Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map

Protein function space: viewing the limits or limited by our view?

Given that the number of protein functions on earth is finite, the rapid expansion of biological knowledge and the concomitant exponential increase in the number of protein sequences should, at some point, enable the estimation of the limits of protein function space. The functional coverage of protein sequences can be investigated using computational methods, especially given the massive amount of data being generated by large-scale environmental sequencing (metagenomics). In completely sequenced genomes, the fraction of proteins to which at least some functional features can be assigned has recently risen to as much as approximately 85%. Although this fraction is more uncertain in metagenomics surveys, because of environmental complexities and differences in analysis protocols, our global knowledge of protein functions still appears to be considerable. However, when we consider protein families, continued sequencing seems to yield an ever-increasing number of novel families. Until we reconcile these two views, the limits of protein space will remain obscured.

Regulation of Histone H3 Lysine 56 Acetylation in Schizosaccharomyces pombe

In Saccharomyces cerevisiae, acetylation of lysine 56 (Lys-56) in the globular domain of histone H3 plays an important role in response to genotoxic agents that interfere with DNA replication. However, the regulation and biological function of this modification are poorly defined in other eukaryotes. Here we show that Lys-56 acetylation in Schizosaccharomyces pombe occurs transiently during passage through S-phase and is normally removed in G(2). Genotoxic agents that cause DNA double strand breaks during replication elicit a delay in deacetylation of histone H3 Lys-56. In addition, mutant cells that cannot acetylate Lys-56 are acutely sensitive to genotoxic agents that block DNA replication. Moreover, we show that Spbc342.06cp, a previously uncharacterized open reading frame, encodes the functional homolog of S. cerevisiae Rtt109, and that this protein acetylates H3 Lys-56 both in vitro and in vivo. Altogether, our results indicate that both the regulation of histone H3 Lys-56 acetylation by its histone acetyltransferase and histone deacetylase and its role in the DNA damage response are conserved among two distantly related yeast model organisms.

Why are there still over 1000 uncharacterized yeast genes?

The yeast genetics community has embraced genomic biology, and there is a general understanding that obtaining a full encyclopedia of functions of the approximately 6000 genes is a worthwhile goal. The yeast literature comprises over 40,000 research papers, and the number of yeast researchers exceeds the number of genes. There are mutated and tagged alleles for virtually every gene, and hundreds of high-throughput data sets and computational analyses have been described. Why, then, are there >1000 genes still listed as uncharacterized on the Saccharomyces Genome Database, 10 years after sequencing the genome of this powerful model organism? Examination of the currently uncharacterized gene set suggests that while some are small or newly discovered, the vast majority were evident from the initial genome sequence. Most are present in multiple genomics data sets, which may provide clues to function. In addition, roughly half contain recognizable protein domains, and many of these suggest specific metabolic activities. Notably, the uncharacterized gene set is highly enriched for genes whose only homologs are in other fungi. Achieving a full catalog of yeast gene functions may require a greater focus on the life of yeast outside the laboratory.

CCR4/NOT complex associates with the proteasome and regulates histone methylation

The proteasome regulates histone lysine methylation and gene transcription, but how it does so is poorly understood. To better understand this process, we used the epistatic miniarray profile (E-MAP) approach to identify factors that genetically interact with proteasomal subunits. In addition to members of the Set1 complex that mediate histone H3 lysine 4 methylation (H3K4me), we found that deleting members of the CCR4/NOT mRNA processing complex exhibit synthetic phenotypes when combined with proteasome mutants. Further biochemical analyses revealed physical associations between CCR4/NOT and the proteasome in vivo. Consistent with the genetic and biochemical interactions linking CCR4/NOT with proteasome and Set1-mediated methylation, we find that loss of Not4 decreases global and gene-specific H3K4 trimethylation (H3K4me3) and decreases 19S proteasome recruitment to the PMA1 gene. Similar to proteasome regulation of histone methylation, loss of CCR4/NOT members does not affect ubiquitinated H2B. Mapping of Not4 identified the RING finger domain as essential for H3K4me3, suggesting a role for ubiquitin in this process. Consistent with this idea, loss of the Not4-interacting protein Ubc4, a known ubiquitin-conjugating enzyme, decreases H3K4me3. These studies implicate CCR4/NOT in the regulation of H3K4me3 through a ubiquitin-dependent pathway that likely involves the proteasome.

