Automated genome-wide visual profiling of cellular proteins involved in HIV infection

Recent genome-wide RNAi screens have identified >842 human genes that affect the human immunodeficiency virus (HIV) cycle. The list of genes implicated in infection differs between screens, and there is minimal overlap. A reason for this variance is the interdependence of HIV infection and host cell function, producing a multitude of indirect or pleiotropic cellular effects affecting the viral infection during RNAi screening. To overcome this, the authors devised a 15-dimensional phenotypic profile to define the viral infection block induced by CD4 silencing in HeLa cells. They demonstrate that this phenotypic profile excludes nonspecific, RNAi-based side effects and viral replication defects mediated by silencing of housekeeping genes. To achieve statistical robustness, the authors used automatically annotated RNAi arrays for seven independent genome-wide RNAi screens. This identified 56 host genes, which reliably reproduced CD4-like phenotypes upon HIV infection. The factors include 11 known HIV interactors and 45 factors previously not associated with HIV infection. As proof of concept, the authors confirmed that silencing of PAK1, Ku70, and RNAseH2A impaired HIV replication in Jurkat cells. In summary, multidimensional, visual profiling can identify genes required for HIV infection.     

Knockdown of specific host factors protects against influenza virus-induced cell death

Cell death is a characteristic consequence of cellular infection by influenza virus. Mounting evidence indicates the critical involvement of host-mediated cellular death pathways in promoting efficient influenza virus replication. Furthermore, it appears that many signaling pathways, such as NF-κB, formerly suspected to solely promote cell survival, can also be manipulated to induce cell death. Current understanding of the cell death pathways involved in influenza virus-mediated cytopathology and in virus replication is limited. This study was designed to identify host genes that are required for influenza-induced cell death. The approach was to perform genome-wide lentiviral-mediated human gene silencing in A549 cells and determine which genes could be silenced to provide resistance to influenza-induced cell death. The assay proved to be highly reproducible with 138 genes being identified in independent screens. The results were independently validated using siRNA to each of these candidates. Graded protection was observed in this screen with the silencing of any of 19 genes, each providing >85% protection. Three gene products, TNFSF13 (APRIL), TNFSF12-TNFSF13 (TWE-PRIL) and USP47, were selected because of the high levels of protection conferred by their silencing. Protein and mRNA silencing and protection from influenza-induced cell death was confirmed using multiple shRNA clones and siRNA, indicating the specificity of the effects. USP47 knockdown prevented proper viral entry into the host cell, whereas TNFSF12-13/TNFSF13 knockdown blocked a late stage in viral replication. This screening approach offers the means to identify a large number of potential candidates for the analysis of viral-induced cell death. These results may also have much broader applicability in defining regulatory mechanisms involved in cell survival.     

Network-based prediction and analysis of HIV dependency factors

HIV Dependency Factors (HDFs) are a class of human proteins that are essential for HIV replication, but are not lethal to the host cell when silenced. Three previous genome-wide RNAi experiments identified HDF sets with little overlap. We combine data from these three studies with a human protein interaction network to predict new HDFs, using an intuitive algorithm called SinkSource and four other algorithms published in the literature. Our algorithm achieves high precision and recall upon cross validation, as do the other methods. A number of HDFs that we predict are known to interact with HIV proteins. They belong to multiple protein complexes and biological processes that are known to be manipulated by HIV. We also demonstrate that many predicted HDF genes show significantly different programs of expression in early response to SIV infection in two non-human primate species that differ in AIDS progression. Our results suggest that many HDFs are yet to be discovered and that they have potential value as prognostic markers to determine pathological outcome and the likelihood of AIDS development. More generally, if multiple genome-wide gene-level studies have been performed at independent labs to study the same biological system or phenomenon, our methodology is applicable to interpret these studies simultaneously in the context of molecular interaction networks and to ask if they reinforce or contradict each other.     

