49 patients who have a reported history of at least one family member affected with hematological malignancies, 6 patients harbored known P/LP germline variants and the remaining patients had at least one variant of uncertain significance, suggesting a need for further functional validation studies. Using CHEK2 as an example, we show that three-dimensional protein modeling can be one of the effective methodologies to prioritize variants of unknown significance for functional studies. Further, we evaluated an in silico approach that applies ACMG curation in an automated manner using the tool for assessment and (TAPES) prioritization in exome studies, which can minimize manual curation time for variants. Overall, our findings suggest a need to comprehensively understand the predisposition potential of many germline variants in order to enable closer monitoring for disease management and treatment interventions for affected patients and families.

Sarbecovirus (CoV) infections, including Severe Acute Respiratory CoV (SARS-CoV) and SARS-CoV-2, are considerable human threats. Human GWAS studies have recently identified loci associated with variation in SARS-CoV-2 susceptibility. However, genetically tractable models that reproduce human CoV disease outcomes are needed to mechanistically evaluate genetic determinants of CoV susceptibility. We used the Collaborative Cross (CC) and human GWAS datasets to elucidate host susceptibility loci that regulate CoV infections and to identify host quantitative trait loci that modulate severe CoV and pan-CoV disease outcomes including a major disease regulating loci including CCR9. CCR9 ablation resulted in enhanced titer, weight loss, respiratory dysfunction, mortality, and inflammation, providing mechanistic support in mitigating protection from severe SARS-CoV-2 pathogenesis across species. This study represents a comprehensive analysis of susceptibility loci for an entire genus of human pathogens conducted, identifies a large collection of susceptibility loci and candidate genes that regulate multiple aspects type-specific and cross-CoV pathogenesis, and also validates the paradigm of using the CC platform to identify common cross-species susceptibility loci and genes for newly emerging and pre-epidemic viruses.

Invadopodia are actin-based proteolytic membrane protrusions required for invasive behavior and tumor growth. In this study, we used our high-content screening assay to identify kinases whose activity affects invadopodia formation. Among the top hits selected for further analysis was TAO3, an STE20-like kinase of the GCK subfamily. TAO3 was overexpressed in many human cancers and regulated invadopodia formation in melanoma, breast, and bladder cancers. Furthermore, TAO3 catalytic activity facilitated melanoma growth in three-dimensional matrices and in vivo. A novel, potent catalytic inhibitor of TAO3 was developed that inhibited invadopodia formation and function as well as tumor cell extravasation and growth. Treatment with this inhibitor demonstrated that TAO3 activity is required for endosomal trafficking of TKS5α, an obligate invadopodia scaffold protein. A phosphoproteomics screen for TAO3 substrates revealed the dynein subunit protein LIC2 as a relevant substrate. Knockdown of LIC2 or expression of a phosphomimetic form promoted invadopodia formation. Thus, TAO3 is a new therapeutic target with a distinct mechanism of action. Significance: An unbiased screening approach identifies TAO3 as a regulator of invadopodia formation and function, supporting clinical development of this class of target.

The COVID-19 pandemic has revealed that infection with SARS-CoV-2 can result in a wide range of clinical outcomes in humans. An incomplete understanding of immune correlates of protection represents a major barrier to the design of vaccines and therapeutic approaches to prevent infection or limit disease. This deficit is largely due to the lack of prospectively collected, pre-infection samples from individuals that go on to become infected with SARS-CoV-2. Here, we utilized data from genetically diverse Collaborative Cross (CC) mice infected with SARS-CoV to determine whether baseline T cell signatures are associated with a lack of viral control and severe disease upon infection. SARS-CoV infection of CC mice results in a variety of viral load trajectories and disease outcomes. Overall, a dysregulated, pro-inflammatory signature of circulating T cells at baseline was associated with severe disease upon infection. Our study serves as proof of concept that circulating T cell signatures at baseline can predict clinical and virologic outcomes upon SARS-CoV infection. Identification of basal immune predictors in humans could allow for identification of individuals at highest risk of severe clinical and virologic outcomes upon infection, who may thus most benefit from available clinical interventions to restrict infection and disease., Author summary We used a screen of genetically diverse mice from the Collaborative Cross infected with mouse-adapted SARS-CoV in combination with comprehensive pre-infection immunophenotyping to identify baseline circulating immune correlates of severe virologic and clinical outcomes upon SARS-CoV infection.

When the COVID-19 pandemic began, formal frameworks to collect data about affected patients were lacking. The COVID-19 and Cancer Consortium (CCC19) was formed to collect granular data on patients with cancer and COVID-19 at scale and as rapidly as possible. CCC19 has grown from five initial institutions to 125 institutions with >400 collaborators. More than 5,000 cases with complete baseline data have been accrued. Future directions include increased electronic health record integration for direct data ingestion, expansion to additional domestic and international sites, more intentional patient involvement, and granular analyses of still-unanswered questions related to cancer subtypes and treatments.

SUMMARY Programmable RNA editing is gaining momentum as an approach to repair mutations, but its efficiency in repairing endogenous mutant RNA in complex tissue is unknown. Here we apply this approach to the brain and successfully repair a guanosine-to-adenosine mutation in methyl CpG binding protein 2 RNA that causes the neurodevelopmental disease Rett syndrome. Repair is mediated by hippocampal injections of juvenile Mecp2317G>A mice with an adeno-associated virus expressing the hyperactive catalytic domain of adenosine deaminase acting on RNA 2 and Mecp2 guide. After 1 month, 50% of Mecp2 RNA is recoded in three different hippocampal neuronal populations. MeCP2 protein localization to heterochromatin is restored in neurons to 50% of wild-type levels. Whole-transcriptome RNA analysis of one neuronal population indicates that the majority of off-target editing sites exhibit rates of 30% or less. This study demonstrates that programmable RNA editing can be utilized to repair mutations in mouse models of neurological disease., Graphical Abstract, In Brief Sinnamon et al. show that the Mecp2 guide-targeted “editase,” introduced by an adeno-associated virus into the hippocampus of a Rett syndrome mouse model, repairs a large fraction of pathological Mecp2G>A RNA. MeCP2 function, visualized by chromatin association in neurons, is repaired to similar levels. The results point toward a potential therapy for Rett syndrome.

