Practical Issues in Imputation-Based Association Mapping

Imputation-based association methods provide a powerful framework for testing untyped variants for association with phenotypes and for combining results from multiple studies that use different genotyping platforms. Here, we consider several issues that arise when applying these methods in practice, including: (i) factors affecting imputation accuracy, including choice of reference panel; (ii) the effects of imputation accuracy on power to detect associations; (iii) the relative merits of Bayesian and frequentist approaches to testing imputed genotypes for association with phenotype; and (iv) how to quickly and accurately compute Bayes factors for testing imputed SNPs. We find that imputation-based methods can be robust to imputation accuracy and can improve power to detect associations, even when average imputation accuracy is poor. We explain how ranking SNPs for association by a standard likelihood ratio test gives the same results as a Bayesian procedure that uses an unnatural prior assumption—specifically, that difficult-to-impute SNPs tend to have larger effects—and assess the power gained from using a Bayesian approach that does not make this assumption. Within the Bayesian framework, we find that good approximations to a full analysis can be achieved by simply replacing unknown genotypes with a point estimate—their posterior mean. This approximation considerably reduces computational expense compared with published sampling-based approaches, and the methods we present are practical on a genome-wide scale with very modest computational resources (e.g., a single desktop computer). The approximation also facilitates combining information across studies, using only summary data for each SNP. Methods discussed here are implemented in the software package BIMBAM, which is available from http://stephenslab.uchicago.edu/software.html

Cardiosphere-derived cells suppress allogeneic lymphocytes by production of PGE2 acting via the EP4 receptor

derived cells (CDCs) are a cardiac progenitor cell population, which have been shown to possess cardiac regenerative properties and can improve heart function in a variety of cardiac diseases. Studies in large animal models have predominantly focussed on using autologous cells for safety, however allogeneic cell banks would allow for a practical, cost-effective and efficient use in a clinical setting. The aim of this work was to determine the immunomodulatory status of these cells using CDCs and lymphocytes from 5 dogs. CDCs expressed MHC I but not MHC II molecules and in mixed lymphocyte reactions demonstrated a lack of lymphocyte proliferation in response to MHC-mismatched CDCs. Furthermore, MHC-mismatched CDCs suppressed lymphocyte proliferation and activation in response to Concanavalin A. Transwell experiments demonstrated that this was predominantly due to direct cell-cell contact in addition to soluble mediators whereby CDCs produced high levels of PGE2 under inflammatory conditions. This led to down-regulation of CD25 expression on lymphocytes via the EP4 receptor. Blocking prostaglandin synthesis restored both, proliferation and activation (measured via CD25 expression) of stimulated lymphocytes. We demonstrated for the first time in a large animal model that CDCs inhibit proliferation in allo-reactive lymphocytes and have potent immunosuppressive activity mediated via PGE2

A fluidic device for the controlled formation and real-time monitoring of soft membranes self-assembled at liquid interfaces

The work was supported by the European Research Council Starting Grant (STROFUNSCAFF) and the Marie Curie Career Integration Grant (BIOMORPH). L.B. acknowledges fnancial support from the European Community through grant no. 618335 ‘FlowMat: Flow and Capillarity in Materials Science’ and ERC Starting Grant FLEXNANOFLOW no. 715475. Te authors thank Karla E. Inostroza-Brito for the constructive support in this work

Molecular identification of 1-Cys peroxiredoxin and anthocyanidin/flavonol 3-O-galactosyltransferase from proanthocyanidin-rich young fruits of persimmon (Diospyros kaki Thunb.)