Backup without redundancy: genetic interactions reveal the cost of duplicate gene loss

We show that genetic interaction profiles offer a powerful approach to elicit phenotypes that are far richer than is attainable using single gene deletions. This has allowed us to address the long-standing question of the role played by duplicate genes (paralogs) in robustness against deletion.

We provide for the first time direct evidence that the capacity of some duplicates to cover for the loss of their paralogs can account for the observed difference in fitness between duplicate and singleton deletions mutants, but that the overall contribution of this effect to dispensability is small.

More broadly, we demonstrate that paralogs possessing apparent backup capacity in some environments have in fact distinct and non-overlapping functions, and are unable to provide backup across a range of compromising conditions. This resolves the previous paradox of how backup genes conferring dispensability can nevertheless be independently maintained in the population.

From a practical point of view, our findings suggest efficient strategies to elicit rich deletion phenotypes that should be highly relevant for the design of future phenotypic screens.

Much of our understanding of biological processes has been derived from the characterization of the functional consequence to an organism of altering one or more of its genes. Efforts to systematically evaluate the phenotypic effects of gene loss, however, have been hampered by the fact that the disruption of most genes has surprisingly modest effects on cell growth and viability. The high proportion of genes with no apparent deletion effect has wide-ranging practical and theoretical implications and has been the subject of considerable interest (Wagner, 2000, 2005; Giaever et al, 2002; Gu et al, 2003; Papp et al, 2004; Kafri et al, 2005). One factor that has been implicated as contributing to the high degree of dispensability is the abundance of closely related paralogs present in most genomes (Winzeler et al, 1999; Wagner, 2000; Giaever et al, 2002). Indeed, recent work in S. cerevisiae has shown that the existence of a paralog elsewhere in the genome significantly increases the chance that deletion of a given gene has little effect on growth (Gu et al, 2003). However, current analyses have been mostly correlative, and direct mechanistic evidence supporting or refuting the role of backup compensation in mutational robustness is still largely missing. Furthermore, backup between duplicates is not easily justified in evolutionary terms, in that a genuine ability to comprehensively cover for the loss of another gene is evolutionarily unstable (Brookfield, 1992).

Here, we exploit the recent availability of high-density quantitative genetic interaction profiles (EMAPs) to address these issues directly. To test whether SSL paralogs can account for the excess fitness of duplicates, we classified genes into fitness categories according to their deletion growth defect (Materials and methods). The subset of genes covered by our combined data set exhibits an over-representation of duplicate genes in the weak/no deletion phenotype (WNP) class similar to that reported previously (Gu et al, 2003) (Figure 1B). Strikingly, this difference corresponds to the number of WNP duplicates that have an SSL interaction with their corresponding paralog (Figure 1C). Our data thus provide direct evidence that it is indeed duplicate compensation that accounts for the observed difference in deletion growth defect between duplicates and singletons, at least for the genes covered by our data set.

Apart from the mechanism itself, the characteristic features of buffering duplicates have received considerable attention (Gu et al, 2003; Kafri et al, 2005; Wagner, 2005). Our data allowed us to unambiguously distinguish the subset of duplicates whose dispensability can be attributed to the existence of a backup paralog. The ability to identify backup duplicates directly put us in a position to study their features, and how they differ from other duplicates without buffering properties. In particular, we asked to what extent the observed buffering in rich media reflects functional similarity and a genuine ability to cover for the loss of a paralog in a broader range of conditions.

To assess the extent to which SSL duplicates can provide genuine backup under compromising conditions, we fist used genetic interaction profiles as a more stringent test for redundancy that assesses the effect of gene loss in the background of additional gene deletions. In contrast to the expectation that truly buffered duplicates should have few if any synthetic interactions, we find that the number is in fact substantial and often exceeds that of random genes and non-SSL duplicates (Figure 2B). Similarly, using a recent data set of sensitivity profiles of deletion strains to a range of agents and environments (Brown et al, 2006), we find that the deletion of SSL duplicates across a range of environments has on average no weaker (and in fact a slightly stronger) effect on cellular growth rate than that of non-SSL duplicates or random genes. Taken together, these findings suggest that the backup capacity of SSL duplicates is limited and not indicative of a comprehensive ability to cover for the loss of the paralogous partner.