Much of what is known about the neurotrophic receptor tyrosine kinase (NTRK) genes in cancer was revealed through identification and characterization of activating Trk fusions across many tumor types. A resurgence of interest in these receptors has emerged owing to the realization that they are promising therapeutic targets. The remarkable efficacy of pan-Trk inhibitors larotrectinib and entrectinib in clinical trials led to their accelerated, tissue-agnostic US Food and Drug Administration (FDA) approval for adult and pediatric patients with Trk-driven solid tumors. Despite our enhanced understanding of Trk biology in solid tumors, the importance of Trk signaling in hematological malignancies is underexplored and warrants further investigation. Herein, we describe mutations in NTRK2 and NTRK3 identified via deep sequencing of 185 patients with hematological malignancies. Ten patients contained a point mutation in NTRK2 or NTRK3; among these, we identified 9 unique point mutations. Of these 9 mutations, 4 were oncogenic (NTRK2A203T, NTRK2R458G, NTRK3E176D, and NTRK3L449F), determined via cytokine-independent cellular assays. Our data demonstrate that these mutations have transformative potential to promote downstream survival signaling and leukemogenesis. Specifically, the 3 mutations located within extracellular (ie, NTRK2A203T and NTRK3E176D) and transmembrane (ie, NTRK3L449F) domains increased receptor dimerization and cell-surface abundance. The fourth mutation, NTRK2R458G, residing in the juxtamembrane domain, activates TrkB via noncanonical mechanisms that may involve altered interactions between the mutant receptor and lipids in the surrounding environment. Importantly, these 4 activating mutations can be clinically targeted using entrectinib. Our findings contribute to ongoing efforts to define the mutational landscape driving hematological malignancies and underscore the utility of FDA-approved Trk inhibitors for patients with aggressive Trk-driven leukemias.

FLT3 mutations are prevalent in AML patients and confer poor prognosis. Crenolanib, a potent type I pan-FLT3 inhibitor, is effective against both internal tandem duplications and resistance-conferring tyrosine kinase domain mutations. While crenolanib monotherapy has demonstrated clinical benefit in heavily pretreated relapsed/refractory AML patients, responses are transient and relapse eventually occurs. Here, to investigate the mechanisms of crenolanib resistance, we perform whole exome sequencing of AML patient samples before and after crenolanib treatment. Unlike other FLT3 inhibitors, crenolanib does not induce FLT3 secondary mutations, and mutations of the FLT3 gatekeeper residue are infrequent. Instead, mutations of NRAS and IDH2 arise, mostly as FLT3-independent subclones, while TET2 and IDH1 predominantly co-occur with FLT3-mutant clones and are enriched in crenolanib poor-responders. The remaining patients exhibit post-crenolanib expansion of mutations associated with epigenetic regulators, transcription factors, and cohesion factors, suggesting diverse genetic/epigenetic mechanisms of crenolanib resistance. Drug combinations in experimental models restore crenolanib sensitivity. FLT3 is commonly mutated in acute myeloid leukaemia and treatment with FLT3 inhibitors often ends with relapse. Here, the authors perform exome sequencing of samples from patients treated with the FLT3 inhibitor, crenolanib, to show that resistance occurs due to diverse molecular mechanisms, not primarily due to secondary FLT3 mutations.

Summary Host genetic factors play a fundamental role in regulating humoral immunity to viral infection, including influenza A virus (IAV). Here, we utilize the Collaborative Cross (CC), a mouse genetic reference population, to study genetic regulation of variation in antibody response following IAV infection. CC mice show significant heritable variation in the magnitude, kinetics, and composition of IAV-specific antibody response. We map 23 genetic loci associated with this variation. Analysis of a subset of these loci finds that they broadly affect the antibody response to IAV as well as other viruses. Candidate genes are identified based on predicted variant consequences and haplotype-specific expression patterns, and several show overlap with genes identified in human mapping studies. These findings demonstrate that the host antibody response to IAV infection is under complex genetic control and highlight the utility of the CC in modeling and identifying genetic factors with translational relevance to human health and disease., Graphical Abstract, Highlights • Humoral response to influenza A virus varies across genetically diverse mice • Distinct genetic loci are important for different aspects of the humoral response • Loci that regulate antibody to influenza are also important for other pathogens • Comparison across datasets informs rational selection of candidate genes, Noll et al. use the Collaborative Cross, a mouse genetic reference population, to map genetic loci associated with variation in the humoral response to influenza virus infection. Cross-dataset comparison shows that mapped loci are important for antibody response to multiple pathogens, and candidate genes with likely translational relevance are identified.

