STAR: ultrafast universal RNA-seq aligner

Mosquito genomics. Highly evolvable malaria vectors: the genomes of 16 Anopheles mosquitoes

Variation in vectorial capacity for human malaria among Anopheles mosquito species is determined by many factors, including behavior, immunity, and life history. To investigate the genomic basis of vectorial capacity and explore new avenues for vector control, we sequenced the genomes of 16 anopheline mosquito species from diverse locations spanning ~100 million years of evolution. Comparative analyses show faster rates of gene gain and loss, elevated gene shuffling on the X chromosome, and more intron losses, relative to Drosophila. Some determinants of vectorial capacity, such as chemosensory genes, do not show elevated turnover but instead diversify through protein-sequence changes. This dynamism of anopheline genes and genomes may contribute to their flexible capacity to take advantage of new ecological niches, including adapting to humans as primary hosts.

An integrated transcriptome and expressed variant analysis of sepsis survival and death

Background

Sepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality.

Methods

The Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (SIRS due to infection), including 78 sepsis survivors and 28 sepsis non-survivors who had previously undergone plasma proteomic and metabolomic profiling. Gene expression differences were identified between sepsis survivors, sepsis non-survivors, and SIRS followed by gene enrichment pathway analysis. Expressed sequence variants were identified followed by testing for association with sepsis outcomes.

Results

The expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflecting immune activation in sepsis. Expression of 1,238 genes differed with sepsis outcome: non-survivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease-rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors. The presence of variants was associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology.

Conclusions

The activation of immune response-related genes seen in sepsis survivors was muted in sepsis non-survivors. The association of sepsis survival with a robust immune response and the presence of missense variants in VPS9D1 warrants replication and further functional studies.

Trial registration

ClinicalTrials.gov NCT00258869. Registered on 23 November 2005.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-014-0111-5) contains supplementary material, which is available to authorized users.

Network dynamics determine the autocrine and paracrine signaling functions of TNF

A hallmark of the inflammatory response to pathogen exposure is the production of tumor necrosis factor (TNF) that coordinates innate and adaptive immune responses by functioning in an autocrine or paracrine manner. Numerous molecular mechanisms contributing to TNF production have been identified, but how they function together in macrophages remains unclear. Here, we pursued an iterative systems biology approach to develop a quantitative understanding of the regulatory modules that control TNF mRNA synthesis and processing, mRNA half-life and translation, and protein processing and secretion. By linking the resulting model of TNF production to models of the TLR-, the TNFR-, and the NFκB signaling modules, we were able to study TNF's functions during the inflammatory response to diverse TLR agonists. Contrary to expectation, we predicted and then experimentally confirmed that in response to lipopolysaccaride, TNF does not have an autocrine function in amplifying the NFκB response, although it plays a potent paracrine role in neighboring cells. However, in response to CpG DNA, autocrine TNF extends the duration of NFκB activity and shapes CpG-induced gene expression programs. Our systems biology approach revealed that network dynamics of MyD88 and TRIF signaling and of cytokine production and response govern the stimulus-specific autocrine and paracrine functions of TNF.

Transcription restores DNA repair to heterochromatin, determining regional mutation rates in cancer genomes

Somatic mutations in cancer are more frequent in heterochromatic and late-replicating regions of the genome. We report that regional disparities in mutation density are virtually abolished within transcriptionally silent genomic regions of cutaneous squamous cell carcinomas (cSCCs) arising in an XPC(-/-) background. XPC(-/-) cells lack global genome nucleotide excision repair (GG-NER), thus establishing differential access of DNA repair machinery within chromatin-rich regions of the genome as the primary cause for the regional disparity. Strikingly, we find that increasing levels of transcription reduce mutation prevalence on both strands of gene bodies embedded within H3K9me3-dense regions, and only to those levels observed in H3K9me3-sparse regions, also in an XPC-dependent manner. Therefore, transcription appears to reduce mutation prevalence specifically by relieving the constraints imposed by chromatin structure on DNA repair. We model this relationship among transcription, chromatin state, and DNA repair, revealing a new, personalized determinant of cancer risk.

Development of novel activin-targeted therapeutics

Soluble activin type II receptors (ActRIIA/ActRIIB), via binding to diverse TGF-β proteins, can increase muscle and bone mass, correct anemia or protect against diet-induced obesity. While exciting, these multiple actions of soluble ActRIIA/IIB limit their therapeutic potential and highlight the need for new reagents that target specific ActRIIA/IIB ligands. Here, we modified the activin A and activin B prodomains, regions required for mature growth factor synthesis, to generate specific activin antagonists. Initially, the prodomains were fused to the Fc region of mouse IgG2A antibody and, subsequently, "fastener" residues (Lys(45), Tyr(96), His(97), and Ala(98); activin A numbering) that confer latency to other TGF-β proteins were incorporated. For the activin A prodomain, these modifications generated a reagent that potently (IC(50) 5 nmol/l) and specifically inhibited activin A signaling in vitro, and activin A-induced muscle wasting in vivo. Interestingly, the modified activin B prodomain inhibited both activin A and B signaling in vitro (IC(50) ~2 nmol/l) and in vivo, suggesting it could serve as a general activin antagonist. Importantly, unlike soluble ActRIIA/IIB, the modified prodomains did not inhibit myostatin or GDF-11 activity. To underscore the therapeutic utility of specifically antagonising activin signaling, we demonstrate that the modified activin prodomains promote significant increases in muscle mass.

Long noncoding RNA EWSAT1-mediated gene repression facilitates Ewing sarcoma oncogenesis

Chromosomal translocation that results in fusion of the genes encoding RNA-binding protein EWS and transcription factor FLI1 (EWS-FLI1) is pathognomonic for Ewing sarcoma. EWS-FLI1 alters gene expression through mechanisms that are not completely understood. We performed RNA sequencing (RNAseq) analysis on primary pediatric human mesenchymal progenitor cells (pMPCs) expressing EWS-FLI1 in order to identify gene targets of this oncoprotein. We determined that long noncoding RNA-277 (Ewing sarcoma-associated transcript 1 [EWSAT1]) is upregulated by EWS-FLI1 in pMPCs. Inhibition of EWSAT1 expression diminished the ability of Ewing sarcoma cell lines to proliferate and form colonies in soft agar, whereas EWSAT1 inhibition had no effect on other cell types tested. Expression of EWS-FLI1 and EWSAT1 repressed gene expression, and a substantial fraction of targets that were repressed by EWS-FLI1 were also repressed by EWSAT1. Analysis of RNAseq data from primary human Ewing sarcoma further supported a role for EWSAT1 in mediating gene repression. We identified heterogeneous nuclear ribonucleoprotein (HNRNPK) as an RNA-binding protein that interacts with EWSAT1 and found a marked overlap in HNRNPK-repressed genes and those repressed by EWS-FLI1 and EWSAT1, suggesting that HNRNPK participates in EWSAT1-mediated gene repression. Together, our data reveal that EWSAT1 is a downstream target of EWS-FLI1 that facilitates the development of Ewing sarcoma via the repression of target genes.

