Obsessive-compulsive disorder (OCD) is a common, debilitating neuropsychiatric illness with complex genetic etiology. The International OCD Foundation Genetics Collaborative (IOCDF-GC) is a multi-national collaboration established to discover the genetic variation predisposing to OCD. A set of individuals affected with DSM-IV OCD, a subset of their parents, and unselected controls, were genotyped with several different Illumina SNP microarrays. After extensive data cleaning, 1465 cases, 5557 ancestry-matched controls and 400 complete trios remained, with a common set of 469 410 autosomal and 9657 X-chromosome single nucleotide polymorphisms (SNPs). Ancestry-stratified case–control association analyses were conducted for three genetically-defined subpopulations and combined in two meta-analyses, with and without the trio-based analysis. In the case–control analysis, the lowest two P-values were located within DLGAP1 (P=2.49 × 10⁻⁶ and P=3.44 × 10⁻⁶), a member of the neuronal postsynaptic density complex. In the trio analysis, rs6131295, near BTBD3, exceeded the genome-wide significance threshold with a P-value=3.84 × 10⁻⁸. However, when trios were meta-analyzed with the case–control samples, the P-value for this variant was 3.62 × 10⁻⁵, losing genome-wide significance. Although no SNPs were identified to be associated with OCD at a genome-wide significant level in the combined trio–case–control sample, a significant enrichment of methylation QTLs (P<0.001) and frontal lobe expression quantitative trait loci (eQTLs) (P=0.001) was observed within the top-ranked SNPs (P<0.01) from the trio–case–control analysis, suggesting these top signals may have a broad role in gene expression in the brain, and possibly in the etiology of OCD.

In mammals, oocyte activation at fertilization is thought to be induced by the sperm-specific phospholipase C zeta (PLCζ). However, it still remains to be conclusively shown that PLCζ is the endogenous agent of oocyte activation. Some types of human infertility appear to be caused by failure of the sperm to activate and this may be due to specific defects in PLCζ. Immunofluorescence studies showed PLCζ to be localized in the equatorial region of sperm from fertile men, but sperm deficient in oocyte activation exhibited no specific signal in this same region. Immunoblot analysis revealed reduced amounts of PLCζ in sperm from infertile men, and in some cases, the presence of an abnormally low molecular weight form of PLCζ. In one non-globozoospermic case, DNA analysis identified a point mutation in the PLCζ gene that leads to a significant amino acid change in the catalytic region of the protein. Structural modelling suggested that this defect may have important effects upon the structure and function of the PLCζ protein. cRNA corresponding to mutant PLCζ failed to induce calcium oscillations when microinjected into mouse oocytes. Injection of infertile human sperm into mouse oocytes failed to activate the oocyte or trigger calcium oscillations. Injection of such infertile sperm followed by two calcium pulses, induced by assisted oocyte activation, activated the oocytes without inducing the typical pattern of calcium oscillations. Our findings illustrate the importance of PLCζ during fertilization and suggest that mutant forms of PLCζ may underlie certain types of human male infertility.

• Biosynthesis of the sesquiterpene lactone and potent antimalarial drug artemisinin occurs in glandular trichomes of Artemisia annua plants and is subjected to a strict network of developmental and other regulatory cues. • The effects of three hormones, jasmonate, gibberellin and cytokinin, were studied at the structural and molecular levels in two different A. annua chemotypes by microscopic analysis of gland development, and by targeted metabolite and transcript profiling. Furthermore, a genome-wide cDNA-amplified fragment length polymorphism (AFLP)-based transcriptome profiling was carried out of jasmonate-elicited leaves at different developmental stages. • Although cytokinin and gibberellin positively affected at least one aspect of gland formation, these two hormones did not stimulate artemisinin biosynthesis. Only jasmonate simultaneously promoted gland formation and coordinated transcriptional activation of biosynthetic gene expression, which ultimately led to increased sesquiterpenoid accumulation with chemotype-dependent effects on the distinct pathway branches. Transcriptome profiling revealed a trichome-specific fatty acyl- coenzyme A reductase, trichome-specific fatty acyl-CoA reductase 1 (TFAR1), the expression of which correlates with trichome development and sesquiterpenoid biosynthesis. • TFAR1 is potentially involved in cuticular wax formation during glandular trichome expansion in leaves and flowers of A. annua plants. Analysis of phytohormone-modulated transcriptional regulons provides clues to dissect the concerted regulation of metabolism and development of plant trichomes.