Invadopodia are actin-based proteolytic membrane protrusions required for invasive behavior and tumor growth. We used our high-content screening assay to identify kinases impacting invadopodia formation. Among the top hits we selected TAO3, a STE20-like kinase of the GCK subfamily, for further analysis. TAO3 was over-expressed in many human cancers, and regulated invadopodia formation in melanoma, breast and bladder cancers. Furthermore, TAO3 catalytic activity facilitated melanoma growth in 3-dimensional matrices andin vivo. We developed potent catalytic inhibitors of TAO3 that inhibited invadopodia formation and function, and tumor cell extravasation and growth. Using these inhibitors, we determined that TAO3 activity was required for endosomal trafficking of TKS5α, an obligate invadopodia scaffold protein. A phosphoproteomics screen for TAO3 substrates revealed the dynein subunit protein LIC2 as a relevant substrate. Knockdown of LIC2 or expression of a phosphomimetic form promoted invadopodia formation. Thus, TAO3 is a new therapeutic target with a distinct mechanism of action.SIGNIFICANCETargeting tumor invasive behavior represents an understudied opportunity. We used an unbiased screening approach to identify kinases required for invadopodia formation and function. We validated TAO3, both genetically and with a novel inhibitor, and determined TAO3 function. Our data support clinical development of this class of target.

RNA base editing is gaining momentum as an approach to repair mutations, but its application to neurological disease has not been established. We have succeeded in directed transcript editing of a pathological mutation in a mouse model of the neurodevelopmental disease, Rett syndrome. Specifically, we directed editing of a guanosine to adenosine mutation in RNA encoding Methyl CpG Binding Protein 2 (MECP2). Repair was mediated by injecting the hippocampus of juvenile Rett mice with an adeno-associated virus expressing both an engineered enzyme containing the catalytic domain of Adenosine Deaminase Acting on RNA 2 and a Mecp2 targeting guide. After one month, 50% of Mecp2 RNA was recoded in three different hippocampal neuronal subtypes, and the ability of MeCP2 protein to associate with heterochromatin was similarly restored to 50% of wild-type levels. This study represents the first in vivo programmable RNA editing applied to a model of neurological disease.

Using incipient lines of the Collaborative Cross (CC), a murine genetic reference population, we previously identified a quantitative trait loci (QTL) associated with low SARS-CoV titer. In this study, we integrated sequence information and RNA expression of genes within the QTL to identify mucin 4 (Muc4) as a high priority candidate for controlling SARS-CoV titer in the lung. To test this hypothesis, we infected Muc4-/- mice and found that female, but not male, Muc4-/- mice developed more weight loss and disease following infection with SARS-CoV. Female Muc4-/- mice also had more difficulty breathing despite reduced lung pathology; however, no change in viral titers was observed. Comparing across viral families, studies with chikungunya virus, a mosquito-borne arthralgic virus, suggests that Muc4’s impact on viral pathogenesis may be widespread. Although not confirming the original titer QTL, our data identifies a role for Muc4 in the SARS-CoV disease and viral pathogenesis.ImportanceGiven the recent emergence of SARS-CoV-2, this work suggest that Muc4 expression plays a protective role in female mice not conserved in male mice following SARS-CoV infection. With the SARS-CoV-2 outbreak continuing, treatments that modulate or enhance Muc4 activity may provide an avenue for treatment and improved outcomes. In addition, the work highlights the importance of studying host factors including host genetics and biological sex as key parameters influencing infection and disease outcomes.

Despite widespread use of the Bacillus Calmette-Guerin vaccine, tuberculosis, caused by infection with Mycobacterium tuberculosis, remains a leading cause of morbidity and mortality worldwide. As CD8+ T cells are critical to tuberculosis host defense and a phase 2b vaccine trial of modified vaccinia Ankara expressing Ag85a that failed to demonstrate efficacy, also failed to induce a CD8+ T cell response, an effective tuberculosis vaccine may need to induce CD8+ T cells. However, little is known about CD8, as compared to CD4, antigens in tuberculosis. Herein, we report the results of the first ever HLA allele independent genome-wide CD8 antigen discovery program. Using CD8+ T cells derived from humans with latent tuberculosis infection or tuberculosis and an interferon-γ ELISPOT assay, we screened a synthetic peptide library representing 10% of the Mycobacterium tuberculosis proteome, selected to be enriched for Mycobacterium tuberculosis antigens. We defined a set of immunodominant CD8 antigens including part or all of 74 Mycobacterium tuberculosis proteins, only 16 of which are previously known CD8 antigens. Immunogenicity was associated with the degree of expression of mRNA and protein. Immunodominant antigens were enriched in cell wall proteins with preferential recognition of Esx protein family members, and within proteins comprising the Mycobacterium tuberculosis secretome. A validation study of immunodominant antigens demonstrated that these antigens were strongly recognized in Mycobacterium tuberculosis-infected individuals from a tuberculosis endemic region in Africa. The tuberculosis vaccine field will likely benefit from this greatly increased known repertoire of CD8 immunodominant antigens and definition of properties of Mycobacterium tuberculosis proteins important for CD8 antigenicity., Tuberculosis: Defining the proteins that drive immune responses Specific bacterial proteins have been found that drive effective immune responses to tuberculosis, with use in making more effective vaccines. Immunity to tuberculosis (TB) is facilitated by two types of white blood cell; however, most research has focused on one: the CD4+ T cell. Deborah A. Lewinsohn and David Lewinsohn, of the Oregon Health & Science University, USA, and collaborators lay out the essential functions of the oft-neglected CD8+ T cell, and undertook a broad approach to catalogue and define the bacterial proteins that activate the CD8+ T cell response. The team found that TB-infected humans reacted strongly to their protein library, and described several characteristics of CD8+ T cell ‘antigens’ (activators of immune cells) that will likely prove highly useful in the design of more protective TB vaccines.

