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Novel treatments for Huntington’s disease (HD), a progressive neurodegenerative disorder, include selective targeting of the mutant allele of the huntingtin gene (mHTT) carrying the abnormally expanded disease-causing cytosine-adenine-guanine (CAG) repeat. WVE-120101 and WVE-120102 are investigational stereopure antisense oligonucleotides that enable selective suppression of mHTT by targeting single-nucleotide polymorphisms (SNPs) that are in haplotype phase with the CAG repeat expansion. Recently developed long-read sequencing technologies can capture CAG expansions and distant SNPs of interest and potentially facilitate haplotype-based identification of patients for clinical trials of oligonucleotide therapies. However, improved methods are needed to phase SNPs with CAG repeat expansions directly and reliably without need for familial genotype/haplotype data. Our haplotype phasing method uses single-molecule real-time sequencing and a custom algorithm to determine with confidence bases at SNPs on mutant alleles, even without familial data. Herein, we summarize this methodology and validate the approach using patient-derived samples with known phasing results. Comparison of experimentally measured CAG repeat lengths, heterozygosity, and phasing with previously determined results showed improved performance. Our methodology enables the haplotype phasing of SNPs of interest and the disease-causing, expanded CAG repeat of the huntingtin gene, enabling accurate identification of patients with HD eligible for allele-selective clinical studies., Graphical Abstract, Svrzikapa et al. describe a method using single-molecule real-time long-read sequencing and a custom algorithm to determine bases at SNPs on mutant alleles. Accurate haplotype phasing of SNPs in relationship to the expanded CAG repeat of the huntingtin gene enables identification of patients with Huntington’s disease eligible for allele-selective clinical studies.

The human sperm is one of the smallest cells in the body, but also one of the most important, as it serves as the entire paternal genetic contribution to a child. Investigating RNA and mutations in sperm is especially relevant for diseases such as autism spectrum disorders (ASD), which have been correlated with advanced paternal age. Historically, studies have focused on the assessment of bulk sperm, wherein millions of individual sperm are present and only high-frequency variants can be detected. Using 10× Chromium single-cell sequencing technology, we assessed the transcriptome from >65,000 single spermatozoa across six sperm donors (scSperm-RNA-seq), including two who fathered multiple children with ASD and four fathers of neurotypical children. Using RNA-seq methods for differential expression and variant analysis, we found clusters of sperm mutations in each donor that are indicative of the sperm being produced by different stem cell pools. Finally, we have shown that genetic variations can be found in single sperm.

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Delay in cancer diagnosis often results in metastasis and an inability to successfully treat the tumor. The use of broadly cancer-specific biomarkers at an early stage may improve cancer treatment and staging. This study has explored circulatory exosomal miRNAs as potential diagnostic biomarkers to identify cancer patients. Secretory exosomal miRNAs were isolated from 13 canine cancer cell lines (lymphoma, mast cell tumor, histiocytic cell line, osteosarcoma, melanoma, and breast tumor) and were sequenced by Next-Generation sequencing (NGS). We have identified 6 miRNAs (cfa-miR-9, -1841, −1306, −345, −132, and −26b) by NGS that were elevated in all cancer cell types. The miRNAs identified by NGS were then examined by Q-RT-PCR. The PCR data demonstrated similar expression patterns to those seen with NGS but provided fold differences that were much lower than those seen for NGS. Cfa-miR-9 was found to be the most consistently elevated miRNA in NGS and PCR, making it the most likely miRNA to prove diagnostic. In this study, we have demonstrated that it is possible to identify exosomal miRNAs with elevated secretion across multiple tumor types that could be used as circulatory diagnostic biomarkers for liquid biopsy in the future., Highlights • Circulatory exosomal miRNAs are useful as diagnostic biomarkers for early cancer detection. • Secretory miRNAs can be sequenced and identified by Next-Generation sequencing. • Six miRNAs were elevated in canine cancer cell lines. • Q-RT-PCR was used to analyze and validate miRNAs expression. • Cfa-miR-9 was most consistently elevated miRNAs in all cancer cell types.

Background Clinical interpretation of genetic variants in the context of the patient’s phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interpretation by integrating predictive methods with the growing knowledge of genetic disease. Here we assess the diagnostic performance of Fabric GEM, a new, AI-based, clinical decision support tool for expediting genome interpretation. Methods We benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole-genome or whole-exome sequencing (WGS, WES). We replicated our analyses in a separate cohort of 60 cases collected from five academic medical centers. For comparison, we also analyzed these cases with current state-of-the-art variant prioritization tools. Included in the comparisons were trio, duo, and singleton cases. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted from clinical notes by two means: manually and using an automated clinical natural language processing (CNLP) tool. Finally, 14 previously unsolved cases were reanalyzed. Results GEM ranked over 90% of the causal genes among the top or second candidate and prioritized for review a median of 3 candidate genes per case, using either manually curated or CNLP-derived phenotype descriptions. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top candidate and in 19/20 within the top five, irrespective of whether SV calls were provided or inferred ab initio by GEM using its own internal SV detection algorithm. GEM showed similar performance in absence of parental genotypes. Analysis of 14 previously unsolved cases resulted in a novel finding for one case, candidates ultimately not advanced upon manual review for 3 cases, and no new findings for 10 cases. Conclusions GEM enabled diagnostic interpretation inclusive of all variant types through automated nomination of a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing cost and expediting case review.