Genomic regions identified by overlapping clusters of nominally-positive SNPs from genome-wide studies of alcohol and illegal substance dependence

Declaring "replication" from results of genome wide association (GWA) studies is straightforward when major gene effects provide genome-wide significance for association of the same allele of the same SNP in each of multiple independent samples. However, such unambiguous replication is unlikely when phenotypes display polygenic genetic architecture, allelic heterogeneity, locus heterogeneity and when different samples display linkage disequilibria with different fine structures. We seek chromosomal regions that are tagged by clustered SNPs that display nominally-significant association in each of several independent samples. This approach provides one "nontemplate" approach to identifying overall replication of groups of GWA results in the face of difficult genetic architectures. We apply this strategy to 1 M SNP GWA results for dependence on: a) alcohol (including many individuals with dependence on other addictive substances) and b) at least one illegal substance (including many individuals dependent on alcohol). This approach provides high confidence in rejecting the null hypothesis that chance alone accounts for the extent to which clustered, nominally-significant SNPs from samples of the same racial/ethnic background identify the same sets of chromosomal regions. It identifies several genes that are also reported in other independent alcohol-dependence GWA datasets. There is more modest confidence in: a) identification of individual chromosomal regions and genes that are not also identified by data from other independent samples, b) the more modest overlap between results from samples of different racial/ethnic backgrounds and c) the extent to which any gene not identified herein is excluded, since the power of each of these individual samples is modest. Nevertheless, the strong overlap identified among the samples with similar racial/ethnic backgrounds supports contributions to individual differences in vulnerability to addictions that come from newer allelic variants that are common in subsets of current humans.     

Genome-wide screening for gene function using RNAi in mammalian cells

Mammalian genome sequencing has identified numerous genes requiring functional annotation. The discovery that dsRNA can direct gene-specific silencing in both model organisms and mammalian cells through RNA interference (RNAi) has provided a platform for dissecting the function of independent genes. The generation of large-scale RNAi libraries targeting all predicted genes within mouse, rat and human cells, combined with the large number of cell-based assays, provides a unique opportunity to perform high-throughput genetics in these complex cell systems. Many different formats exist for the generation of genome-wide RNAi libraries for use in mammalian cells. Furthermore, the use of these libraries in either genetic screens or genetic selections allows for the identification of known and novel genes involved in complex cellular phenotypes and biological processes, some of which underpin human disease. In this review, we examine genome-wide RNAi libraries used in model organisms and mammalian cells and provide examples of how these information rich reagents can be used for determining gene function, discovering novel therapeutic targets and dissecting signalling pathways, cellular processes and complex phenotypes.     

Integrating 'omic' information: a bridge between genomics and systems biology

The availability of genome sequences for several organisms, including humans, and the resulting first-approximation lists of genes, have allowed a transition from molecular biology to 'modular biology'. In modular biology, biological processes of interest, or modules, are studied as complex systems of functionally interacting macromolecules. Functional genomic and proteomic ('omic') approaches can be helpful to accelerate the identification of the genes and gene products involved in particular modules, and to describe the functional relationships between them. However, the data emerging from individual omic approaches should be viewed with caution because of the occurrence of false-negative and false-positive results and because single annotations are not sufficient for an understanding of gene function. To increase the reliability of gene function annotation, multiple independent datasets need to be integrated. Here, we review the recent development of strategies for such integration and we argue that these will be important for a systems approach to modular biology.     

Hypertension and Genetic Variation in Endothelial-Specific Genes

Genome-wide association (GWA) studies usually detect common genetic variants with low-to-medium effect sizes. Many contributing variants are not revealed, since they fail to reach significance after strong correction for multiple comparisons. The WTCCC study for hypertension, for example, failed to identify genome-wide significant associations. We hypothesized that genetic variation in genes expressed specifically in the endothelium may be important for hypertension development. Results from the WTCCC study were combined with previously published gene expression data from mice to specifically investigate SNPs located within endothelial-specific genes, bypassing the requirement for genome-wide significance. Six SNPs from the WTCCC study were selected for independent replication in 5205 hypertensive patients and 5320 population-based controls, and successively in a cohort of 16537 individuals. A common variant (rs10860812) in the DRAM (damage-regulated autophagy modulator) locus showed association with hypertension (P = 0.008) in the replication study. The minor allele (A) had a protective effect (OR = 0.93; 95% CI 0.88–0.98 per A-allele), which replicates the association in the WTCCC GWA study. However, a second follow-up, in the larger cohort, failed to reveal an association with blood pressure. We further tested the endothelial-specific genes for co-localization with a panel of newly discovered SNPs from large meta-GWAS on hypertension or blood pressure. There was no significant overlap between those genes and hypertension or blood pressure loci. The result does not support the hypothesis that genetic variation in genes expressed in endothelium plays an important role for hypertension development. Moreover, the discordant association of rs10860812 with blood pressure in the case control study versus the larger Malmö Preventive Project–study highlights the importance of rigorous replication in multiple large independent studies.     

