Colm J. Ryan

Hierarchical Modularity and the Evolution of Genetic Interactomes across Species

To date, cross-species comparisons of genetic interactomes have been restricted to small or functionally related gene sets, limiting our ability to infer evolutionary trends. To facilitate a more comprehensive analysis, we constructed a genome-scale epistasis map (E-MAP) for the fission yeast Schizosaccharomyces pombe, providing phenotypic signatures for ~60% of the nonessential genome. Using these signatures, we generated a catalog of 297 functional modules, and we assigned function to 144 previously uncharacterized genes, including mRNA splicing and DNA damage checkpoint factors. Comparison with an integrated genetic interactome from the budding yeast Saccharomyces cerevisiae revealed a hierarchical model for the evolution of genetic interactions, with conservation highest within protein complexes, lower within biological processes, and lowest between distinct biological processes. Despite the large evolutionary distance and extensive rewiring of individual interactions, both networks retain conserved features and display similar levels of functional crosstalk between biological processes, suggesting general design principles of genetic interactomes.

High-resolution network biology: connecting sequence with function

Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein–protein, genetic and drug–gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies.

ATR inhibitors as a synthetic lethal therapy for tumours deficient in ARID1A

Identifying genetic biomarkers of synthetic lethal drug sensitivity effects provides one approach to the development of targeted cancer therapies. Mutations in ARID1A represent one of the most common molecular alterations in human cancer, but therapeutic approaches that target these defects are not yet clinically available. We demonstrate that defects in ARID1A sensitize tumour cells to clinical inhibitors of the DNA damage checkpoint kinase, ATR, both in vitro and in vivo. Mechanistically, ARID1A deficiency results in topoisomerase 2A and cell cycle defects, which cause an increased reliance on ATR checkpoint activity. In ARID1A mutant tumour cells, inhibition of ATR triggers premature mitotic entry, genomic instability and apoptosis. The data presented here provide the pre-clinical and mechanistic rationale for assessing ARID1A defects as a biomarker of single-agent ATR inhibitor response and represents a novel synthetic lethal approach to targeting tumour cells.

Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines

Summary One approach to identifying cancer-specific vulnerabilities and therapeutic targets is to profile genetic dependencies in cancer cell lines. Here, we describe data from a series of siRNA screens that identify the kinase genetic dependencies in 117 cancer cell lines from ten cancer types. By integrating the siRNA screen data with molecular profiling data, including exome sequencing data, we show how vulnerabilities/genetic dependencies that are associated with mutations in specific cancer driver genes can be identified. By integrating additional data sets into this analysis, including protein-protein interaction data, we also demonstrate that the genetic dependencies associated with many cancer driver genes form dense connections on functional interaction networks. We demonstrate the utility of this resource by using it to predict the drug sensitivity of genetically or histologically defined subsets of tumor cell lines, including an increased sensitivity of osteosarcoma cell lines to FGFR inhibitors and SMAD4 mutant tumor cells to mitotic inhibitors.

The yeast SR-like protein Npl3 links chromatin modification to mRNA processing.

Eukaryotic gene expression involves tight coordination between transcription and pre–mRNA splicing; however, factors responsible for this coordination remain incompletely defined. Here, we explored the genetic, functional, and biochemical interactions of a likely coordinator, Npl3, an SR-like protein in Saccharomyces cerevisiae that we recently showed is required for efficient co-transcriptional recruitment of the splicing machinery. We surveyed the NPL3 genetic interaction space and observed a significant enrichment for genes involved in histone modification and chromatin remodeling. Specifically, we found that Npl3 genetically interacts with both Bre1, which mono-ubiquitinates histone H2B as part of the RAD6 Complex, and Ubp8, the de-ubiquitinase of the SAGA Complex. In support of these genetic data, we show that Bre1 physically interacts with Npl3 in an RNA–independent manner. Furthermore, using a genome-wide splicing microarray, we found that the known splicing defect of a strain lacking Npl3 is exacerbated by deletion of BRE1 or UBP8, a phenomenon phenocopied by a point mutation in H2B that abrogates ubiquitination. Intriguingly, even in the presence of wild-type NPL3, deletion of BRE1 exhibits a mild splicing defect and elicits a growth defect in combination with deletions of early and late splicing factors. Taken together, our data reveal a connection between Npl3 and an extensive array of chromatin factors and describe an unanticipated functional link between histone H2B ubiquitination and pre–mRNA splicing.