Islet-enriched transcription factors (TFs) exert broad control over cellular processes in pancreatic α and β cells, and changes in their expression are associated with developmental state and diabetes. However, the implications of heterogeneity in TF expression across islet cell populations are not well understood. To define this TF heterogeneity and its consequences for cellular function, we profiled more than 40,000 cells from normal human islets by single-cell RNA-Seq and stratified α and β cells based on combinatorial TF expression. Subpopulations of islet cells coexpressing ARX/MAFB (α cells) and MAFA/MAFB (β cells) exhibited greater expression of key genes related to glucose sensing and hormone secretion relative to subpopulations expressing only one or neither TF. Moreover, all subpopulations were identified in native pancreatic tissue from multiple donors. By Patch-Seq, MAFA/MAFB-coexpressing β cells showed enhanced electrophysiological activity. Thus, these results indicate that combinatorial TF expression in islet α and β cells predicts highly functional, mature subpopulations.

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3–2.8, one-sided p = 6.0 × 10−4), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ., International Bipolar Sequencing Consortium (NIMH) R01 MH 110437, Whole Genome Sequencing for Schizophrenia and Biopolar Disorder in the GPS (NIMH) UO1 MH105653, Whole Genome and Exome Sequencing for Bipolar Disorder (NIMH) R01 MH 094145, Multi-ethnic GWAS of Bipolar I Disorder (NIH) R01 MH 085543, Genetic Epidemiology Research in Adult Health and Aging (GERA) RC2 AG036607, Kaiser Permanente Research Program on Genes, Environment, and Health, Rare Bipolar Loci Identification Through Synaptome Sequencing (NIMH) R01 MH 087979 MH 087992, 2/2 Large Scale Genetic Studies of Schizophrenia in Sweden R01MH095034, 1/3 Genetic Analysis of the International Cohort Collection for Bipolar Disorder R01MH106531, 1/2 Large Scale Genetic Studies of Schizophrenia in Sweden R01MH077139, 2/3 Genetic Analysis of the International Cohort Collection for Bipolar Disorder R01MH106527, Dalio Foundation

The molecular mechanisms underlying the clinical manifestations of COVID-19 and what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome, remains poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match this data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue compartment-specific damage wrought by SARS-CoV-2 infection, evident as a function of varying viral loads during the clinical course of infection and tissue type specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections., Graphical Abstract, Park et al. report system-wide transcriptome damage and tissue identity loss wrought by SARS-CoV-2, influenza, and bacterial infection across multiple organs (heart, liver, lung, kidney, and lymph nodes) and provide spatio-temporal landscape of COVID-19 in the lung.

Burkitt lymphoma (BL) is an aggressive, MYC-driven lymphoma comprising 3 distinct clinical subtypes: sporadic BLs that occur worldwide, endemic BLs that occur predominantly in sub-Saharan Africa, and immunodeficiency-associated BLs that occur primarily in the setting of HIV. In this study, we comprehensively delineated the genomic basis of BL through whole-genome sequencing (WGS) of 101 tumors representing all 3 subtypes of BL to identify 72 driver genes. These data were additionally informed by CRISPR screens in BL cell lines to functionally annotate the role of oncogenic drivers. Nearly every driver gene was found to have both coding and non-coding mutations, highlighting the importance of WGS for identifying driver events. Our data implicate coding and non-coding mutations in IGLL5, BACH2, SIN3A, and DNMT1. Epstein-Barr virus (EBV) infection was associated with higher mutation load, with type 1 EBV showing a higher mutational burden than type 2 EBV. Although sporadic and immunodeficiency-associated BLs had similar genetic profiles, endemic BLs manifested more frequent mutations in BCL7A and BCL6 and fewer genetic alterations in DNMT1, SNTB2, and CTCF. Silencing mutations in ID3 were a common feature of all 3 subtypes of BL. In vitro, mass spectrometry–based proteomics demonstrated that the ID3 protein binds primarily to TCF3 and TCF4. In vivo knockout of ID3 potentiated the effects of MYC, leading to rapid tumorigenesis and tumor phenotypes consistent with those observed in the human disease.

