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Single-stranded RNA viruses encompass broad classes of infectious agents and cause the common cold, cancer, AIDS and other serious health threats. Viral replication is regulated at many levels, including the use of conserved genomic RNA structures. Most potential regulatory elements in viral RNA genomes are uncharacterized. Here we report the structure of an entire HIV-1 genome at single nucleotide resolution using SHAPE, a high-throughput RNA analysis technology. The genome encodes protein structure at two levels. In addition to the correspondence between RNA and protein primary sequences, a correlation exists between high levels of RNA structure and sequences that encode inter-domain loops in HIV proteins. This correlation suggests that RNA structure modulates ribosome elongation to promote native protein folding. Some simple genome elements previously shown to be important, including the ribosomal gag-pol frameshift stem-loop, are components of larger RNA motifs. We also identify organizational principles for unstructured RNA regions, including splice site acceptors and hypervariable regions. These results emphasize that the HIV-1 genome and, potentially, many coding RNAs are punctuated by previously unrecognized regulatory motifs and that extensive RNA structure constitutes an important component of the genetic code. Inside HIV-1: structure of an entire RNA gnome The secondary structure of a complete HIV-1 RNA genome has been determined, based on analysis of authentic HIV RNA extracted from infectious virions. Secondary structures within single-stranded viral RNA genomes are known to serve functional and regulatory roles, but until now there has been no comprehensive analysis of total RNA for any virus. SHAPE technology (high-throughput selective 2′-hydroxyl acylation analysed by primer extension) was used to characterize all structures formed by the HIV-1 RNA genome. Numerous highly structured motifs were discovered, and functions can be inferred for many of these motifs. Importantly, the presence of RNA structural elements was found to influence the translation of proteins and to facilitate proper protein folding. These results emphasize that the HIV-1 genome does have a structure, elements of which are critical to viral fitness. Insights from this work could lead to a better understanding of HIV-1 biology and to new antiretroviral interventions. Single-stranded RNA viruses are responsible for the common cold, cancer, AIDS and other serious health threats. The genomes of these viruses form conserved secondary structures that have functional and regulatory roles, but most potential regulatory elements in viral RNA genomes remain uncharacterized. Here however, the structure of an entire HIV-1 genome at single nucleotide resolution is reported.

RNA secondary structure plays a central role in the replication and metabolism of all RNA viruses, including retroviruses like HIV-1. However, structures with known function represent only a fraction of the secondary structure reported for HIV-1(NL4-3). One tool to assess the importance of RNA structures is to examine their conservation over evolutionary time. To this end, we used SHAPE to model the secondary structure of a second primate lentiviral genome, SIVmac239, which shares only 50% sequence identity at the nucleotide level with HIV-1NL4-3. Only about half of the paired nucleotides are paired in both genomic RNAs and, across the genome, just 71 base pairs form with the same pairing partner in both genomes. On average the RNA secondary structure is thus evolving at a much faster rate than the sequence. Structure at the Gag-Pro-Pol frameshift site is maintained but in a significantly altered form, while the impact of selection for maintaining a protein binding interaction can be seen in the conservation of pairing partners in the small RRE stems where Rev binds. Structures that are conserved between SIVmac239 and HIV-1(NL4-3) also occur at the 5' polyadenylation sequence, in the plus strand primer sites, PPT and cPPT, and in the stem-loop structure that includes the first splice acceptor site. The two genomes are adenosine-rich and cytidine-poor. The structured regions are enriched in guanosines, while unpaired regions are enriched in adenosines, and functionaly important structures have stronger base pairing than nonconserved structures. We conclude that much of the secondary structure is the result of fortuitous pairing in a metastable state that reforms during sequence evolution. However, secondary structure elements with important function are stabilized by higher guanosine content that allows regions of structure to persist as sequence evolution proceeds, and, within the confines of selective pressure, allows structures to evolve.

A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets (‘polypharmacology’). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

All aspects of plant and animal development are controlled by complex networks of transcription factors. Transcription factors are essential for converting signaling inputs, such as changes in daylength, into complex gene regulatory outputs. While some transcription factors control gene expression by binding to cis-regulatory elements as individual subunits, others function in a combinatorial fashion. How individual subunits of combinatorial transcription factors are spatially and temporally deployed (e.g. expression-level, posttranslational modifications and subcellular localization) has profound effects on their control of gene expression. In the model plant Arabidopsis (Arabidopsis thaliana), we have identified 36 Nuclear Factor Y (NF-Y) transcription factor subunits (10 NF-YA, 13 NF-YB, and 13 NF-YC subunits) that can theoretically combine to form 1,690 unique complexes. Individual plant subunits have functions in flowering time, embryo maturation, and meristem development, but how they combine to control these processes is unknown. To assist in the process of defining unique NF-Y complexes, we have created promoter:β-glucuronidase fusion lines for all 36 Arabidopsis genes. Here, we show NF-Y expression patterns inferred from these promoter:β-glucuronidase lines for roots, light- versus dark-grown seedlings, rosettes, and flowers. Additionally, we review the phylogenetic relationships and examine protein alignments for each NF-Y subunit family. The results are discussed with a special emphasis on potential roles for NF-Y subunits in photoperiod-controlled flowering time.

