FCGR3B copy number variation is associated with systemic lupus erythematosus risk in Afro-Caribbeans.

OBJECTIVES: To evaluate FCGR3B copy number variation (CNV) in African and European populations and to determine if FCGR3B copy number is associated with SLE and SLE nephritis risk in Afro-Caribbeans, adjusting for African genetic ancestry. METHODS: We estimated FCGR3B to determine if there were ethnic variations in CNV (unrelated unadmixed Europeans and Africans). We then examined CNV at FCGR3B in relation to SLE and SLE nephritis within a case-control collection of 134 cases of SLE (37 with SLE nephritis) and 589 population controls of mainly Afro-Caribbean descent resident in Trinidad. RESULTS: We found a significant difference in copy number FCGR3B distribution between unadmixed African and European UK cohorts, with 27 (29%) vs 3 (5%) for those with low (0 or 1) copy FCGR3B, respectively, P = 0.002. In a Trinidadian SLE case-control study, low FCGR3B CNV was associated with SLE risk 1.7 (95% CI 1.1, 2.8), P = 0.02, which remained after adjustment for African genetic ancestry; odds ratios (ORs) 1.7 (95% CI 1.0, 2.8), P = 0.04. CONCLUSION: Our studies suggest that FCGR3B low copy number is associated with SLE risk in Afro-Caribbean populations independently of CNV due to African ancestry

Switching quantum transport in a three donors silicon fin-field effect transistor

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Rare and common epilepsies converge on a shared gene regulatory network providing opportunities for novel antiepileptic drug discovery

Background The relationship between monogenic and polygenic forms of epilepsy is poorly understood, and the extent to which the genetic and acquired epilepsies share common pathways is unclear. Here, we use an integrated systems-level analysis of brain gene expression data to identify molecular networks disrupted in epilepsy. Results We identify a co-expression network of 320 genes (M30), which is significantly enriched for non-synonymous de novo mutations ascertained from patients with monogenic epilepsy, and for common variants associated with polygenic epilepsy. The genes in M30 network are expressed widely in the human brain under tight developmental control, and encode physically interacting proteins involved in synaptic processes. The most highly connected proteins within M30 network are preferentially disrupted by deleterious de novo mutations for monogenic epilepsy, in line with the centrality-lethality hypothesis. Analysis of M30 expression revealed consistent down-regulation in the epileptic brain in heterogeneous forms of epilepsy including human temporal lobe epilepsy, a mouse model of acquired temporal lobe epilepsy, and a mouse model of monogenic Dravet (SCN1A) disease. These results suggest functional disruption of M30 via gene mutation or altered expression as a convergent mechanism regulating susceptibility to epilepsy broadly. Using the large collection of drug-induced gene expression data from Connectivity Map, several drugs were predicted to preferentially restore the down-regulation of M30 in epilepsy toward health, most notably valproic acid, whose effect on M30 expression was replicated in neurons. Conclusions Taken together, our results suggest targeting the expression of M30 as a potential new therapeutic strategy in epilepsy

Genetic Influences on Brain Gene Expression in Rats Selected for Tameness and Aggression

Inter-individual differences in many behaviors are partly due to genetic differences, but the identification of the genes and variants that influence behavior remains challenging. Here, we studied an F2 intercross of two outbred lines of rats selected for tame and aggressive behavior towards humans for more than 64 generations. By using a mapping approach that is able to identify genetic loci segregating within the lines, we identified four times more loci influencing tameness and aggression than by an approach that assumes fixation of causative alleles, suggesting that many causative loci were not driven to fixation by the selection. We used RNA sequencing in 150 F2 animals to identify hundreds of loci that influence brain gene expression. Several of these loci colocalize with tameness loci and may reflect the same genetic variants. Through analyses of correlations between allele effects on behavior and gene expression, differential expression between the tame and aggressive rat selection lines, and correlations between gene expression and tameness in F2 animals, we identify the genes Gltscr2, Lgi4, Zfp40 and Slc17a7 as candidate contributors to the strikingly different behavior of the tame and aggressive animals