De-regulation of gene expression and alternative splicing affects distinct cellular pathways in the aging hippocampus

Aging is accompanied by gradually increasing impairment of cognitive abilities and constitutes the main risk factor of neurodegenerative conditions like Alzheimer's disease (AD). The underlying mechanisms are however not well understood. Here we analyze the hippocampal transcriptome of young adult mice and two groups of mice at advanced age using RNA sequencing. This approach enabled us to test differential expression of coding and non-coding transcripts, as well as differential splicing and RNA editing. We report a specific age-associated gene expression signature that is associated with major genetic risk factors for late-onset AD (LOAD). This signature is dominated by neuroinflammatory processes, specifically activation of the complement system at the level of increased gene expression, while de-regulation of neuronal plasticity appears to be mediated by compromised RNA splicing.

TP53 engagement with the genome occurs in distinct local chromatin environments via pioneer factor activity

Despite overwhelming evidence that transcriptional activation by TP53 is critical for its tumor suppressive activity, the mechanisms by which TP53 engages the genome in the context of chromatin to activate transcription are not well understood. Using a compendium of novel and existing genome-wide data sets, we examined the relationship between TP53 binding and the dynamics of the local chromatin environment. Our analysis revealed three distinct categories of TP53 binding events that differ based on the dynamics of the local chromatin environment. The first class of TP53 binding events occurs near transcriptional start sites (TSS) and is defined by previously characterized promoter-associated chromatin modifications. The second class comprises a large cohort of preestablished, promoter-distal enhancer elements that demonstrates dynamic histone acetylation and transcription upon TP53 binding. The third class of TP53 binding sites is devoid of classic chromatin modifications and, remarkably, fall within regions of inaccessible chromatin, suggesting that TP53 has intrinsic pioneer factor activity and binds within structurally inaccessible regions of chromatin. Intriguingly, these inaccessible TP53 binding sites feature several enhancer-like properties in cell types within the epithelial lineage, indicating that TP53 binding events include a group of “proto-enhancers” that become active enhancers given the appropriate cellular context. These data indicate that TP53, along with TP63, may act as pioneer factors to specify epithelial enhancers. Further, these findings suggest that rather than following a global cell-type invariant stress response program, TP53 may tune its response based on the lineage-specific epigenomic landscape.

Nuclear stability and transcriptional directionality separate functionally distinct RNA species

Mammalian genomes are pervasively transcribed, yielding a complex transcriptome with high variability in composition and cellular abundance. Although recent efforts have identified thousands of new long non-coding (lnc) RNAs and demonstrated a complex transcriptional repertoire produced by protein-coding (pc) genes, limited progress has been made in distinguishing functional RNA from spurious transcription events. This is partly due to present RNA classification, which is typically based on technical rather than biochemical criteria. Here we devise a strategy to systematically categorize human RNAs by their sensitivity to the ribonucleolytic RNA exosome complex and by the nature of their transcription initiation. These measures are surprisingly effective at correctly classifying annotated transcripts, including lncRNAs of known function. The approach also identifies uncharacterized stable lncRNAs, hidden among a vast majority of unstable transcripts. The predictive power of the approach promises to streamline the functional analysis of known and novel RNAs.

An update on LNCipedia: a database for annotated human lncRNA sequences

The human genome is pervasively transcribed, producing thousands of non-coding RNA transcripts. The majority of these transcripts are long non-coding RNAs (lncRNAs) and novel lncRNA genes are being identified at rapid pace. To streamline these efforts, we created LNCipedia, an online repository of lncRNA transcripts and annotation. Here, we present LNCipedia 3.0 (http://www.lncipedia.org), the latest version of the publicly available human lncRNA database. Compared to the previous version of LNCipedia, the database grew over five times in size, gaining over 90,000 new lncRNA transcripts. Assessment of the protein-coding potential of LNCipedia entries is improved with state-of-the art methods that include large-scale reprocessing of publicly available proteomics data. As a result, a high-confidence set of lncRNA transcripts with low coding potential is defined and made available for download. In addition, a tool to assess lncRNA gene conservation between human, mouse and zebrafish has been implemented.

PRC2 is recurrently inactivated through EED or SUZ12 loss in malignant peripheral nerve sheath tumors

Malignant peripheral nerve sheath tumors (MPNSTs) represent a group of highly aggressive soft-tissue sarcomas that may occur sporadically, in association with neurofibromatosis type I (NF1 associated) or after radiotherapy. Using comprehensive genomic approaches, we identified loss-of-function somatic alterations of the Polycomb repressive complex 2 (PRC2) components (EED or SUZ12) in 92% of sporadic, 70% of NF1-associated and 90% of radiotherapy-associated MPNSTs. MPNSTs with PRC2 loss showed complete loss of trimethylation at lysine 27 of histone H3 (H3K27me3) and aberrant transcriptional activation of multiple PRC2-repressed homeobox master regulators and their regulated developmental pathways. Introduction of the lost PRC2 component in a PRC2-deficient MPNST cell line restored H3K27me3 levels and decreased cell growth. Additionally, we identified frequent somatic alterations of CDKN2A (81% of all MPNSTs) and NF1 (72% of non-NF1-associated MPNSTs), both of which significantly co-occur with PRC2 alterations. The highly recurrent and specific inactivation of PRC2 components, NF1 and CDKN2A highlights their critical and potentially cooperative roles in MPNST pathogenesis.

GeneFriends: a human RNA-seq-based gene and transcript co-expression database

Co-expression networks have proven effective at assigning putative functions to genes based on the functional annotation of their co-expressed partners, in candidate gene prioritization studies and in improving our understanding of regulatory networks. The growing number of genome resequencing efforts and genome-wide association studies often identify loci containing novel genes and there is a need to infer their functions and interaction partners. To facilitate this we have expanded GeneFriends, an online database that allows users to identify co-expressed genes with one or more user-defined genes. This expansion entails an RNA-seq-based co-expression map that includes genes and transcripts that are not present in the microarray-based co-expression maps, including over 10 000 non-coding RNAs. The results users obtain from GeneFriends include a co-expression network as well as a summary of the functional enrichment among the co-expressed genes. Novel insights can be gathered from this database for different splice variants and ncRNAs, such as microRNAs and lincRNAs. Furthermore, our updated tool allows candidate transcripts to be linked to diseases and processes using a guilt-by-association approach. GeneFriends is freely available from http://www.GeneFriends.org and can be used to quickly identify and rank candidate targets relevant to the process or disease under study.

