Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

Multiple genetic paths including massive gene amplification allow Mycobacterium tuberculosis to overcome loss of ESX-3 secretion system substrates.

Mycobacterium tuberculosis (Mtb) possesses five type VII secretion systems (T7SS), virulence determinants that include the secretion apparatus and associated secretion substrates. Mtb strains deleted for the genes encoding substrates of the ESX-3 T7SS, esxG or esxH, require iron supplementation for in vitro growth and are highly attenuated in vivo. In a subset of infected mice, suppressor mutants of esxG or esxH deletions were isolated, which enabled growth to high titers or restored virulence. Suppression was conferred by mechanisms that cause overexpression of an ESX-3 paralogous region that lacks genes for the secretion apparatus but encodes EsxR and EsxS, apparent ESX-3 orphan substrates that functionally compensate for the lack of EsxG or EsxH. The mechanisms include the disruption of a transcriptional repressor and a massive 38- to 60-fold gene amplification. These data identify an iron acquisition regulon, provide insight into T7SS, and reveal a mechanism of Mtb chromosome evolution involving "accordion-type" amplification.

TP53 structure-function relationships in metastatic castrate-sensitive prostate cancer and the impact of APR-246 treatment.

PURPOSE: Despite well-informed work in several malignancies, the phenotypic effects of TP53 mutations in metastatic castration-sensitive prostate cancer (mCSPC) progression and metastasis are not clear. We characterized the structure-function and clinical impact of TP53 mutations in mCSPC. PATIENTS AND METHODS: We performed an international retrospective review of men with mCSPC who underwent next-generation sequencing and were stratified according to TP53 mutational status and metastatic burden. Clinical outcomes included radiographic progression-free survival (rPFS) and overall survival (OS) evaluated with Kaplan-Meier and multivariable Cox regression. We also utilized isogenic cancer cell lines to assess the effect of TP53 mutations and APR-246 treatment on migration, invasion, colony formation in vitro, and tumor growth in vivo. Preclinical experimental observations were compared using t-tests and ANOVA. RESULTS: Dominant-negative (DN) TP53 mutations were enriched in patients with synchronous (vs. metachronous) (20.7% vs. 6.3%, p < 0.01) and polymetastatic (vs. oligometastatic) (14.4% vs. 7.9%, p < 0.01) disease. On multivariable analysis, DN mutations were associated with worse rPFS (hazards ratio [HR] = 1.97, 95% confidence interval [CI]: 1.31-2.98) and overall survival [OS] (HR = 2.05, 95% CI: 1.14-3.68) compared to TP53 wild type (WT). In vitro, 22Rv1 TP53 R175H cells possessed stronger migration, invasion, colony formation ability, and cellular movement pathway enrichment in RNA sequencing analysis compared to 22Rv1 TP53 WT cells. Treatment with APR-246 reversed the effects of TP53 mutations in vitro and inhibited 22Rv1 TP53 R175H tumor growth in vivo in a dosage-dependent manner. CONCLUSIONS: DN TP53 mutations correlated with worse prognosis in prostate cancer patients and higher metastatic potential, which could be counteracted by APR-246 treatment suggesting a potential future therapeutic avenue.

Single nuclei transcriptomics delineates complex immune and kidney cell interactions contributing to kidney allograft fibrosis.

Chronic allograft dysfunction (CAD), characterized histologically by interstitial fibrosis and tubular atrophy, is the major cause of kidney allograft loss. Here, using single nuclei RNA sequencing and transcriptome analysis, we identified the origin, functional heterogeneity, and regulation of fibrosis-forming cells in kidney allografts with CAD. A robust technique was used to isolate individual nuclei from kidney allograft biopsies and successfully profiled 23,980 nuclei from five kidney transplant recipients with CAD and 17,913 nuclei from three patients with normal allograft function. Our analysis revealed two distinct states of fibrosis in CAD; low and high extracellular matrix (ECM) with distinct kidney cell subclusters, immune cell types, and transcriptional profiles. Imaging mass cytometry analysis confirmed increased ECM deposition at the protein level. Proximal tubular cells transitioned to an injured mixed tubular (MT1) phenotype comprised of activated fibroblasts and myofibroblast markers, generated provisional ECM which recruited inflammatory cells, and served as the main driver of fibrosis. MT1 cells in the high ECM state achieved replicative repair evidenced by dedifferentiation and nephrogenic transcriptional signatures. MT1 in the low ECM state showed decreased apoptosis, decreased cycling tubular cells, and severe metabolic dysfunction, limiting the potential for repair. Activated B, T and plasma cells were increased in the high ECM state, while macrophage subtypes were increased in the low ECM state. Intercellular communication between kidney parenchymal cells and donor-derived macrophages, detected several years post-transplantation, played a key role in injury propagation. Thus, our study identified novel molecular targets for interventions aimed to ameliorate or prevent allograft fibrogenesis in kidney transplant recipients.