Background The public transit is a built environment with high occupant density across the globe, and identifying factors shaping public transit air microbiomes will help design strategies to minimize the transmission of pathogens. However, the majority of microbiome works dedicated to the public transit air are limited to amplicon sequencing, and our knowledge regarding the functional potentials and the repertoire of resistance genes (i.e. resistome) is limited. Furthermore, current air microbiome investigations on public transit systems are focused on single cities, and a multi-city assessment of the public transit air microbiome will allow a greater understanding of whether and how broad environmental, building, and anthropogenic factors shape the public transit air microbiome in an international scale. Therefore, in this study, the public transit air microbiomes and resistomes of six cities across three continents (Denver, Hong Kong, London, New York City, Oslo, Stockholm) were characterized. Results City was the sole factor associated with public transit air microbiome differences, with diverse taxa identified as drivers for geography-associated functional potentials, concomitant with geographical differences in species- and strain-level inferred growth profiles. Related bacterial strains differed among cities in genes encoding resistance, transposase, and other functions. Sourcetracking estimated that human skin, soil, and wastewater were major presumptive resistome sources of public transit air, and adjacent public transit surfaces may also be considered presumptive sources. Large proportions of detected resistance genes were co-located with mobile genetic elements including plasmids. Biosynthetic gene clusters and city-unique coding sequences were found in the metagenome-assembled genomes. Conclusions Overall, geographical specificity transcends multiple aspects of the public transit air microbiome, and future efforts on a global scale are warranted to increase our understanding of factors shaping the microbiome of this unique built environment.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin–angiotensin–aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Individuals with monogenic disorders can experience variable phenotypes that are influenced by genetic variation. To investigate this in sickle cell disease (SCD), we performed whole-genome sequencing (WGS) of 722 individuals with hemoglobin HbSS or HbSβ0-thalassemia from Baylor College of Medicine and from the St. Jude Children’s Research Hospital Sickle Cell Clinical Research and Intervention Program (SCCRIP) longitudinal cohort study. We developed pipelines to identify genetic variants that modulate sickle hemoglobin polymerization in red blood cells and combined these with pain-associated variants to build a polygenic score (PGS) for acute vaso-occlusive pain (VOP). Overall, we interrogated the α-thalassemia deletion −α3.7 and 133 candidate single-nucleotide polymorphisms (SNPs) across 66 genes for associations with VOP in 327 SCCRIP participants followed longitudinally over 6 years. Twenty-one SNPs in 9 loci were associated with VOP, including 3 (BCL11A, MYB, and the β-like globin gene cluster) that regulate erythrocyte fetal hemoglobin (HbF) levels and 6 (COMT, TBC1D1, KCNJ6, FAAH, NR3C1, and IL1A) that were associated previously with various pain syndromes. An unweighted PGS integrating all 21 SNPs was associated with the VOP event rate (estimate, 0.35; standard error, 0.04; P = 5.9 × 10−14) and VOP event occurrence (estimate, 0.42; standard error, 0.06; P = 4.1 × 10−13). These associations were stronger than those of any single locus. Our findings provide insights into the genetic modulation of VOP in children with SCD. More generally, we demonstrate the utility of WGS for investigating genetic contributions to the variable expression of SCD-associated morbidities.

Islet-enriched transcription factors (TFs) exert broad control over cellular processes in pancreatic α and β cells and changes in their expression are associated with developmental state and diabetes. However, the implications of heterogeneity in TF expression across islet cell populations are not well understood. To define this TF heterogeneity and its consequences for cellular function, we profiled >40,000 cells from normal human islets by scRNA-seq and stratified α and β cells based on combinatorial TF expression. Subpopulations of islet cells co-expressingARX/MAFB(α cells) andMAFA/MAFB(β cells) exhibited greater expression of key genes related to glucose sensing and hormone secretion relative to subpopulations expressing only one or neither TF. Moreover, all subpopulations were identified in native pancreatic tissue from multiple donors. By Patch-seq,MAFA/MAFBco-expressing β cells showed enhanced electrophysiological activity. Thus, these results indicate combinatorial TF expression in islet α and β cells predicts highly functional, mature subpopulations.

The Michael J. Fox Foundation’s Parkinson’s Progression Markers Initiative (PPMI) is an observational study to comprehensively evaluate Parkinson’s disease (PD) patients using imaging, biologic sampling, clinical and behavioural assessments to identify biomarkers of PD progression. As part of this study, we obtained 4,756 whole blood samples from 1,570 subjects at baseline, 0.5, 1, 2, and 3 years from enrollment in the study. We isolated RNA and performed whole transcriptome sequencing in this longitudinal cohort. Here, we describe and quantify technical variability associated with this dataset through the use of pooled reference samples, including plate distribution, RNA quality, and outliers. This large, uniformly processed dataset is available to researchers at https://www.ppmi-info.org.

International audience; Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Chronic kidney disease (CKD), which can ultimately progress to kidney failure, is influenced by genetics and the environment. Genes identified in human genome wide association studies (GWAS) explain only a small proportion of the heritable variation and lack functional validation, indicating the need for additional model systems. Outbred heterogeneous stock (HS) rats have been used for genetic fine-mapping of complex traits, but have not previously been used for CKD traits. We performed GWAS for urinary protein excretion (UPE) and CKD related serum biochemistries in 245 male HS rats. Quantitative trait loci (QTL) were identified using a linear mixed effect model that tested for association with imputed genotypes. Candidate genes were identified using bioinformatics tools and targeted RNAseq followed by testing in a novel in vitro model of human tubule, hypoxia-induced damage. We identified two QTL for UPE and five for serum biochemistries. Protein modeling identified a missense variant within Septin 8 (Sept8) as a candidate for UPE. Sept8/SEPTIN8 expression increased in HS rats with elevated UPE and tubulointerstitial injury and in the in vitro hypoxia model. SEPTIN8 is detected within proximal tubule cells in human kidney samples and localizes with acetyl-alpha tubulin in the culture system. After hypoxia, SEPTIN8 staining becomes diffuse and appears to relocalize with actin. These data suggest a role of SEPTIN8 in cellular organization and structure in response to environmental stress. This study demonstrates that integration of a rat genetic model with an environmentally induced tubule damage system identifies Sept8/SEPTIN8 and informs novel aspects of the complex gene by environmental interactions contributing to CKD risk.

Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling. Next-generation sequencing platforms are benchmarked using human, bacterial and metagenomics reference materials.

Endogenous β cell regeneration could alleviate diabetes, but proliferative stimuli within the islet microenvironment are incompletely understood. We previously found that β cell recovery following hypervascularization-induced β cell loss involves interactions with endothelial cells (ECs) and macrophages (MΦs). Here we show that proliferative ECs modulate MΦ infiltration and phenotype during β cell loss, and recruited MΦs are essential for β cell recovery. Furthermore, VEGFR2 inactivation in quiescent ECs accelerates islet vascular regression during β cell recovery and leads to increased β cell proliferation without changes in MΦ phenotype or number. Transcriptome analysis of β cells, ECs, and MΦs reveals that β cell proliferation coincides with elevated expression of extracellular matrix remodeling molecules and growth factors likely driving activation of proliferative signaling pathways in β cells. Collectively, these findings suggest a new β cell regeneration paradigm whereby coordinated interactions between intra-islet MΦs, ECs, and extracellular matrix mediate β cell self-renewal.

