A global genetic interaction network by single-cell imaging and machine learning.

Cellular and organismal phenotypes are controlled by complex gene regulatory networks. However, reference maps of gene function are still scarce across different organisms. Here, we generated synthetic genetic interaction and cell morphology profiles of more than 6,800 genes in cultured Drosophila cells. The resulting map of genetic interactions was used for machine learning-based gene function discovery, assigning functions to genes in 47 modules. Furthermore, we devised Cytoclass as a method to dissect genetic interactions for discrete cell states at the single-cell resolution. This approach identified an interaction of Cdk2 and the Cop9 signalosome complex, triggering senescence-associated secretory phenotypes and immunogenic conversion in hemocytic cells. Together, our data constitute a genome-scale resource of functional gene profiles to uncover the mechanisms underlying genetic interactions and their plasticity at the single-cell level.

Time-resolved mapping of genetic interactions to model rewiring of signaling pathways.

Context-dependent changes in genetic interactions are an important feature of cellular pathways and their varying responses under different environmental conditions. However, methodological frameworks to investigate the plasticity of genetic interaction networks over time or in response to external stresses are largely lacking. To analyze the plasticity of genetic interactions, we performed a combinatorial RNAi screen in Drosophila cells at multiple time points and after pharmacological inhibition of Ras signaling activity. Using an image-based morphology assay to capture a broad range of phenotypes, we assessed the effect of 12768 pairwise RNAi perturbations in six different conditions. We found that genetic interactions form in different trajectories and developed an algorithm, termed MODIFI, to analyze how genetic interactions rewire over time. Using this framework, we identified more statistically significant interactions compared to end-point assays and further observed several examples of context-dependent crosstalk between signaling pathways such as an interaction between Ras and Rel which is dependent on MEK activity. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

A large-scale RNAi screen identifies Deaf1 as a regulator of innate immune responses in Drosophila.

Innate immune signalling pathways are evolutionarily conserved between invertebrates and vertebrates. The analysis of NF-kappaB signalling in Drosophila has contributed important insights into how organisms respond to infection. Nevertheless, significant gaps remain in our understanding of how the activation of intracellular signalling elicits specific transcriptional programs. Here we report a genome-wide RNA interference survey for transcription factors that are required for Toll-dependent immune responses. In addition to the NF-kappaB homologs Dif, Dorsal and factors of the general transcription machinery, we identified Deformed Epidermal Autoregulatory Factor 1 (Deaf1) to be required for the expression of the Toll target gene Drosomycin in cultured cells and in Drosophila in vivo. We show that Deaf1 is required for the survival of flies after fungal, but not E. coli, infection. We determine that Deaf1 acts downstream of the NF-kappaB factors Dorsal and Dif. These results indicate that Deaf1 is an important contributor to innate immune responses in vivo.

Mosaic genome architecture of the Anopheles gambiae species complex.

BACKGROUND: Attempts over the last three decades to reconstruct the phylogenetic history of the Anopheles gambiae species complex have been important for developing better strategies to control malaria transmission. METHODOLOGY: We used fingerprint genotyping data from 414 field-collected female mosquitoes at 42 microsatellite loci to infer the evolutionary relationships of four species in the A. gambiae complex, the two major malaria vectors A. gambiae sensu stricto (A. gambiae s.s.) and A. arabiensis, as well as two minor vectors, A. merus and A. melas. PRINCIPAL FINDINGS: We identify six taxonomic units, including a clear separation of West and East Africa A. gambiae s.s. S molecular forms. We show that the phylogenetic relationships vary widely between different genomic regions, thus demonstrating the mosaic nature of the genome of these species. The two major malaria vectors are closely related and closer to A. merus than to A. melas at the genome-wide level, which is also true if only autosomes are considered. However, within the Xag inversion region of the X chromosome, the M and two S molecular forms are most similar to A. merus. Near the X centromere, outside the Xag region, the two S forms are highly dissimilar to the other taxa. Furthermore, our data suggest that the centromeric region of chromosome 3 is a strong discriminator between the major and minor malaria vectors. CONCLUSIONS: Although further studies are needed to elucidate the basis of the phylogenetic variation among the different regions of the genome, the preponderance of sympatric admixtures among taxa strongly favor introgression of different genomic regions between species, rather than lineage sorting of ancestral polymorphism, as a possible mechanism.

Life cycle transcriptome of the malaria mosquito Anopheles gambiae and comparison with the fruitfly Drosophila melanogaster.

The African mosquito Anopheles gambiae is the major vector of human malaria. We report a genome-wide survey of mosquito gene expression profiles clustered temporally into developmental programs and spatially into adult tissue-specific patterns. Global expression analysis shows that genes that belong to related functional categories or that encode the same or functionally linked protein domains are associated with characteristic developmental programs or tissue patterns. Comparative analysis of our data together with data published from Drosophila melanogaster reveal an overall strong and positive correlation of developmental expression between orthologous genes. The degree of correlation varies, depending on association of orthologs with certain developmental programs or functional groups. Interestingly, the similarity of gene expression is not correlated with the coding sequence similarity of orthologs, indicating that expression profiles and coding sequences evolve independently. In addition to providing a comprehensive view of temporal and spatial gene expression during the A. gambiae life cycle, this large-scale comparative transcriptomic analysis has detected important evolutionary features of insect transcriptomes.