Single-cell RNA sequencing reveals peripheral blood mononuclear immune cell landscape associated with operational tolerance in a kidney transplant recipient.

Operational tolerance (OT) after kidney transplantation is defined as stable graft acceptance without the need for immunosuppression therapy. However, it is not clear which cellular and molecular pathways are driving tolerance in these patients. In this first-of-its-kind pilot study, we assessed the immune landscape associated with OT using single-cell analyses. Peripheral mononuclear cells from a kidney transplant recipient with OT (Tol), 2 healthy individuals (HC), and a kidney transplant recipient with normal kidney function on standard-of-care immunosuppression (SOC) were evaluated. The immune landscape of the Tol was drastically different from that of SOC and emerged closer to the profile of HC. TCL1A+ naive B cells and LSGAL1+ regulatory T cells (Tregs) were in higher proportions in Tol. We were unable to identify the Treg subcluster in SOC. The ligand-receptor analysis in HC and Tol identified interactions between B cells, and Tregs that enhance the proliferation and suppressive function of Tregs. SOC reported the highest proportion of activated B cells with more cells in the G2M phase. Our single-cell RNA sequencing study identified the mediators of tolerance; however, it emphasizes the requirement of similar investigations on a larger cohort to reaffirm the role of immune cells in tolerance.

Determining Aspergillus fumigatus transcription factor expression and function during invasion of the mammalian lung.

To gain a better understanding of the transcriptional response of Aspergillus fumigatus during invasive pulmonary infection, we used a NanoString nCounter to assess the transcript levels of 467 A. fumigatus genes during growth in the lungs of immunosuppressed mice. These genes included ones known to respond to diverse environmental conditions and those encoding most transcription factors in the A. fumigatus genome. We found that invasive growth in vivo induces a unique transcriptional profile as the organism responds to nutrient limitation and attack by host phagocytes. This in vivo transcriptional response is largely mimicked by in vitro growth in Aspergillus minimal medium that is deficient in nitrogen, iron, and/or zinc. From the transcriptional profiling data, we selected 9 transcription factor genes that were either highly expressed or strongly up-regulated during in vivo growth. Deletion mutants were constructed for each of these genes and assessed for virulence in mice. Two transcription factor genes were found to be required for maximal virulence. One was rlmA, which is required for the organism to achieve maximal fungal burden in the lung. The other was sltA, which regulates of the expression of multiple secondary metabolite gene clusters and mycotoxin genes independently of laeA. Using deletion and overexpression mutants, we determined that the attenuated virulence of the ΔsltA mutant is due in part to decreased expression aspf1, which specifies a ribotoxin, but is not mediated by reduced expression of the fumigaclavine gene cluster or the fumagillin-pseruotin supercluster. Thus, in vivo transcriptional profiling focused on transcription factors genes provides a facile approach to identifying novel virulence regulators.

Comparative transcriptomics from intestinal cells of permissive and non-permissive hosts during Ancylostoma ceylanicum infection reveals unique signatures of protection and host specificity.

