Search

Changes in the blood-based RNA transcriptome have the potential to inform biomarkers of Parkinson’s disease (PD) progression. Here we sequenced a discovery set of whole-blood RNA species in 4,871 longitudinally collected samples from 1,570 clinically phenotyped individuals from the Parkinson’s Progression Marker Initiative (PPMI) cohort. Samples were sequenced to an average of 100 million read pairs to create a high-quality transcriptome. Participants with PD in the PPMI had significantly altered RNA expression (>2,000 differentially expressed genes), including an early and persistent increase in neutrophil gene expression, with a concomitant decrease in lymphocyte cell counts. This was validated in a cohort from the Parkinson’s Disease Biomarkers Program (PDBP) consisting of 1,599 participants and by alterations in immune cell subtypes. This publicly available transcriptomic dataset, coupled with available detailed clinical data, provides new insights into PD biological processes impacting whole blood and new paths for developing diagnostic and prognostic PD biomarkers. The authors report whole-blood RNA-seq for 4,871 samples from 1,570 participants in the Parkinson Progression Marker Initiative. This Resource documents blood-based transcriptomic changes associated with PD, including early increases in neutrophil gene expression with a decrease in lymphocytes.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

Precise estimates of the single-nucleotide mutation rate and its variability are essential to the study of human genome evolution and genetic diseases. Here we use ~36 million singleton variants observed in 3,716 whole-genome sequences to characterize the heterogeneity of germline mutation rates across the genome. Adjacent-nucleotide context is the strongest predictor of mutability, with mutation rates varying by >650-fold depending on the identity of three bases upstream or downstream of the mutated site. Histone modifications, replication timing, recombination rate, and other local genomic features further modify mutability; magnitude and direction of this modification varies with the sequence context. Compared to estimates based on common variants used in previous approaches, singleton-based estimates provide a more accurate prediction of the mutation patterns seen in an independent dataset of ~46,000 de novo mutations; and incorporating the effects of genomic features further improves the prediction. The effects of sequence contexts, genomic features, and their interactions reported here capture the most refined portrait to date of the germline mutation patterns in humans.

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.

Annual cyanobacterial blooms dominated by Microcystis have occurred in western Lake Erie (U.S./Canada) during summer months since 1995. The production of toxins by bloom-forming cyanobacteria can lead to drinking water crises, such as the one experienced by the city of Toledo in August of 2014, when the city was rendered without drinking water for2 days. It is important to understand the conditions and environmental cues that were driving this specific bloom to provide a scientific framework for management of future bloom events. To this end, samples were collected and metatranscriptomes generated coincident with the collection of environmental metrics for eight sites located in the western basin of Lake Erie, including a station proximal to the water intake for the city of Toledo. These data were used to generate a basin-wide ecophysiological fingerprint of Lake Erie Microcystis populations in August 2014 for comparison to previous bloom communities. Our observations and analyses indicate that, at the time of sample collection, Microcystis populations were under dual nitrogen (N) and phosphorus (P) stress, as genes involved in scavenging of these nutrients were being actively transcribed. Targeted analysis of urea transport and hydrolysis suggests a potentially important role for exogenous urea as a nitrogen source during the 2014 event. Finally, simulation data suggest a wind event caused microcystin-rich water from Maumee Bay to be transported east along the southern shoreline past the Toledo water intake. Coupled with a significant cyanophage infection, these results reveal that a combination of biological and environmental factors led to the disruption of the Toledo water supply. This scenario was not atypical of reoccurring Lake Erie blooms and thus may reoccur in the future.