High-throughput RNA sequencing-based virome analysis of 50 lymphoma cell lines from the Cancer Cell Line Encyclopedia project

Using high-throughput RNA sequencing data from 50 common lymphoma cell culture models from the Cancer Cell Line Encyclopedia project, we performed an unbiased global interrogation for the presence of a panel of 740 viruses and strains known to infect human and other mammalian cells. This led to the findings of previously identified infections by Epstein-Barr virus (EBV), Kaposi's sarcoma herpesvirus (KSHV), and human T-lymphotropic virus type 1 (HTLV-1). In addition, we also found a previously unreported infection of one cell line (DEL) with a murine leukemia virus. High expression of murine leukemia virus (MuLV) transcripts was observed in DEL cells, and we identified four transcriptionally active integration sites, one being in the TNFRSF6B gene. We also found low levels of MuLV reads in a number of other cell lines and provided evidence suggesting cross-contamination during sequencing. Analysis of HTLV-1 integrations in two cell lines, HuT 102 and MJ, identified 14 and 66 transcriptionally active integration sites with potentially activating integrations in immune regulatory genes, including interleukin-15 (IL-15), IL-6ST, STAT5B, HIVEP1, and IL-9R. Although KSHV and EBV do not typically integrate into the genome, we investigated a previously identified integration of EBV into the BACH2 locus in Raji cells. This analysis identified a BACH2 disruption mechanism involving splice donor sequestration. Through viral gene expression analysis, we detected expression of stable intronic RNAs from the EBV BamHI W repeats that may be part of long transcripts spanning the repeat region. We also observed transcripts at the EBV vIL-10 locus exclusively in the Hodgkin's lymphoma cell line, Hs 611.T, the expression of which were uncoupled from other lytic genes. Assessment of the KSHV viral transcriptome in BCP-1 cells showed expression of the viral immune regulators, K2/vIL-6, K4/vIL-8-like vCCL1, and K5/E2-ubiquitin ligase 1 that was significantly higher than expression of the latency-associated nuclear antigen. Together, this investigation sheds light into the virus composition across these lymphoma model systems and provides insights into common viral mechanistic principles.

IMPORTANCE

Viruses cause cancer in humans. In lymphomas the Epstein-Barr virus (EBV), Kaposi's sarcoma herpesvirus (KSHV) and human T-lymphotropic virus type 1 are major contributors to oncogenesis. We assessed virus-host interactions using a high throughput sequencing method that facilitates the discovery of new virus-host associations and the investigation into how the viruses alter their host environment. We found a previously unknown murine leukemia virus infection in one cell line. We identified cellular genes, including cytokine regulators, that are disrupted by virus integration, and we determined mechanisms through which virus integration causes deregulation of cellular gene expression. Investigation into the KSHV transcriptome in the BCP-1 cell line revealed high-level expression of immune signaling genes. EBV transcriptome analysis showed expression of vIL-10 transcripts in a Hodgkin's lymphoma that was uncoupled from lytic genes. These findings illustrate unique mechanisms of viral gene regulation and to the importance of virus-mediated host immune signaling in lymphomas.

Expression profiles of long non-coding RNAs located in autoimmune disease-associated regions reveal immune cell-type specificity

Background

Although genome-wide association studies (GWAS) have identified hundreds of variants associated with a risk for autoimmune and immune-related disorders (AID), our understanding of the disease mechanisms is still limited. In particular, more than 90% of the risk variants lie in non-coding regions, and almost 10% of these map to long non-coding RNA transcripts (lncRNAs). lncRNAs are known to show more cell-type specificity than protein-coding genes.

Methods

We aimed to characterize lncRNAs and protein-coding genes located in loci associated with nine AIDs which have been well-defined by Immunochip analysis and by transcriptome analysis across seven populations of peripheral blood leukocytes (granulocytes, monocytes, natural killer (NK) cells, B cells, memory T cells, naive CD4⁺ and naive CD8⁺ T cells) and four populations of cord blood-derived T-helper cells (precursor, primary, and polarized (Th1, Th2) T-helper cells).

Results

We show that lncRNAs mapping to loci shared between AID are significantly enriched in immune cell types compared to lncRNAs from the whole genome (α <0.005). We were not able to prioritize single cell types relevant for specific diseases, but we observed five different cell types enriched (α <0.005) in five AID (NK cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, and psoriasis; memory T and CD8⁺ T cells in juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, and rheumatoid arthritis; Th0 and Th2 cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, and rheumatoid arthritis). Furthermore, we show that co-expression analyses of lncRNAs and protein-coding genes can predict the signaling pathways in which these AID-associated lncRNAs are involved.

Conclusions

The observed enrichment of lncRNA transcripts in AID loci implies lncRNAs play an important role in AID etiology and suggests that lncRNA genes should be studied in more detail to interpret GWAS findings correctly. The co-expression results strongly support a model in which the lncRNA and protein-coding genes function together in the same pathways.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-014-0088-0) contains supplementary material, which is available to authorized users.

Analytical tools and current challenges in the modern era of neuroepigenomics

Over the past decade, rapid advances in epigenomics research have extensively characterized critical roles for chromatin regulatory events during normal periods of eukaryotic cell development and plasticity, as well as part of aberrant processes implicated in human disease. Application of such approaches to studies of the CNS, however, is more recent. Here we provide a comprehensive overview of available tools for analyzing neuroepigenomics data, as well as a discussion of pending challenges specific to the field of neuroscience. Integration of numerous unbiased genome-wide and proteomic approaches will be necessary to fully understand the neuroepigenome and the extraordinarily complex nature of the human brain. This will be critical to the development of future diagnostic and therapeutic strategies aimed at alleviating the vast array of heterogeneous and genetically distinct disorders of the CNS.

Mating-type switching by chromosomal inversion in methylotrophic yeasts suggests an origin for the three-locus Saccharomyces cerevisiae system

Saccharomyces cerevisiae has a complex system for switching the mating type of haploid cells, requiring the genome to have three mating-type (MAT)-like loci and a mechanism for silencing two of them. How this system originated is unknown, because the three-locus system is present throughout the family Saccharomycetaceae, whereas species in the sister Candida clade have only one locus and do not switch. Here we show that yeasts in a third clade, the methylotrophs, have a simpler two-locus switching system based on reversible inversion of a section of chromosome with MATa genes at one end and MATalpha genes at the other end. In Hansenula polymorpha the 19-kb invertible region lies beside a centromere so that, depending on the orientation, either MATa or MATalpha is silenced by centromeric chromatin. In Pichia pastoris, the orientation of a 138-kb invertible region puts either MATa or MATalpha beside a telomere and represses transcription of MATa2 or MATalpha2. Both species are homothallic, and inversion of their MAT regions can be induced by crossing two strains of the same mating type. The three-locus system of S. cerevisiae, which uses a nonconservative mechanism to replace DNA at MAT, likely evolved from a conservative two-locus system that swapped genes between expression and nonexpression sites by inversion. The increasing complexity of the switching apparatus, with three loci, donor bias, and cell lineage tracking, can be explained by continuous selection to increase sporulation ability in young colonies. Our results provide an evolutionary context for the diversity of switching and silencing mechanisms.

piPipes: a set of pipelines for piRNA and transposon analysis via small RNA-seq, RNA-seq, degradome- and CAGE-seq, ChIP-seq and genomic DNA sequencing

Motivation: PIWI-interacting RNAs (piRNAs), 23–36 nt small silencing RNAs, repress transposon expression in the metazoan germ line, thereby protecting the genome. Although high-throughput sequencing has made it possible to examine the genome and transcriptome at unprecedented resolution, extracting useful information from gigabytes of sequencing data still requires substantial computational skills. Additionally, researchers may analyze and interpret the same data differently, generating results that are difficult to reconcile. To address these issues, we developed a coordinated set of pipelines, ‘piPipes’, to analyze piRNA and transposon-derived RNAs from a variety of high-throughput sequencing libraries, including small RNA, RNA, degradome or 7-methyl guanosine cap analysis of gene expression (CAGE), chromatin immunoprecipitation (ChIP) and genomic DNA-seq. piPipes can also produce figures and tables suitable for publication. By facilitating data analysis, piPipes provides an opportunity to standardize computational methods in the piRNA field.