Soil-transmitted nematodes (STNs) place a tremendous burden on health and economics worldwide with an estimate of at least 1.5 billion people, or 24% of the population, being infected with at least 1 STN globally. Children and pregnant women carry the heavier pathological burden, and disease caused by the blood-feeding worm in the intestine can result in anaemia and delays in physical and intellectual development. These parasites are capable of infecting and reproducing in various host species, but what determines host specificity remains unanswered. Identifying the molecular determinants of host specificity would provide a crucial breakthrough towards understanding the biology of parasitism and could provide attractive targets for intervention. To investigate specificity mechanisms, members of the hookworm genus Ancylostoma provide a powerful system as they range from strict specialists to generalists. Using transcriptomics, differentially expressed genes (DEGs) in permissive (hamster) and non-permissive (mouse) hosts at different early time points during infection with A. ceylanicum were examined. Analysis of the data has identified unique immune responses in mice, as well as potential permissive signals in hamsters. Specifically, immune pathways associated with resistance to infection are upregulated in the non-permissive host, providing a possible protection mechanism that is absent in the permissive host. Furthermore, unique signatures of host specificity that may inform the parasite that it has invaded a permissive host were identified. These data provide novel insight into the tissue-specific gene expression differences between permissive and non-permissive hosts in response to hookworm infection.

Evolutionary history of modern Samoans.

Archaeological studies estimate the initial settlement of Samoa at 2,750 to 2,880 y ago and identify only limited settlement and human modification to the landscape until about 1,000 to 1,500 y ago. At this point, a complex history of migration is thought to have begun with the arrival of people sharing ancestry with Near Oceanic groups (i.e., Austronesian-speaking and Papuan-speaking groups), and was then followed by the arrival of non-Oceanic groups during European colonialism. However, the specifics of this peopling are not entirely clear from the archaeological and anthropological records, and is therefore a focus of continued debate. To shed additional light on the Samoan population history that this peopling reflects, we employ a population genetic approach to analyze 1,197 Samoan high-coverage whole genomes. We identify population splits between the major Samoan islands and detect asymmetrical gene flow to the capital city. We also find an extreme bottleneck until about 1,000 y ago, which is followed by distinct expansions across the islands and subsequent bottlenecks consistent with European colonization. These results provide for an increased understanding of Samoan population history and the dynamics that inform it, and also demonstrate how rapid demographic processes can shape modern genomes.

Evolutionary genomic dynamics of Peruvians before, during, and after the Inca Empire.

Native Americans from the Amazon, Andes, and coastal geographic regions of South America have a rich cultural heritage but are genetically understudied, therefore leading to gaps in our knowledge of their genomic architecture and demographic history. In this study, we sequence 150 genomes to high coverage combined with an additional 130 genotype array samples from Native American and mestizo populations in Peru. The majority of our samples possess greater than 90% Native American ancestry, which makes this the most extensive Native American sequencing project to date. Demographic modeling reveals that the peopling of Peru began ∼12,000 y ago, consistent with the hypothesis of the rapid peopling of the Americas and Peruvian archeological data. We find that the Native American populations possess distinct ancestral divisions, whereas the mestizo groups were admixtures of multiple Native American communities that occurred before and during the Inca Empire and Spanish rule. In addition, the mestizo communities also show Spanish introgression largely following Peruvian Independence, nearly 300 y after Spain conquered Peru. Further, we estimate migration events between Peruvian populations from all three geographic regions with the majority of between-region migration moving from the high Andes to the low-altitude Amazon and coast. As such, we present a detailed model of the evolutionary dynamics which impacted the genomes of modern-day Peruvians and a Native American ancestry dataset that will serve as a beneficial resource to addressing the underrepresentation of Native American ancestry in sequencing studies.

Bioinformatic analysis of bacteria and host cell dual RNA-sequencing experiments.

Bacterial pathogens subvert host cells by manipulating cellular pathways for survival and replication; in turn, host cells respond to the invading pathogen through cascading changes in gene expression. Deciphering these complex temporal and spatial dynamics to identify novel bacterial virulence factors or host response pathways is crucial for improved diagnostics and therapeutics. Dual RNA sequencing (dRNA-Seq) has recently been developed to simultaneously capture host and bacterial transcriptomes from an infected cell. This approach builds on the high sensitivity and resolution of RNA sequencing technology and is applicable to any bacteria that interact with eukaryotic cells, encompassing parasitic, commensal or mutualistic lifestyles. Several laboratory protocols have been presented that outline the collection, extraction and sequencing of total RNA for dRNA-Seq experiments, but there is relatively little guidance available for the detailed bioinformatic analyses required. This protocol outlines a typical dRNA-Seq experiment, based on a Chlamydia trachomatis-infected host cell, with a detailed description of the necessary bioinformatic analyses with currently available software tools.