An increasing number of variants of unknown significance (VUS) are being identified in leukemia patients with the application of deep sequencing and these include CSF3R cytoplasmic mutations. Previous studies have demonstrated oncogenic potential of certain CSF3R truncation mutations prior to internalization motifs. However, the oncogenic potential of truncating the more distal region of CSF3R cytoplasmic domain as well as cytoplasmic missense mutations remains uncharacterized. Here we identified that CSF3R distal cytoplasmic truncation mutations (Q793–Q823) also harbored leukemogenic potential. Mechanistically, these distal cytoplasmic truncation mutations demonstrated markedly decreased receptor degradation, probably due to loss of the de-phosphorylation domain (residues N818–F836). Furthermore, all truncations prior to Q823 demonstrated increased expression of the higher molecular weight CSF3R band, which is shown to be essential for the receptor surface expression and the oncogenic potential. We further demonstrated that sufficient STAT5 activation is essential for oncogenic potential. In addition, CSF3R K704A demonstrated transforming capacity due to interruption of receptor ubiquitination and degradation. In summary, we have expanded the region of the CSF3R cytoplasmic domain in which truncation or missense mutations exhibit leukemogenic capacity, which will be useful for evaluating the relevance of CSF3R mutations in patients and helpful in defining targeted therapy strategies.

Background Virus infections result in a range of clinical outcomes for the host, from asymptomatic to severe or even lethal disease. Despite global efforts to prevent and treat virus infections to limit morbidity and mortality, the continued emergence and re-emergence of new outbreaks as well as common infections such as influenza persist as a health threat. Challenges to the prevention of severe disease after virus infection include both a paucity of protective vaccines, as well as the early identification of individuals with the highest risk that may require supportive treatment. Methods We completed a screen of mice from the Collaborative Cross (CC) that we infected with influenza, SARS-coronavirus, and West Nile virus. Results CC mice exhibited a range of disease manifestations upon infections, and we used this natural variation to identify strains with mortality following infection and strains exhibiting no mortality. We then used comprehensive pre-infection immunophenotyping to identify global baseline immune correlates of protection from mortality to virus infection. Conclusions These data suggest that immune phenotypes might be leveraged to identify humans at highest risk of adverse clinical outcomes upon infection, who may most benefit from intensive clinical interventions, in addition to providing insight for rational vaccine design.

The relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community., Microbial communities are commonly studied using culture-independent methods, such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination, particularly in low-microbial-biomass niches. Computational approaches to identify contaminant sequences have been proposed, but their performance has not been independently evaluated. To identify the impact of decreasing microbial biomass on polymicrobial 16S rRNA gene sequencing experiments, we created a mock microbial community dilution series. We evaluated four computational approaches to identify and remove contaminants, as follows: (i) filtering sequences present in a negative control, (ii) filtering sequences based on relative abundance, (iii) identifying sequences that have an inverse correlation with DNA concentration implemented in Decontam, and (iv) predicting the sequence proportion arising from defined contaminant sources implemented in SourceTracker. As expected, the proportion of contaminant bacterial DNA increased with decreasing starting microbial biomass, with 80.1% of the most diluted sample arising from contaminant sequences. Inclusion of contaminant sequences led to overinflated diversity estimates and distorted microbiome composition. All methods for contaminant identification successfully identified some contaminant sequences, which varied depending on the method parameters used and contaminant prevalence. Notably, removing sequences present in a negative control erroneously removed >20% of expected sequences. SourceTracker successfully removed over 98% of contaminants when the experimental environments were well defined. However, SourceTracker misclassified expected sequences and performed poorly when the experimental environment was unknown, failing to remove >97% of contaminants. In contrast, the Decontam frequency method did not remove expected sequences and successfully removed 70 to 90% of the contaminants. IMPORTANCE The relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community.

Acute Myeloid Leukemia (AML) develops due to the acquisition of mutations from multiple functional classes. Here, we demonstrate that activating mutations in the granulocyte colony stimulating factor receptor (CSF3R), cooperate with loss of function mutations in the transcription factor CEBPA to promote acute leukemia development. This finding of mutation-synergy is broadly applicable other mutations that activate the JAK/STAT pathway or disrupt CEBPA function (i.e. activating mutations in JAK3 and Core Binding Factor translocations). The interaction between these distinct classes of mutations occurs at the level of myeloid lineage enhancers where mutant CEBPA prevents activation of subset of differentiation associated enhancers. To confirm this enhancer-dependent mechanism, we demonstrate that CEBPA mutations must occur as the initial event in AML initiation, confirming predictions from clinical sequencing data. This improved mechanistic understanding will facilitate therapeutic development targeting the intersection of oncogene cooperativity.

Multi-parent populations (MPPs) capture and maintain the genetic diversity from multiple inbred founder strains to provide a resource for high-resolution genetic mapping through the accumulation of recombination events over many generations. Breeding designs that maintain a large effective population size with randomized assignment of breeders at each generation can minimize the impact of selection, inbreeding, and genetic drift on allele frequencies. Small deviations from expected allele frequencies will have little effect on the power and precision of genetic analysis, but a major distortion could result in reduced power and loss of important functional alleles. We detected strong transmission ratio distortion in the Diversity Outbred (DO) mouse population on chromosome 2, caused by meiotic drive favoring transmission of the WSB/EiJ allele at the R2d2 locus. The distorted region harbors thousands of polymorphisms derived from the seven non-WSB founder strains and many of these would be lost if the sweep was allowed to continue. To ensure the utility of the DO population to study genetic variation on chromosome 2, we performed an artificial selection against WSB/EiJ alleles at the R2d2 locus. Here, we report that we have purged the WSB/EiJ allele from the drive locus while preserving WSB/EiJ alleles in the flanking regions. We observed minimal disruption to allele frequencies across the rest of the autosomal genome. However, there was a shift in haplotype frequencies of the mitochondrial genome and an increase in the rate of an unusual sex chromosome aneuploidy. The DO population has been restored to genome-wide utility for genetic analysis, but our experience underscores that vigilant monitoring of similar genetic resource populations is needed to ensure their long-term utility.

