Muhammed A. Yildirim

High-quality binary protein interaction map of the yeast interactome network

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a “second-generation” high-quality, high-throughput Y2H data set covering ∼20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.

Edgetic perturbation models of human inherited disorders

Cellular functions are mediated through complex systems of macromolecules and metabolites linked through biochemical and physical interactions, represented in interactome models as ‘nodes’ and ‘edges’, respectively. Better understanding of genotype‐to‐phenotype relationships in human disease will require modeling of how disease‐causing mutations affect systems or interactome properties. Here we investigate how perturbations of interactome networks may differ between complete loss of gene products (‘node removal’) and interaction‐specific or edge‐specific (‘edgetic’) alterations. Global computational analyses of ∼50 000 known causative mutations in human Mendelian disorders revealed clear separations of mutations probably corresponding to those of node removal versus edgetic perturbations. Experimental characterization of mutant alleles in various disorders identified diverse edgetic interaction profiles of mutant proteins, which correlated with distinct structural properties of disease proteins and disease mechanisms. Edgetic perturbations seem to confer distinct functional consequences from node removal because a large fraction of cases in which a single gene is linked to multiple disorders can be modeled by distinguishing edgetic network perturbations. Edgetic network perturbation models might improve both the understanding of dissemination of disease alleles in human populations and the development of molecular therapeutic strategies.

Proto-genes and de novo gene birth

Novel protein-coding genes can arise either through re-organization of pre-existing genes or de novo. Processes involving re-organization of pre-existing genes, notably after gene duplication, have been extensively described. In contrast, de novo gene birth remains poorly understood, mainly because translation of sequences devoid of genes, or ‘non-genic’ sequences, is expected to produce insignificant polypeptides rather than proteins with specific biological functions. Here we formalize an evolutionary model according to which functional genes evolve de novo through transitory proto-genes generated by widespread translational activity in non-genic sequences. Testing this model at the genome scale in Saccharomyces cerevisiae, we detect translation of hundreds of short species-specific open reading frames (ORFs) located in non-genic sequences. These translation events seem to provide adaptive potential, as suggested by their differential regulation upon stress and by signatures of retention by natural selection. In line with our model, we establish that S. cerevisiae ORFs can be placed within an evolutionary continuum ranging from non-genic sequences to genes. We identify ∼1,900 candidate proto-genes among S. cerevisiae ORFs and find that de novo gene birth from such a reservoir may be more prevalent than sporadic gene duplication. Our work illustrates that evolution exploits seemingly dispensable sequences to generate adaptive functional innovation.

Belief Propagation on Partially Ordered Sets

In this paper, which is based on the important recent work of Yedidia, Freeman, and Weiss, we present a generalized form of belief propagation, viz. belief propagation on a partially ordered set (PBP). PBP is an iterative message-passing algorithm for solving, either exactly or approximately, the marginalized product density problem, which is a general computational problem of wide applicability. We will show that PBP can be thought of as an algorithm for minimizing a certain “free energy” function, and by exploiting this interpretation, we will exhibit a one-to-one correspondence between the fixed points of PBP and the stationary points of the free energy.

A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster

Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.

Using random walks to generate associations between objects.

Measuring similarities between objects based on their attributes has been an important problem in many disciplines. Object-attribute associations can be depicted as links on a bipartite graph. A similarity measure can be thought as a unipartite projection of this bipartite graph. The most widely used bipartite projection techniques make assumptions that are not often fulfilled in real life systems, or have the focus on the bipartite connections more than on the unipartite connections. Here, we define a new similarity measure that utilizes a practical procedure to extract unipartite graphs without making a priori assumptions about underlying distributions. Our similarity measure captures the relatedness between two objects via the likelihood of a random walker passing through these nodes sequentially on the bipartite graph. An important aspect of the method is that it is robust to heterogeneous bipartite structures and it controls for the transitivity similarity, avoiding the creation of unrealistic homogeneous degree distributions in the resulting unipartite graphs. We test this method using real world examples and compare the obtained results with alternative similarity measures, by validating the actual and orthogonal relations between the entities.

Systems engineering to systems biology.

Mol Syst Biol. 4: 185 The ‘bottom‐up’ approach to systems biology entails quantitatively studying complex biological processes by analyzing their molecular components. A converse system biology approach is to infer properties of biological systems in a ‘top‐down’ fashion, using a variety of network reverse engineering methods, data‐driven modeling and data integration strategies. Application of a top‐down approach to the quantitative biology of a small size system is however less common. In a recent publication, Mettetal et al (2008) have insightfully applied such a strategy to successfully decode critical properties of osmo‐adaptation in the yeast Saccharomyces cerevisiae . A biological system can, in principle, be dissected by successively inactivating each component individually and measuring how the overall input–output characteristics of the system change. For cellular systems, such dissection involves gene knockouts and/or knockdowns. However, given the complexity of living cells, it is difficult to link the function of single components (e.g. a protein) to observed outputs. Moreover, invasive knockout/knockdown often leads to undesired complications (e.g. lethality). Mettetal et al followed a different systems reverse‐engineering approach by which they considered the system first as a ‘black box’ and assumed it to be equivalent to a linear time‐invariant (LTI) system (Oppenheim et al , 1997) (Figure 1A and B). An LTI system has two defining properties: first, the output from a set of inputs represents the linear sum of the outputs from each individual input (Figure 1C). Second, the generated output is independent of the time point at which the causal input was applied (Figure 1D). An LTI system is characterized by a single ‘response function.’ Once the response function is known, the output for any arbitrary input can be …

Implied Comparative Advantage

Ricardian theories of production often take the comparative advantage of locations in different industries to be uncorrelated. They are seen as the outcome of the realization of a random extreme value distribution. These theories do not take a stance regarding the counterfactual or implied comparative advantage if the country does not make the product. Here, we find that industries in countries and cities tend to have a relative size that is systematically correlated with that of other industries. Industries also tend to have a relative size that is systematically correlated with the size of the industry in similar countries and cities. We illustrate this using export data for a large set of countries and for city-level data for the US, Chile and India. These stylized facts can be rationalized using a Ricardian framework where comparative advantage is correlated across technologically related industries. More interestingly, the deviations between actual industry intensity and the implied intensity obtained from that of related industries or related locations tend to be highly predictive of future industry growth, especially at horizons of a decade or more. This result holds both at the intensive as well as the extensive margin, indicating that future comparative advantage is already implied in todays pattern of production.