Previous genome-wide association studies (GWAS), conducted by our group and others, have identified loci that harbor risk variants for neurodegenerative diseases, including Alzheimer's disease (AD). Human disease variants are enriched for polymorphisms that affect gene expression, including some that are known to associate with expression changes in the brain. Postulating that many variants confer risk to neurodegenerative disease via transcriptional regulatory mechanisms, we have analyzed gene expression levels in the brain tissue of subjects with AD and related diseases. Herein, we describe our collective datasets comprised of GWAS data from 2,099 subjects; microarray gene expression data from 773 brain samples, 186 of which also have RNAseq; and an independent cohort of 556 brain samples with RNAseq. We expect that these datasets, which are available to all qualified researchers, will enable investigators to explore and identify transcriptional mechanisms contributing to neurodegenerative diseases. Design Type(s) disease state design • individual genetic characteristics comparison design Measurement Type(s) genetic sequence variation analysis • transcription profiling by array assay Technology Type(s) Whole Genome Association Study • RNA-seq assay Factor Type(s) regional part of brain • diagnosis Sample Characteristic(s) Homo sapiens • cerebellum • temporal cortex Machine-accessible metadata file describing the reported data (ISA-Tab format)

There is great interindividual variability in HIV-1 viral setpoint after seroconversion, some of which is known to be due to genetic differences among infected individuals. Here, our focus is on determining, genome-wide, the contribution of variable gene expression to viral control, and to relate it to genomic DNA polymorphism. RNA was extracted from purified CD4+ T-cells from 137 HIV-1 seroconverters, 16 elite controllers, and 3 healthy blood donors. Expression levels of more than 48,000 mRNA transcripts were assessed by the Human-6 v3 Expression BeadChips (Illumina). Genome-wide SNP data was generated from genomic DNA using the HumanHap550 Genotyping BeadChip (Illumina). We observed two distinct profiles with 260 genes differentially expressed depending on HIV-1 viral load. There was significant upregulation of expression of interferon stimulated genes with increasing viral load, including genes of the intrinsic antiretroviral defense. Upon successful antiretroviral treatment, the transcriptome profile of previously viremic individuals reverted to a pattern comparable to that of elite controllers and of uninfected individuals. Genome-wide evaluation of cis-acting SNPs identified genetic variants modulating expression of 190 genes. Those were compared to the genes whose expression was found associated with viral load: expression of one interferon stimulated gene, OAS1, was found to be regulated by a SNP (rs3177979, p = 4.9E-12); however, we could not detect an independent association of the SNP with viral setpoint. Thus, this study represents an attempt to integrate genome-wide SNP signals with genome-wide expression profiles in the search for biological correlates of HIV-1 control. It underscores the paradox of the association between increasing levels of viral load and greater expression of antiviral defense pathways. It also shows that elite controllers do not have a fully distinctive mRNA expression pattern in CD4+ T cells. Overall, changes in global RNA expression reflect responses to viral replication rather than a mechanism that might explain viral control.

How sex stays in fashion The origin and persistence of sexual reproduction in living organisms remains one of the deepest mysteries of biology. Although several plausible theories have been proposed, they make predictions that are hard to test in real life. But an experiment run in an artificial gene network model shows that a condition postulated by a leading theory, the mutation deterministic hypothesis, may evolve more easily than was thought. The condition, negative epistasis, is one in which gene mutations are more harmful when combined in the same genome than when separate. In fact the model suggests that negative epistasis can actually evolve as a consequence of sexual reproduction itself. The mutational deterministic hypothesis for the origin and maintenance of sexual reproduction posits that sex enhances the ability of natural selection to purge deleterious mutations after recombination brings them together into single genomes 1 . This explanation requires negative epistasis, a type of genetic interaction where mutations are more harmful in combination than expected from their separate effects. The conceptual appeal of the mutational deterministic hypothesis has been offset by our inability to identify the mechanistic and evolutionary bases of negative epistasis. Here we show that negative epistasis can evolve as a consequence of sexual reproduction itself. Using an artificial gene network model 2 , 3 , we find that recombination between gene networks imposes selection for genetic robustness, and that negative epistasis evolves as a by-product of this selection. Our results suggest that sexual reproduction selects for conditions that favour its own maintenance, a case of evolution forging its own path.

People with loss of function of MyD88 or IRAK4 have a surprisingly limited altered phenotype. Chaussabel and colleagues use a systems approach to identify defined signaling modules that are altered in such people. Loss of function of the kinase IRAK4 or the adaptor MyD88 in humans interrupts a pathway critical for pathogen sensing and ignition of inflammation. However, patients with loss-of-function mutations in the genes encoding these factors are, unexpectedly, susceptible to only a limited range of pathogens. We employed a systems approach to investigate transcriptome responses following in vitro exposure of patients' blood to agonists of Toll-like receptors (TLRs) and receptors for interleukin 1 (IL-1Rs) and to whole pathogens. Responses to purified agonists were globally abolished, but variable residual responses were present following exposure to whole pathogens. Further delineation of the latter responses identified a narrow repertoire of transcriptional programs affected by loss of MyD88 function or IRAK4 function. Our work introduces the use of a systems approach for the global assessment of innate immune responses and the characterization of human primary immunodeficiencies.

[...]a set of ten tumor-normal pairs from actual patients will be made available to any team, after approval by the ICGC Data Access Compliance Office. The best-performing methods will be applied retrospectively to over 10,000 cancer genomes stored in CGHub, and the results will be distributed to the research community. [...]the top-scoring methods will be made available as open source tools, allowing users around the world to process their own data with the same pipelines validated and used by the ICGC and TCGA.