Standardized variant curation is essential for clinical care recommendations for patients with inherited disorders. Clinical Genome Resource (ClinGen) variant curation expert panels are developing disease-associated gene specifications using the 2015 American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) guidelines to reduce curation discrepancies. The ClinGen Myeloid Malignancy Variant Curation Expert Panel (MM-VCEP) was created collaboratively between the American Society of Hematology and ClinGen to perform gene- and disease-specific modifications for inherited myeloid malignancies. The MM-VCEP began optimizing ACMG/AMP rules for RUNX1 because many germline variants have been described in patients with familial platelet disorder with a predisposition to acute myeloid leukemia, characterized by thrombocytopenia, platelet functional/ultrastructural defects, and a predisposition to hematologic malignancies. The 28 ACMG/AMP codes were tailored for RUNX1 variants by modifying gene/disease specifications, incorporating strength adjustments of existing rules, or both. Key specifications included calculation of minor allele frequency thresholds, formulating a semi-quantitative approach to counting multiple independent variant occurrences, identifying functional domains and mutational hotspots, establishing functional assay thresholds, and characterizing phenotype-specific guidelines. Preliminary rules were tested by using a pilot set of 52 variants; among these, 50 were previously classified as benign/likely benign, pathogenic/likely pathogenic, variant of unknown significance (VUS), or conflicting interpretations (CONF) in ClinVar. The application of RUNX1-specific criteria resulted in a reduction in CONF and VUS variants by 33%, emphasizing the benefit of gene-specific criteria and sharing internal laboratory data. Refereed/Peer-reviewed

Herpesvirus latency has been difficult to understand molecularly due to low levels of viral genomes and gene expression. In the case of the betaherpesvirus human cytomegalovirus (HCMV), this is further complicated by the heterogeneity inherent to hematopoietic subpopulations harboring genomes and, as a consequence, the various patterns of infection that simultaneously exist in a host, ranging from latent to lytic. Single-cell RNA sequencing (scRNA-seq) provides tremendous potential in measuring the gene expression profiles of heterogeneous cell populations for a wide range of applications, including in studies of cancer, immunology, and infectious disease. A recent study by Shnayder et al. (mBio 9:e00013-18, 2018, https://doi.org/10.1128/mBio.00013-18 ) utilized scRNA-seq to define transcriptomal characteristics of HCMV latency. They conclude that latency-associated gene expression is similar to the late lytic viral program but at lower levels of expression. The study highlights the numerous challenges, from the definition of latency to the analysis of scRNA-seq, that exist in defining a latent transcriptome.

Medical castration that interferes with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, clinical progression is universal, and tumors with AR-independent resistance mechanisms appear to be increasing in frequency. Consequently, there is an urgent need to develop new treatments targeting molecular pathways enriched in lethal prostate cancer. Lysine-specific demethylase 1 (LSD1) is a histone demethylase and an important regulator of gene expression. Here, we show that LSD1 promotes the survival of prostate cancer cells, including those that are castration-resistant, independently of its demethylase function and of the AR. Importantly, this effect is explained in part by activation of a lethal prostate cancer gene network in collaboration with LSD1’s binding protein, ZNF217. Finally, that a small-molecule LSD1 inhibitor―SP-2509―blocks important demethylase-independent functions and suppresses castration-resistant prostate cancer cell viability demonstrates the potential of LSD1 inhibition in this disease.

ObjectiveOur goal was to create a synthetic dataset and curricular materials to assist in teaching fundamentals of translational data science.Materials and MethodsA literature review was conducted to extract current cardiovascular risk score logic, data elements, and population characteristics. Then, clinical data elements in the models were pulled from clinical data and transformed to the Observational Medical Outcomes Partnership (OMOP) common data model; genetic data elements were added based on population rates. A hybrid Bayesian network was used to create synthetic data from the logical elements of the risk scores and the underlying population frequencies of the clinical data.ResultsA synthetic dataset of 446,000 patients was created. A two-day curriculum was created based on this synthetic data with exploratory data analysis and machine learning components. The curriculum was offered on two separate occasions; the two groups of learners were given the curriculum and data, and results were tallied, summarized, and compared. Students’ ability to complete the challenge was mixed; more experienced students achieved a range of 70%-85% in balanced accuracy, but many others did not perform better than the baseline model.DiscussionOverall, students enjoyed the course and dataset, but some struggled to consistently apply machine learning techniques. The curriculum, data set, techniques for generation, and results are available for others to use for their own training.ConclusionA realistic synthetic data with clinical and genetic components helps students learn issues in cardiovascular risk scoring, practice data science skills, and compete in a challenge to improve identification of risk.

Objective Recent evidence indicates that the adult hematopoietic system is susceptible to diet-induced lineage skewing. It is not known whether the developing hematopoietic system is subject to metabolic programming via in utero high-fat diet (HFD) exposure, an established mechanism of adult disease in several organ systems. We previously reported substantial losses in offspring liver size with prenatal HFD. As the liver is the main hematopoietic organ in the fetus, we asked whether the developmental expansion of the hematopoietic stem and progenitor cell (HSPC) pool is compromised by prenatal HFD and/or maternal obesity. Methods We used quantitative assays, progenitor colony formation, flow cytometry, transplantation, and gene expression assays with a series of dietary manipulations to test the effects of gestational high-fat diet and maternal obesity on the day 14.5 fetal liver hematopoietic system. Results Maternal obesity, particularly when paired with gestational HFD, restricts physiological expansion of fetal HSPCs while promoting the opposing cell fate of differentiation. Importantly, these effects are only partially ameliorated by gestational dietary adjustments for obese dams. Competitive transplantation reveals compromised repopulation and myeloid-biased differentiation of HFD-programmed HSPCs to be a niche-dependent defect, apparent in HFD-conditioned male recipients. Fetal HSPC deficiencies coincide with perturbations in genes regulating metabolism, immune and inflammatory processes, and stress response, along with downregulation of genes critical for hematopoietic stem cell self-renewal and activation of pathways regulating cell migration. Conclusions Our data reveal a previously unrecognized susceptibility to nutritional and metabolic developmental programming in the fetal HSPC compartment, which is a partially reversible and microenvironment-dependent defect perturbing stem and progenitor cell expansion and hematopoietic lineage commitment.