Supplementary information: Supplementary information, including flowcharts and example figures for each pipeline, are available at Bioinformatics online.

Availability and implementation: piPipes is implemented in Bash, C++, Python, Perl and R. piPipes is free, open-source software distributed under the GPLv3 license and is available at http://bowhan.github.io/piPipes/.

Contact: Phillip.Zamore@umassmed.edu or Zhiping.Weng@umassmed.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Measuring the effect of inter-study variability on estimating prediction error

Background

The biomarker discovery field is replete with molecular signatures that have not translated into the clinic despite ostensibly promising performance in predicting disease phenotypes. One widely cited reason is lack of classification consistency, largely due to failure to maintain performance from study to study. This failure is widely attributed to variability in data collected for the same phenotype among disparate studies, due to technical factors unrelated to phenotypes (e.g., laboratory settings resulting in “batch-effects”) and non-phenotype-associated biological variation in the underlying populations. These sources of variability persist in new data collection technologies.

Methods

Here we quantify the impact of these combined “study-effects” on a disease signature’s predictive performance by comparing two types of validation methods: ordinary randomized cross-validation (RCV), which extracts random subsets of samples for testing, and inter-study validation (ISV), which excludes an entire study for testing. Whereas RCV hardwires an assumption of training and testing on identically distributed data, this key property is lost in ISV, yielding systematic decreases in performance estimates relative to RCV. Measuring the RCV-ISV difference as a function of number of studies quantifies influence of study-effects on performance.

Results

As a case study, we gathered publicly available gene expression data from 1,470 microarray samples of 6 lung phenotypes from 26 independent experimental studies and 769 RNA-seq samples of 2 lung phenotypes from 4 independent studies. We find that the RCV-ISV performance discrepancy is greater in phenotypes with few studies, and that the ISV performance converges toward RCV performance as data from additional studies are incorporated into classification.

Conclusions

We show that by examining how fast ISV performance approaches RCV as the number of studies is increased, one can estimate when “sufficient” diversity has been achieved for learning a molecular signature likely to translate without significant loss of accuracy to new clinical settings.

Populus tremula (European aspen) shows no evidence of sexual dimorphism

BACKGROUND

Evolutionary theory suggests that males and females may evolve sexually dimorphic phenotypic and biochemical traits concordant with each sex having different optimal strategies of resource investment to maximise reproductive success and fitness. Such sexual dimorphism would result in sex biased gene expression patterns in non-floral organs for autosomal genes associated with the control and development of such phenotypic traits.

RESULTS

We examined morphological, biochemical and herbivory traits to test for sexually dimorphic resource allocation strategies within collections of sexually mature and immature Populus tremula (European aspen) trees. In addition we profiled gene expression in mature leaves of sexually mature wild trees using whole-genome oligonucleotide microarrays and RNA-Sequencing.

CONCLUSIONS

We found no evidence of sexual dimorphism or differential resource investment strategies between males and females in either sexually immature or mature trees. Similarly, single-gene differential expression and machine learning approaches revealed no evidence of large-scale sex biased gene expression. However, two significantly differentially expressed genes were identified from the RNA-Seq data, one of which is a robust diagnostic marker of sex in P. tremula.

Rcount: simple and flexible RNA-Seq read counting

SUMMARY

Analysis of differential gene expression by RNA sequencing (RNA-Seq) is frequently done using feature counts, i.e. the number of reads mapping to a gene. However, commonly used count algorithms (e.g. HTSeq) do not address the problem of reads aligning with multiple locations in the genome (multireads) or reads aligning with positions where two or more genes overlap (ambiguous reads). Rcount specifically addresses these issues. Furthermore, Rcount allows the user to assign priorities to certain feature types (e.g. higher priority for protein-coding genes compared to rRNA-coding genes) or to add flanking regions.

AVAILABILITY AND IMPLEMENTATION

Rcount provides a fast and easy-to-use graphical user interface requiring no command line or programming skills. It is implemented in C++ using the SeqAn (www.seqan.de) and the Qt libraries (qt-project.org). Source code and 64 bit binaries for (Ubuntu) Linux, Windows (7) and MacOSX are released under the GPLv3 license and are freely available on github.com/MWSchmid/Rcount.

CONTACT

marcschmid@gmx.ch

SUPPLEMENTARY INFORMATION

Test data, genome annotation files, useful Python and R scripts and a step-by-step user guide (including run-time and memory usage tests) are available on github.com/MWSchmid/Rcount.

Primate-specific endogenous retrovirus-driven transcription defines naive-like stem cells

Naive embryonic stem cells hold great promise for research and therapeutics as they have broad and robust developmental potential. While such cells are readily derived from mouse blastocysts it has not been possible to isolate human equivalents easily, although human naive-like cells have been artificially generated (rather than extracted) by coercion of human primed embryonic stem cells by modifying culture conditions or through transgenic modification. Here we show that a sub-population within cultures of human embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs) manifests key properties of naive state cells. These naive-like cells can be genetically tagged, and are associated with elevated transcription of HERVH, a primate-specific endogenous retrovirus. HERVH elements provide functional binding sites for a combination of naive pluripotency transcription factors, including LBP9, recently recognized as relevant to naivety in mice. LBP9-HERVH drives hESC-specific alternative and chimaeric transcripts, including pluripotency-modulating long non-coding RNAs. Disruption of LBP9, HERVH and HERVH-derived transcripts compromises self-renewal. These observations define HERVH expression as a hallmark of naive-like hESCs, and establish novel primate-specific transcriptional circuitry regulating pluripotency.

Quality Control for RNA-Seq (QuaCRS): An Integrated Quality Control Pipeline

QuaCRS (Quality Control for RNA-Seq) is an integrated, simplified quality control (QC) system for RNA-seq data that allows easy execution of several open-source QC tools, aggregation of their output, and the ability to quickly identify quality issues by performing meta-analyses on QC metrics across large numbers of samples in different studies. It comprises two main sections. First is the QC Pack wrapper, which executes three QC tools: FastQC, RNA-SeQC, and selected functions from RSeQC. Combining these three tools into one wrapper provides increased ease of use and provides a much more complete view of sample data quality than any individual tool. Second is the QC database, which displays the resulting metrics in a user-friendly web interface. It was designed to allow users with less computational experience to easily generate and view QC information for their data, to investigate individual samples and aggregate reports of sample groups, and to sort and search samples based on quality. The structure of the QuaCRS database is designed to enable expansion with additional tools and metrics in the future. The source code for not-for-profit use and a fully functional sample user interface with mock data are available at http://bioserv.mps.ohio-state.edu/QuaCRS/.

A new rhesus macaque assembly and annotation for next-generation sequencing analyses

Background

The rhesus macaque (Macaca mulatta) is a key species for advancing biomedical research. Like all draft mammalian genomes, the draft rhesus assembly (rheMac2) has gaps, sequencing errors and misassemblies that have prevented automated annotation pipelines from functioning correctly. Another rhesus macaque assembly, CR_1.0, is also available but is substantially more fragmented than rheMac2 with smaller contigs and scaffolds. Annotations for these two assemblies are limited in completeness and accuracy. High quality assembly and annotation files are required for a wide range of studies including expression, genetic and evolutionary analyses.

