Does replication groups scoring reduce false positive rate in SNP interaction discovery?

BACKGROUNG. Computational methods that infer single nucleotide polymorphism (SNP) interactions from phenotype data may uncover new biological mechanisms in non-Mendelian diseases. However, practical aspects of such analysis face many problems. Present experimental studies typically use SNP arrays with hundreds of thousands of SNPs but record only hundreds of samples. Candidate SNP pairs inferred by interaction analysis may include a high proportion of false positives. Recently, Gayan et al. (2008) proposed to reduce the number of false positives by combining results of interaction analysis performed on subsets of data (replication groups), rather than analyzing the entire data set directly. If performing as hypothesized, replication groups scoring could improve interaction analysis and also any type of feature ranking and selection procedure in systems biology. Because Gayan et al. do not compare their approach to the standard interaction analysis techniques, we here investigate if replication groups indeed reduce the number of reported false positive interactions. RESULTS. A set of simulated and false interaction-imputed experimental SNP data sets were used to compare the inference of SNP-SNP interactions by means of replication groups to the standard approach where the entire data set was directly used to score all candidate SNP pairs. In all our experiments, the inference of interactions from the entire data set (e.g. without using the replication groups) reported fewer false positives. CONCLUSIONS. With respect to the direct scoring approach the utility of replication groups does not reduce false positive rates, and may, depending on the data set, often perform worse

Heterogeneous computing architecture for fast detection of SNP-SNP interactions

The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems

Heterogeneous computing architecture for fast detection of SNP-SNP interactions

The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems

Does replication groups scoring reduce false positive rate in SNP interaction discovery?

<p>Abstract</p> <p>Background</p> <p>Computational methods that infer single nucleotide polymorphism (SNP) interactions from phenotype data may uncover new biological mechanisms in non-Mendelian diseases. However, practical aspects of such analysis face many problems. Present experimental studies typically use SNP arrays with hundreds of thousands of SNPs but record only hundreds of samples. Candidate SNP pairs inferred by interaction analysis may include a high proportion of false positives. Recently, Gayan et al. (2008) proposed to reduce the number of false positives by combining results of interaction analysis performed on subsets of data (replication groups), rather than analyzing the entire data set directly. If performing as hypothesized, replication groups scoring could improve interaction analysis and also any type of feature ranking and selection procedure in systems biology. Because Gayan et al. do not compare their approach to the standard interaction analysis techniques, we here investigate if replication groups indeed reduce the number of reported false positive interactions.</p> <p>Results</p> <p>A set of simulated and false interaction-imputed experimental SNP data sets were used to compare the inference of SNP-SNP interactions by means of replication groups to the standard approach where the entire data set was directly used to score all candidate SNP pairs. In all our experiments, the inference of interactions from the entire data set (e.g. without using the replication groups) reported fewer false positives.</p> <p>Conclusions</p> <p>With respect to the direct scoring approach the utility of replication groups does not reduce false positive rates, and may, depending on the data set, often perform worse.</p

Polymorphic members of the lag gene family mediate kin discrimination in Dictyostelium

Self and kin discrimination are observed in most kingdoms of life and are mediated by highly polymorphic plasma membrane proteins. Sequence polymorphism, which is essential for effective recognition, is maintained by balancing selection. Dictyostelium discoideum are social amoebas that propagate as unicellular organisms but aggregate upon starvation and form fruiting bodies with viable spores and dead stalk cells. Aggregative development exposes Dictyostelium to the perils of chimerism, including cheating, which raises questions about how the victims survive in nature and how social cooperation persists. Dictyostelids can minimize the cost of chimerism by preferential cooperation with kin, but the mechanisms of kin discrimination are largely unknown. Dictyostelium lag genes encode transmembrane proteins with multiple immunoglobulin (Ig) repeats that participate in cell adhesion and signaling. Here, we describe their role in kin discrimination. We show that lagB1 and lagC1 are highly polymorphic in natural populations and that their sequence dissimilarity correlates well with wild-strain segregation. Deleting lagB1 and lagC1 results in strain segregation in chimeras with wild-type cells, whereas elimination of the nearly invariant homolog lagD1 has no such consequences. These findings reveal an early evolutionary origin of kin discrimination and provide insight into the mechanism of social recognition and immunity

Yeast Saccharomyces cerevisiae adiponectin receptor homolog Izh2 is involved in the regulation of zinc, phospholipid and pH homeostasis