Summary: The lack of visualization frameworks to guide interpretation and facilitate discovery is a potential bottleneck for precision medicine, systems genetics and other studies. To address this we have developed an interactive, reproducible, web-based prioritization approach that builds on our earlier work. HitWalker2 is highly flexible and can utilize many data types and prioritization methods based upon available data and desired questions, allowing it to be utilized in a diverse range of studies such as cancer, infectious disease and psychiatric disorders. Availability and implementation: Source code is freely available at https://github.com/biodev/HitWalker2 and implemented using Python/Django, Neo4j and Javascript (D3.js and jQuery). We support major open source browsers (e.g. Firefox and Chromium/Chrome). Contact: wilmotb@ohsu.edu Supplementary information: Supplementary data are available at Bioinformatics online. Additional information/instructions are available at https://github.com/biodev/HitWalker2/wiki

The recently developed concept of cancer stem cells (CSC) sheds new light on various aspects of tumor growth and progression. Here, we present a mathematical model of malignancies to investigate how a hierarchical organized cancer cell population affects the fundamental properties of solid malignancies. We establish that tumors modeled in a CSC context more faithfully resemble human malignancies and show invasive behavior, whereas tumors without a CSC hierarchy do not. These findings are corroborated by in vitro studies. In addition, we provide evidence that the CSC model is accompanied by highly altered evolutionary dynamics compared with the ones predicted to exist in a stochastic, nonhierarchical tumor model. Our main findings indicate that the CSC model allows for significantly higher tumor heterogeneity, which may affect therapy resistance. Moreover, we show that therapy which fails to target the CSC population is not only unsuccessful in curing the patient, but also promotes malignant features in the recurring tumor. These include rapid expansion, increased invasion, and enhanced heterogeneity. Cancer Res; 70(1); 46–56

Menin is the protein product of the MEN1 tumorsuppressor gene; one allele of MEN1 is inactivated in the germ line of patients with “multiple endocrine neoplasia type 1” (MEN1) cancer syndrome. Menin interacts with several proteins involved in transcriptional regulation. RNA expression analyses have identified several menin-regulated genes that could represent proximal or distal interaction sites for menin. This report presents a substantial and unbiased sampling of menin-occupied chromatin regions using Serial Analysis of Chromatin Occupancy; this method combines chromatin immunoprecipitation with Serial Analysis of Gene Expression. Hundreds of menin-occupied genomic sites were identified in promoter regions (32% of menin-occupied loci), near the 3' end of genes (14%), or inside genes (21%), extending other data about menin recruitments to many sites of transcriptional activity. A large number of meninoccupied sites (33%) were located outside known gene regions. Additional annotation of the human genome could help in identifying genes at these loci, or these might be gene-free regions of the genome where menin occupancy could play some structural or regulatory role. Menin occupancy at many intragenic positions distant from the core promoter reveals an unexpected type of menin target region at many loci in the genome. These unbiased data also suggest that menin could play a broad role in transcriptional regulation.

Recent studies have revealed that p27, a nuclear cyclin-dependent kinase (Cdk) inhibitor and tumor suppressor, can acquire oncogenic activities upon mislocalization to the cytoplasm. To understand how these antagonistic activities influence oncogenesis, we dissected the nuclear and cytoplasmic functions of p27 in chronic myeloid leukemia (CML), a well-characterized malignancy caused by the BCR-ABL1 tyrosine kinase. p27 is predominantly cytoplasmic in CML and nuclear in normal cells. BCR-ABL1 regulates nuclear and cytoplasmic p27 abundance by kinase-dependent and -independent mechanisms, respectively. p27 knockdown in CML cell lines with predominantly cytoplasmic p27 induces apoptosis, consistent with a leukemogenic role of cytoplasmic p27. Accordingly, a p27 mutant (p27(CK-)) devoid of Cdk inhibitory nuclear functions enhances leukemogenesis in a murine CML model compared with complete absence of p27. In contrast, p27 mutations that enhance its stability (p27(T187A)) or nuclear retention (p27(S10A)) attenuate leukemogenesis over wild-type p27, validating the tumor-suppressor function of nuclear p27 in CML. We conclude that BCR-ABL1 kinase-dependent and -independent mechanisms convert p27 from a nuclear tumor suppressor to a cytoplasmic oncogene. These findings suggest that cytoplasmic mislocalization of p27 despite BCR-ABL1 inhibition by tyrosine kinase inhibitors may contribute to drug resistance, and effective therapeutic strategies to stabilize nuclear p27 must also prevent cytoplasmic mislocalization.