Results

We report a new de novo assembly of the rhesus macaque genome (MacaM) that incorporates both the original Sanger sequences used to assemble rheMac2 and new Illumina sequences from the same animal. MacaM has a weighted average (N50) contig size of 64 kilobases, more than twice the size of the rheMac2 assembly and almost five times the size of the CR_1.0 assembly. The MacaM chromosome assembly incorporates information from previously unutilized mapping data and preliminary annotation of scaffolds. Independent assessment of the assemblies using Ion Torrent read alignments indicates that MacaM is more complete and accurate than rheMac2 and CR_1.0. We assembled messenger RNA sequences from several rhesus tissues into transcripts which allowed us to identify a total of 11,712 complete proteins representing 9,524 distinct genes. Using a combination of our assembled rhesus macaque transcripts and human transcripts, we annotated 18,757 transcripts and 16,050 genes with complete coding sequences in the MacaM assembly. Further, we demonstrate that the new annotations provide greatly improved accuracy as compared to the current annotations of rheMac2. Finally, we show that the MacaM genome provides an accurate resource for alignment of reads produced by RNA sequence expression studies.

Conclusions

The MacaM assembly and annotation files provide a substantially more complete and accurate representation of the rhesus macaque genome than rheMac2 or CR_1.0 and will serve as an important resource for investigators conducting next-generation sequencing studies with nonhuman primates.

Reviewers

This article was reviewed by Dr. Lutz Walter, Dr. Soojin Yi and Dr. Kateryna Makova.

Targeted combinatorial alternative splicing generates brain region-specific repertoires of neurexins

Molecular diversity of surface receptors has been hypothesized to provide a mechanism for selective synaptic connectivity. Neurexins are highly diversified receptors that drive the morphological and functional differentiation of synapses. Using a single cDNA sequencing approach, we detected 1,364 unique neurexin-α and 37 neurexin-β mRNAs produced by alternative splicing of neurexin pre-mRNAs. This molecular diversity results from near-exhaustive combinatorial use of alternative splice insertions in Nrxn1α and Nrxn2α. By contrast, Nrxn3α exhibits several highly stereotyped exon selections that incorporate novel elements for posttranscriptional regulation of a subset of transcripts. Complexity of Nrxn1α repertoires correlates with the cellular complexity of neuronal tissues, and a specific subset of isoforms is enriched in a purified cell type. Our analysis defines the molecular diversity of a critical synaptic receptor and provides evidence that neurexin diversity is linked to cellular diversity in the nervous system.

RNA-seq Data: Challenges in and Recommendations for Experimental Design and Analysis

RNA-seq is widely used to determine differential expression of genes or transcripts as well as identify novel transcripts, identify allele-specific expression, and precisely measure translation of transcripts. Thoughtful experimental design and choice of analysis tools are critical to ensure high-quality data and interpretable results. Important considerations for experimental design include number of replicates, whether to collect paired-end or single-end reads, sequence length, and sequencing depth. Common analysis steps in all RNA-seq experiments include quality control, read alignment, assigning reads to genes or transcripts, and estimating gene or transcript abundance. Our aims are two-fold: to make recommendations for common components of experimental design and assess tool capabilities for each of these steps. We also test tools designed to detect differential expression, since this is the most widespread application of RNA-seq. We hope that these analyses will help guide those who are new to RNA-seq and will generate discussion about remaining needs for tool improvement and development.

Computational Prediction of MicroRNAs from Toxoplasma gondii Potentially Regulating the Hosts’ Gene Expression

MicroRNAs (miRNAs) were discovered two decades ago, yet there is still a great need for further studies elucidating their genesis and targeting in different phyla. Since experimental discovery and validation of miRNAs is difficult, computational predictions are indispensable and today most computational approaches employ machine learning. Toxoplasma gondii, a parasite residing within the cells of its hosts like human, uses miRNAs for its post-transcriptional gene regulation. It may also regulate its hosts’ gene expression, which has been shown in brain cancer. Since previous studies have shown that overexpressed miRNAs within the host are causal for disease onset, we hypothesized that T. gondii could export miRNAs into its host cell. We computationally predicted all hairpins from the genome of T. gondii and used mouse and human models to filter possible candidates. These were then further compared to known miRNAs in human and rodents and their expression was examined for T. gondii grown in mouse and human hosts, respectively. We found that among the millions of potential hairpins in T. gondii, only a few thousand pass filtering using a human or mouse model and that even fewer of those are expressed. Since they are expressed and differentially expressed in rodents and human, we suggest that there is a chance that T. gondii may export miRNAs into its hosts for direct regulation.

RNA-Seq gene profiling--a systematic empirical comparison

Accurately quantifying gene expression levels is a key goal of experiments using RNA-sequencing to assay the transcriptome. This typically requires aligning the short reads generated to the genome or transcriptome before quantifying expression of pre-defined sets of genes. Differences in the alignment/quantification tools can have a major effect upon the expression levels found with important consequences for biological interpretation. Here we address two main issues: do different analysis pipelines affect the gene expression levels inferred from RNA-seq data? And, how close are the expression levels inferred to the "true" expression levels? We evaluate fifty gene profiling pipelines in experimental and simulated data sets with different characteristics (e.g, read length and sequencing depth). In the absence of knowledge of the 'ground truth' in real RNAseq data sets, we used simulated data to assess the differences between the "true" expression and those reconstructed by the analysis pipelines. Even though this approach does not take into account all known biases present in RNAseq data, it still allows to estimate the accuracy of the gene expression values inferred by different analysis pipelines. The results show that i) overall there is a high correlation between the expression levels inferred by the best pipelines and the true quantification values; ii) the error in the estimated gene expression values can vary considerably across genes; and iii) a small set of genes have expression estimates with consistently high error (across data sets and methods). Finally, although the mapping software is important, the quantification method makes a greater difference to the results.

CODEX: a next-generation sequencing experiment database for the haematopoietic and embryonic stem cell communities

CODEX (http://codex.stemcells.cam.ac.uk/) is a user-friendly database for the direct access and interrogation of publicly available next-generation sequencing (NGS) data, specifically aimed at experimental biologists. In an era of multi-centre genomic dataset generation, CODEX provides a single database where these samples are collected, uniformly processed and vetted. The main drive of CODEX is to provide the wider scientific community with instant access to high-quality NGS data, which, irrespective of the publishing laboratory, is directly comparable. CODEX allows users to immediately visualize or download processed datasets, or compare user-generated data against the database's cumulative knowledge-base. CODEX contains four types of NGS experiments: transcription factor chromatin immunoprecipitation coupled to high-throughput sequencing (ChIP-Seq), histone modification ChIP-Seq, DNase-Seq and RNA-Seq. These are largely encompassed within two specialized repositories, HAEMCODE and ESCODE, which are focused on haematopoiesis and embryonic stem cell samples, respectively. To date, CODEX contains over 1000 samples, including 221 unique TFs and 93 unique cell types. CODEX therefore provides one of the most complete resources of publicly available NGS data for the direct interrogation of transcriptional programmes that regulate cellular identity and fate in the context of mammalian development, homeostasis and disease.

