Wrestling with pleiotropy: genomic and topological analysis of the yeast gene expression network

The vast majority (>95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized "gene expression network"--a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 different yeast gene deletion mutants.(1) We find that gene expression interactions form a robust, error-tolerant "scale-free" network, similar to metabolic pathways(2) and artificial networks such as power grids and the internet.(3-5) Because the connectivity between genes in the gene expression network is unevenly distributed, a scale-free organization helps make organisms resistant to the deleterious effects of mutation, and is thus highly adaptive. The existence of a gene expression network poses practical considerations for the study of gene function, since most mutant phenotypes are the result of changes in the expression of many genes. Using principles of scale-free network topology, we propose that fragmenting the gene expression network via "genome-engineering" may be a viable and practical approach to isolating gene function.     

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).     

三维基因组学与精准生物学

三维基因组学是以研究真核生物核内基因组空间构象,及其对不同基因转录调控的生物学效应为主要研究内容的一个新的学科方向;也是后基因组学时代研究的一个热门领域。它的研究重点是空间构象与基因转录调控间的关系。通过三维基因组学技术,科学家将能对基因组的折叠和空间构象、转录调控机制、复杂生物学性状、信号传导通路和基因组的运行机制等一系列重要问题进行更深入的探讨和研究,为系统解读生命百科全书和精准生物学的实施奠定坚实基础。本文综述了目前三维基因组学研究领域中的主要技术、研究现状、科研进展、存在问题、未来及与精准生物学的关系等内容。以期能较系统地展示三维基因组学取得的一系列成果,解读从三维空间构象信息到不同基因功能研究的路径,精准决定在转录调控网络中不同基因表达的时空特异性的可能模式。     

SPINE: a framework for signaling-regulatory pathway inference from cause-effect experiments

MOTIVATION: The complex program of gene expression allows the cell to cope with changing genetic, developmental and environmental conditions. The accumulating large-scale measurements of gene knockout effects and molecular interactions allow us to begin to uncover regulatory and signaling pathways within the cell that connect causal to affected genes on a network of physical interactions. RESULTS: We present a novel framework, SPINE, for Signaling-regulatory Pathway INferencE. The framework aims at explaining gene expression experiments in which a gene is knocked out and as a result multiple genes change their expression levels. To this end, an integrated network of protein-protein and protein-DNA interactions is constructed, and signaling pathways connecting the causal gene to the affected genes are searched for in this network. The reconstruction problem is translated into that of assigning an activation/repression attribute with each protein so as to explain (in expectation) a maximum number of the knockout effects observed. We provide an integer programming formulation for the latter problem and solve it using a commercial solver. We validate the method by applying it to a yeast subnetwork that is involved in mating. In cross-validation tests, SPINE obtains very high accuracy in predicting knockout effects (99%). Next, we apply SPINE to the entire yeast network to predict protein effects and reconstruct signaling and regulatory pathways. Overall, we are able to infer 861 paths with confidence and assign effects to 183 genes. The predicted effects are found to be in high agreement with current biological knowledge. AVAILABILITY: The algorithm and data are available at http://cs.tau.ac.il/~roded/SPINE.html.     

Repression of germline RNAi pathways in somatic cells by retinoblastoma pathway chromatin complexes