JunD/AP1 regulatory network analysis during macrophage activation in a rat model of crescentic glomerulonephritis

Background: Function and efficiency of a transcription factor (TF) are often modulated by interactions with other proteins or TFs to achieve finely tuned regulation of target genes. However, complex TF interactions are often not taken into account to identify functionally active TF-targets and characterize their regulatory network. Here, we have developed a computational framework for integrated analysis of genome-wide ChIP-seq and gene expression data to identify the functional interacting partners of a TF and characterize the TF-driven regulatory network. We have applied this methodology in a rat model of macrophage dependent crescentic glomerulonephritis (Crgn) where we have previously identified JunD as a TF gene responsible for enhanced macrophage activation associated with susceptibility to Crgn in the Wistar-Kyoto (WKY) strain. Results: To evaluate the regulatory effects of JunD on its target genes, we analysed data from two rat strains (WKY and WKY.LCrgn2) that show 20-fold difference in their JunD expression in macrophages. We identified 36 TFs interacting with JunD/Jun and JunD/ATF complexes (i.e., AP1 complex), which resulted in strain-dependent gene expression regulation of 1,274 target genes in macrophages. After lipopolysaccharide (LPS) stimulation we found that 2.4 fold more JunD/ATF-target genes were up-regulated as compared with JunD/Jun-target genes. The enriched 314 genes up-regulated by AP1 complex during LPS stimulation were most significantly enriched for immune response (P = 6.9 × 10-4) and antigen processing and presentation functions (P = 2.4 × 10-5), suggesting a role for these genes in macrophage LPS-stimulated activation driven by JunD interaction with Jun/ATF. Conclusions: In summary, our integrated analyses revealed a large network of TFs interacting with JunD and their regulated targets. Our data also suggest a previously unappreciated contribution of the ATF complex to JunD-mediated mechanisms of macrophage activation in a rat model of crescentic glomerulonephritis

MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues.

MOTIVATION: Analysing the joint association between a large set of responses and predictors is a fundamental statistical task in integrative genomics, exemplified by numerous expression Quantitative Trait Loci (eQTL) studies. Of particular interest are the so-called ': hotspots ': , important genetic variants that regulate the expression of many genes. Recently, attention has focussed on whether eQTLs are common to several tissues, cell-types or, more generally, conditions or whether they are specific to a particular condition. RESULTS: We have implemented MT-HESS, a Bayesian hierarchical model that analyses the association between a large set of predictors, e.g. SNPs, and many responses, e.g. gene expression, in multiple tissues, cells or conditions. Our Bayesian sparse regression algorithm goes beyond ': one-at-a-time ': association tests between SNPs and responses and uses a fully multivariate model search across all linear combinations of SNPs, coupled with a model of the correlation between condition/tissue-specific responses. In addition, we use a hierarchical structure to leverage shared information across different genes, thus improving the detection of hotspots. We show the increase of power resulting from our new approach in an extensive simulation study. Our analysis of two case studies highlights new hotspots that would remain undetected by standard approaches and shows how greater prediction power can be achieved when several tissues are jointly considered. AVAILABILITY AND IMPLEMENTATION: C[Formula: see text] source code and documentation including compilation instructions are available under GNU licence at http://www.mrc-bsu.cam.ac.uk/software/

MicroRNA profiles in hippocampal granule cells and plasma of rats with pilocarpine-induced epilepsy - Comparison with human epileptic samples