Massively parallel read mapping on GPUs with the q-group index and PEANUT

We present the q-group index, a novel data structure for read mapping tailored towards graphics processing units (GPUs) with a small memory footprint and efficient parallel algorithms for querying and building. On top of the q-group index we introduce PEANUT, a highly parallel GPU-based read mapper. PEANUT provides the possibility to output both the best hits or all hits of a read. Our benchmarks show that PEANUT outperforms other state-of-the-art read mappers in terms of speed while maintaining or slightly increasing precision, recall and sensitivity.

Transcriptional diversity during lineage commitment of human blood progenitors

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine.

ARYANA: Aligning Reads by Yet Another Approach

Motivation

Although there are many different algorithms and software tools for aligning sequencing reads, fast gapped sequence search is far from solved. Strong interest in fast alignment is best reflected in the $10⁶ prize for the Innocentive competition on aligning a collection of reads to a given database of reference genomes. In addition, de novo assembly of next-generation sequencing long reads requires fast overlap-layout-concensus algorithms which depend on fast and accurate alignment.

Contribution

We introduce ARYANA, a fast gapped read aligner, developed on the base of BWA indexing infrastructure with a completely new alignment engine that makes it significantly faster than three other aligners: Bowtie2, BWA and SeqAlto, with comparable generality and accuracy. Instead of the time-consuming backtracking procedures for handling mismatches, ARYANA comes with the seed-and-extend algorithmic framework and a significantly improved efficiency by integrating novel algorithmic techniques including dynamic seed selection, bidirectional seed extension, reset-free hash tables, and gap-filling dynamic programming. As the read length increases ARYANA's superiority in terms of speed and alignment rate becomes more evident. This is in perfect harmony with the read length trend as the sequencing technologies evolve. The algorithmic platform of ARYANA makes it easy to develop mission-specific aligners for other applications using ARYANA engine.

Availability

ARYANA with complete source code can be obtained from http://github.com/aryana-aligner

High-resolution transcriptome analysis with long-read RNA sequencing

RNA sequencing (RNA-seq) enables characterization and quantification of individual transcriptomes as well as detection of patterns of allelic expression and alternative splicing. Current RNA-seq protocols depend on high-throughput short-read sequencing of cDNA. However, as ongoing advances are rapidly yielding increasing read lengths, a technical hurdle remains in identifying the degree to which differences in read length influence various transcriptome analyses. In this study, we generated two paired-end RNA-seq datasets of differing read lengths (2×75 bp and 2×262 bp) for lymphoblastoid cell line GM12878 and compared the effect of read length on transcriptome analyses, including read-mapping performance, gene and transcript quantification, and detection of allele-specific expression (ASE) and allele-specific alternative splicing (ASAS) patterns. Our results indicate that, while the current long-read protocol is considerably more expensive than short-read sequencing, there are important benefits that can only be achieved with longer read length, including lower mapping bias and reduced ambiguity in assigning reads to genomic elements, such as mRNA transcript. We show that these benefits ultimately lead to improved detection of cis-acting regulatory and splicing variation effects within individuals.

SNP-guided identification of monoallelic DNA-methylation events from enrichment-based sequencing data

Monoallelic gene expression is typically initiated early in the development of an organism. Dysregulation of monoallelic gene expression has already been linked to several non-Mendelian inherited genetic disorders. In humans, DNA-methylation is deemed to be an important regulator of monoallelic gene expression, but only few examples are known. One important reason is that current, cost-affordable truly genome-wide methods to assess DNA-methylation are based on sequencing post-enrichment. Here, we present a new methodology based on classical population genetic theory, i.e. the Hardy–Weinberg theorem, that combines methylomic data from MethylCap-seq with associated SNP profiles to identify monoallelically methylated loci. Applied on 334 MethylCap-seq samples of very diverse origin, this resulted in the identification of 80 genomic regions featured by monoallelic DNA-methylation. Of these 80 loci, 49 are located in genic regions of which 25 have already been linked to imprinting. Further analysis revealed statistically significant enrichment of these loci in promoter regions, further establishing the relevance and usefulness of the method. Additional validation was done using both 14 whole-genome bisulfite sequencing data sets and 16 mRNA-seq data sets. Importantly, the developed approach can be easily applied to other enrichment-based sequencing technologies, like the ChIP-seq-based identification of monoallelic histone modifications.

A genetic dichotomy between pure sclerosing epithelioid fibrosarcoma (SEF) and hybrid SEF/low-grade fibromyxoid sarcoma: a pathologic and molecular study of 18 cases

Sclerosing epithelioid fibrosarcoma (SEF) is a rare soft tissue tumor exhibiting considerable morphologic overlap with low-grade fibromyxoid sarcoma (LGFMS). Moreover, both SEF and LGFMS show MUC4 expression by immunohistochemistry. While the majority of LGFMS cases are characterized by a FUS-CREB3L1 fusion, both FUS-CREB3L2 and EWSR1-CREB3L1 fusions were recently demonstrated in a small number of LGFMS and SEF/LGFMS hybrid tumors. In contrast, recent studies pointed out that SEF harbor frequent EWSR1 rearrangements, with only a minority of cases showing FUS-CREB3L2 fusions. In an effort to further characterize the molecular characteristics of pure SEF and hybrid SEF/LGFMS lesions, we undertook a clinicopathologic, immunohistochemical and genetic analysis of a series of 10 SEF and 8 hybrid SEF/LGFMS tumors. The mortality rate was similar between the two groups, 44% within the pure SEF group and 37% in the hybrid SEF/LGFMS with a mean overall follow-up of 66 months. All but one pure SEF and all hybrid SEF/LGFMS-tested cases showed MUC4 immunoreactivity. The majority (90%) of pure SEF cases showed EWSR1 gene rearrangements by fluorescence in situ hybridization with only one case exhibiting FUS rearrangement. Of the nine EWSR1 positive cases, six cases harbored CREB3L1 break-apart, two had CREB3L2 rearrangement (a previously unreported finding) and one lacked evidence of CREB3L1/2 abnormalities. In contrast, all hybrid SEF/LGFMS tumors exhibited FUS and CREB3L2 rearrangements. These results further demarcate a relative cytogenetic dichotomy between pure SEF, often characterized by EWSR1 rearrangements, and hybrid SEF/LGFMS, harboring FUS-CREB3L2 fusion; the latter group recapitulating the genotype of LGFMS.

Early and late response of Nematostella vectensis transcriptome to heavy metals

Environmental contamination from heavy metals poses a global concern for the marine environment, as heavy metals are passed up the food chain and persist in the environment long after the pollution source is contained. Cnidarians play an important role in shaping marine ecosystems, but environmental pollution profoundly affects their vitality. Among the cnidarians, the sea anemone Nematostella vectensis is an advantageous model for addressing questions in molecular ecology and toxicology as it tolerates extreme environments and its genome has been published. Here, we employed a transcriptome-wide RNA-Seq approach to analyse N. vectensis molecular defence mechanisms against four heavy metals: Hg, Cu, Cd and Zn. Altogether, more than 4800 transcripts showed significant changes in gene expression. Hg had the greatest impact on up-regulating transcripts, followed by Cu, Zn and Cd. We identified, for the first time in Cnidaria, co-up-regulation of immediate-early transcription factors such as Egr1, AP1 and NF-κB. Time-course analysis of these genes revealed their early expression as rapidly as one hour after exposure to heavy metals, suggesting that they may complement or substitute for the roles of the metal-mediating Mtf1 transcription factor. We further characterized the regulation of a large array of stress-response gene families, including Hsp, ABC, CYP members and phytochelatin synthase, that may regulate synthesis of the metal-binding phytochelatins instead of the metallothioneins that are absent from Cnidaria genome. This study provides mechanistic insight into heavy metal toxicity in N. vectensis and sheds light on ancestral stress adaptations.