Detecting geospatial patterns of Plasmodium falciparum parasite migration in Cambodia using optimized estimated effective migration surfaces.

BACKGROUND: Understanding the genetic structure of natural populations provides insight into the demographic and adaptive processes that have affected those populations. Such information, particularly when integrated with geospatial data, can have translational applications for a variety of fields, including public health. Estimated effective migration surfaces (EEMS) is an approach that allows visualization of the spatial patterns in genomic data to understand population structure and migration. In this study, we developed a workflow to optimize the resolution of spatial grids used to generate EEMS migration maps and applied this optimized workflow to estimate migration of Plasmodium falciparum in Cambodia and bordering regions of Thailand and Vietnam. METHODS: The optimal density of EEMS grids was determined based on a new workflow created using density clustering to define genomic clusters and the spatial distance between genomic clusters. Topological skeletons were used to capture the spatial distribution for each genomic cluster and to determine the EEMS grid density; i.e., both genomic and spatial clustering were used to guide the optimization of EEMS grids. Model accuracy for migration estimates using the optimized workflow was tested and compared to grid resolutions selected without the optimized workflow. As a test case, the optimized workflow was applied to genomic data generated from P. falciparum sampled in Cambodia and bordering regions, and migration maps were compared to estimates of malaria endemicity, as well as geographic properties of the study area, as a means of validating observed migration patterns. RESULTS: Optimized grids displayed both high model accuracy and reduced computing time compared to grid densities selected in an unguided manner. In addition, EEMS migration maps generated for P. falciparum using the optimized grid corresponded to estimates of malaria endemicity and geographic properties of the study region that might be expected to impact malaria parasite migration, supporting the validity of the observed migration patterns. CONCLUSIONS: Optimized grids reduce spatial uncertainty in the EEMS contours that can result from user-defined parameters, such as the resolution of the spatial grid used in the model. This workflow will be useful to a broad range of EEMS users as it can be applied to analyses involving other organisms of interest and geographic areas.

Streptococcus pneumoniae in the heart subvert the host response through biofilm-mediated resident macrophage killing.

For over 130 years, invasive pneumococcal disease has been associated with the presence of extracellular planktonic pneumococci, i.e. diplococci or short chains in affected tissues. Herein, we show that Streptococcus pneumoniae that invade the myocardium instead replicate within cellular vesicles and transition into non-purulent biofilms. Pneumococci within mature cardiac microlesions exhibited salient biofilm features including intrinsic resistance to antibiotic killing and the presence of an extracellular matrix. Dual RNA-seq and subsequent principal component analyses of heart- and blood-isolated pneumococci confirmed the biofilm phenotype in vivo and revealed stark anatomical site-specific differences in virulence gene expression; the latter having major implications on future vaccine antigen selection. Our RNA-seq approach also identified three genomic islands as exclusively expressed in vivo. Deletion of one such island, Region of Diversity 12, resulted in a biofilm-deficient and highly inflammogenic phenotype within the heart; indicating a possible link between the biofilm phenotype and a dampened host-response. We subsequently determined that biofilm pneumococci released greater amounts of the toxin pneumolysin than did planktonic or RD12 deficient pneumococci. This allowed heart-invaded wildtype pneumococci to kill resident cardiac macrophages and subsequently subvert cytokine/chemokine production and neutrophil infiltration into the myocardium. This is the first report for pneumococcal biofilm formation in an invasive disease setting. We show that biofilm pneumococci actively suppress the host response through pneumolysin-mediated immune cell killing. As such, our findings contradict the emerging notion that biofilm pneumococci are passively immunoquiescent.

A comparative analysis of library prep approaches for sequencing low input translatome samples.

