The Mitochondrial Protein MAVS Stabilizes p53 to Suppress Tumorigenesis.

Recent reports have shown the critical role of the mitochondrial antiviral signaling (MAVS) protein in virus-induced apoptosis, but the involvement of MAVS in tumorigenesis is still poorly understood. Herein, we report that MAVS is a key regulator of p53 activation and is critical for protecting against tumorigenesis. We find that MAVS promotes p53-dependent cell death in response to DNA damage. MAVS interacts with p53 and mediates p53 mitochondrial recruitment under genotoxic stress. Mechanistically, MAVS inhibits p53 ubiquitination by blocking the formation of the p53-murine double-minute 2 (MDM2) complex, leading to the stabilization of p53. Notably, compared with their wild-type littermates, MAVS knockout mice display decreased resistance to azoxymethane (AOM) or AOM/dextran sulfate sodium salt (DSS)-induced colon cancer. MAVS expression is significantly downregulated in human colon cancer tissues. These results unveil roles for MAVS in DNA damage response and tumor suppression.

Tumor Microenvironment Regulation by the Endoplasmic Reticulum Stress Transmission Mediator Golgi Protein 73 in Mice.

The unfolded protein response (UPR) signal in tumor cells activates UPR signaling in neighboring macrophages, which leads to tumor-promoting inflammation by up-regulating UPR target genes and proinflammatory cytokines. However, the molecular basis of this endoplasmic reticulum (ER) stress transmission remains largely unclear. Here, we identified the secreted form of Golgi protein 73 (GP73), a Golgi-associated protein functional critical for hepatocellular carcinoma (HCC) growth and metastasis, is indispensable for ER stress transmission. Notably, ER stressors increased the cellular secretion of GP73. Through GRP78, the secreted GP73 stimulated ER stress activation in neighboring macrophages, which then released cytokines and chemokines involved in the tumor-associated macrophage (TAM) phenotype. Analysis of HCC patients revealed a positive correlation of GP73 with glucose-regulated protein 78 (GRP78) expression and TAM density. High GP73 and CD206 expression was associated with poor prognosis. Blockade of GP73 decreased the density of TAMs, inhibited tumor growth, and prolonged survival in two mouse HCC models. Conclusion: Our findings provide insight into the molecular mechanisms of extracellular GP73 in the amplification and transmission of ER stress signals.

Genotyping Informatics and Quality Control for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

The Kaiser Permanente (KP) Research Program on Genes, Environment and Health (RPGEH), in collaboration with the University of California-San Francisco, undertook genome-wide genotyping of >100,000 subjects that constitute the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The project, which generated >70 billion genotypes, represents the first large-scale use of the Affymetrix Axiom Genotyping Solution. Because genotyping took place over a short 14-month period, creating a near-real-time analysis pipeline for experimental assay quality control and final optimized analyses was critical. Because of the multi-ethnic nature of the cohort, four different ethnic-specific arrays were employed to enhance genome-wide coverage. All assays were performed on DNA extracted from saliva samples. To improve sample call rates and significantly increase genotype concordance, we partitioned the cohort into disjoint packages of plates with similar assay contexts. Using strict QC criteria, the overall genotyping success rate was 103,067 of 109,837 samples assayed (93.8%), with a range of 92.1-95.4% for the four different arrays. Similarly, the SNP genotyping success rate ranged from 98.1 to 99.4% across the four arrays, the variation depending mostly on how many SNPs were included as single copy vs. double copy on a particular array. The high quality and large scale of genotype data created on this cohort, in conjunction with comprehensive longitudinal data from the KP electronic health records of participants, will enable a broad range of highly powered genome-wide association studies on a diversity of traits and conditions.

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm.

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.

Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array.

The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.

Gene structure-based splice variant deconvolution using a microarray platform.

MOTIVATION: Alternative splicing allows a single gene to generate multiple mRNAs, which can be translated into functionally and structurally diverse proteins. One gene can have multiple variants coexisting at different concentrations. Estimating the relative abundance of each variant is important for the study of underlying biological function. Microarrays are standard tools that measure gene expression. But most design and analysis has not accounted for splice variants. Thus splice variant-specific chip designs and analysis algorithms are needed for accurate gene expression profiling. RESULTS: Inspired by Li and Wong (2001), we developed a gene structure-based algorithm to determine the relative abundance of known splice variants. Probe intensities are modeled across multiple experiments using gene structures as constraints. Model parameters are obtained through a maximum likelihood estimation (MLE) process/framework. The algorithm produces the relative concentration of each variant, as well as an affinity term associated with each probe. Validation of the algorithm is performed by a set of controlled spike experiments as well as endogenous tissue samples using a human splice variant array.

Structure-based comparison of four eukaryotic genomes.

The field of comparative genomics allows us to elucidate the molecular mechanisms necessary for the machinery of an organism by contrasting its genome against those of other organisms. In this paper, we contrast the genome of homo sapiens against C. Elegans, Drosophila melanogaster, and S. cerevisiae to gain insights on what structural domains are present in each organism. Previous work has assessed this using sequence-based homology recognition systems such as Pfam [1] and Interpro [2]. Here, we pursue a structure-based assessment, analyzing genomes according to domains in the SCOP structural domain dictionary. Compared to other eukaryotic genomes, we observe additional domains in the human genome relating to signal transduction, immune response, transport, and certain enzymes. Compared to the metazoan genomes, the yeast genome shows an absence of domains relating to immune response, cell-cell interactions, and cell signaling.