Resetting transcription factor control circuitry toward ground-state pluripotency in human

Current human pluripotent stem cells lack the transcription factor circuitry that governs the ground state of mouse embryonic stem cells (ESC). Here, we report that short-term expression of two components, NANOG and KLF2, is sufficient to ignite other elements of the network and reset the human pluripotent state. Inhibition of ERK and protein kinase C sustains a transgene-independent rewired state. Reset cells self-renew continuously without ERK signaling, are phenotypically stable, and are karyotypically intact. They differentiate in vitro and form teratomas in vivo. Metabolism is reprogrammed with activation of mitochondrial respiration as in ESC. DNA methylation is dramatically reduced and transcriptome state is globally realigned across multiple cell lines. Depletion of ground-state transcription factors, TFCP2L1 or KLF4, has marginal impact on conventional human pluripotent stem cells but collapses the reset state. These findings demonstrate feasibility of installing and propagating functional control circuitry for ground-state pluripotency in human cells.

Genetic alterations of the cohesin complex genes in myeloid malignancies

Somatic cohesin mutations have been reported in myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). To account for the morphologic and cytogenetic diversity of these neoplasms, a well-annotated cohort of 1060 patients with myeloid malignancies including MDS (n = 386), myeloproliferative neoplasms (MPNs) (n = 55), MDS/MPNs (n = 169), and AML (n = 450) were analyzed for cohesin gene mutational status, gene expression, and therapeutic and survival outcomes. Somatic cohesin defects were detected in 12% of patients with myeloid malignancies, whereas low expression of these genes was present in an additional 15% of patients. Mutations of cohesin genes were mutually exclusive and mostly resulted in predicted loss of function. Patients with low cohesin gene expression showed similar expression signatures as those with somatic cohesin mutations. Cross-sectional deep-sequencing analysis for clonal hierarchy demonstrated STAG2, SMC3, and RAD21 mutations to be ancestral in 18%, 18%, and 47% of cases, respectively, and each expanded to clonal dominance concordant with disease transformation. Cohesin mutations were significantly associated with RUNX1, Ras-family oncogenes, and BCOR and ASXL1 mutations and were most prevalent in high-risk MDS and secondary AML. Cohesin defects were associated with poor overall survival (27.2 vs 40 months; P = .023), especially in STAG2 mutant MDS patients surviving >12 months (median survival 35 vs 50 months; P = .017).

The landscape of kinase fusions in cancer

Human cancer genomes harbour a variety of alterations leading to the deregulation of key pathways in tumour cells. The genomic characterization of tumours has uncovered numerous genes recurrently mutated, deleted or amplified, but gene fusions have not been characterized as extensively. Here we develop heuristics for reliably detecting gene fusion events in RNA-seq data and apply them to nearly 7,000 samples from The Cancer Genome Atlas. We thereby are able to discover several novel and recurrent fusions involving kinases. These findings have immediate clinical implications and expand the therapeutic options for cancer patients, as approved or exploratory drugs exist for many of these kinases.

Kinases activated by gene fusions represent potentially important targets for the development of cancer drugs. Here, the authors develop a method for detecting gene fusion events in RNA sequencing data from The Cancer Genome Atlas and identify several novel recurrent fusions involving kinases.

Systematic annotation of celiac disease loci refines pathological pathways and suggests a genetic explanation for increased interferon-gamma levels

Although genome-wide association studies and fine mapping have identified 39 non-HLA loci associated with celiac disease (CD), it is difficult to pinpoint the functional variants and susceptibility genes in these loci. We applied integrative approaches to annotate and prioritize functional single nucleotide polymorphisms (SNPs), genes and pathways affected in CD. CD-associated SNPs were intersected with regulatory elements categorized by the ENCODE project to prioritize functional variants, while results from cis-expression quantitative trait loci (eQTL) mapping in 1469 blood samples were combined with co-expression analyses to prioritize causative genes. To identify the key cell types involved in CD, we performed pathway analysis on RNA-sequencing data from different immune cell populations and on publicly available expression data on non-immune tissues. We discovered that CD SNPs are significantly enriched in B-cell-specific enhancer regions, suggesting that, besides T-cell processes, B-cell responses play a major role in CD. By combining eQTL and co-expression analyses, we prioritized 43 susceptibility genes in 36 loci. Pathway and tissue-specific expression analyses on these genes suggested enrichment of CD genes in the Th1, Th2 and Th17 pathways, but also predicted a role for four genes in the intestinal barrier function. We also discovered an intricate transcriptional connectivity between CD susceptibility genes and interferon-γ, a key effector in CD, despite the absence of CD-associated SNPs in the IFNG locus. Using systems biology, we prioritized the CD-associated functional SNPs and genes. By highlighting a role for B cells in CD, which classically has been described as a T-cell-driven disease, we offer new insights into the mechanisms and pathways underlying CD.

The olfactory transcriptomes of mice

The olfactory (OR) and vomeronasal receptor (VR) repertoires are collectively encoded by 1700 genes and pseudogenes in the mouse genome. Most OR and VR genes were identified by comparative genomic techniques and therefore, in many of those cases, only their protein coding sequences are defined. Some also lack experimental support, due in part to the similarity between them and their monogenic, cell-specific expression in olfactory tissues. Here we use deep RNA sequencing, expression microarray and quantitative RT-PCR in both the vomeronasal organ and whole olfactory mucosa to quantify their full transcriptomes in multiple male and female mice. We find evidence of expression for all VR, and almost all OR genes that are annotated as functional in the reference genome, and use the data to generate over 1100 new, multi-exonic, significantly extended receptor gene annotations. We find that OR and VR genes are neither equally nor randomly expressed, but have reproducible distributions of abundance in both tissues. The olfactory transcriptomes are only minimally different between males and females, suggesting altered gene expression at the periphery is unlikely to underpin the striking sexual dimorphism in olfactory-mediated behavior. Finally, we present evidence that hundreds of novel, putatively protein-coding genes are expressed in these highly specialized olfactory tissues, and carry out a proof-of-principle validation. Taken together, these data provide a comprehensive, quantitative catalog of the genes that mediate olfactory perception and pheromone-evoked behavior at the periphery.

The sense of smell in mice involves the detection of odors and pheromones by many hundreds of olfactory and vomeronasal receptors. The genes that encode these receptors account for around 5% of the whole gene catalog, but they are poorly understood because they are very similar to each other, and are thought to be turned on randomly in only a small number of cells. Here we use multiple gene expression technologies to curate and measure the activity of all the genes involved in the detection of odors and find evidence of many new ones. We show that most genes encoding olfactory and vomeronasal receptors have complex, multi-exonic structures that generate different isoforms. We find that some receptors are consistently more abundant in the nose than others, which suggests they are not turned on randomly. This may explain why mice are particularly sensitive to some odors, but less attuned to others. We find that overall males and females differ very little in gene expression, despite having altered behavioral responses to the same odors. Thus diversity in receptor expression can explain differences in odor sensitivity, but does not appear to dictate whether sex pheromones are differentially detected by males or females.