BACKGROUND: Cell type-specific ribosome-pulldown has become an increasingly popular method for analysis of gene expression. It allows for expression analysis from intact tissues and monitoring of protein synthesis in vivo. However, while its utility has been assessed, technical aspects related to sequencing of these samples, often starting with a smaller amount of RNA, have not been reported. In this study, we evaluated the performance of five library prep protocols for ribosome-associated mRNAs when only 250 pg-4 ng of total RNA are used. RESULTS: We obtained total and RiboTag-IP RNA, in three biological replicates. We compared 5 methods of library preparation for Illumina Next Generation sequencing: NuGEN Ovation RNA-Seq system V2 Kit, TaKaRa SMARTer Stranded Total RNA-Seq Kit, TaKaRa SMART-Seq v4 Ultra Low Input RNA Kit, Illumina TruSeq RNA Library Prep Kit v2 and NEBNext® Ultra™ Directional RNA Library Prep Kit using slightly modified protocols each with 4 ng of total RNA. An additional set of samples was processed using the TruSeq kit with 70 ng, as a 'gold standard' control and the SMART-Seq v4 with 250 pg of total RNA. TruSeq-processed samples had the best metrics overall, with similar results for the 4 ng and 70 ng samples. The results of the SMART-Seq v4 processed samples were similar to TruSeq (Spearman correlation > 0.8) despite using lower amount of input RNA. All RiboTag-IP samples had an increase in the intronic reads compared with the corresponding whole tissue, suggesting that the IP captures some immature mRNAs. The SMARTer-processed samples had a higher representation of ribosomal and non-coding RNAs leading to lower representation of protein coding mRNA. The enrichment or depletion of IP samples compared to corresponding input RNA was similar across all kits except for SMARTer kit. CONCLUSION: RiboTag-seq can be performed successfully with as little as 250 pg of total RNA when using the SMART-Seq v4 kit and 4 ng when using the modified protocols of other library preparation kits. The SMART-Seq v4 and TruSeq kits resulted in the highest quality libraries. RiboTag IP RNA contains some immature transcripts.

Identification of a gene expression signature associated with the metastasis suppressor function of NME1: prognostic value in human melanoma.

Although NME1 is well known for its ability to suppress metastasis of melanoma, the molecular mechanisms underlying this activity are not completely understood. Herein, we utilized a bioinformatics approach to systematically identify genes whose expression is correlated with the metastasis suppressor function of NME1. This was accomplished through a search for genes that were regulated by NME1, but not by NME1 variants lacking metastasis suppressor activity. This approach identified a number of novel genes, such as ALDOC, CXCL11, LRP1b, and XAGE1 as well as known targets such as NETO2, which were collectively designated as an NME1-Regulated Metastasis Suppressor Signature (MSS). The MSS was associated with prolonged overall survival in a large cohort of melanoma patients in The Cancer Genome Atlas (TCGA). The median overall survival of melanoma patients with elevated expression of the MSS genes was >5.6 years longer compared with that of patients with lower expression of the MSS genes. These data demonstrate that NMEl represents a powerful tool for identifying genes whose expression is associated with metastasis and survival of melanoma patients, suggesting their potential applications as prognostic markers and therapeutic targets in advanced forms of this lethal cancer.

New signaling pathways govern the host response to C. albicans infection in various niches.

Candida albicans, the major invasive fungal pathogen of humans, can cause both debilitating mucosal infections and fatal invasive infections. Understanding the complex nature of the host-pathogen interaction in each of these contexts is essential to developing desperately needed therapies to treat fungal infections. RNA-seq enables a systems-level understanding of infection by facilitating comprehensive analysis of transcriptomes from multiple species (e.g., host and pathogen) simultaneously. We used RNA-seq to characterize the transcriptomes of both C. albicans and human endothelial cells or oral epithelial cells during in vitro infection. Network analysis of the differentially expressed genes identified the activation of several signaling pathways that have not previously been associated with the host response to fungal pathogens. Using an siRNA knockdown approach, we demonstrate that two of these pathways-platelet-derived growth factor BB (PDGF BB) and neural precursor-cell-expressed developmentally down-regulated protein 9 (NEDD9)-govern the host-pathogen interaction by regulating the uptake of C. albicans by host cells. Using RNA-seq analysis of a mouse model of hematogenously disseminated candidiasis (HDC) and episodes of vulvovaginal candidiasis (VVC) in humans, we found evidence that many of the same signaling pathways are activated during mucosal (VVC) and/or disseminated (HDC) infections in vivo. Our analyses have uncovered several signaling pathways at the interface between C. albicans and host cells in various contexts of infection, and suggest that PDGF BB and NEDD9 play important roles in this interaction. In addition, these data provide a valuable community resource for better understanding host-fungal pathogen interactions.