Enteropathy-associated T cell lymphoma (EATL) is the most common oncologic complication of celiac disease. Moffitt and colleagues identify novel EATL-defining mutations in SETD2, as well as clinically relevant mutations in the JAK-STAT pathway., Enteropathy-associated T cell lymphoma (EATL) is a lethal, and the most common, neoplastic complication of celiac disease. Here, we defined the genetic landscape of EATL through whole-exome sequencing of 69 EATL tumors. SETD2 was the most frequently silenced gene in EATL (32% of cases). The JAK-STAT pathway was the most frequently mutated pathway, with frequent mutations in STAT5B as well as JAK1, JAK3, STAT3, and SOCS1. We also identified mutations in KRAS, TP53, and TERT. Type I EATL and type II EATL (monomorphic epitheliotropic intestinal T cell lymphoma) had highly overlapping genetic alterations indicating shared mechanisms underlying their pathogenesis. We modeled the effects of SETD2 loss in vivo by developing a T cell–specific knockout mouse. These mice manifested an expansion of γδ T cells, indicating novel roles for SETD2 in T cell development and lymphomagenesis. Our data render the most comprehensive genetic portrait yet of this uncommon but lethal disease and may inform future classification schemes.

© 2017, Association of Biomolecular Resource Facilities. All rights reserved. The Extreme Microbiome Project (XMP) is a project launched by the Association of Biomolecular Resource Facilities Metagenomics Research Group (ABRF MGRG) that focuses on whole genome shotgun sequencing of extreme and unique environments using a wide variety of biomolecular techniques. The goals are multifaceted, including development and refinement of new techniques for the following: 1) the detection and characterization of novel microbes, 2) the evaluation of nucleic acid techniques for extremophilic samples, and 3) the identification and implementation of the appropriate bioinformatics pipelines. Here, we highlight the different ongoing projects that we have been working on, as well as details on the various methods we use to characterize the microbiome and metagenome of these complex samples. In particular, we present data of a novel multienzyme extraction protocol that we developed, called Polyzyme or MetaPolyZyme. Presently, the XMP is characterizing sample sites around the world with the intent of discovering new species, genes, and gene clusters. Once a project site is complete, the resulting data will be publically available. Sites include Lake Hillier in Western Australia, the “Door to Hell” crater in Turkmenistan, deep ocean brine lakes of the Gulf of Mexico, deep ocean sediments from Greenland, permafrost tunnels in Alaska, ancient microbial biofilms from Antarctica, Blue Lagoon Iceland, Ethiopian toxic hot springs, and the acidic hypersaline ponds in Western Australia.

Hepatosplenic T-cell lymphoma (HSTL) is a rare and lethal lymphoma; the genetic drivers of this disease are unknown. Through whole-exome sequencing of 68 HSTLs, we define recurrently mutated driver genes and copy-number alterations in the disease. Chromatin-modifying genes, including SETD2, INO80, and ARID1B, were commonly mutated in HSTL, affecting 62% of cases. HSTLs manifest frequent mutations in STAT5B (31%), STAT3 (9%), and PIK3CD (9%), for which there currently exist potential targeted therapies. In addition, we noted less frequent events in EZH2, KRAS, and TP53. SETD2 was the most frequently silenced gene in HSTL. We experimentally demonstrated that SETD2 acts as a tumor suppressor gene. In addition, we found that mutations in STAT5B and PIK3CD activate critical signaling pathways important to cell survival in HSTL. Our work thus defines the genetic landscape of HSTL and implicates gene mutations linked to HSTL pathogenesis and potential treatment targets. Significance: We report the first systematic application of whole-exome sequencing to define the genetic basis of HSTL, a rare but lethal disease. Our work defines SETD2 as a tumor suppressor gene in HSTL and implicates genes including INO80 and PIK3CD in the disease. Cancer Discov; 7(4); 369–79. ©2017 AACR. See related commentary by Yoshida and Weinstock, p. 352. This article is highlighted in the In This Issue feature, p. 339

Carotid intima-media thickness (cIMT) is a subclinical measure of atherosclerosis with mounting evidence that higher cIMT confers an increased risk of cardiovascular disease. The ryanodine receptor 3 gene (RYR3) has previously been linked to increased cIMT; however, the causal variants have not yet been localized. Therefore, we sequenced 339,480 bp encompassing 104 exons and 2 kb flanking region of the RYR3 gene in 96 HIV-positive white men from the extremes of the distribution of common cIMT from the Fat Redistribution and Metabolic Changes in HIV infection study (FRAM). We identified 2710 confirmed variants (2414 single-nucleotide polymorphisms (SNPs) and 296 insertion/deletions (indels)), with a mean count of 736 SNPs (ranging from 528 to 1032) and 170 indels (ranging from 128 to 214) distributed in each individual. There were 39 variants in the exons and 15 of these were non-synonymous, of which with only 4 were common variants and the remaining 11 were rare variants, one was a novel SNP. We confirmed that the common variant rs2229116 was significantly associated with cIMT in this design (P