RNA G-quadruplexes cause eIF4A-dependent oncogene translation in cancer

The translational control of oncoprotein expression is implicated in many cancers. Here we report an eIF4A RNA helicase-dependent mechanism of translational control that contributes to oncogenesis and underlies the anticancer effects of silvestrol and related compounds. For example, eIF4A promotes T-cell acute lymphoblastic leukaemia development in vivo and is required for leukaemia maintenance. Accordingly, inhibition of eIF4A with silvestrol has powerful therapeutic effects against murine and human leukaemic cells in vitro and in vivo. We use transcriptome-scale ribosome footprinting to identify the hallmarks of eIF4A-dependent transcripts. These include 5' untranslated region (UTR) sequences such as the 12-nucleotide guanine quartet (CGG)4 motif that can form RNA G-quadruplex structures. Notably, among the most eIF4A-dependent and silvestrol-sensitive transcripts are a number of oncogenes, superenhancer-associated transcription factors, and epigenetic regulators. Hence, the 5' UTRs of select cancer genes harbour a targetable requirement for the eIF4A RNA helicase.

Organoid cultures derived from patients with advanced prostate cancer

The lack of in vitro prostate cancer models that recapitulate the diversity of human prostate cancer has hampered progress in understanding disease pathogenesis and therapy response. Using a 3D organoid system, we report success in long-term culture of prostate cancer from biopsy specimens and circulating tumor cells. The first seven fully characterized organoid lines recapitulate the molecular diversity of prostate cancer subtypes, including TMPRSS2-ERG fusion, SPOP mutation, SPINK1 overexpression, and CHD1 loss. Whole-exome sequencing shows a low mutational burden, consistent with genomics studies, but with mutations in FOXA1 and PIK3R1, as well as in DNA repair and chromatin modifier pathways that have been reported in advanced disease. Loss of p53 and RB tumor suppressor pathway function are the most common feature shared across the organoid lines. The methodology described here should enable the generation of a large repertoire of patient-derived prostate cancer lines amenable to genetic and pharmacologic studies.

Detecting and correcting systematic variation in large-scale RNA sequencing data

High-throughput RNA sequencing (RNA-seq) enables comprehensive scans of entire transcriptomes, but best practices for analyzing RNA-seq data have not been fully defined, particularly for data collected with multiple sequencing platforms or at multiple sites. Here we used standardized RNA samples with built-in controls to examine sources of error in large-scale RNA-seq studies and their impact on the detection of differentially expressed genes (DEGs). Analysis of variations in guanine-cytosine content, gene coverage, sequencing error rate and insert size allowed identification of decreased reproducibility across sites. Moreover, commonly used methods for normalization (cqn, EDASeq, RUV2, sva, PEER) varied in their ability to remove these systematic biases, depending on sample complexity and initial data quality. Normalization methods that combine data from genes across sites are strongly recommended to identify and remove site-specific effects and can substantially improve RNA-seq studies.

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

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.

Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study

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.

RNA-seq Transcriptional Profiling of Peripheral Blood Leukocytes from Cattle Infected with Mycobacterium bovis

Bovine tuberculosis, caused by infection with Mycobacterium bovis, is a major endemic disease affecting cattle populations worldwide, despite the implementation of stringent surveillance and control programs in many countries. The development of high-throughput functional genomics technologies, including gene expression microarrays and RNA-sequencing (RNA-seq), has enabled detailed analysis of the host transcriptome to M. bovis infection, particularly at the macrophage and peripheral blood level. In the present study, we have analyzed the peripheral blood leukocyte (PBL) transcriptome of eight natural M. bovis-infected and eight age- and sex-matched non-infected control Holstein-Friesian animals using RNA-seq. In addition, we compared gene expression profiles generated using RNA-seq with those previously generated using the high-density Affymetrix^® GeneChip^® Bovine Genome Array platform from the same PBL-extracted RNA. A total of 3,250 differentially expressed (DE) annotated genes were detected in the M. bovis-infected samples relative to the controls (adjusted P-value ≤0.05), with the number of genes displaying decreased relative expression (1,671) exceeding those with increased relative expression (1,579). Ingenuity^® Systems Pathway Analysis (IPA) of all DE genes revealed enrichment for genes with immune function. Notably, transcriptional suppression was observed among several of the top-ranking canonical pathways including Leukocyte Extravasation Signaling. Comparative platform analysis demonstrated that RNA-seq detected a larger number of annotated DE genes (3,250) relative to the microarray (1,398), of which 917 genes were common to both technologies and displayed the same direction of expression. Finally, we show that RNA-seq had an increased dynamic range compared to the microarray for estimating differential gene expression.

Infection with MERS-CoV causes lethal pneumonia in the common marmoset

The availability of a robust disease model is essential for the development of countermeasures for Middle East respiratory syndrome coronavirus (MERS-CoV). While a rhesus macaque model of MERS-CoV has been established, the lack of uniform, severe disease in this model complicates the analysis of countermeasure studies. Modeling of the interaction between the MERS-CoV spike glycoprotein and its receptor dipeptidyl peptidase 4 predicted comparable interaction energies in common marmosets and humans. The suitability of the marmoset as a MERS-CoV model was tested by inoculation via combined intratracheal, intranasal, oral and ocular routes. Most of the marmosets developed a progressive severe pneumonia leading to euthanasia of some animals. Extensive lesions were evident in the lungs of all animals necropsied at different time points post inoculation. Some animals were also viremic; high viral loads were detected in the lungs of all infected animals, and total RNAseq demonstrated the induction of immune and inflammatory pathways. This is the first description of a severe, partially lethal, disease model of MERS-CoV, and as such will have a major impact on the ability to assess the efficacy of vaccines and treatment strategies as well as allowing more detailed pathogenesis studies.

The development of vaccines and treatment strategies is aided by robust animal disease models that accurately depict the illness that is observed in humans. Here we describe a new, improved model for MERS-CoV using the common marmoset, whereby the severe, and even lethal, illness that has been observed in many human cases is recapitulated. Prior to the development of this model, the only available animal models for MERS-CoV infection were the rhesus macaque and a mouse model that requires adenovirus-transduced expression of the human version of the protein required for virus entry. The rhesus macaque model more closely mimics the mild to moderate disease observed in some patients—mainly those without significant comorbidities. The increased severity of illness in the common marmoset model is an important advance in the ability to evaluate potential therapeutic agents against MERS-CoV, as discrimination between successfully treated and control animals should be more apparent. In addition, the closer models recapitulate the disease observed in humans, the more likely findings can be eventually translated into use in humans.

Acceleration of short and long DNA read mapping without loss of accuracy using suffix array

HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20× for long reads) and more sensitive (over 98% in a wide range of read lengths) than the current state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies.

AVAILABILITY AND IMPLEMENTATION

https://github.com/opencb/hpg-aligner.