An Activation Force-based Affinity Measure for Analyzing Complex Networks

Affinity measure is a key factor that determines the quality of the analysis of a complex network. Here, we introduce a type of statistics, activation forces, to weight the links of a complex network and thereby develop a desired affinity measure. We show that the approach is superior in facilitating the analysis through experiments on a large-scale word network and a protein-protein interaction (PPI) network consisting of ∼5,000 human proteins. The experiment on the word network verifies that the measured word affinities are highly consistent with human knowledge. Further, the experiment on the PPI network verifies the measure and presents a general method for the identification of functionally similar proteins based on PPIs. Most strikingly, we find an affinity network that compactly connects the cancer-associated proteins to each other, which may reveal novel information for cancer study; this includes likely protein interactions and key proteins in cancer-related signal transduction pathways

Enhanced gene repair mediated by methyl-CpG-modified single-stranded oligonucleotides

Gene editing mediated by oligonucleotides has been shown to induce stable single base alterations in genomic DNA in both prokaryotic and eukaryotic organisms. However, the low frequencies of gene repair have limited its applicability for both basic manipulation of genomic sequences and for the development of therapeutic approaches for genetic disorders. Here, we show that single-stranded oligodeoxynucleotides (ssODNs) containing a methyl-CpG modification and capable of binding to the methyl-CpG binding domain protein 4 (MBD4) are able to induce >10-fold higher levels of gene correction than ssODNs lacking the specific modification. Correction was stably inherited through cell division and was confirmed at the protein, transcript and genomic levels. Downregulation of MBD4 expression using RNAi prevented the enhancement of gene correction efficacy obtained using the methyl-CpG-modified ssODN, demonstrating the specificity of the repair mechanism being recruited. Our data demonstrate that efficient manipulation of genomic targets can be achieved and controlled by the type of ssODN used and by modulation of the repair mechanism involved in the correction process. This new generation of ssODNs represents an important technological advance that is likely to have an impact on multiple applications, especially for gene therapy where permanent correction of the genetic defect has clear advantages over viral and other nonviral approaches currently being tested

The Network Composition of Aggregate Unemployment

We develop a theory of unemployment in which workers search for jobs through a network of firms, the labor flow network (LFN). The lack of an edge between two companies indicates the impossibility of labor flows between them due to high frictions. In equilibrium, firms' hiring behavior correlates through the network, modulating labor flows and generating aggregate unemployment. This theory provides new micro-foundations for the aggregate matching function, the Beveridge curve, wage dispersion, and the employer-size premium. Using employer-employee matched records, we study the effect of the LFN topology through a new concept: `firm-specific unemployment'

Variation in the RAD51 gene and familial breast cancer

INTRODUCTION: Human RAD51 is a homologue of the Escherichia coli RecA protein and is known to function in recombinational repair of double-stranded DNA breaks. Mutations in the lower eukaryotic homologues of RAD51 result in a deficiency in the repair of double-stranded DNA breaks. Loss of RAD51 function would therefore be expected to result in an elevated mutation rate, leading to accumulation of DNA damage and, hence, to increased cancer risk. RAD51 interacts directly or indirectly with a number of proteins implicated in breast cancer, such as BRCA1 and BRCA2. Similar to BRCA1 mice, RAD51(-/- )mice are embryonic lethal. The RAD51 gene region has been shown to exhibit loss of heterozygosity in breast tumours, and deregulated RAD51 expression in breast cancer patients has also been reported. Few studies have investigated the role of coding region variation in the RAD51 gene in familial breast cancer, with only one coding region variant – exon 6 c.449G>A (p.R150Q) – reported to date. METHODS: All nine coding exons of the RAD51 gene were analysed for variation in 46 well-characterised, BRCA1/2-negative breast cancer families using denaturing high-performance liquid chromatography. Genotyping of the exon 6 p.R150Q variant was performed in an additional 66 families. Additionally, lymphoblastoid cell lines from breast cancer patients were subjected to single nucleotide primer extension analysis to assess RAD51 expression. RESULTS: No coding region variation was found, and all intronic variation detected was either found in unaffected controls or was unlikely to have functional consequences. Single nucleotide primer extension analysis did not reveal any allele-specific changes in RAD51 expression in all lymphoblastoid cell lines tested. CONCLUSION: Our study indicates that RAD51 is not a major familial breast cancer predisposition gene