Massively parallel DNA sequencing is a critical tool for genomics research and clinical diagnostics. Here, we describe the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Phase II Study to measure quality and reproducibility of DNA sequencing. Replicates of human and bacterial reference DNA samples were generated across multiple sequencing platforms, including well-established technologies such as Illumina, ThermoFisher Ion Torrent, and Pacific Biosciences, as well as emerging technologies such as BGI, Genapsys, and Oxford Nanopore. A total of 202 datasets were generated to investigate the performance of a total of 16 sequencing platforms, including mappability of reads, coverage and error rates in difficult genomic regions, and detection of small-scale polymorphisms and large-scale structural variants. This study provides a comprehensive baseline resource for continual benchmarking as chemistries, methods, and platforms evolve for DNA sequencing.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin–angiotensin–aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies., Here, using clinical samples and autopsy tissues, the authors combine fast-colorimetric test (LAMP) for SARS-CoV-2 infection and large-scale shotgun metatranscriptomics for host, viral, and microbial profiling and provide a map of the viral genetic features of the New York City outbreak and associate specific host responses and gene expression perturbations with SARS-CoV-2 infection.

Posttransplantation diabetes mellitus (PTDM) is a common and significant complication related to immunosuppressive agents required to prevent organ or cell transplant rejection. To elucidate the effects of 2 commonly used agents, the calcineurin inhibitor tacrolimus (TAC) and the mTOR inhibitor sirolimus (SIR), on islet function and test whether these effects could be reversed or prevented, we investigated human islets transplanted into immunodeficient mice treated with TAC or SIR at clinically relevant levels. Both TAC and SIR impaired insulin secretion in fasted and/or stimulated conditions. Treatment with TAC or SIR increased amyloid deposition and islet macrophages, disrupted insulin granule formation, and induced broad transcriptional dysregulation related to peptide processing, ion/calcium flux, and the extracellular matrix; however, it did not affect regulation of β cell mass. Interestingly, these β cell abnormalities reversed after withdrawal of drug treatment. Furthermore, cotreatment with a GLP-1 receptor agonist completely prevented TAC-induced β cell dysfunction and partially prevented SIR-induced β cell dysfunction. These results highlight the importance of both calcineurin and mTOR signaling in normal human β cell function in vivo and suggest that modulation of these pathways may prevent or ameliorate PTDM.

Background Adjuvant System 03 (AS03) markedly enhances responses to influenza A/H5N1 vaccines, but the mechanisms of this enhancement are incompletely understood. Methods Using ribonucleic acid sequencing on peripheral blood mononuclear cells (PBMCs) from AS03-adjuvanted and unadjuvanted inactivated H5N1 vaccine recipients, we identified differentially expressed genes, enriched pathways, and genes that correlated with serologic responses. We compared bulk PBMC findings with our previously published assessments of flow-sorted immune cell types. Results AS03-adjuvanted vaccine induced the strongest differential signals on day 1 postvaccination, activating multiple innate immune pathways including interferon and JAK-STAT signaling, Fcγ receptor (FcγR)-mediated phagocytosis, and antigen processing and presentation. Changes in signal transduction and immunoglobulin genes predicted peak hemagglutinin inhibition (HAI) titers. Compared with individual immune cell types, activated PBMC genes and pathways were most similar to innate immune cells. However, several pathways were unique to PBMCs, and several pathways identified in individual cell types were absent in PBMCs. Conclusions Transcriptomic analysis of PBMCs after AS03-adjuvanted H5N1 vaccination revealed early activation of innate immune signaling, including a 5- to 8-fold upregulation of FcγR1A/1B/1C genes. Several early gene responses were correlated with HAI titer, indicating links with the adaptive immune response. Although PBMCs and cell-specific results shared key innate immune signals, unique signals were identified by both approaches.

Deficiency in diacylglycerol acyltransferase (DGAT1) is a rare cause of neonatal diarrhea, without a known mechanism or in vitro model. A patient presenting at our institution at 7 weeks of life with failure to thrive and diarrhea was found by whole-exome sequencing to have a homozygous DGAT1 truncation mutation. Duodenal biopsies showed loss of DGAT1 and deficits in apical membrane transporters and junctional proteins in enterocytes. When placed on a very low-fat diet, the patient's diarrhea resolved with normalization of brush border transporter localization in endoscopic biopsies. DGAT1 knockdown in Caco2-BBe cells modeled the deficits in apical trafficking, with loss of apical DPPIV and junctional occludin. Elevation in cellular lipid levels, including diacylglycerol (DAG) and phospholipid metabolites of DAG, was documented by lipid analysis in DGAT1 knockdown cells. Culture of the DGAT1 knockdown cells in lipid-depleted media led to re-establishment of occludin and return of apical DPPIV. DGAT1 loss appears to elicit global changes in enterocyte polarized trafficking that could account for deficits in absorption seen in the patient. The in vitro modeling of this disease should allow for investigation of possible therapeutic targets.