High-throughput RNAi in Caenorhabditis elegans: genome-wide screens and functional genomics

The phenomenon of RNA-mediated interference (RNAi) was first discovered in the nematode Caenorhabditis elegans, in which introduction of double-stranded RNA causes specific inactivation of genes with corresponding sequences. Technical advances in RNAi methodology and the availability of the complete genome sequence have enabled the high-throughput, genome-wide RNAi analysis of this organism. Several groups have used large-scale RNAi to systematically examine every C. elegans gene for knock-down phenotypes, providing basal information to be mined in more detailed studies. Now, in addition to functional genomic RNAi analyses, high-throughput RNAi is also routinely used for rapid, genome-wide screens for genes involved in specific biological processes. The integration of high-throughput RNAi experiments with other large-scale data, such as DNA microarrays and protein-protein interaction maps, enhances the speed and reliability of such screens. The accumulation of RNAi phenotype data dramatically accelerates our understanding of this organism at the genetic level.     

Genome-Wide Analysis of Host Factors in Nodavirus RNA Replication

Flock House virus (FHV), the best studied of the animal nodaviruses, has been used as a model for positive-strand RNA virus research. As one approach to identify host genes that affect FHV RNA replication, we performed a genome-wide analysis using a yeast single gene deletion library and a modified, reporter gene-expressing FHV derivative. A total of 4,491 yeast deletion mutants were tested for their ability to support FHV replication. Candidates for host genes modulating FHV replication were selected based on the initial genome-wide reporter gene assay and validated in repeated Northern blot assays for their ability to support wild type FHV RNA1 replication. Overall, 65 deletion strains were confirmed to show significant changes in the replication of both FHV genomic RNA1 and sub-genomic RNA3 with a false discovery rate of 5%. Among them, eight genes support FHV replication, since their deletion significantly reduced viral RNA accumulation, while 57 genes limit FHV replication, since their deletion increased FHV RNA accumulation. Of the gene products implicated in affecting FHV replication, three are localized to mitochondria, where FHV RNA replication occurs, 16 normally reside in the nucleus and may have indirect roles in FHV replication, and the remaining 46 are in the cytoplasm, with functions enriched in translation, RNA processing and trafficking.     

Network-guided analysis of genes with altered somatic copy number and gene expression reveals pathways commonly perturbed in metastatic melanoma

Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression ('SCNA-genes') in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer.     

Genome-wide RNAi of C. elegans using the hypersensitive rrf-3 strain reveals novel gene functions

RNA-mediated interference (RNAi) is a method to inhibit gene function by introduction of double-stranded RNA (dsRNA). Recently, an RNAi library was constructed that consists of bacterial clones expressing dsRNA, corresponding to nearly 90% of the 19,427 predicted genes of C. elegans. Feeding of this RNAi library to the standard wild-type laboratory strain Bristol N2 detected phenotypes for approximately 10% of the corresponding genes. To increase the number of genes for which a loss-of-function phenotype can be detected, we undertook a genome-wide RNAi screen using the rrf-3 mutant strain, which we found to be hypersensitive to RNAi. Feeding of the RNAi library to rrf-3 mutants resulted in additional loss-of-function phenotypes for 393 genes, increasing the number of genes with a phenotype by 23%. These additional phenotypes are distributed over different phenotypic classes. We also studied interexperimental variability in RNAi results and found persistent levels of false negatives. In addition, we used the RNAi phenotypes obtained with the genome-wide screens to systematically clone seven existing genetic mutants with visible phenotypes. The genome-wide RNAi screen using rrf-3 significantly increased the functional data on the C. elegans genome. The resulting dataset will be valuable in conjunction with other functional genomics approaches, as well as in other model organisms.     