Missing value imputation for epistatic MAPs

BackgroundEpistatic miniarray profiling (E-MAPs) is a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others. An effective method for imputing interactions would therefore increase the types of possible analysis, as well as increase the potential to identify novel functional interactions between gene pairs. Several methods have been developed to handle missing values in microarray data, but it is unclear how applicable these methods are to E-MAP data because of their pairwise nature and the significantly larger number of missing values. Here we evaluate four alternative imputation strategies, three local (Nearest neighbor-based) and one global (PCA-based), that have been modified to work with symmetric pairwise data.ResultsWe identify different categories for the missing data based on their underlying cause, and show that values from the largest category can be imputed effectively. We compare local and global imputation approaches across a variety of distinct E-MAP datasets, showing that both are competitive and preferable to filling in with zeros. In addition we show that these methods are effective in an E-MAP from a different species, suggesting that pairwise imputation techniques will be increasingly useful as analogous epistasis mapping techniques are developed in different species. We show that strongly alleviating interactions are significantly more difficult to predict than strongly aggravating interactions. Finally we show that imputed interactions, generated using nearest neighbor methods, are enriched for annotations in the same manner as measured interactions. Therefore our method potentially expands the number of mapped epistatic interactions. In addition we make implementations of our algorithms available for use by other researchers.ConclusionsWe address the problem of missing value imputation for E-MAPs, and suggest the use of symmetric nearest neighbor based approaches as they offer consistently accurate imputations across multiple datasets in a tractable manner.

Key Functional Regions in the Histone Variant H2A.Z C-Terminal Docking Domain

ABSTRACT The incorporation of histone variants into nucleosomes represents one way of altering the chromatin structure to accommodate diverse functions. Histone variant H2A.Z has specific roles in gene regulation, heterochromatin boundary formation, and genomic integrity. The precise features required for H2A.Z to function and specify an identity different from canonical H2A remain to be fully explored. Analysis of the C-terminal docking domain of H2A.Z in Saccharomyces cerevisiae using epistatic miniarray profile (E-MAP) uncovered nuanced requirements of the H2A.Z C-terminal region for cell growth when additional genes were compromised. Moreover, the H2A.Z(1–114) truncation, lacking the last 20 amino acids of the protein, did not support regular H2A.Z functions, such as resistance to genotoxic stress, restriction of heterochromatin in its native context, GAL1 gene activation, and chromatin anchoring. The corresponding region of H2A could fully rescue the strong defects caused by loss of this functionally essential region in the C terminus of H2A.Z. Despite the dramatic reduction in function, the H2A.Z(1–114) truncation still bound the H2A.Z deposition complex SWR1-C, the histone chaperone Chz1, and histone H2B. These data are consistent with a model in which retaining the variant in chromatin after its deposition by SWR1-C is a crucial determinant of its function.

Genetic Interaction Mapping Reveals a Role for the SWI/SNF Nucleosome Remodeler in Spliceosome Activation in Fission Yeast

Although numerous regulatory connections between pre-mRNA splicing and chromatin have been demonstrated, the precise mechanisms by which chromatin factors influence spliceosome assembly and/or catalysis remain unclear. To probe the genetic network of pre-mRNA splicing in the fission yeast Schizosaccharomyces pombe, we constructed an epistatic mini-array profile (E-MAP) and discovered many new connections between chromatin and splicing. Notably, the nucleosome remodeler SWI/SNF had strong genetic interactions with components of the U2 snRNP SF3 complex. Overexpression of SF3 components in ΔSWI/SNF cells led to inefficient splicing of many fission yeast introns, predominantly those with non-consensus splice sites. Deletion of SWI/SNF decreased recruitment of the splicing ATPase Prp2, suggesting that SWI/SNF promotes co-transcriptional spliceosome assembly prior to first step catalysis. Importantly, defects in SWI/SNF as well as SF3 overexpression each altered nucleosome occupancy along intron-containing genes, illustrating that the chromatin landscape both affects—and is affected by—co-transcriptional splicing.