The retinoblastoma (Rb) tumor suppressor acts with a number of chromatin cofactors in a wide range of species to suppress cell proliferation. The Caenorhabditis elegans retinoblastoma gene and many of these cofactors, called synMuv B genes, were identified in genetic screens for cell lineage defects caused by growth factor misexpression. Mutations in many synMuv B genes, including lin-35/Rb, also cause somatic misexpression of the germline RNA processing P granules and enhanced RNAi. We show here that multiple small RNA components, including a set of germline-specific Argonaute genes, are misexpressed in the soma of many synMuv B mutant animals, revealing one node for enhanced RNAi. Distinct classes of synMuv B mutants differ in the subcellular architecture of their misexpressed P granules, their profile of misexpressed small RNA and P granule genes, as well as their enhancement of RNAi and the related silencing of transgenes. These differences define three classes of synMuv B genes, representing three chromatin complexes: a LIN-35/Rb-containing DRM core complex, a SUMO-recruited Mec complex, and a synMuv B heterochromatin complex, suggesting that intersecting chromatin pathways regulate the repression of small RNA and P granule genes in the soma and the potency of RNAi. Consistent with this, the DRM complex and the synMuv B heterochromatin complex were genetically additive and displayed distinct antagonistic interactions with the MES-4 histone methyltransferase and the MRG-1 chromodomain protein, two germline chromatin regulators required for the synMuv phenotype and the somatic misexpression of P granule components. Thus intersecting synMuv B chromatin pathways conspire with synMuv B suppressor chromatin factors to regulate the expression of small RNA pathway genes, which enables heightened RNAi response. Regulation of small RNA pathway genes by human retinoblastoma may also underlie its role as a tumor suppressor gene.     

Mesoscale Modeling of Nucleosome-Binding Antibody PL2-6: Mono- versus Bivalent Chromatin Complexes

Interactions of chromatin with bivalent immunoglobin nucleosome-binding antibodies and their monovalent (papain-derived) antigen-binding fragment analogs are useful probes for examining chromatin conformational states. To help interpret antibody-chromatin interactions and explore how antibodies might compete for interactions with chromatin components, we incorporate coarse-grained PL2-6 antibody modeling into our mesoscale chromatin model. We analyze interactions and fiber structures for the antibody-chromatin complexes in open and condensed chromatin, with and without H1 linker histone (LH). Despite minimal and transient interactions at physiological salt, we capture significant differences in antibody-chromatin complex configurations in open fibers, with more intense interactions between the bivalent antibody and chromatin compared to monovalent antigen-binding fragments. For these open chromatin fiber morphologies, antibody binding to histone tails is increased and compaction is greater for bivalent compared to monovalent and antibody-free systems. Differences between monovalent and bivalent binding result from antibody competition with internal chromatin fiber components (nucleosome core and linker DNA) for histone tail (H3, H4, H2A, H2B) interactions. This antibody competition for tail contacts reduces tail-core and tail-linker interactions and increases tail-antibody interactions. Such internal structural changes in open fibers resemble mechanisms of LH condensation, driven by charge screening and entropy changes. For condensed fibers at physiological salt, the three systems are much more similar overall, but some subtle tail interaction differences can be noted. Adding LH results in less-dramatic changes for all systems, except that the bivalent complex at physiological salt shows cooperative effects between LH and the antibodies in condensing chromatin fibers. Such dynamic interactions that depend on the internal structure and complex-stabilizing interactions within the chromatin fiber have implications for gene regulation and other chromatin complexes such as with LH, remodeling proteins, and small molecular chaperones that bind and modulate chromatin structure.     

Navigating the chaperone network: an integrative map of physical and genetic interactions mediated by the hsp90 chaperone

Physical, genetic, and chemical-genetic interactions centered on the conserved chaperone Hsp90 were mapped at high resolution in yeast using systematic proteomic and genomic methods. Physical interactions were identified using genome-wide two hybrid screens combined with large-scale affinity purification of Hsp90-containing protein complexes. Genetic interactions were uncovered using synthetic genetic array technology and by a microarray-based chemical-genetic screen of a set of about 4700 viable yeast gene deletion mutants for hypersensitivity to the Hsp90 inhibitor geldanamycin. An extended network, consisting of 198 putative physical interactions and 451 putative genetic and chemical-genetic interactions, was found to connect Hsp90 to cofactors and substrates involved in a wide range of cellular functions. Two novel Hsp90 cofactors, Tah1 (YCR060W) and Pih1 (YHR034C), were also identified. These cofactors interact physically and functionally with the conserved AAA(+)-type DNA helicases Rvb1/Rvb2, which are key components of several chromatin remodeling factors, thereby linking Hsp90 to epigenetic gene regulation.