Extracellular tumor-related mRNA in plasma of lymphoma patients and survival implications.

BACKGROUND We studied anomalous extracellular mRNAs in plasma from patients with diffuse large B-cell lymphoma (DLBCL) and their survival implications. mRNAs studied have been reported in the literature as markers of poor (BCL2, CCND2, MYC) and favorable outcome (LMO2, BCL6, FN1) in tumors. These markers were also analyzed in lymphoma tissues to test possible associations with their presence in plasma. METHODOLOGY/PRINCIPAL FINDINGS mRNA from 42 plasma samples and 12 tumors from patients with DLBCL was analyzed by real-time PCR. Samples post-treatment were studied. The immunohistochemistry of BCL2 and BCL6 was defined. Presence of circulating tumor cells was determined by analyzing the clonality of the immunoglobulin heavy-chain genes by PCR. In DLBCL, MYC mRNA was associated with short overall survival. mRNA targets with unfavorable outcome in tumors were associated with characteristics indicative of poor prognosis, with partial treatment response and with short progression-free survival in patients with complete response. In patients with low IPI score, unfavorable mRNA targets were related to shorter overall survival, partial response, high LDH levels and death. mRNA disappeared in post-treatment samples of patients with complete response, and persisted in those with partial response or death. No associations were found between circulating tumor cells and plasma mRNA. Absence of BCL6 protein in tumors was associated with presence of unfavorable plasma mRNA. CONCLUSIONS/SIGNIFICANCE Through a non-invasive procedure, tumor-derived mRNAs can be obtained in plasma. mRNA detected in plasma did not proceed from circulating tumor cells. In our study, unfavorable targets in plasma were associated with poor prognosis in B-cell lymphomas, mainly MYC mRNA. Moreover, the unfavorable targets in plasma could help us to classify patients with poor outcome within the good prognosis group according to IPI.

Conservation and developmental expression of ubiquitin isopeptidases in Schistosoma mansoni

Several genes related to the ubiquitin (Ub)-proteasome pathway, including those coding for proteasome subunits and conjugation enzymes, are differentially expressed during the Schistosoma mansoni life cycle. Although deubiquitinating enzymes have been reported to be negative regulators of protein ubiquitination and shown to play an important role in Ub-dependent processes, little is known about their role in S. mansoni . In this study, we analysed the Ub carboxyl-terminal hydrolase (UCHs) proteins found in the database of the parasite’s genome. An in silicoana- lysis (GeneDB and MEROPS) identified three different UCH family members in the genome, Sm UCH-L3, Sm UCH-L5 and SmBAP-1 and a phylogenetic analysis confirmed the evolutionary conservation of the proteins. We performed quantitative reverse transcription-polymerase chain reaction and observed a differential expression profile for all of the investigated transcripts between the cercariae and adult worm stages. These results were corroborated by low rates of Z-Arg-Leu-Arg-Gly-Gly-AMC hydrolysis in a crude extract obtained from cercariae in parallel with high Ub conjugate levels in the same extracts. We suggest that the accumulation of ubiquitinated proteins in the cercaria and early schistosomulum stages is related to a decrease in 26S proteasome activity. Taken together, our data suggest that UCH family members contribute to regulating the activity of the Ub-proteasome system during the life cycle of this parasite.

Genomic analysis of a nontoxigenic, invasive Corynebacterium diphtheriae strain from Brazil

We report the complete genome sequence and analysis of an invasive Corynebacterium diphtheriae strain that caused endocarditis in Rio de Janeiro, Brazil. It was selected for sequencing on the basis of the current relevance of nontoxigenic strains for public health. The genomic information was explored in the context of diversity, plasticity and genetic relatedness with other contemporary strains.

Social meets molecular: Combining phylogenetic and latent class analyses to understand HIV-1 transmission in Switzerland.

Switzerland has a complex human immunodeficiency virus (HIV) epidemic involving several populations. We examined transmission of HIV type 1 (HIV-1) in a national cohort study. Latent class analysis was used to identify socioeconomic and behavioral groups among 6,027 patients enrolled in the Swiss HIV Cohort Study between 2000 and 2011. Phylogenetic analysis of sequence data, available for 4,013 patients, was used to identify transmission clusters. Concordance between sociobehavioral groups and transmission clusters was assessed in correlation and multiple correspondence analyses. A total of 2,696 patients were infected with subtype B, 203 with subtype C, 196 with subtype A, and 733 with recombinant subtypes (mainly CRF02_AG and CRF01_AE). Latent class analysis identified 8 patient groups. Most transmission clusters of subtype B were shared between groups of gay men (groups 1-3) or between the heterosexual groups "heterosexual people of lower socioeconomic position" (group 4) and "injection drug users" (group 8). Clusters linking homosexual and heterosexual groups were associated with "older heterosexual and gay people on welfare" (group 5). "Migrant women in heterosexual partnerships" (group 6) and "heterosexual migrants on welfare" (group 7) shared non-B clusters with groups 4 and 5. Combining approaches from social and molecular epidemiology can provide insights into HIV-1 transmission and inform the design of prevention strategies.