Background Heterogeneous stock (HS/NPT) mice have been used to create lines selectively bred in replicate for elevated drinking in the dark (DID). Both selected lines routinely reach a blood ethanol (EtOH) concentration (BEC) of 1.00 mg/ml or greater at the end of the 4-hour period of access in Day 2. The mechanisms through which genetic differences influence DID are currently unclear. Therefore, the current study examines the transcriptome, the first stage at which genetic variability affects neurobiology. Rather than focusing solely on differential expression (DE), we also examine changes in the ways that gene transcripts collectively interact with each other, as revealed by changes in coexpression patterns. Methods Naive mice (N = 48/group) were genotyped using the Mouse Universal Genotyping Array, which provided 3,683 informative markers. Quantitative trait locus (QTL) analysis used a marker-by-marker strategy with the threshold for a significant logarithm of odds (LOD) set at 10.6. Gene expression in the ventral striatum was measured using the Illumina Mouse 8.2 array. Differential gene expression and the weighted gene coexpression network analysis (WGCNA) were implemented largely as described elsewhere. Results Significant QTLs for elevated BECs after DID were detected on chromosomes 4, 14, and 16; the latter 2 were associated with gene-poor regions. None of the QTLs overlapped with known QTLs for EtOH preference drinking. Ninety-four transcripts were detected as being differentially expressed in both selected lines versus HS controls; there was no overlap with known preference genes. The WGCNA revealed 2 modules as showing significant effects of both selections on intramodular connectivity. A number of genes known to be associated with EtOH phenotypes (e.g., Gabrg1, Glra2, Grik1, Npy2r, and Nts) showed significant changes in connectivity. Conclusions We found marked and consistent effects of selection on coexpression patterns; DE changes were more modest and less concordant. The QTLs and differentially expressed genes detected here are distinct from the preference phenotype. This is consistent with behavioral data and suggests that the DID and preference phenotypes are markedly different genetically.

Identification of CD8(+) T cell antigens/epitopes expressed by human pathogens with large genomes is especially challenging, yet necessary for vaccine development. Immunity to tuberculosis, a leading cause of mortality worldwide, requires CD8(+) T cell immunity, yet the repertoire of CD8 antigens/epitopes remains undefined. We used integrated computational and proteomic approaches to screen 10% of the Mycobacterium tuberculosis (Mtb) proteome for CD8 Mtb antigens. We designed a weighting schema based upon a Multiple Attribute Decision Making:framework to select 10% of the Mtb proteome with a high probability of containing CD8(+) T cell epitopes. We created a synthetic peptide library consisting of 15-mers overlapping by 11 aa. Using the interferon-γ ELISPOT assay and Mtb-infected dendritic cells as antigen presenting cells, we screened Mtb-specific CD8(+) T cell clones restricted by classical MHC class I molecules (MHC class Ia molecules), that were isolated from Mtb-infected humans, against this library. Three novel CD8 antigens were unambiguously identified: the EsxJ family (Rv1038c, Rv1197, Rv3620c, Rv2347c, Rv1792), PE9 (Rv1088), and PE_PGRS42 (Rv2487c). The epitopes are B5701-restricted EsxJ24-34, B3905-restricted PE953-67, and B3514-restricted PE_PGRS4248-56, respectively. The utility of peptide libraries in identifying unknown epitopes recognized by classically restricted CD8(+) T cells was confirmed, which can be applied to other intracellular pathogens with large size genomes. In addition, we identified three novel Mtb epitopes/antigens that may be evaluated for inclusion in vaccines and/or diagnostics for tuberculosis.

Virus infection is a complex biological phenomenon for which in vitro experiments provide a uniquely concise view where data is often obtained from a single population of cells, under controlled environmental conditions. Nonetheless, data interpretation and real understanding of viral dynamics is still hampered by the sheer complexity of the various intertwined spatio-temporal processes. In this paper we present a tool to address these issues: a cellular automata model describing critical aspects of in vitro viral infections taking into account spatial characteristics of virus spreading within a culture well. The aim of the model is to understand the key mechanisms of SARS-CoV infection dynamics during the first 24 hours post infection. Using a simulated annealing algorithm we tune free parameters with data from SARS-CoV infection of cultured lung epithelial cells. We also interrogate the model using a Latin Hypercube sensitivity analysis to identify which mechanisms are critical to the observed infection of host cells and the release of measured virus particles.

Complex Mus Musculus crosses e.g. heterogeneous stock, provide increased resolution for quantitative trait loci detection. However, increased genetic complexity challenges detection methods, with discordant results due to low data quality or complex genetic architecture. We quantified the impact of theses factors across three mouse crosses and two different detection methods, identifying procedures that greatly improve detection quality. Importantly, heterogeneous stock populations have complex genetic architectures not fully captured by the whole-genome kinship matrix, calling for incorporating chromosome specific relatedness information. We analyze three increasingly complex crosses, using gene expression levels as quantitative traits. The three crosses were an F2 intercross, a heterogeneous stock formed by crossing four inbred strains (HS4), and a heterogeneous stock (HS-CC) derived from the eight lines found in the collaborative cross. Brain (striatum) gene expression and genotype data were obtained using the Illumina platform. We found large disparities between methods, with concordance varying as genetic complexity increased; this problem was more acute for probes with distant regulatory elements (trans). A suite of data filtering steps resulted in substantial increases in reproducibility. Genetic relatedness between samples generated overabundance of detected eQTLs; an adjustment procedure that includes the kinship matrix attenuates this problem. However, we find that relatedness between individuals is not evenly distributed across the genome; information from distinct chromosomes results in relatedness structure different from the whole genome kinship matrix. Shared polymorphisms from distinct chromosomes collectively affect expression levels, confounding eQTL detection. We suggest that considering chromosome-specific relatedness can result in improved eQTL detection.