[EN] The functional link between zinc homeostasis and membrane-related processes, including lipid metabolism regulation, extends from yeast to humans, and has a likely role in the pathogenesis of diabetes. The yeast Izh2 protein has been previously implicated in zinc ion homeostasis and in the regulation of lipid and phosphate metabolism, but its precise molecular function is not known. We performed a chemogenomics experiment to determine the genes conferring resistance or sensitivity to different environmental zinc concentrations. We then determined at normal, depleted and excess zinc concentrations, the genetic interactions of IZH2 at the genome-wide level and measured changes in the transcriptome caused by deletion of IZH2. We found evidence for an important cellular function of the Rim101 pathway in zinc homeostasis in neutral or acidic environments, and observed that phosphatidylinositol is a source of inositol when zinc availability is limited. Comparison of our experimental profiles with published gene expression and genetic interaction profiles revealed pleiotropic functions for Izh2. We propose that Izh2 acts as an integrator of intra- and extracellular signals in providing adequate cellular responses to maintain homeostasis under different external conditions, including but not limited to alterations in zinc concentrations. Guardar / Salir Siguiente >This work was supported by grant P1-0207 from the Slovenian Research Agency. M.M.U. was supported by the Young Investigator fellowship scheme from the Slovenian Research Agency. Work done in the group of L.Y. was funded by grant BFU2011-30197-C03-03 from the Spanish Ministry of Science and Innovation (Madrid, Spain). C.P. was supported by a pre-doctoral fellowship from the Spanish Research Council.Mattiazzi Usaj, M.; Prelec, M.; Brioznic, M.; Primo Planta, C.; Curk, T.; Scancar, J.; Yenush, L.... (2015). Yeast Saccharomyces cerevisiae adiponectin receptor homolog Izh2 is involved in the regulation of zinc, phospholipid and pH homeostasis. Metallomics. 7(9):1338-1351. https://doi.org/10.1039/c5mt00095e133813517

iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution

The unique composition and spatial arrangement of RNA-binding proteins (RBPs) on a transcript guide the diverse aspects of post-transcriptional regulation1. Therefore, an essential step towards understanding transcript regulation at the molecular level is to gain positional information on the binding sites of RBPs2

Tia1 dependent regulation of mRNA subcellular location and translation controls p53 expression in B cells.

Post-transcriptional regulation of cellular mRNA is essential for protein synthesis. Here we describe the importance of mRNA translational repression and mRNA subcellular location for protein expression during B lymphocyte activation and the DNA damage response. Cytoplasmic RNA granules are formed upon cell activation with mitogens, including stress granules that contain the RNA binding protein Tia1. Tia1 binds to a subset of transcripts involved in cell stress, including p53 mRNA, and controls translational silencing and RNA granule localization. DNA damage promotes mRNA relocation and translation in part due to dissociation of Tia1 from its mRNA targets. Upon DNA damage, p53 mRNA is released from stress granules and associates with polyribosomes to increase protein synthesis in a CAP-independent manner. Global analysis of cellular mRNA abundance and translation indicates that this is an extended ATM-dependent mechanism to increase protein expression of key modulators of the DNA damage response.Sequestering mRNA in cytoplasmic stress granules is a mechanism for translational repression. Here the authors find that p53 mRNA, present in stress granules in activated B lymphocytes, is released upon DNA damage and is translated in a CAP-independent manner

dictyBase—a Dictyostelium bioinformatics resource update

dictyBase (http://dictybase.org) is the model organism database for Dictyostelium discoideum. It houses the complete genome sequence, ESTs and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome. This dictyBase update describes the annotations and features implemented since 2006, including improved strain and phenotype representation, integration of predicted transcriptional regulatory elements, protein domain information, biochemical pathways, improved searching and a wiki tool that allows members of the research community to provide annotations

Human Tra2 proteins jointly control a CHEK1 splicing switch among alternative and constitutive target exons

Alternative splicing—the production of multiple messenger RNA isoforms from a single gene—is regulated in part by RNA binding proteins. While the RBPs transformer2 alpha (Tra2α) and Tra2β have both been implicated in the regulation of alternative splicing, their relative contributions to this process are not well understood. Here we find simultaneous—but not individual—depletion of Tra2α and Tra2β induces substantial shifts in splicing of endogenous Tra2β target exons, and that both constitutive and alternative target exons are under dual Tra2α–Tra2β control. Target exons are enriched in genes associated with chromosome biology including CHEK1, which encodes a key DNA damage response protein. Dual Tra2 protein depletion reduces expression of full-length CHK1 protein, results in the accumulation of the DNA damage marker γH2AX and decreased cell viability. We conclude Tra2 proteins jointly control constitutive and alternative splicing patterns via paralog compensation to control pathways essential to the maintenance of cell viability