We next tested the degree of functional similarity of buffering duplicates using similarity in genetic interaction as well as environmental sensitivity profiles as indicators of shared functionality (Tong et al, 2004; Schuldiner et al, 2005; Brown et al, 2006; Pan et al, 2006). In spite of their rich media buffering properties, we find that the interaction and sensitivity patterns of most SSL duplicates are divergent and are usually more similar to those of other, non-paralogous genes (Figure 2C and D; Supplementary Figure 10).

Lastly, in addition to our analysis of duplicate phenotypes, we used genetic interaction spectra as deletion phenotypes for generic genes whose single deletion in standard conditions has little measurable effect. As expected, genetic interactions provide a deletion phenotype for many more genes (80–90%) than single gene deletions in standard growth environments (Steinmetz et al, 2002), which yield a detectable growth defect only for 30–40% (Figure 4B). To assess whether these interactions reflect the cost of gene loss (gene importance), we asked if there is a relationship between the probability of a gene being retained between related species and its number of genetic interactions. Indeed, genetic interactivity exhibits a strong correlation with gene retention across related phyla (Figure 4C and Supplementary Figure 7), and predicts the likelihood of gene loss better than lethality/viability, quantitative growth deficiency or environmental specificity (Supplementary Figure 8). Thus, genetic interactions provide a cost of gene loss that effectively recapitulates evolutionary constraints. This is further supported by the observation that genetic interactions are significantly correlated with environmental sensitivity across a range of conditions. Thus, our findings suggest that for most genes there is a substantial cost of gene loss, even though this is often not reflected in single gene deletion tests carried out in standard conditions.

Many genes can be deleted with little phenotypic consequences. By what mechanism and to what extent the presence of duplicate genes in the genome contributes to this robustness against deletions has been the subject of considerable interest. Here, we exploit the availability of high-density genetic interaction maps to provide direct support for the role of backup compensation, where functionally overlapping duplicates cover for the loss of their paralog. However, we find that the overall contribution of duplicates to robustness against null mutations is low (∼25%). The ability to directly identify buffering paralogs allowed us to further study their properties, and how they differ from non-buffering duplicates. Using environmental sensitivity profiles as well as quantitative genetic interaction spectra as high-resolution phenotypes, we establish that even duplicate pairs with compensation capacity exhibit rich and typically non-overlapping deletion phenotypes, and are thus unable to comprehensively cover against loss of their paralog. Our findings reconcile the fact that duplicates can compensate for each other's loss under a limited number of conditions with the evolutionary instability of genes whose loss is not associated with a phenotypic penalty.

A protein interaction network for pluripotency of embryonic stem cells

Embryonic stem (ES) cells are pluripotent and of therapeutic potential in regenerative medicine. Understanding pluripotency at the molecular level should illuminate fundamental properties of stem cells and the process of cellular reprogramming. Through cell fusion the embryonic cell phenotype can be imposed on somatic cells, a process promoted by the homeodomain protein Nanog, which is central to the maintenance of ES cell pluripotency. Nanog is thought to function in concert with other factors such as Oct4 (ref. 8) and Sox2 (ref. 9) to establish ES cell identity. Here we explore the protein network in which Nanog operates in mouse ES cells. Using affinity purification of Nanog under native conditions followed by mass spectrometry, we have identified physically associated proteins. In an iterative fashion we also identified partners of several Nanog-associated proteins (including Oct4), validated the functional relevance of selected newly identified components and constructed a protein interaction network. The network is highly enriched for nuclear factors that are individually critical for maintenance of the ES cell state and co-regulated on differentiation. The network is linked to multiple co-repressor pathways and is composed of numerous proteins whose encoding genes are putative direct transcriptional targets of its members. This tight protein network seems to function as a cellular module dedicated to pluripotency.