148 research outputs found

    YunJung Lee, Organ

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    Toccata and Fugue in f Major, BWV 540 / Johann Sebastian Bach; Fantasia settima sopra tre soggetti , from Il primo libro delle 12 Fantasie; Canzon sesta detta La Pesenti , from Canzoni alla fracese in partitura / Girolamo Alessandro Frescobaldi; Chorale in B minor, M 39 / César Franck; Prelude et fugue sur le nom d\u27Alain, Op. 7 / Maurice Durufl

    YunJung Lee, Organ

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    Präludium und Fuge in C, BWV 531 / Johann Sebastian Bach; Suite du Premier Ton / Louis Nicolas Clérambault; From Eleven Chorale Preludes for organ, Op. 122 / Johannes Brahms; Introduktion und Passacaglia f-Moll, Op. 63 / Max Rege

    Consumer Motivations to Search E-Health Information

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    Phospholipase A2β mediates light-induced stomatal opening in Arabidopsis

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    Phospholipase A2 (PLA2) catalyses the hydrolysis of phospholipids into lysophospholipids and free fatty acids. Physiological studies have indicated that PLA2 is involved in stomatal movement. However, genetic evidence of a role of PLA2 in guard cell signalling has not yet been reported. To identify PLA2 gene(s) that is (are) involved in light-induced stomatal opening, stomatal movement was examined in Arabidopsis thaliana plants in which the expression of PLA2 isoforms was reduced or knocked-out. Light-induced stomatal opening in PLA2α knockout plants did not differ from wild-type plants. Plants in which PLA2β was silenced by RNA interference exhibited delayed light-induced stomatal opening, and this phenotype was reversed by exogenous lysophospholipids, which are products of PLA2. Stomatal opening in transgenic plants that over-expressed PLA2β was faster than wild-type plants. The expression of PLA2β was localized to the endoplasmic reticulum of guard cells, and increased in response to light in the mature leaf. Aristolochic acid, which inhibits light-induced stomatal opening, inhibited the activity of purified PLA2β. Collectively, these results provide evidence that PLA2β is involved in light-induced stomatal opening in Arabidopsis

    Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

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    Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination

    No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study

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    It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest

    Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

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    Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression
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