Functional analysis: evaluation of response intensities--tailoring ANOVA for lists of expression subsets.

Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions. Geneset analysis methods have been described previously to analyze the expression values of several genes related by known biological criteria (metabolic pathway, pathology signature, co-regulation by a common factor, etc.) at the same time and the cost of these methods allows for the use of more values to help discover the underlying biological mechanisms. Results: As several methods assume different null hypotheses, we propose to reformulate the main question that biologists seek to answer. To determine which genesets are associated with expression values that differ between two experiments, we focused on three ad hoc criteria: expression levels, the direction of individual gene expression changes (up or down regulation), and correlations between genes. We introduce the FAERI methodology, tailored from a two-way ANOVA to examine these criteria. The significance of the results was evaluated according to the self-contained null hypothesis, using label sampling or by inferring the null distribution from normally distributed random data. Evaluations performed on simulated data revealed that FAERI outperforms currently available methods for each type of set tested. We then applied the FAERI method to analyze three real-world datasets on hypoxia response. FAERI was able to detect more genesets than other methodologies, and the genesets selected were coherent with current knowledge of cellular response to hypoxia. Moreover, the genesets selected by FAERI were confirmed when the analysis was repeated on two additional related datasets. Conclusions: The expression values of genesets are associated with several biological effects. The underlying mathematical structure of the genesets allows for analysis of data from several genes at the same time. Focusing on expression levels, the direction of the expression changes, and correlations, we showed that two-step data reduction allowed us to significantly improve the performance of geneset analysis using a modified two-way ANOVA procedure, and to detect genesets that current methods fail to detect.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

Generalized canonical correlation analysis of matrices with different row and column orders

A Method is offered that makes it possible to apply generalized canonicalcorrelations analysis (CANCOR) to two or more matrices of different row and column order. The new method optimizes the generalized canonical correlationanalysis objective by considering only the observed values. This is achieved byemploying selection matrices. We present and discuss fit measures to assessthe quality of the solutions. In a simulation study we assess the performance of our new method and compare it to an existing procedure called GENCOM,proposed by Green and Carroll. We find that our new method outperforms the GENCOM algorithm both with respect to model fit and recovery of the truestructure. Moreover, as our new method does not require any type of iteration itis easier to implement and requires less computation. We illustrate the methodby means of an example concerning the relative positions of the political parties inthe Netherlands based on provincial data.

The genome of the fire ant Solenopsis invicta.

Ants have evolved very complex societies and are key ecosystem members. Some ants, such as the fire ant Solenopsis invicta, are also major pests. Here, we present a draft genome of S. invicta, assembled from Roche 454 and Illumina sequencing reads obtained from a focal haploid male and his brothers. We used comparative genomic methods to obtain insight into the unique features of the S. invicta genome. For example, we found that this genome harbors four adjacent copies of vitellogenin. A phylogenetic analysis revealed that an ancestral vitellogenin gene first underwent a duplication that was followed by possibly independent duplications of each of the daughter vitellogenins. The vitellogenin genes have undergone subfunctionalization with queen- and worker-specific expression, possibly reflecting differential selection acting on the queen and worker castes. Additionally, we identified more than 400 putative olfactory receptors of which at least 297 are intact. This represents the largest repertoire reported so far in insects. S. invicta also harbors an expansion of a specific family of lipid-processing genes, two putative orthologs to the transformer/feminizer sex differentiation gene, a functional DNA methylation system, and a single putative telomerase ortholog. EST data indicate that this S. invicta telomerase ortholog has at least four spliceforms that differ in their use of two sets of mutually exclusive exons. Some of these and other unique aspects of the fire ant genome are likely linked to the complex social behavior of this species.

Gene loss and evolutionary rates following whole-genome duplication in teleost fishes.