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific-filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

High-throughput RNA sequencing (RNA-seq) greatly expands the potential for genomics discoveries, but the wide variety of platforms, protocols and performance capabilitites has created the need for comprehensive reference data. Here we describe the Association of Biomolecular Resource Facilities next-generation sequencing (ABRF-NGS) study on RNA-seq. We carried out replicate experiments across 15 laboratory sites using reference RNA standards to test four protocols (poly-A-selected, ribo-depleted, size-selected and degraded) on five sequencing platforms (Illumina HiSeq, Life Technologies PGM and Proton, Pacific Biosciences RS and Roche 454). The results show high intraplatform (Spearman rank R > 0.86) and inter-platform (R > 0.83) concordance for expression measures across the deep-count platforms, but highly variable efficiency and cost for splice junction and variant detection between all platforms. For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA depletion enables effective analysis of degraded RNA samples. This study provides a broad foundation for cross-platform standardization, evaluation and improvement of RNA-seq.

In this study, we define the genetic landscape of mantle cell lymphoma (MCL) through exome sequencing of 56 cases of MCL. We identified recurrent mutations in ATM, CCND1, MLL2, and TP53. We further identified a number of novel genes recurrently mutated in patients with MCL including RB1, WHSC1, POT1, and SMARCA4. We noted that MCLs have a distinct mutational profile compared with lymphomas from other B-cell stages. The ENCODE project has defined the chromatin structure of many cell types. However, a similar characterization of primary human mature B cells has been lacking. We defined, for the first time, the chromatin structure of primary human naïve, germinal center, and memory B cells through chromatin immunoprecipitation and sequencing for H3K4me1, H3K4me3, H3Ac, H3K36me3, H3K27me3, and PolII. We found that somatic mutations that occur more frequently in either MCLs or Burkitt lymphomas were associated with open chromatin in their respective B cells of origin, naïve B cells, and germinal center B cells. Our work thus elucidates the landscape of gene-coding mutations in MCL and the critical interplay between epigenetic alterations associated with B-cell differentiation and the acquisition of somatic mutations in cancer.

Many microbial phyla that are widely distributed in open environments have few or no representatives within animal-associated microbiota. Among them, the Chloroflexi comprises taxonomically and physiologically diverse lineages adapted to a wide range of aquatic and terrestrial habitats. A distinct group of uncultured chloroflexi related to free-living anaerobic Anaerolineae inhabits the mammalian gastrointestinal tract and includes low-abundance human oral bacteria that appear to proliferate in periodontitis. Using a single-cell genomics approach, we obtained the first draft genomic reconstruction for these organisms and compared their inferred metabolic potential with free-living chloroflexi. Genomic data suggest that oral chloroflexi are anaerobic heterotrophs, encoding abundant carbohydrate transport and metabolism functionalities, similar to those seen in environmental Anaerolineae isolates. The presence of genes for a unique phosphotransferase system and N-acetylglucosamine metabolism suggests an important ecological niche for oral chloroflexi in scavenging material from lysed bacterial cells and the human tissue. The inferred ability to produce sialic acid for cell membrane decoration may enable them to evade the host defence system and colonize the subgingival space. As with other low abundance but persistent members of the microbiota, discerning community and host factors that influence the proliferation of oral chloroflexi may help understand the emergence of oral pathogens and the microbiota dynamics in health and disease states.

SummaryPancreatic islet endocrine cell and endothelial cell (EC) interactions mediated by vascular endothelial growth factor-A (VEGF-A) signaling are important for islet differentiation and the formation of highly vascularized islets. To dissect how VEGF-A signaling modulates intra-islet vasculature, islet microenvironment, and β cell mass, we transiently increased VEGF-A production by β cells. VEGF-A induction dramatically increased the number of intra-islet ECs but led to β cell loss. After withdrawal of the VEGF-A stimulus, β cell mass, function, and islet structure normalized as a result of a robust, but transient, burst in proliferation of pre-existing β cells. Bone marrow-derived macrophages (MΦs) recruited to the site of β cell injury were crucial for the β cell proliferation, which was independent of pancreatic location and circulating factors such as glucose. Identification of the signals responsible for the proliferation of adult, terminally differentiated β cells will improve strategies aimed at β cell regeneration and expansion.