It is estimated that ∼1% of the world's population has intellectual disability, with males affected more often than females. OGT is an X-linked gene encoding for the enzyme O-GlcNAc transferase (OGT), which carries out the reversible addition of N-acetylglucosamine (GlcNAc) to Ser/Thr residues of its intracellular substrates. Three missense mutations in the tetratricopeptide (TPR) repeats of OGT have recently been reported to cause X-linked intellectual disability (XLID). Here, we report the discovery of two additional novel missense mutations (c.775 G>A, p.A259T, and c.1016 A>G, p.E339G) in the TPR domain of OGT that segregate with XLID in affected families. Characterization of all five of these XLID missense variants of OGT demonstrates modest declines in thermodynamic stability and/or activities of the variants. We engineered each of the mutations into a male human embryonic stem cell line using CRISPR/Cas9. Investigation of the global O-GlcNAc profile as well as OGT and O-GlcNAc hydrolase levels by Western blotting showed no gross changes in steady-state levels in the engineered lines. However, analyses of the differential transcriptomes of the OGT variant-expressing stem cells revealed shared deregulation of genes involved in cell fate determination and liver X receptor/retinoid X receptor signaling, which has been implicated in neuronal development. Thus, here we reveal two additional mutations encoding residues in the TPR regions of OGT that appear causal for XLID and provide evidence that the relatively stable and active TPR variants may share a common, unelucidated mechanism of altering gene expression profiles in human embryonic stem cells.

Serving over three billion passengers annually, air travel serves as a conduit for infectious disease spread, including emerging infections and pandemics. Over two dozen cases of in-flight transmissions have been documented. To understand these risks, a characterization of the airplane cabin microbiome is necessary. Our study team collected 229 environmental samples on ten transcontinental US flights with subsequent 16S rRNA sequencing. We found that bacterial communities were largely derived from human skin and oral commensals, as well as environmental generalist bacteria. We identified clear signatures for air versus touch surface microbiome, but not for individual types of touch surfaces. We also found large flight-to-flight beta diversity variations with no distinguishing signatures of individual flights, rather a high between-flight diversity for all touch surfaces and particularly for air samples. There was no systematic pattern of microbial community change from pre- to post-flight. Our findings are similar to those of other recent studies of the microbiome of built environments. In summary, the airplane cabin microbiome has immense airplane to airplane variability. The vast majority of airplane-associated microbes are human commensals or non-pathogenic, and the results provide a baseline for non-crisis-level airplane microbiome conditions. Electronic supplementary material The online version of this article (10.1007/s00248-018-1191-3) contains supplementary material, which is available to authorized users.

The 17 genes of the T-box family are transcriptional regulators that are involved in all stages of embryonic development, including craniofacial, brain, heart, skeleton and immune system. Malformation syndromes have been linked to many of the T-box genes. For example, haploinsufficiency of TBX1 is responsible for many structural malformations in DiGeorge syndrome caused by a chromosome 22q11.2 deletion. We report four individuals with an overlapping spectrum of craniofacial dysmorphisms, cardiac anomalies, skeletal malformations, immune deficiency, endocrine abnormalities and developmental impairments, reminiscent of DiGeorge syndrome, who are heterozygotes for TBX2 variants. The p.R20Q variant is shared by three affected family members in an autosomal dominant manner; the fourth unrelated individual has a de novo p.R305H mutation. Bioinformatics analyses indicate that these variants are rare and predict them to be damaging. In vitro transcriptional assays in cultured cells show that both variants result in reduced transcriptional repressor activity of TBX2. We also show that the variants result in reduced protein levels of TBX2. Heterologous over-expression studies in Drosophila demonstrate that both p.R20Q and p.R305H function as partial loss-of-function alleles. Hence, these and other data suggest that TBX2 is a novel candidate gene for a new multisystem malformation disorder.

SUMMARY Many patients with type 1 diabetes (T1D) have residual β cells producing small amounts of C-peptide long after disease onset but develop an inadequate glucagon response to hypoglycemia following T1D diagnosis. The features of these residual β cells and α cells in the islet endocrine compartment are largely unknown, due to the difficulty of comprehensive investigation. By studying the T1D pancreas and isolated islets, we show that remnant β cells appeared to maintain several aspects of regulated insulin secretion. However, the function of T1D α cells was markedly reduced, and these cells had alterations in transcription factors constituting α and β cell identity. In the native pancreas and after placing the T1D islets into a non-autoimmune, normoglycemic in vivo environment, there was no evidence of α-to-β cell conversion. These results suggest an explanation for the disordered T1D counterregulatory glucagon response to hypoglycemia., In Brief Brissova et al. find that β cells in the type 1 diabetic (T1D) pancreas maintain several functional and molecular features, but α cells have impaired glucagon secretion and an altered gene expression profile. These findings provide insight into the mechanism of α cell dysfunction in T1D.

OBJECTIVE Obesity is a major risk factor for multiple diseases and is in part heritable, yet the majority of causative genetic variants that drive excessive adiposity remain unknown. Here, outbred heterogeneous stock (HS) rats were used in controlled environmental conditions to fine-map novel genetic modifiers of adiposity. METHODS Body weight and visceral fat pad weights were measured in male HS rats that were also genotyped genome-wide. Quantitative trait loci (QTL) were identified by genome-wide association of imputed single-nucleotide polymorphism (SNP) genotypes using a linear mixed effect model that accounts for unequal relatedness between the HS rats. Candidate genes were assessed by protein modeling and mediation analysis of expression for coding and noncoding variants, respectively. RESULTS HS rats exhibited large variation in adiposity traits, which were highly heritable and correlated with metabolic health. Fine-mapping of fat pad weight and body weight revealed three QTL and prioritized five candidate genes. Fat pad weight was associated with missense SNPs in Adcy3 and Prlhr and altered expression of Krtcap3 and Slc30a3, whereas Grid2 was identified as a candidate within the body weight locus. CONCLUSIONS These data demonstrate the power of HS rats for identification of known and novel heritable mediators of obesity traits.