Fruits of persimmon (Diospyros kaki Thunb.) accumulate large amounts of proanthocyanidins (PAs) in the early stages of development. Astringent (A)-type fruits remain rich in soluble PAs even after they reach full-mature stage, whereas non-astringent (NA)-type fruits lose these compounds before full maturation. As a first step to elucidate the mechanism of PA accumulation in this non-model species, we used suppression subtractive hybridization to identify transcripts accumulating differently in young fruits of A- and NA-type. Interestingly, only a few clones involved in PA biosynthesis were identified in A–NA libraries. Represented by multiple clones were those encoding a novel 1-Cys peroxiredoxin and a new member of family 1 glycosyltransferases. Quantitative RT-PCR analyses confirmed correlation of the amount of PAs and accumulation of transcripts encoding these proteins in young persimmon fruits. Furthermore, the new family 1 glycosyltransferase was produced in Escherichia coli and shown to efficiently catalyze galactosylation at 3-hydroxyl groups of several anthocyanidins and flavonols. These findings suggest a complex mechanism of PA accumulation in persimmon fruits

Analyses and Comparison of Imputation-Based Association Methods

Genotype imputation methods have become increasingly popular for recovering untyped genotype data. An important application with imputed genotypes is to test genetic association for diseases. Imputation-based association test can provide additional insight beyond what is provided by testing on typed tagging SNPs only. A variety of effective imputation-based association tests have been proposed. However, their performances are affected by a variety of genetic factors, which have not been well studied. In this study, using both simulated and real data sets, we investigated the effects of LD, MAF of untyped causal SNP and imputation accuracy rate on the performances of seven popular imputation-based association methods, including MACH2qtl/dat, SNPTEST, ProbABEL, Beagle, Plink, BIMBAM and SNPMStat. We also aimed to provide a comprehensive comparison among methods. Results show that: 1). imputation-based association tests can boost signals and improve power under medium and high LD levels, with the power improvement increasing with strengthening LD level; 2) the power increases with higher MAF of untyped causal SNPs under medium to high LD level; 3). under low LD level, a high imputation accuracy rate cannot guarantee an improvement of power; 4). among methods, MACH2qtl/dat, ProbABEL and SNPTEST perform similarly and they consistently outperform other methods. Our results are helpful in guiding the choice of imputation-based association test in practical application

Inferring robust gene networks from expression data by a sensitivity-based incremental evolution method

<p>Abstract</p> <p>Background</p> <p>Reconstructing gene regulatory networks (GRNs) from expression data is one of the most important challenges in systems biology research. Many computational models and methods have been proposed to automate the process of network reconstruction. Inferring robust networks with desired behaviours remains challenging, however. This problem is related to network dynamics but has yet to be investigated using network modeling.</p> <p>Results</p> <p>We propose an incremental evolution approach for inferring GRNs that takes network robustness into consideration and can deal with a large number of network parameters. Our approach includes a sensitivity analysis procedure to iteratively select the most influential network parameters, and it uses a swarm intelligence procedure to perform parameter optimization. We have conducted a series of experiments to evaluate the external behaviors and internal robustness of the networks inferred by the proposed approach. The results and analyses have verified the effectiveness of our approach.</p> <p>Conclusions</p> <p>Sensitivity analysis is crucial to identifying the most sensitive parameters that govern the network dynamics. It can further be used to derive constraints for network parameters in the network reconstruction process. The experimental results show that the proposed approach can successfully infer robust GRNs with desired system behaviors.</p

Caffeine Reduces 11β-Hydroxysteroid Dehydrogenase Type 2 Expression in Human Trophoblast Cells through the Adenosine A2B Receptor

Maternal caffeine consumption is associated with reduced fetal growth, but the underlying molecular mechanisms are unknown. Since there is evidence that decreased placental 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2) is linked to fetal growth restriction, we hypothesized that caffeine may inhibit fetal growth partly through down regulating placental 11β-HSD2. As a first step in examining this hypothesis, we studied the effects of caffeine on placental 11β-HSD2 activity and expression using our established primary human trophoblast cells as an in vitro model system. Given that maternal serum concentrations of paraxanthine (the primary metabolite of caffeine) were greater in women who gave birth to small-for-gestational age infants than to appropriately grown infants, we also studied the effects of paraxanthine. Our main findings were: (1) both caffeine and paraxanthine decreased placental 11β-HSD2 activity, protein and mRNA in a concentration-dependent manner; (2) this inhibitory effect was mediated by the adenosine A2B receptor, since siRNA-mediated knockdown of this receptor prevented caffeine- and paraxanthine-induced inhibition of placental 11β-HSD2; and (3) forskolin (an activator of adenyl cyclase and a known stimulator of 11β-HSD2) abrogated the inhibitory effects of both caffeine and paraxanthine, which provides evidence for a functional link between exposure to caffeine and paraxanthine, decreased intracellular levels of cAMP and reduced placental 11β-HSD2. Taken together, these findings reveal that placental 11β-HSD2 is a novel molecular target through which caffeine may adversely affect fetal growth. They also uncover a previously unappreciated role for the adenosine A2B receptor signaling in regulating placental 11β-HSD2, and consequently fetal development