MicroRNAs have been implicated in various skin cancers, including melanoma, squamous cell carcinoma, and basal cell carcinoma; however, the expression of microRNAs and their role in Merkel cell carcinoma (MCC) have yet to be explored in depth. To identify microRNAs specific to MCC (MCC-miRs), next-generation sequencing (NGS) of small RNA libraries was performed on different tissue samples including MCCs, other cutaneous tumors, and normal skin. Comparison of the profiles identified several microRNAs upregulated and downregulated in MCC. For validation, their expression was measured via qRT-PCR in a larger group of MCC and in a comparison group of non-MCC cutaneous tumors and normal skin. Eight microRNAs were upregulated in MCC: miR-502-3p, miR-9, miR-7, miR-340, miR-182, miR-190b, miR-873, and miR-183. Three microRNAs were downregulated: miR-3170, miR-125b, and miR-374c. Many of these MCC-miRs, the miR-183/182/96a cistron in particular, have connections to tumorigenic pathways implicated in MCC pathogenesis.In situhybridization confirmed that the highly expressed MCC-miR, miR-182, is localized within tumor cells. Furthermore, NGS and qRT-PCR reveal that several of these MCC-miRs are highly expressed in the patient-derived MCC cell line, MS-1. These data indicate that we have identified a set of MCC-miRs with important implications for MCC research.

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu)., Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P, This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch.

One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited.In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can differ by over three orders of magnitude on the same datasets. Various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species. Overall, pairing tools with different classification strategies (k-mer, alignment, marker) can combine their respective advantages.This study provides positive and negative controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision, accuracy, and recall. We show that proper experimental design and analysis parameters can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

Summary Identification of cell-surface markers specific to human pancreatic β cells would allow in vivo analysis and imaging. Here we introduce a biomarker, ectonucleoside triphosphate diphosphohydrolase-3 (NTPDase3), that is expressed on the cell surface of essentially all adult human β cells, including those from individuals with type 1 or type 2 diabetes. NTPDase3 is expressed dynamically during postnatal human pancreas development, appearing first in acinar cells at birth, but several months later its expression declines in acinar cells while concurrently emerging in islet β cells. Given its specificity and membrane localization, we utilized an NTPDase3 antibody for purification of live human β cells as confirmed by transcriptional profiling, and, in addition, for in vivo imaging of transplanted human β cells. Thus, NTPDase3 is a cell-surface biomarker of adult human β cells, and the antibody directed to this protein should be a useful new reagent for β cell sorting, in vivo imaging, and targeting.

Recent progress has been made in the identification of protein-coding genes and miRNAs that are expressed in and alter the behavior of colonic epithelia. However, the role of long non-coding RNAs (lncRNAs) in colonic homeostasis is just beginning to be explored. By gene expression profiling of post-mitotic, differentiated tops and proliferative, progenitor-compartment bottoms of microdissected adult mouse colonic crypts, we identified several lncRNAs more highly expressed in crypt bottoms. One identified lncRNA, designated non-coding Nras functional RNA (ncNRFR), resides within the Nras locus but appears to be independent of the Nras coding transcript. Stable overexpression of ncNRFR in non-transformed, conditionally immortalized mouse colonocytes results in malignant transformation, as determined by growth in soft agar and formation of highly invasive tumors in nude mice. Moreover, ncNRFR appears to inhibit the function of the tumor suppressor let-7. These results suggest precise regulation of ncNRFR is necessary for proper cell growth in the colonic crypt, and its misregulation results in neoplastic transformation.