Teleost fishes provide the first unambiguous support for ancient whole-genome duplication in an animal lineage. Studies in yeast or plants have shown that the effects of such duplications can be mediated by a complex pattern of gene retention and changes in evolutionary pressure. To explore such patterns in fishes, we have determined by phylogenetic analysis the evolutionary origin of 675 Tetraodon duplicated genes assigned to chromosomes, using additional data from other species of actinopterygian fishes. The subset of genes, which was retained in double after the genome duplication, is enriched in development, signaling, behavior, and regulation functional categories. The evolutionary rate of duplicate fish genes appears to be determined by 3 forces: 1) fish proteins evolve faster than mammalian orthologs; 2) the genes kept in double after genome duplication represent the subset under strongest purifying selection; and 3) following duplication, there is an asymmetric acceleration of evolutionary rate in one of the paralogs. These results show that similar mechanisms are at work in fishes as in yeast or plants and provide a framework for future investigation of the consequences of duplication in fishes and other animals.

Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits.

Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8)) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.

Comparative genomic and phylogeographic analysis of Mycobacterium leprae.

Reductive evolution and massive pseudogene formation have shaped the 3.31-Mb genome of Mycobacterium leprae, an unculturable obligate pathogen that causes leprosy in humans. The complete genome sequence of M. leprae strain Br4923 from Brazil was obtained by conventional methods (6x coverage), and Illumina resequencing technology was used to obtain the sequences of strains Thai53 (38x coverage) and NHDP63 (46x coverage) from Thailand and the United States, respectively. Whole-genome comparisons with the previously sequenced TN strain from India revealed that the four strains share 99.995% sequence identity and differ only in 215 polymorphic sites, mainly SNPs, and by 5 pseudogenes. Sixteen interrelated SNP subtypes were defined by genotyping both extant and extinct strains of M. leprae from around the world. The 16 SNP subtypes showed a strong geographical association that reflects the migration patterns of early humans and trade routes, with the Silk Road linking Europe to China having contributed to the spread of leprosy.

Genome-wide analysis of Sphingomonas wittichii RW1 behaviour during inoculation and growth in contaminated sand.

The efficacy of inoculation of single pure bacterial cultures into complex microbiomes, for example, in order to achieve increased pollutant degradation rates in contaminated material (that is, bioaugmentation), has been frustrated by insufficient knowledge on the behaviour of the inoculated bacteria under the specific abiotic and biotic boundary conditions. Here we present a comprehensive analysis of genome-wide gene expression of the bacterium Sphingomonas wittichii RW1 in contaminated non-sterile sand, compared with regular suspended batch growth in liquid culture. RW1 is a well-known bacterium capable of mineralizing dibenzodioxins and dibenzofurans. We tested the reactions of the cells both during the immediate transition phase from liquid culture to sand with or without dibenzofuran, as well as during growth and stationary phase in sand. Cells during transition show stationary phase characteristics, evidence for stress and for nutrient scavenging, and adjust their primary metabolism if they were not precultured on the same contaminant as found in the soil. Cells growing and surviving in sand degrade dibenzofuran but display a very different transcriptome signature as in liquid or in liquid culture exposed to chemicals inducing drought stress, and we obtain evidence for numerous 'soil-specific' expressed genes. Studies focusing on inoculation efficacy should test behaviour under conditions as closely as possible mimicking the intended microbiome conditions.

PhylomeDB v4: zooming into the plurality of evolutionary histories of a genome

Phylogenetic trees representing the evolutionary relationships of homologous genes are the entry point for many evolutionary analyses. For instance, the use of a phylogenetic tree can aid in the inference of orthology and paralogy relationships, and in the detection of relevant evolutionary events such as gene family expansions and contractions, horizontal gene transfer, recombination or incomplete lineage sorting. Similarly, given the plurality of evolutionary histories among genes encoded in a given genome, there is a need for the combined analysis of genome-wide collections of phylogenetic trees (phylomes). Here, we introduce a new release of PhylomeDB (http://phylomedb.org), a public repository of phylomes. Currently, PhylomeDB hosts 120 public phylomes, comprising >1.5 million maximum likelihood trees and multiple sequence alignments. In the current release, phylogenetic trees are annotated with taxonomic, protein-domain arrangement, functional and evolutionary information. PhylomeDB is also a major source for phylogeny-based predictions of orthology and paralogy, covering >10 million proteins across 1059 sequenced species. Here we describe newly implemented PhylomeDB features, and discuss a benchmark of the orthology predictions provided by the database, the impact of proteome updates and the use of the phylome approach in the analysis of newly sequenced genomes and transcriptomes.

Meta-analysis and imputation refines the association of 15q25 with smoking quantity.

Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.