Background: With the advent of the GeneChip Exon Arrays, it is now possible to extract "exon-level" expression estimates, allowing for detection of alternative splicing events, one of the primary mechanisms of transcript diversity. In the context of 1) a complex trait use case and 2) a human cerebellum vs. heart comparison on previously validated data, we present a transcript-based statistical model and validation framework to allow detection of alternative exon usage (AEU) between different groups. To illustrate the approach, we detect and confirm differences in exon usage in the two of the most widely studied mouse genetic models (the C57BL/6J and DBA/2J inbred strains) and in a human dataset. Results: We developed a computational framework that consists of probe level annotation mapping and statistical modelling to detect putative AEU events, as well as visualization and alignment with known splice events. We show a dramatic improvement (~25 fold) in the ability to detect these events using the appropriate annotation and statistical model which is actually specified at the transcript level, as compared with the transcript cluster/gene level annotation used on the array. An additional component of this workflow is a probe index that allows ranking AEU candidates for validation and can aid in identification of false positives due to single nucleotide polymorphisms. Discussion: Our work highlights the importance of concordance between the functional unit interrogated (e.g., gene, transcripts) and the entity (e.g., exon, probeset) within the statistical model. The framework we present is broadly applicable to other platforms (including RNAseq).

Brain development in the early stages of life has been suggested to be one of the factors that may influence an individual's risk of Alzheimer disease (AD) later in life. Four microcephaly genes, which regulate brain development in utero and have been suggested to play a role in the evolution of the human brain, were selected as candidate genes that may modulate the risk of AD. We examined the association between single nucleotide polymorphisms tagging common sequence variations in these genes and risk of AD in two case-control samples. We found that the G allele of rs2442607 in microcephalin 1 was associated with an increased risk of AD (under an additive genetic model, P=0.01; odds ratio=3.41; confidence interval, 1.77-6.57). However, this association was not replicated using another case-control sample research participants from the Alzheimer Disease Neuroimaging Initiative. We conclude that the common variations we measured in the 4 microcephaly genes do not affect the risk of AD or that their effect size is small.

BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.

Global gene expression data combined with bioinformatic analysis provides strong evidence that mammalian miRNAs mediate repression of gene expression primarily through binding sites within the 3′ untranslated region (UTR). Using RNA induced silencing complex immunoprecipitation (RISC-IP) techniques we have identified multiple cellular targets for a human cytomegalovirus (HCMV) miRNA, miR-US25-1. Strikingly, this miRNA binds target sites primarily within 5′UTRs, mediating significant reduction in gene expression. Intriguingly, many of the genes targeted by miR-US25-1 are associated with cell cycle control, including cyclin E2, BRCC3, EID1, MAPRE2, and CD147, suggesting that miR-US25-1 is targeting genes within a related pathway. Deletion of miR-US25-1 from HCMV results in over expression of cyclin E2 in the context of viral infection. Our studies demonstrate that a viral miRNA mediates translational repression of multiple cellular genes by targeting mRNA 5′UTRs., Author Summary Regulation of gene expression is as important as the genes themselves in determining the diverse array of living creatures we see in nature. Recently, scientists have discovered a whole new level of gene regulation through the actions of small molecules called microRNAs (miRNAs). It is currently thought that miRNAs regulate gene expression primarily through binding to target sites within the 3′UTR of mRNAs. Here we identify a population of cellular genes that are targeted by a virally encoded miRNA. Many of the genes are related to cell cycle control, suggesting that the viral miRNA is targeting genes within a related pathway. In contrast to most miRNAs, this miRNA inhibits gene expression through binding to target sites within the 5′UTRs, suggesting that viral miRNAs may target genes through mechanisms divergent from cellular miRNAs.

Background Allelic variation is the cornerstone of genetically determined differences in gene expression, gene product structure, physiology, and behavior. However, allelic variation, particularly cryptic (unknown or not annotated) variation, is problematic for follow up analyses. Polymorphisms result in a high incidence of false positive and false negative results in hybridization based analyses and hinder the identification of the true variation underlying genetically determined differences in physiology and behavior. Given the proliferation of mouse genetic models (e.g., knockout models, selectively bred lines, heterogeneous stocks derived from standard inbred strains and wild mice) and the wealth of gene expression microarray and phenotypic studies using genetic models, the impact of naturally-occurring polymorphisms on these data is critical. With the advent of next-generation, high-throughput sequencing, we are now in a position to determine to what extent polymorphisms are currently cryptic in such models and their impact on downstream analyses. Results We sequenced the two most commonly used inbred mouse strains, DBA/2J and C57BL/6J, across a region of chromosome 1 (171.6 – 174.6 megabases) using two next generation high-throughput sequencing platforms: Applied Biosystems (SOLiD) and Illumina (Genome Analyzer). Using the same templates on both platforms, we compared realignments and single nucleotide polymorphism (SNP) detection with an 80 fold average read depth across platforms and samples. While public datasets currently annotate 4,527 SNPs between the two strains in this interval, thorough high-throughput sequencing identified a total of 11,824 SNPs in the interval, including 7,663 new SNPs. Furthermore, we confirmed 40 missense SNPs and discovered 36 new missense SNPs. Conclusion Comparisons utilizing even two of the best characterized mouse genetic models, DBA/2J and C57BL/6J, indicate that more than half of naturally-occurring SNPs remain cryptic. The magnitude of this problem is compounded when using more divergent or poorly annotated genetic models. This warrants full genomic sequencing of the mouse strains used as genetic models.

Summary: Determining the functional relevance of identified sequence variants in cancer is a prerequisite to ultimately matching specific therapies with individual patients. This level of mechanistic understanding requires integration of genomic information with complementary functional analyses to identify oncogenic targets and relies on the development of computational frameworks to aid in the prioritization and visualization of these diverse data types. In response to this, we have developed HitWalker, which prioritizes patient variants relative to their weighted proximity to functional assay results in a protein–protein interaction network. It is highly extensible, allowing incorporation of diverse data types to refine prioritization. In addition to a ranked list of variants, we have also devised a simple shortest path-based approach of visualizing the results in an intuitive manner to provide biological interpretation. Availability and implementation: The program, documentation and example data are available as an R package from www.biodevlab.org/HitWalker.html. Contact: bottomly@ohsu.edu Supplementary information: Supplementary data are available at Bioinformatics online.