Single cell RNA-sequencing (scRNA-seq) approaches are continuously improving at the point of data collection and analysis to simultaneously profile all cell types within islet microorgans to better understand heterogeneity and phenotype-function relationships and how these change with aging and disease. To better understand the advantages and limitations of scRNA-seq, we used the ChromiumTMplatform to profile human islets with a robust insulin and glucagon secretion by perifusion (5 nondiabetic donors, ages 14-66 years) and compared these results to scRNA-seq analysis of purified α and β cells. In context of the same donor (n=2), purified α and β cells (using NTPDase3 marker) showed high correlation (r=0.99) with the Seurat-identified α and β subsets originating from dispersed whole islets. Based on the analysis of a very large pool of single cells (79,881 cells; 2316 genes/cell), the Seurat-guided analysis identified cell types that segregated into eight different clusters (17% β, 66% α, 4% δ, 4% ductal, 4% mesenchymal, 2% acinar, 2% endothelial, and 1% immune). Interstingly, in this large single cell context, we did not identify the four β cell subsets previously reported on the basis of alternative cell surface markers, but found a β cell cluster with highly expressed ER stress-associated genes and an α cell cluster with higher cell cycle regulation marker expression. We concurrently investigated expression of functionally important MAFA and MAFB genes, which are expressed only in a fraction of β cells by histological analysis, and found that PERK-mediated UPR transcripts were enriched in the MAFB-expressing β cells, while the MAFA-expressing β cells differentially expressed genes associated with β cell function. Overall, our study indicates high fidelity of α and β cell clustering in dispersed and sorted islet cells and points to a different pattern of β cell heterogeneity when β cells are purified using NTPDase3 expression compared to other cell surface markers. Disclosure S. Shrestha: None. D.C. Saunders: None. J.T. Walker: None. R. Haliyur: None. G. Poffenberger: None. R. Aramandla: None. A. Jones: None. N. Prasad: None. S.E. Levy: None. A.C. Powers: None. M. Brissova: None.

The human sperm is one of the smallest cells in the body, but also one of the most important, as it serves as the entire paternal genetic contribution to a child. This is especially relevant for diseases such as Autism Spectrum Disorders (ASD), which have been correlated with advance paternal age. Historically, most studies of sperm have focused on the assessment of a bulk sperm, wherein millions of individual sperm are present and only high-frequency variants can be detected. Using 10X Chromium single cell sequencing technology, we have assessed the RNA from >65,000 single sperm cells across 6 donors (scsperm-RNA-seq), including two of whom have autistic children and four that do not. Using multiple RNA-seq methods for differential expression and variant analysis, we found clusters of sperm mutations in each donor that are indicative of the sperm being produced by different stem cell pools. Moreover, by comparing the two groups, we have found expression changes that can separate out the two sets of donors. Finally, through our novel variant calling from single-cell RNA-seq methods, we have shown that we can detect mutation rates in sperm from ASD donors that is distinct from the controls, highlighting this method as a new means to characterize ASD risk.

Background Sequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions. Results By evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10−5 to 10−4, which is 10- to 100-fold lower than generally considered achievable (10−3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10−5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10−4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target-enrichment PCR led to ~ 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1 ~ 0.01% frequency with the current NGS technology by applying in silico error suppression. Conclusions We present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing. Electronic supplementary material The online version of this article (10.1186/s13059-019-1659-6) contains supplementary material, which is available to authorized users.

MODY can be wrongly diagnosed as type 1 diabetes in children. We aimed to find the prevalence of MODY in a nationwide population-based registry of childhood diabetes. Using next-generation sequencing, we screened the HNF1A, HNF4A, HNF1B, GCK and INS genes in all 469 children (12.1%) negative for both GAD and IA-2 autoantibodies and 469 antibody-positive matched controls selected from the Norwegian Childhood Diabetes Registry (3882 children). Variants were classified using clinical diagnostic criteria for pathogenicity ranging from class 1 (neutral) to class 5 (pathogenic). We identified 58 rare exonic and splice variants in cases and controls. Among antibody-negative patients, 6.5% had genetic variants of classes 3–5 (vs 2.4% in controls; p = 0.002). For the stricter classification (classes 4 and 5), the corresponding number was 4.1% (vs 0.2% in controls; p = 1.6 × 10−5). HNF1A showed the strongest enrichment of class 3–5 variants, with 3.9% among antibody-negative patients (vs 0.4% in controls; p = 0.0002). Antibody-negative carriers of variants in class 3 had a similar phenotype to those carrying variants in classes 4 and 5. This is the first study screening for MODY in all antibody-negative children in a nationwide population-based registry. Our results suggest that the prevalence of MODY in antibody-negative childhood diabetes may reach 6.5%. One-third of these MODY cases had not been recognised by clinicians. Since a precise diagnosis is important for treatment and genetic counselling, molecular screening of all antibody-negative children should be considered in routine diagnostics.