Background: Candida albicans biofilms are commonly found on indwelling medical devices. However, the molecular basis of biofilm formation and development is not completely understood. Expression analysis of genes potentially involved in these processes, such as the ALS (Agglutinine Like Sequence) gene family can be performed using quantitative PCR (qPCR). In the present study, we investigated the expression stability of eight housekeeping genes potentially useful as reference genes to study gene expression in Candida albicans (C. albicans) biofilms, using the geNorm Visual Basic Application (VBA) for Microsoft Excel. To validate our normalization strategies we determined differences in ALS1 and ALS3 expression levels between C. albicans biofilm cells and their planktonic counterparts. Results: The eight genes tested in this study are ranked according to their expression stability (from most stable to least stable) as follows: ACT1 (β-actin)/PMA1 (adenosine triphosphatase), RIP (ubiquinol cytochrome-c reductase complex component), RPP2B (cytosolic ribosomal acidic protein P2B), LSC2 (succinyl-CoA synthetase β-subunit fragment), IMH3 (inosine-5'-monophosphate dehydrogenase fragment), CPA1 (carbamoyl-phosphate synthethase small subunit) and GAPDH (glyceraldehyde-3-phosphate dehydrogenase). Our data indicate that five genes are necessary for accurate and reliable normalization of gene expression data in C. albicans biofilms. Using different normalization strategies, we found a significant upregulation of the ALS1 gene and downregulation of the ALS3 gene in C. albicans biofilms grown on silicone disks in a continous flow system, the CDC reactor (Centre for Disease Control), for 24 hours. Conclusion: In conclusion, we recommend the use of the geometric mean of the relative expression values from the five housekeeping genes (ACT1, PMA1, RIP, RPP2B and LSC2) for normalization, when analysing differences in gene expression levels between C. albicans biofilm cells and planktonic cells. Validation of the normalization strategies described above showed that the ALS1 gene is overexpressed and the ALS3 gene is underexpressed in C. albicans biofilms grown on silicone in the CDC reactor for 24 hours.

Background: Candida albicans infections are often associated with biofilm formation. Previous work demonstrated that the expression of HWP1 (hyphal wall protein) and of genes belonging to the ALS (agglutinin-like sequence), SAP (secreted aspartyl protease), PLB (phospholipase B) and LIP (lipase) gene families is associated with biofilm growth on mucosal surfaces. We investigated using real-time PCR whether genes encoding potential virulence factors are also highly expressed in biofilms associated with abiotic surfaces. For this, C. albicans biofilms were grown on silicone in microtiter plates (MTP) or in the Centres for Disease Control (CDC) reactor, on polyurethane in an in vivo subcutaneous catheter rat (SCR) model, and on mucosal surfaces in the reconstituted human epithelium (RHE) model. Results: HWP1 and genes belonging to the ALS, SAP, PLB and LIP gene families were constitutively expressed in C. albicans biofilms. ALS1-5 were upregulated in all model systems, while ALS9 was mostly downregulated. ALS6 and HWP1 were overexpressed in all models except in the RHE and MTP, respectively. The expression levels of SAP1 were more pronounced in both in vitro models, while those of SAP2, SAP4 and SAP6 were higher in the in vivo model. Furthermore, SAP5 was highly upregulated in the in vivo and RHE models. For SAP9 and SAP10 similar gene expression levels were observed in all model systems. PLB genes were not considerably upregulated in biofilms, while LIP1-3, LIP5-7 and LIP9-10 were highly overexpressed in both in vitro models. Furthermore, an elevated lipase activity was detected in supernatans of biofilms grown in the MTP and RHE model. Conclusions: Our findings show that HWP1 and most of the genes belonging to the ALS, SAP and LIP gene families are upregulated in C. albicans biofilms. Comparison of the fold expression between the various model systems revealed similar expression levels for some genes, while for others model-dependent expression levels were observed. This suggests that data obtained in one biofilm model cannot be extrapolated to other model systems. Therefore, the need to use multiple model systems when studying the expression of genes encoding potential virulence factors in C. albicans biofilms is highlighted.

Transcriptome analysis through next-generation sequencing technologies allows the generation of detailed gene catalogs for non-model species, at the cost of new challenges with regards to computational requirements and bioinformatics expertise. Here, we present TRAPID, an online tool for the fast and efficient processing of assembled RNA-Seq transcriptome data, developed to mitigate these challenges. TRAPID offers high-throughput open reading frame detection, frameshift correction and includes a functional, comparative and phylogenetic toolbox, making use of 175 reference proteomes. Benchmarking and comparison against state-of-the-art transcript analysis tools reveals the efficiency and unique features of the TRAPID system. TRAPID is freely available at http://bioinformatics.psb.ugent.be/webtools/trapid/.