AnoEST: toward A. gambiae functional genomics.

Here, we present an analysis of 215,634 EST and cDNA sequences of a major vector of human malaria Anopheles gambiae structured into the AnoEST database. The expressed sequences are grouped into clusters using genomic sequence as template and associated with inferred functional annotation, including the following: corresponding Ensembl gene prediction, putative orthologous genes in other species, homology to known proteins, protein domains, associated Gene Ontology terms, and corresponding classification into broad GO-slim functional groups. AnoEST is a vital resource for interpretation of expression profiles derived using recently developed A. gambiae cDNA microarrays. Using these cDNA microarrays, we have experimentally confirmed the expression of 7961 clusters during mosquito development. Of these, 3100 are not associated with currently predicted genes. Moreover, we found that clusters with confirmed expression are nonbiased with respect to the current gene annotation or homology to known proteins. Consequently, we expect that many as yet unconfirmed clusters are likely to be actual A. gambiae genes. [AnoEST is publicly available at http://komar.embl.de, and is also accessible as a Distributed Annotation Service (DAS).].

Immunity-related genes and gene families in Anopheles gambiae.

We have identified 242 Anopheles gambiae genes from 18 gene families implicated in innate immunity and have detected marked diversification relative to Drosophila melanogaster. Immune-related gene families involved in recognition, signal modulation, and effector systems show a marked deficit of orthologs and excessive gene expansions, possibly reflecting selection pressures from different pathogens encountered in these insects' very different life-styles. In contrast, the multifunctional Toll signal transduction pathway is substantially conserved, presumably because of counterselection for developmental stability. Representative expression profiles confirm that sequence diversification is accompanied by specific responses to different immune challenges. Alternative RNA splicing may also contribute to expansion of the immune repertoire.

The genome sequence of the malaria mosquito Anopheles gambiae.

Anopheles gambiae is the principal vector of malaria, a disease that afflicts more than 500 million people and causes more than 1 million deaths each year. Tenfold shotgun sequence coverage was obtained from the PEST strain of A. gambiae and assembled into scaffolds that span 278 million base pairs. A total of 91% of the genome was organized in 303 scaffolds; the largest scaffold was 23.1 million base pairs. There was substantial genetic variation within this strain, and the apparent existence of two haplotypes of approximately equal frequency ("dual haplotypes") in a substantial fraction of the genome likely reflects the outbred nature of the PEST strain. The sequence produced a conservative inference of more than 400,000 single-nucleotide polymorphisms that showed a markedly bimodal density distribution. Analysis of the genome sequence revealed strong evidence for about 14,000 protein-encoding transcripts. Prominent expansions in specific families of proteins likely involved in cell adhesion and immunity were noted. An expressed sequence tag analysis of genes regulated by blood feeding provided insights into the physiological adaptations of a hematophagous insect.

Genetic loci affecting resistance to human malaria parasites in a West African mosquito vector population.

Successful propagation of the malaria parasite Plasmodium falciparum within a susceptible mosquito vector is a prerequisite for the transmission of malaria. A field-based genetic analysis of the major human malaria vector, Anopheles gambiae, has revealed natural factors that reduce the transmission of P. falciparum. Differences in P. falciparum oocyst numbers between mosquito isofemale families fed on the same infected blood indicated a large genetic component affecting resistance to the parasite, and genome-wide scanning in pedigrees of wild mosquitoes detected segregating resistance alleles. The apparently high natural frequency of resistance alleles suggests that malaria parasites (or a similar pathogen) exert a significant selective pressure on vector populations.

A comparative genomic analysis of two distant diptera, the fruit fly, Drosophila melanogaster, and the malaria mosquito, Anopheles gambiae.

Genome evolution entails changes in the DNA sequence of genes and intergenic regions, changes in gene numbers, and also changes in gene order along the chromosomes. Genes are reshuffled by chromosomal rearrangements such as deletions/insertions, inversions, translocations, and transpositions. Here we report a comparative study of genome organization in the main African malaria vector, Anopheles gambiae, relative to the recently determined sequence of the Drosophila melanogaster genome. The ancestral lines of these two dipteran insects are thought to have separated approximately 250 Myr, a long period that makes this genome comparison especially interesting. Sequence comparisons have identified 113 pairs of putative orthologs of the two species. Chromosomal mapping of orthologous genes reveals that each polytene chromosome arm has a homolog in the other species. Between 41% and 73% of the known orthologous genes remain linked in the respective homologous chromosomal arms, with the remainder translocated to various nonhomologous arms. Within homologous arms, gene order is extensively reshuffled, but a limited degree of conserved local synteny (microsynteny) can be recognized.