The EHEC Type III Effector NleL Is an E3 Ubiquitin Ligase That Modulates Pedestal Formation

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 causes hemorrhagic colitis and may result in potentially fatal hemolytic uremia syndrome in humans. EHEC colonize the intestinal mucosa and promote the formation of actin-rich pedestals via translocated type III effectors. Two EHEC type III secreted effectors, Tir and EspFu/TccP, are key players for pedestal formation. We discovered that an EHEC effector protein called Non-LEE-encoded Ligase (NleL) is an E3 ubiquitin ligase. In vitro, we showed that the NleL C753 residue is critical for its E3 ligase activity. Functionally, we demonstrated that NleL E3 ubiquitin ligase activity is involved in modulating Tir-mediated pedestal formation. Surprisingly, EHEC mutant strain deficient in the E3 ligase activity induced more pedestals than the wild-type strain. The canonical EPEC strain E2348/69 normally lacks the nleL gene, and the ectopic expression of the wild-type EHEC nleL, but not the catalytically-deficient nleL(C753A) mutant, in this strain resulted in fewer actin-rich pedestals. Furthermore, we showed that the C. rodentium NleL homolog is a E3 ubiquitin ligase and is required for efficient infection of murine colonic epithelial cells in vivo. In summary, our study demonstrated that EHEC utilizes NleL E3 ubiquitin ligase activity to modulate Tir-mediated pedestal formation.National Institutes of Health (U.S.) (grant AI078092)National Institutes of Health (U.S.) (grant AI068655

Single Molecule Analysis of Replicated DNA Reveals the Usage of Multiple KSHV Genome Regions for Latent Replication

Kaposi's sarcoma associated herpesvirus (KSHV), an etiologic agent of Kaposi's sarcoma, Body Cavity Based Lymphoma and Multicentric Castleman's Disease, establishes lifelong latency in infected cells. The KSHV genome tethers to the host chromosome with the help of a latency associated nuclear antigen (LANA). Additionally, LANA supports replication of the latent origins within the terminal repeats by recruiting cellular factors. Our previous studies identified and characterized another latent origin, which supported the replication of plasmids ex-vivo without LANA expression in trans. Therefore identification of an additional origin site prompted us to analyze the entire KSHV genome for replication initiation sites using single molecule analysis of replicated DNA (SMARD). Our results showed that replication of DNA can initiate throughout the KSHV genome and the usage of these regions is not conserved in two different KSHV strains investigated. SMARD also showed that the utilization of multiple replication initiation sites occurs across large regions of the genome rather than a specified sequence. The replication origin of the terminal repeats showed only a slight preference for their usage indicating that LANA dependent origin at the terminal repeats (TR) plays only a limited role in genome duplication. Furthermore, we performed chromatin immunoprecipitation for ORC2 and MCM3, which are part of the pre-replication initiation complex to determine the genomic sites where these proteins accumulate, to provide further characterization of potential replication initiation sites on the KSHV genome. The ChIP data confirmed accumulation of these pre-RC proteins at multiple genomic sites in a cell cycle dependent manner. Our data also show that both the frequency and the sites of replication initiation vary within the two KSHV genomes studied here, suggesting that initiation of replication is likely to be affected by the genomic context rather than the DNA sequences