A Bayesian Framework to Account for Complex Non-Genetic Factors in Gene Expression Levels Greatly Increases Power in eQTL Studies

Gene expression measurements are influenced by a wide range of factors, such as the state of the cell, experimental conditions and variants in the sequence of regulatory regions. To understand the effect of a variable of interest, such as the genotype of a locus, it is important to account for variation that is due to confounding causes. Here, we present VBQTL, a probabilistic approach for mapping expression quantitative trait loci (eQTLs) that jointly models contributions from genotype as well as known and hidden confounding factors. VBQTL is implemented within an efficient and flexible inference framework, making it fast and tractable on large-scale problems. We compare the performance of VBQTL with alternative methods for dealing with confounding variability on eQTL mapping datasets from simulations, yeast, mouse, and human. Employing Bayesian complexity control and joint modelling is shown to result in more precise estimates of the contribution of different confounding factors resulting in additional associations to measured transcript levels compared to alternative approaches. We present a threefold larger collection of cis eQTLs than previously found in a whole-genome eQTL scan of an outbred human population. Altogether, 27% of the tested probes show a significant genetic association in cis, and we validate that the additional eQTLs are likely to be real by replicating them in different sets of individuals. Our method is the next step in the analysis of high-dimensional phenotype data, and its application has revealed insights into genetic regulation of gene expression by demonstrating more abundant cis-acting eQTLs in human than previously shown. Our software is freely available online at http://www.sanger.ac.uk/resources/software/peer/

A Microhomology-Mediated Break-Induced Replication Model for the Origin of Human Copy Number Variation

Chromosome structural changes with nonrecurrent endpoints associated with genomic disorders offer windows into the mechanism of origin of copy number variation (CNV). A recent report of nonrecurrent duplications associated with Pelizaeus-Merzbacher disease identified three distinctive characteristics. First, the majority of events can be seen to be complex, showing discontinuous duplications mixed with deletions, inverted duplications, and triplications. Second, junctions at endpoints show microhomology of 2–5 base pairs (bp). Third, endpoints occur near pre-existing low copy repeats (LCRs). Using these observations and evidence from DNA repair in other organisms, we derive a model of microhomology-mediated break-induced replication (MMBIR) for the origin of CNV and, ultimately, of LCRs. We propose that breakage of replication forks in stressed cells that are deficient in homologous recombination induces an aberrant repair process with features of break-induced replication (BIR). Under these circumstances, single-strand 3′ tails from broken replication forks will anneal with microhomology on any single-stranded DNA nearby, priming low-processivity polymerization with multiple template switches generating complex rearrangements, and eventual re-establishment of processive replication

Bipolar disorders

Bipolar disorder is characterized by (hypo)manic episodes and depressive episodes which alternate with euthymic periods. It causes serious disability with poor outcome, increased suicidality risk, and significant societal costs. This chapter describes the findings of the PET/SPECT research efforts and the current ideas on the pathophysiology of bipolar disorder. First, the cerebral blood flow and cerebral metabolism findings in the prefrontal cortex, limbic system, subcortical structures, and other brain regions are discussed, followed by an overview of the corticolimbic theory of mood disorders that explains these observations. Second, the neurotransmitter studies are discussed. The serotonin transporter alterations are described, and the variation in study results is explained, followed by an overview of the results of the various dopamine receptor and transporter molecules studies, taking into account also the relation to psychosis. Third, a concise overview is given of dominant bipolar disorder pathophysiological models, proposing starting points for future molecular imaging studies. Finally, the most important conclusions are summarized, followed by remarks about the observed molecular imaging study designs specific for bipolar disorder.</p