A comparison of cataloged variation between International HapMap Consortium and 1000 Genomes Project data.

BACKGROUND: Since publication of the human genome in 2003, geneticists have been interested in risk variant associations to resolve the etiology of traits and complex diseases. The International HapMap Consortium undertook an effort to catalog all common variation across the genome (variants with a minor allele frequency (MAF) of at least 5% in one or more ethnic groups). HapMap along with advances in genotyping technology led to genome-wide association studies which have identified common variants associated with many traits and diseases. In 2008 the 1000 Genomes Project aimed to sequence 2500 individuals and identify rare variants and 99% of variants with a MAF of <1%. METHODS: To determine whether the 1000 Genomes Project includes all the variants in HapMap, we examined the overlap between single nucleotide polymorphisms (SNPs) genotyped in the two resources using merged phase II/III HapMap data and low coverage pilot data from 1000 Genomes. RESULTS: Comparison of the two data sets showed that approximately 72% of HapMap SNPs were also found in 1000 Genomes Project pilot data. After filtering out HapMap variants with a MAF of <5% (separately for each population), 99% of HapMap SNPs were found in 1000 Genomes data. CONCLUSIONS: Not all variants cataloged in HapMap are also cataloged in 1000 Genomes. This could affect decisions about which resource to use for SNP queries, rare variant validation, or imputation. Both the HapMap and 1000 Genomes Project databases are useful resources for human genetics, but it is important to understand the assumptions made and filtering strategies employed by these projects.

Initialization Parameter Sweep in ATHENA: Optimizing Neural Networks for Detecting Gene-Gene Interactions in the Presence of Small Main Effects.

Recent advances in genotyping technology have led to the generation of an enormous quantity of genetic data. Traditional methods of statistical analysis have proved insufficient in extracting all of the information about the genetic components of common, complex human diseases. A contributing factor to the problem of analysis is that amongst the small main effects of each single gene on disease susceptibility, there are non-linear, gene-gene interactions that can be difficult for traditional, parametric analyses to detect. In addition, exhaustively searching all multi-locus combinations has proved computationally impractical. Novel strategies for analysis have been developed to address these issues. The Analysis Tool for Heritable and Environmental Network Associations (ATHENA) is an analytical tool that incorporates grammatical evolution neural networks (GENN) to detect interactions among genetic factors. Initial parameters define how the evolutionary process will be implemented. This research addresses how different parameter settings affect detection of disease models involving interactions. In the current study, we iterate over multiple parameter values to determine which combinations appear optimal for detecting interactions in simulated data for multiple genetic models. Our results indicate that the factors that have the greatest influence on detection are: input variable encoding, population size, and parallel computation.

cGMP-dependent protein kinase Ialpha associates with the antidepressant-sensitive serotonin transporter and dictates rapid modulation of serotonin uptake.

BACKGROUND: The Na(+)/Cl(-)-dependent serotonin (5-hydroxytryptamine, 5-HT) transporter (SERT) is a critical element in neuronal 5-HT signaling, being responsible for the efficient elimination of 5-HT after release. SERTs are not only targets for exogenous addictive and therapeutic agents but also can be modulated by endogenous, receptor-linked signaling pathways. We have shown that neuronal A3 adenosine receptor activation leads to enhanced presynaptic 5-HT transport in vitro and an increased rate of SERT-mediated 5-HT clearance in vivo. SERT stimulation by A3 adenosine receptors derives from an elevation of cGMP and subsequent activation of both cGMP-dependent protein kinase (PKG) and p38 mitogen-activated protein kinase. PKG activators such as 8-Br-cGMP are known to lead to transporter phosphorylation, though how this modification supports SERT regulation is unclear. RESULTS: In this report, we explore the kinase isoform specificity underlying the rapid stimulation of SERT activity by PKG activators. Using immortalized, rat serotonergic raphe neurons (RN46A) previously shown to support 8-Br-cGMP stimulation of SERT surface trafficking, we document expression of PKGI, and to a lower extent, PKGII. Quantitative analysis of staining profiles using permeabilized or nonpermeabilized conditions reveals that SERT colocalizes with PKGI in both intracellular and cell surface domains of RN46A cell bodies, and exhibits a more restricted, intracellular pattern of colocalization in neuritic processes. In the same cells, SERT demonstrates a lack of colocalization with PKGII in either intracellular or surface membranes. In keeping with the ability of the membrane permeant kinase inhibitor DT-2 to block 8-Br-cGMP stimulation of SERT, we found that DT-2 treatment eliminated cGMP-dependent kinase activity in PKGI-immunoreactive extracts resolved by liquid chromatography. Similarly, treatment of SERT-transfected HeLa cells with small interfering RNAs targeting endogenous PKGI eliminated 8-Br-cGMP-induced regulation of SERT activity. Co-immunoprecipitation studies show that, in transporter/kinase co-transfected cells, PKGIalpha specifically associates with hSERT. CONCLUSION: Our findings provide evidence of a physical and compartmentalized association between SERT and PKGIalpha that supports rapid, 8-Br-cGMP-induced regulation of SERT. We discuss a model wherein SERT-associated PKGIalpha supports sequentially the mobilization of intracellular transporter-containing vesicles, leading to enhanced surface expression, and the production of catalytic-modulatory SERT phosphorylation, leading to a maximal enhancement of 5-HT clearance capacity.