Network modeling links breast cancer susceptibility and centrosome dysfunction

Many cancer-associated genes remain to be identified to clarify the underlying molecular mechanisms of cancer susceptibility and progression. Better understanding is also required of how mutations in cancer genes affect their products in the context of complex cellular networks. Here we have used a network modeling strategy to identify genes potentially associated with higher risk of breast cancer. Starting with four known genes encoding tumor suppressors of breast cancer, we combined gene expression profiling with functional genomic and proteomic (or 'omic') data from various species to generate a network containing 118 genes linked by 866 potential functional associations. This network shows higher connectivity than expected by chance, suggesting that its components function in biologically related pathways. One of the components of the network is HMMR, encoding a centrosome subunit, for which we demonstrate previously unknown functional associations with the breast cancer-associated gene BRCA1. Two case-control studies of incident breast cancer indicate that the HMMR locus is associated with higher risk of breast cancer in humans. Our network modeling strategy should be useful for the discovery of additional cancer-associated genes.     

Use of whole genome sequencing to estimate the mutation rate of Mycobacterium tuberculosis during latent infection

Tuberculosis poses a global health emergency, which has been compounded by the emergence of drug-resistant Mycobacterium tuberculosis (Mtb) strains. We used whole-genome sequencing to compare the accumulation of mutations in Mtb isolated from cynomolgus macaques with active, latent or reactivated disease. We sequenced 33 Mtb isolates from nine macaques with an average genome coverage of 93% and an average read depth of 117×. Based on the distribution of SNPs observed, we calculated the mutation rates for these disease states. We found a similar mutation rate during latency as during active disease or in a logarithmically growing culture over the same period of time. The pattern of polymorphisms suggests that the mutational burden in vivo is because of oxidative DNA damage. We show that Mtb continues to acquire mutations during disease latency, which may explain why isoniazid monotherapy for latent tuberculosis is a risk factor for the emergence of isoniazid resistance.     

Resequencing of positional candidates identifies low frequency IL23R coding variants protecting against inflammatory bowel disease

Genome-wide association studies (GWAS) have identified dozens of risk loci for many complex disorders, including Crohn's disease. However, common disease-associated SNPs explain at most ～20% of the genetic variance for Crohn's disease. Several factors may account for this unexplained heritability, including rare risk variants not adequately tagged thus far in GWAS. That rare susceptibility variants indeed contribute to variation in multifactorial phenotypes has been demonstrated for colorectal cancer, plasma high-density lipoprotein cholesterol levels, blood pressure, type 1 diabetes, hypertriglyceridemia and, in the case of Crohn's disease, for NOD2 (refs. 14,15). Here we describe the use of high-throughput resequencing of DNA pools to search for rare coding variants influencing susceptibility to Crohn's disease in 63 GWAS-identified positional candidate genes. We identify low frequency coding variants conferring protection against inflammatory bowel disease in IL23R, but we conclude that rare coding variants in positional candidates do not make a large contribution to inherited predisposition to Crohn's disease.     

Highly effective SNP-based association mapping and management of recessive defects in livestock

The widespread use of elite sires by means of artificial insemination in livestock breeding leads to the frequent emergence of recessive genetic defects, which cause significant economic and animal welfare concerns. Here we show that the availability of genome-wide, high-density SNP panels, combined with the typical structure of livestock populations, markedly accelerates the positional identification of genes and mutations that cause inherited defects. We report the fine-scale mapping of five recessive disorders in cattle and the molecular basis for three of these: congenital muscular dystony (CMD) types 1 and 2 in Belgian Blue cattle and ichthyosis fetalis in Italian Chianina cattle. Identification of these causative mutations has an immediate translation into breeding practice, allowing marker assisted selection against the defects through avoidance of at-risk matings.     

Fine mapping of regulatory loci for mammalian gene expression using radiation hybrids

We mapped regulatory loci for nearly all protein-coding genes in mammals using comparative genomic hybridization and expression array measurements from a panel of mouse-hamster radiation hybrid cell lines. The large number of breaks in the mouse chromosomes and the dense genotyping of the panel allowed extremely sharp mapping of loci. As the regulatory loci result from extra gene dosage, we call them copy number expression quantitative trait loci, or ceQTLs. The -2log10P support interval for the ceQTLs was <150 kb, containing an average of <2-3 genes. We identified 29,769 trans ceQTLs with -log10P > 4, including 13 hotspots each regulating >100 genes in trans. Further, this work identifies 2,761 trans ceQTLs harboring no known genes, and provides evidence for a mode of gene expression autoregulation specific to the X chromosome.     

Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis

Although numerous fundamental aspects of development have been uncovered through the study of individual genes and proteins, system-level models are still missing for most developmental processes. The first two cell divisions of Caenorhabditis elegans embryogenesis constitute an ideal test bed for a system-level approach. Early embryogenesis, including processes such as cell division and establishment of cellular polarity, is readily amenable to large-scale functional analysis. A first step toward a system-level understanding is to provide 'first-draft' models both of the molecular assemblies involved and of the functional connections between them. Here we show that such models can be derived from an integrated gene/protein network generated from three different types of functional relationship: protein interaction, expression profiling similarity and phenotypic profiling similarity, as estimated from detailed early embryonic RNA interference phenotypes systematically recorded for hundreds of early embryogenesis genes. The topology of the integrated network suggests that C. elegans early embryogenesis is achieved through coordination of a limited set of molecular machines. We assessed the overall predictive value of such molecular machine models by dynamic localization of ten previously uncharacterized proteins within the living embryo.     

Systematic analysis of genes required for synapse structure and function

Chemical synapses are complex structures that mediate rapid intercellular signalling in the nervous system. Proteomic studies suggest that several hundred proteins will be found at synaptic specializations. Here we describe a systematic screen to identify genes required for the function or development of Caenorhabditis elegans neuromuscular junctions. A total of 185 genes were identified in an RNA interference screen for decreased acetylcholine secretion; 132 of these genes had not previously been implicated in synaptic transmission. Functional profiles for these genes were determined by comparing secretion defects observed after RNA interference under a variety of conditions. Hierarchical clustering identified groups of functionally related genes, including those involved in the synaptic vesicle cycle, neuropeptide signalling and responsiveness to phorbol esters. Twenty-four genes encoded proteins that were localized to presynaptic specializations. Loss-of-function mutations in 12 genes caused defects in presynaptic structure.     

Extremely slow Drude relaxation of correlated electrons

The electrical conduction of metals is governed by how freely mobile electrons can move throughout the material. This movement is hampered by scattering with other electrons, as well as with impurities or thermal excitations (phonons). Experimentally, the scattering processes of single electrons are not observed, but rather the overall response of all mobile charge carriers within a sample. The ensemble dynamics can be described by the relaxation rates, which express how fast the system approaches equilibrium after an external perturbation. Here we measure the frequency-dependent microwave conductivity of the heavy-fermion metal UPd2Al3 (ref. 4), finding that it is accurately described by the prediction for a single relaxation rate (the so-called Drude response). This is notable, as UPd2Al3 has strong interactions among the electrons that might be expected to lead to more complex behaviour. Furthermore, the relaxation rate of just a few gigahertz is extremely low--this is several orders of magnitude below those of conventional metals (which are typically around 10 THz), and at least one order of magnitude lower than previous estimates for comparable metals. These observations are directly related to the high effective mass of the charge carriers in this material and reveal the dynamics of interacting electrons.