Nephrotic syndrome (NS) is divided into steroid-sensitive (SSNS) and -resistant (SRNS) variants. SRNS causes end-stage kidney disease, which cannot be cured. While the disease mechanisms of NS are not well understood, genetic mapping studies suggest a multitude of unknown single-gene causes. We combined homozygosity mapping with whole-exome resequencing and identified an ARHGDIA mutation that causes SRNS. We demonstrated that ARHGDIA is in a complex with RHO GTPases and is prominently expressed in podocytes of rat glomeruli. ARHGDIA mutations (R120X and G173V) from individuals with SRNS abrogated interaction with RHO GTPases and increased active GTP-bound RAC1 and CDC42, but not RHOA, indicating that RAC1 and CDC42 are more relevant to the pathogenesis of this SRNS variant than RHOA. Moreover, the mutations enhanced migration of cultured human podocytes; however, enhanced migration was reversed by treatment with RAC1 inhibitors. The nephrotic phenotype was recapitulated in arhgdia-deficient zebrafish. RAC1 inhibitors were partially effective in ameliorating arhgdia-associated defects. These findings identify a single-gene cause of NS and reveal that RHO GTPase signaling is a pathogenic mediator of SRNS.

Microglia are resident immune cells of the CNS that are activated by infection, neuronal injury, and inflammation. Here, we utilize flow cytometry and deep RNA sequencing of acutely isolated spinal cord microglia to define their activation invivo. Analysis of resting microglia identified 29 genes that distinguish microglia from other CNS cells and peripheral macrophages/monocytes. We then analyzed molecular changes in microglia during neurodegenerative disease activation using the SOD1(G93A) mouse model of amyotrophic lateral sclerosis (ALS). We found that SOD1(G93A) microglia are not derived from infiltrating monocytes, and that both potentially neuroprotective and toxic factors, including Alzheimer's disease genes, are concurrently upregulated. Mutant microglia differed from SOD1(WT), lipopolysaccharide-activated microglia, and M1/M2 macrophages, defining an ALS-specific phenotype. Concurrent messenger RNA/fluorescence-activated cell sorting analysis revealed posttranscriptional regulation of microglia surface receptors and Tcell-associated changes in the transcriptome. These results provide insights into microglia biology and establish a resource for future studies of neuroinflammation.

Acute myeloid leukemia (AML) encompasses a heterogeneous group of diseases, and novel biomarkers for risk refinement and stratification are needed to optimize patient care. To identify novel risk factors, we performed transcriptome sequencing on 68 diagnostic AML samples and identified 2 transcript variants (-E2 and -E2/3) of the α-subunit (ITGA5) of the very late antigen-5 integrin. We then quantified expression of ITGA5 and these splice variants in specimens from participants of the AAML03P1 trial. We found no association between ITGA5 expression and clinical outcome. In contrast, patients with the highest relative expression (Q4) of the -E2/3 ITGA5 splice variant less likely had low-risk disease than Q1-3 patients (21% vs. 38%, P = 0.027). Q4 patients had worse response to chemotherapy with a higher proportion having persistent minimal residual disease (50% vs. 23%, P = 0.003) and inferior overall survival (at 5 years: 48% vs. 67%, P = 0.015); the latter association was limited to low-risk patients (Q4 vs. Q1-3: 56% vs. 85%, P = 0.043) and was not seen in standard-risk (51% vs. 60%, P = 0.340) or high-risk (33% vs. 38%, P = 0.952) patients. Our exploratory studies indicate that transcriptome sequencing is useful for biomarker discovery, as exemplified by the identification of ITGA5 -E2/3 splice variant as potential novel adverse prognostic marker for low-risk AML that, if confirmed, could serve to further risk-stratify this patient subset.