Association of a Novel Mutation in the Plasmodium falciparum Chloroquine Resistance Transporter With Decreased Piperaquine Sensitivity.

Background: Amplified copy number in the plasmepsin II/III genes within Plasmodium falciparum has been associated with decreased sensitivity to piperaquine. To examine this association and test whether additional loci might also contribute, we performed a genome-wide association study of ex vivo P. falciparum susceptibility to piperaquine. Methods: Plasmodium falciparum DNA from 183 samples collected primarily from Cambodia was genotyped at 33716 genome-wide single nucleotide polymorphisms (SNPs). Linear mixed models and random forests were used to estimate associations between parasite genotypes and piperaquine susceptibility. Candidate polymorphisms were evaluated for their association with dihydroartemisinin-piperaquine treatment outcomes in an independent dataset. Results: Single nucleotide polymorphisms on multiple chromosomes were associated with piperaquine 90% inhibitory concentrations (IC90) in a genome-wide analysis. Fine-mapping of genomic regions implicated in genome-wide analyses identified multiple SNPs in linkage disequilibrium with each other that were significantly associated with piperaquine IC90, including a novel mutation within the gene encoding the P. falciparum chloroquine resistance transporter, PfCRT. This mutation (F145I) was associated with dihydroartemisinin-piperaquine treatment failure after adjusting for the presence of amplified plasmepsin II/III, which was also associated with decreased piperaquine sensitivity. Conclusions: Our data suggest that, in addition to plasmepsin II/III copy number, other loci, including pfcrt, may also be involved in piperaquine resistance.

DNA Methylation Patterns in Cord Blood of Neonates Across Gestational Age: Association With Cell-Type Proportions.

BACKGROUND: A statistical methodology is available to estimate the proportion of cell types (cellular heterogeneity) in adult whole blood specimens used in epigenome-wide association studies (EWAS). However, there is no methodology to estimate the proportion of cell types in umbilical cord blood (also a heterogeneous tissue) used in EWAS. OBJECTIVES: The objectives of this study were to determine whether differences in DNA methylation (DNAm) patterns in umbilical cord blood are the result of blood cell type proportion changes that typically occur across gestational age and to demonstrate the effect of cell type proportion confounding by comparing preterm infants exposed and not exposed to antenatal steroids. METHODS: We obtained DNAm profiles of cord blood using the Illumina HumanMethylation27k BeadChip array for 385 neonates from the Boston Birth Cohort. We estimated cell type proportions for six cell types using the deconvolution method developed by . RESULTS: The cell type proportion estimates segregated into two groups that were significantly different by gestational age, indicating that gestational age was associated with cell type proportion. Among infants exposed to antenatal steroids, the number of differentially methylated CpGs dropped from 127 to 1 after controlling for cell type proportion. DISCUSSION: EWAS utilizing cord blood are confounded by cell type proportion. Careful study design including correction for cell type proportion and interpretation of results of EWAS using cord blood are critical.

Drosophila anti-nematode and antibacterial immune regulators revealed by RNA-Seq.