The identification of biomarkers of the transformation of normal to epileptic tissue would help to stratify patients at risk of epilepsy following brain injury, and inform new treatment strategies. MicroRNAs (miRNAs) are an attractive option in this direction. In this study, miRNA microarrays were performed on laser-microdissected hippocampal granule cell layer (GCL) and on plasma, at different time points in the development of pilocarpine-induced epilepsy in the rat: latency, first spontaneous seizure and chronic epileptic phase. Sixty-three miRNAs were differentially expressed in the GCL when considering all time points. Three main clusters were identified that separated the control and chronic phase groups from the latency group and from the first spontaneous seizure group. MiRNAs from rats in the chronic phase were compared to those obtained from the laser-microdissected GCL of epileptic patients, identifying several miRNAs (miR-21-5p, miR-23a-5p, miR-146a-5p and miR- 181c-5p) that were up-regulated in both human and rat epileptic tissue. Analysis of plasma samples revealed different levels between control and pilocarpine-treated animals for 27 miRNAs. Two main clusters were identified that segregated controls from all other groups. Those miRNAs that are altered in plasma before the first spontaneous seizure, like miR-9a-3p, may be proposed as putative biomarkers of epileptogenesis

Heritability and Tissue Specificity of Expression Quantitative Trait Loci

Variation in gene expression is heritable and has been mapped to the genome in humans and model organisms as expression quantitative trait loci (eQTLs). We applied integrated genome-wide expression profiling and linkage analysis to the regulation of gene expression in fat, kidney, adrenal, and heart tissues using the BXH/HXB panel of rat recombinant inbred strains. Here, we report the influence of heritability and allelic effect of the quantitative trait locus on detection of cis- and trans-acting eQTLs and discuss how these factors operate in a tissue-specific context. We identified several hundred major eQTLs in each tissue and found that cis-acting eQTLs are highly heritable and easier to detect than trans-eQTLs. The proportion of heritable expression traits was similar in all tissues; however, heritability alone was not a reliable predictor of whether an eQTL will be detected. We empirically show how the use of heritability as a filter reduces the ability to discover trans-eQTLs, particularly for eQTLs with small effects. Only 3% of cis- and trans-eQTLs exhibited large allelic effects, explaining more than 40% of the phenotypic variance, suggestive of a highly polygenic control of gene expression. Power calculations indicated that, across tissues, minor differences in genetic effects are expected to have a significant impact on detection of trans-eQTLs. Trans-eQTLs generally show smaller effects than cis-eQTLs and have a higher false discovery rate, particularly in more heterogeneous tissues, suggesting that small biological variability, likely relating to tissue composition, may influence detection of trans-eQTLs in this system. We delineate the effects of genetic architecture on variation in gene expression and show the sensitivity of this experimental design to tissue sampling variability in large-scale eQTL studies

Wnt-regulated lncRNA discovery enhanced by in vivo identification and CRISPRi functional validation

Background Wnt signaling is an evolutionarily conserved developmental pathway that is frequently hyperactivated in cancer. While multiple protein-coding genes regulated by Wnt signaling are known, the functional lncRNAs regulated by Wnt signaling have not been systematically characterized. Results We comprehensively mapped lncRNAs from an orthotopic Wnt-addicted pancreatic cancer model, identifying 3,633 lncRNAs, of which 1,503 were regulated by Wnt signaling. We found lncRNAs were much more sensitive to changes in Wnt signaling in xenografts than in cultured cells. To functionally validate Wnt-regulated lncRNAs, we performed CRISPRi screens to assess their role in cancer cell proliferation. Consistent with previous genome-wide lncRNA CRISPRi screens, around 1% (13/1,503) of the Wnt-regulated lncRNAs could modify cancer cell growth in vitro. This included CCAT1 and LINC00263, previously reported to regulate cancer growth. Using an in vivo CRISPRi screen, we doubled the discovery rate, identifying twice as many Wnt-regulated lncRNAs (25/1,503) that had a functional effect on cancer cell growth. Conclusions Our study demonstrates the value of studying lncRNA functions in vivo, provides a valuable resource of lncRNAs regulated by Wnt signaling and establishes a framework for systematic discovery of functional lncRNAs