Background Splenic masses are common in older dogs; yet diagnosis preceding splenectomy and histopathology remains elusive. MicroRNAs (miRNAs) are short, non-coding RNAs that play a role in post-transcriptional regulation, and differential expression of miRNAs between normal and tumor tissue has been used to diagnose neoplastic diseases. The objective of this study was to determine differential expression of miRNAs by use of RNA-sequencing in canine spleens that were histologically confirmed as hemangiosarcoma, nodular hyperplasia, or normal. Results Twenty-two miRNAs were found to be differentially expressed in hemangiosarcoma samples (4 between hemangiosarcoma and both nodular hyperplasia and normal spleen and 18 between hemangiosarcoma and normal spleen only). In particular, mir-26a, mir-126, mir-139, mir-140, mir-150, mir-203, mir-424, mir-503, mir-505, mir-542, mir-30e, mir-33b, mir-365, mir-758, mir-22, and mir-452 are of interest in the pathogenesis of hemangiosarcoma. Conclusions Findings of this study confirm the hypothesis that miRNA expression profiles are different between canine splenic hemangiosarcoma, nodular hyperplasia, and normal spleens. A large portion of the differentially expressed miRNAs have roles in angiogenesis, with an additional group of miRNAs being dysregulated in vascular disease processes. Two other miRNAs have been implicated in cancer pathways such as PTEN and cell cycle checkpoints. The finding of multiple miRNAs with roles in angiogenesis and vascular disease is important, as hemangiosarcoma is a tumor of endothelial cells, which are driven by angiogenic stimuli. This study shows that miRNA dysregulation is a potential player in the pathogenesis of canine splenic hemangiosarcoma.

Recent studies have shown that circular RNAs (circRNAs) are abundant, widely expressed in mammals, and can display cell-type specific expression. However, how production of circRNAs is regulated and their precise biological function remains largely unknown. To study how circRNAs might be regulated during colorectal cancer progression, we used three isogenic colon cancer cell lines that differ only in KRAS mutation status. Cellular RNAs from the parental DLD-1 cells that contain both wild-type and G13D mutant KRAS alleles and isogenically-matched derivative cell lines, DKO-1 (mutant KRAS allele only) and DKs-8 (wild-type KRAS allele only) were analyzed using RNA-Seq. We developed a bioinformatics pipeline to identify and evaluate circRNA candidates from RNA-Seq data. Hundreds of high-quality circRNA candidates were identified in each cell line. Remarkably, circRNAs were significantly down-regulated at a global level in DLD-1 and DKO-1 cells compared to DKs-8 cells, indicating a widespread effect of mutant KRAS on circRNA abundance. This finding was confirmed in two independent colon cancer cell lines HCT116 (KRAS mutant) and HKe3 (KRAS WT). In all three cell lines, circRNAs were also found in secreted extracellular-vesicles, and circRNAs were more abundant in exosomes than cells. Our results suggest that circRNAs may serve as promising cancer biomarkers.

Decreasing glucagon action lowers the blood glucose and may be useful therapeutically for diabetes. However, interrupted glucagon signaling leads to α-cell proliferation. To identify postulated hepatic-derived, circulating factor(s) responsible for α-cell proliferation, we used transcriptomics/proteomics/metabolomics in three models of interrupted glucagon signaling and found that proliferation of mouse, zebrafish, and human α-cells was mTOR- and FoxP transcription factor-dependent. Changes in hepatic amino acid (AA) catabolism gene expression predicted the observed increase in circulating AA. Mimicking these AA levels stimulated α-cell proliferation in a newly developed in vitro assay with L-glutamine being a critical AA. α-cell expression of the AA transporter Slc38a5 was markedly increased in mice with interrupted glucagon signaling and played a role in α-cell proliferation. These results indicate a hepatic-α-islet cell axis where glucagon regulates serum AA availability and AA, especially L-glutamine, regulates α-cell proliferation and mass via mTOR-dependent nutrient sensing.

Mechanical integration of the nucleus with the extracellular matrix (ECM) is established by linkage between the cytoskeleton and the nucleus. This integration is hypothesized to mediate sensing of ECM rigidity, but parsing the function of nucleus-cytoskeleton linkage from other mechanisms has remained a central challenge. Here we took advantage of the fact that the LINC (linker of nucleoskeleton and cytoskeleton) complex is a known molecular linker of the nucleus to the cytoskeleton, and asked how it regulates the sensitivity of genome-wide transcription to substratum rigidity. We show that gene mechanosensitivity is preserved after LINC disruption, but reversed in direction. Combined with myosin inhibition studies, we identify genes that depend on nuclear tension for their regulation. We also show that LINC disruption does not attenuate nuclear shape sensitivity to substrate rigidity. Our results show for the first time that the LINC complex facilitates mechano-regulation of expression across the genome.