BACKGROUND: Drosophila melanogaster activates a variety of immune responses against microbial infections. However, information on the Drosophila immune response to entomopathogenic nematode infections is currently limited. The nematode Heterorhabditis bacteriophora is an insect parasite that forms a mutualistic relationship with the gram-negative bacteria Photorhabdus luminescens. Following infection, the nematodes release the bacteria that quickly multiply within the insect and produce several toxins that eventually kill the host. Although we currently know that the insect immune system interacts with Photorhabdus, information on interaction with the nematode vector is scarce. RESULTS: Here we have used next generation RNA-sequencing to analyze the transcriptional profile of wild-type adult flies infected by axenic Heterorhabditis nematodes (lacking Photorhabdus bacteria), symbiotic Heterorhabditis nematodes (carrying Photorhabdus bacteria), and Photorhabdus bacteria alone. We have obtained approximately 54 million reads from the different infection treatments. Bioinformatic analysis shows that infection with Photorhabdus alters the transcription of a large number of Drosophila genes involved in translational repression as well in response to stress. However, Heterorhabditis infection alters the transcription of several genes that participate in lipidhomeostasis and metabolism, stress responses, DNA/protein synthesis and neuronal functions. We have also identified genes in the fly with potential roles in nematode recognition, anti-nematode activity and nociception. CONCLUSIONS: These findings provide fundamental information on the molecular events that take place in Drosophila upon infection with the two pathogens, either separately or together. Such large-scale transcriptomic analyses set the stage for future functional studies aimed at identifying the exact role of key factors in the Drosophila immune response against nematode-bacteria complexes.

Genome-wide small nucleolar RNA expression analysis of lung cancer by next-generation deep sequencing.

Emerging evidence indicates that small nucleolar RNAs (snoRNAs), a class of small noncoding RNAs, may play important function in tumorigenesis. Nonsmall-cell lung cancer (NSCLC) is the number one cancer killer for men and women. Systematically characterizing snoRNAs in NSCLC will develop biomarkers for its early detection and prognostication. We used next-generation deep sequencing to comprehensively characterize snoRNA profiles in 12 NSCLC tissues. We used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the findings in 40 surgical Stage I NSCLC specimens and 126 frozen NSCLC tissues of different stages. The 126 NSCLC tissues were divided into a training set and a testing set. Deep sequencing identified 458 snoRNAs, of which, 29 had a ≥3.0-fold expression level change in Stage I NSCLC tissues versus normal tissues. qRT-PCR analysis showed that 16 of 29 snoRNAs exhibited consistent changes with deep sequencing data. The 16 snoRNAs exhibited 0.75-0.94 area under receiver-operator characteristic curve values in distinguishing lung tumor from normal lung tissues (all ≤0.0001) with 70.0-95.0% sensitivity and 70.0-95.0% specificity. Six genes (snoRA47, snoRA68, snoRA78, snoRA21, snoRD28 and snoRD66) were identified whose expressions were associated with overall survival of the NSCLC patients. A prediction model consisting of three genes (snoRA47, snoRA68 and snoRA78) was developed in the training set of 77 cases, which could significantly predict overall survival of the NSCLC patients (p < 0.0001). The prognostic performance of the prediction model was confirmed in the testing set of 49 NSCLC patients. The identified snoRNA signatures may provide potential biomarkers for the early detection and prognostication of NSCLC.

Map of open and closed chromatin domains in Drosophila genome.

BACKGROUND: Chromatin compactness has been considered a major determinant of gene activity and has been associated with specific chromatin modifications in studies on a few individual genetic loci. At the same time, genome-wide patterns of open and closed chromatin have been understudied, and are at present largely predicted from chromatin modification and gene expression data. However the universal applicability of such predictions is not self-evident, and requires experimental verification. RESULTS: We developed and implemented a high-throughput analysis for general chromatin sensitivity to DNase I which provides a comprehensive epigenomic assessment in a single assay. Contiguous domains of open and closed chromatin were identified by computational analysis of the data, and correlated to other genome annotations including predicted chromatin "states", individual chromatin modifications, nuclear lamina interactions, and gene expression. While showing that the widely trusted predictions of chromatin structure are correct in the majority of cases, we detected diverse "exceptions" from the conventional rules. We found a profound paucity of chromatin modifications in a major fraction of closed chromatin, and identified a number of loci where chromatin configuration is opposite to that expected from modification and gene expression patterns. Further, we observed that chromatin of large introns tends to be closed even when the genes are expressed, and that a significant proportion of active genes including their promoters are located in closed chromatin. CONCLUSIONS: These findings reveal limitations of the existing predictive models, indicate novel mechanisms of epigenetic regulation, and provide important insights into genome organization and function.