// Joy M. McDaniel 1, 2 , Katherine E. Varley 3 , Jason Gertz 3 , Daniel S. Savic 1 , Brian S. Roberts 1 , Sarah K. Bailey 4 , Lalita A. Shevde 4, 6 , Ryne C. Ramaker 1, 7 , Brittany N. Lasseigne 1 , Marie K. Kirby 1 , Kimberly M. Newberry 1 , E. Christopher Partridge 1 , Angela L. Jones 1 , Braden Boone 1 , Shawn E. Levy 1 , Patsy G. Oliver 5 , Katherine C. Sexton 6 , William E. Grizzle 6 , Andres Forero 6 , Donald J. Buchsbaum 5 , Sara J. Cooper 1 , Richard M. Myers 1 1 HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA 2 The University of Alabama in Huntsville, Huntsville, AL 35899, USA 3 Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, 84112, USA 4 Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA 5 Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA 6 University of Alabama at Birmingham Comprehensive Cancer Center, Birmingham, AL 35294, USA 7 Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, 35294, USA Correspondence to: Richard M. Myers, email: rmyers@hudsonalpha.org Keywords: TNBC, STAT3, ChIP-seq, RNA-seq, invasion Received: August 15, 2016 Accepted: November 14, 2016 Published: December 24, 2016 ABSTRACT Breast cancer is a heterogeneous disease comprised of four molecular subtypes defined by whether the tumor-originating cells are luminal or basal epithelial cells. Breast cancers arising from the luminal mammary duct often express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth receptor 2 (HER2). Tumors expressing ER and/or PR are treated with anti-hormonal therapies, while tumors overexpressing HER2 are targeted with monoclonal antibodies. Immunohistochemical detection of ER, PR, and HER2 receptors/proteins is a critical step in breast cancer diagnosis and guided treatment. Breast tumors that do not express these proteins are known as “triple negative breast cancer” (TNBC) and are typically basal-like. TNBCs are the most aggressive subtype, with the highest mortality rates and no targeted therapy, so there is a pressing need to identify important TNBC tumor regulators. The signal transducer and activator of transcription 3 (STAT3) transcription factor has been previously implicated as a constitutively active oncogene in TNBC. However, its direct regulatory gene targets and tumorigenic properties have not been well characterized. By integrating RNA-seq and ChIP-seq data from 2 TNBC tumors and 5 cell lines, we discovered novel gene signatures directly regulated by STAT3 that were enriched for processes involving inflammation, immunity, and invasion in TNBC. Functional analysis revealed that STAT3 has a key role regulating invasion and metastasis, a characteristic often associated with TNBC. Our findings suggest therapies targeting STAT3 may be important for preventing TNBC metastasis.

The term next-generation sequencing is almost a decade old, but it remains the colloquial way to describe highly parallel or high-output sequencing methods that produce data at or beyond the genome scale. Since the introduction of these technologies, the number of applications and methods that leverage the power of genome-scale sequencing has increased at an exponential pace. This review highlights recent concepts, technologies, and methods from next-generation sequencing to illustrate the breadth and depth of the applications and research areas that are driving progress in genomics.

Background: Drug susceptibility testing for Mycobacterium tuberculosis (MTB) is difficult to perform in resource-limited settings where Acid Fast Bacilli (AFB) smears are commonly used for disease diagnosis and monitoring. We developed a simple method for extraction of MTB DNA from AFB smears for sequencing-based detection of mutations associated with resistance to all first and several second-line anti-tuberculosis drugs. Methods: We isolated MTB DNA by boiling smear content in a Chelex solution, followed by column purification. We sequenced PCR-amplified segments of the rpoB, katG, embB, gyrA, gyrB, rpsL, and rrs genes, the inhA, eis, and pncA promoters and the entire pncA gene. Results: We tested our assay on 1,208 clinically obtained AFB smears from Ghana (n = 379), Kenya (n = 517), Uganda (n = 262), and Zambia (n = 50). Coverage depth varied by target and slide smear grade, ranging from 300X to 12000X on average. Coverage of ≥20X was obtained for all targets in 870 (72%) slides overall. Mono-resistance (5.9%), multi-drug resistance (1.8%), and poly-resistance (2.4%) mutation profiles were detected in 10% of slides overall, and in over 32% of retreatment and follow-up cases. Conclusion: This rapid AFB smear DNA-based method for determining drug resistance may be useful for the diagnosis and surveillance of drug-resistant tuberculosis. This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Using an integrated approach to characterize the pancreatic tissue and isolated islets from a 33-year-old with 17 years of type 1 diabetes (T1D), we found that donor islets contained β cells without insulitis and lacked glucose-stimulated insulin secretion despite a normal insulin response to cAMP-evoked stimulation. With these unexpected findings for T1D, we sequenced the donor DNA and found a pathogenic heterozygous variant in the gene encoding hepatocyte nuclear factor-1α (HNF1A). In one of the first studies of human pancreatic islets with a disease-causing HNF1A variant associated with the most common form of monogenic diabetes, we found that HNF1A dysfunction leads to insulin-insufficient diabetes reminiscent of T1D by impacting the regulatory processes critical for glucose-stimulated insulin secretion and suggest a rationale for a therapeutic alternative to current treatment.

More than a decade ago, the term "next-generation" sequencing was coined to describe what was, at the time, revolutionary new methods to sequence RNA and DNA at a faster pace and cheaper cost than could be performed by standard bench-top protocols. Since then, the field of DNA sequencing has evolved at a rapid pace, with new breakthroughs allowing capacity to exponentially increase and cost to dramatically decrease. As genome-scale sequencing has become routine, a paradigm shift is occurring in genomics, which uses the power of high-throughput, rapid sequencing power with large-scale studies. These new approaches to genetic discovery will provide direct impact to fields such as personalized medicine, evolution, and biodiversity. This work reviews recent technology advances and methods in next-generation sequencing and highlights current large-scale sequencing efforts driving the evolution of the genomics space.