All or Nothing : protein complexes flip essentiality between distantly related eukaryotes

In the budding yeast Saccharomyces cerevisiae, the subunits of any given protein complex are either mostly essential or mostly nonessential, suggesting that essentiality is a property of molecular machines rather than individual components. There are exceptions to this rule, however, that is, nonessential genes in largely essential complexes and essential genes in largely nonessential complexes. Here, we provide explanations for these exceptions, showing that redundancy within complexes, as revealed by genetic interactions, can explain many of the former cases, whereas “moonlighting,” as revealed by membership of multiple complexes, can explain the latter. Surprisingly, we find that redundancy within complexes cannot usually be explained by gene duplication, suggesting alternate buffering mechanisms. In the distantly related Schizosaccharomyces pombe, we observe the same phenomenon of modular essentiality, suggesting that it may be a general feature of eukaryotes. Furthermore, we show that complexes flip essentiality in a cohesive fashion between the two species, that is, they tend to change from mostly essential to mostly nonessential, or vice versa, but not to mixed patterns. We show that these flips in essentiality can be explained by differing lifestyles of the two yeasts. Collectively, our results support a previously proposed model where proteins are essential because of their involvement in essential functional modules rather than because of specific topological features such as degree or centrality.

Evolutionarily conserved genetic interactions with budding and fission yeast MutS identify orthologous relationships in mismatch repair-deficient cancer cells

BackgroundThe evolutionarily conserved DNA mismatch repair (MMR) system corrects base-substitution and insertion-deletion mutations generated during erroneous replication. The mutation or inactivation of many MMR factors strongly predisposes to cancer, where the resulting tumors often display resistance to standard chemotherapeutics. A new direction to develop targeted therapies is the harnessing of synthetic genetic interactions, where the simultaneous loss of two otherwise non-essential factors leads to reduced cell fitness or death. High-throughput screening in human cells to directly identify such interactors for disease-relevant genes is now widespread, but often requires extensive case-by-case optimization. Here we asked if conserved genetic interactors (CGIs) with MMR genes from two evolutionary distant yeast species (Saccharomyces cerevisiae and Schizosaccharomyzes pombe) can predict orthologous genetic relationships in higher eukaryotes.MethodsHigh-throughput screening was used to identify genetic interaction profiles for the MutSα and MutSβ heterodimer subunits (msh2Δ, msh3Δ, msh6Δ) of fission yeast. Selected negative interactors with MutSβ (msh2Δ/msh3Δ) were directly analyzed in budding yeast, and the CGI with SUMO-protease Ulp2 further examined after RNA interference/drug treatment in MSH2-deficient and -proficient human cells.ResultsThis study identified distinct genetic profiles for MutSα and MutSβ, and supports a role for the latter in recombinatorial DNA repair. Approximately 28% of orthologous genetic interactions with msh2Δ/msh3Δ are conserved in both yeasts, a degree consistent with global trends across these species. Further, the CGI between budding/fission yeast msh2 and SUMO-protease Ulp2 is maintained in human cells (MSH2/SENP6), and enhanced by Olaparib, a PARP inhibitor that induces the accumulation of single-strand DNA breaks. This identifies SENP6 as a promising new target for the treatment of MMR-deficient cancers.ConclusionOur findings demonstrate the utility of employing evolutionary distance in tractable lower eukaryotes to predict orthologous genetic relationships in higher eukaryotes. Moreover, we provide novel insights into the genome maintenance functions of a critical DNA repair complex and propose a promising targeted treatment for MMR deficient tumors.