DNA interference: a simple and efficient gene-silencing system for high-throughput functional analysis in the fern adiantum

RNA interference (RNAi) has become a powerful tool for determining gene function and is used in a wide variety of organisms. Since it is necessary to generate double-stranded RNA (dsRNA) as an inducer for RNAi, preparation of RNAi-inducing constructs is somewhat cumbersome and time consuming, especially for the thousands of genes used in a genome-wide analysis. To overcome these problems, we have developed a more convenient gene-silencing method in the fern Adiantum using double-stranded DNA (dsDNA) as a model system for functional analysis in plants. Delivery of dsDNA fragments homologous to an endogenous gene into gametophytic cells can induce sequence-specific gene silencing. As it only requires dsDNA fragments homologous to a target gene, PCR-amplified fragments are enough to trigger gene silencing. Maximum gene silencing efficiencies of >90% have been achieved for transformed plants. In addition, simultaneous transfer of dsDNA fragments corresponding to multiple genes still has a silencing effect for individual genes. We term this approach 'DNA interference'.     

Common variants in a novel gene, FONG on chromosome 2q33.1 confer risk of osteoporosis in Japanese

Osteoporosis is a common disease characterized by low bone mass, decreased bone quality and increased predisposition to fracture. Genetic factors have been implicated in its etiology; however, the specific genes related to susceptibility to osteoporosis are not entirely known. To detect susceptibility genes for osteoporosis, we conducted a genome-wide association study in Japanese using ∼270,000 SNPs in 1,747 subjects (190 cases and 1,557 controls) followed by multiple levels of replication of the association using a total of ∼5,000 subjects (2,092 cases and 3,114 controls). Through these staged association studies followed by resequencing and linkage disequilibrium mapping, we identified a single nucleotide polymorphism (SNP), rs7605378 associated with osteoporosis. (combined P = 1.51×10⁻⁸, odds ratio = 1.25). This SNP is in a previously unknown gene on chromosome 2q33.1, FONG. FONG is predicted to encode a 147 amino-acid protein with a formiminotransferase domain in its N-terminal (FTCD_N domain) and is ubiquitously expressed in various tissues including bone. Our findings would give a new insight into osteoporosis etiology and pathogenesis.     

Recurrent adaptation in RNA interference genes across the Drosophila phylogeny

RNA interference (RNAi) is quickly emerging as a vital component of genome organization, gene regulation, and immunity in Drosophila and other species. Previous studies have suggested that, as a whole, genes involved in RNAi are under intense positive selection in Drosophila melanogaster. Here, we characterize the extent and patterns of adaptive evolution in 23 known Drosophila RNAi genes, both within D. melanogaster and across the Drosophila phylogeny. We find strong evidence for recurrent protein-coding adaptation at a large number of RNAi genes, particularly those involved in antiviral immunity and defense against transposable elements. We identify specific functional domains involved in direct protein-RNA interactions as particular hotspots of recurrent adaptation in multiple RNAi genes, suggesting that targeted coadaptive arms races may be a general feature of RNAi evolution. Our observations suggest a predictive model of how selective pressures generated by evolutionary arms race scenarios may affect multiple genes across protein interaction networks and other biochemical pathways.     

A Genome-Wide CRISPR Library for High-Throughput Genetic Screening in Drosophila Cells

The simplicity of the CRISPR/Cas9 system of genome engineering has opened up the possibility of performing genome-wide targeted mutagenesis in cell lines,enabling screening for cellular phenotypes resulting from genetic aberrations.Drosophila cells have proven to be highly effective in identifying genes involved in cellular processes through similar screens using partial knockdown by RNAi.This is in part due to the lower degree of redundancy between genes in this organism,whilst still maintaining highly conserved gene networks and orthologs of many human disease-causing genes.The ability of CRISPR to generate genetic loss of function mutations not only increases the magnitude of any effect over currently employed RNAi techniques,but allows analysis over longer periods of time which can be critical for certain phenotypes.In this study,we have designed and built a genome-wide CRISPR library covering 13,501 genes,among which 8989 genes are targeted by three or more independent single guide RNAs(sg RNAs).Moreover,we describe strategies to monitor the population of guide RNAs by high throughput sequencing(HTS).We hope that this library will provide an invaluable resource for the community to screen loss of function mutations for cellular phenotypes,and as a source of guide RNA designs for future studies.     

A Genomic Portrait of Haplotype Diversity and Signatures of Selection in Indigenous Southern African Populations

We report a study of genome-wide, dense SNP (∼900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region.