Purpose Childhood cancer survivors are at increased risk of subsequent neoplasms (SNs), but the germline genetic contribution is largely unknown. We assessed the contribution of pathogenic/likely pathogenic (P/LP) mutations in cancer predisposition genes to their SN risk. Patients and Methods Whole-genome sequencing (30-fold) was performed on samples from childhood cancer survivors who were ≥ 5 years since initial cancer diagnosis and participants in the St Jude Lifetime Cohort Study, a retrospective hospital-based study with prospective clinical follow-up. Germline mutations in 60 genes known to be associated with autosomal dominant cancer predisposition syndromes with moderate to high penetrance were classified by their pathogenicity according to the American College of Medical Genetics and Genomics guidelines. Relative rates (RRs) and 95% CIs of SN occurrence by mutation status were estimated using multivariable piecewise exponential regression stratified by radiation exposure. Results Participants were 3,006 survivors (53% male; median age, 35.8 years [range, 7.1 to 69.8 years]; 56% received radiotherapy), 1,120 SNs were diagnosed among 439 survivors (14.6%), and 175 P/LP mutations were identified in 5.8% (95% CI, 5.0% to 6.7%) of survivors. Mutations were associated with significantly increased rates of breast cancer (RR, 13.9; 95% CI, 6.0 to 32.2) and sarcoma (RR, 10.6; 95% CI, 4.3 to 26.3) among irradiated survivors and with increased rates of developing any SN (RR, 4.7; 95% CI, 2.4 to 9.3), breast cancer (RR, 7.7; 95% CI, 2.4 to 24.4), nonmelanoma skin cancer (RR, 11.0; 95% CI, 2.9 to 41.4), and two or more histologically distinct SNs (RR, 18.6; 95% CI, 3.5 to 99.3) among nonirradiated survivors. Conclusion The findings support referral of all survivors for genetic counseling for potential clinical genetic testing, which should be prioritized for nonirradiated survivors with any SN and for those with breast cancer or sarcoma in the field of prior irradiation.

Bipolar disorder is a complex neuropsychiatric disorder presenting with episodic mood disturbances. In this study we use a transcriptomic imputation approach to identify novel genes and pathways associated with bipolar disorder, as well as three diagnostically and genetically distinct subtypes. Transcriptomic imputation approaches leverage well-curated and publicly available eQTL reference panels to create gene-expression prediction models, which may then be applied to “impute” genetically regulated gene expression (GREX) in large GWAS datasets. By testing for association between phenotype and GREX, rather than genotype, we hope to identify more biologically interpretable associations, and thus elucidate more of the genetic architecture of bipolar disorder.We applied GREX prediction models for 13 brain regions (derived from CommonMind Consortium and GTEx eQTL reference panels) to 21,488 bipolar cases and 54,303 matched controls, constituting the largest transcriptomic imputation study of bipolar disorder (BPD) to date. Additionally, we analyzed three specific BPD subtypes, including 14,938 individuals with subtype 1 (BD-I), 3,543 individuals with subtype 2 (BD-II), and 1,500 individuals with schizoaffective subtype (SAB).We identified 125 gene-tissue associations with BPD, of which 53 represent independent associations after FINEMAP analysis. 29/53 associations were novel; i.e., did not lie within 1Mb of a locus identified in the recent PGC-BD GWAS. We identified 37 independent BD-I gene-tissue associations (10 novel), 2 BD-II associations, and 2 SAB associations. Our BPD, BD-I and BD-II associations were significantly more likely to be differentially expressed in post-mortem brain tissue of BPD, BD-I and BD-II cases than we might expect by chance. Together with our pathway analysis, our results support long-standing hypotheses about bipolar disorder risk, including a role for oxidative stress and mitochondrial dysfunction, the post-synaptic density, and an enrichment of circadian rhythm and clock genes within our results.

Background Microbial communities in our built environments have great influence on human health and disease. A variety of built environments have been characterized using a metagenomics-based approach, including some healthcare settings. However, there has been no study to date that has used this approach in pre-hospital settings, such as ambulances, an important first point-of-contact between patients and hospitals. Results We sequenced 398 samples from 137 ambulances across the USA using shotgun sequencing. We analyzed these data to explore the microbial ecology of ambulances including characterizing microbial community composition, nosocomial pathogens, patterns of diversity, presence of functional pathways and antimicrobial resistance, and potential spatial and environmental factors that may contribute to community composition. We found that the top 10 most abundant species are either common built environment microbes, microbes associated with the human microbiome (e.g., skin), or are species associated with nosocomial infections. We also found widespread evidence of antimicrobial resistance markers (hits ~ 90% samples). We identified six factors that may influence the microbial ecology of ambulances including ambulance surfaces, geographical-related factors (including region, longitude, and latitude), and weather-related factors (including temperature and precipitation). Conclusions While the vast majority of microbial species classified were beneficial, we also found widespread evidence of species associated with nosocomial infections and antimicrobial resistance markers. This study indicates that metagenomics may be useful to characterize the microbial ecology of pre-hospital ambulance settings and that more rigorous testing and cleaning of ambulances may be warranted. Electronic supplementary material The online version of this article (10.1186/s40168-017-0339-6) contains supplementary material, which is available to authorized users.