Deletion of TOP3β, a component of FMRP-containing mRNPs, contributes to neurodevelopmental disorders

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Abstract

Implicating particular genes in the generation of complex brain and behavior phenotypes requires multiple lines of evidence. The rarity of most high-impact genetic variants typically precludes the possibility of accruing statistical evidence that they are associated with a given trait. We found that the enrichment of a rare chromosome 22q11.22 deletion in a recently expanded Northern Finnish sub-isolate enabled the detection of association between TOP3B and both schizophrenia and cognitive impairment. Biochemical analysis of TOP3β revealed that this topoisomerase was a component of cytosolic messenger ribonucleoproteins (mRNPs) and was catalytically active on RNA. The recruitment of TOP3β to mRNPs was independent of RNA cis-elements and was coupled to the co-recruitment of FMRP, the disease gene product in fragile X mental retardation syndrome. Our results indicate a previously unknown role for TOP3β in mRNA metabolism and suggest that it is involved in neurodevelopmental disorders.

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Large recurrent microdeletions associated with schizophrenia.

Hreinn Stefansson, Dan Rujescu, Sven Cichon … (2008)

Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.

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RNA and disease.

Thomas Cooper, Lili Wan, Gideon Dreyfuss (2009)

Cellular functions depend on numerous protein-coding and noncoding RNAs and the RNA-binding proteins associated with them, which form ribonucleoprotein complexes (RNPs). Mutations that disrupt either the RNA or protein components of RNPs or the factors required for their assembly can be deleterious. Alternative splicing provides cells with an exquisite capacity to fine-tune their transcriptome and proteome in response to cues. Splicing depends on a complex code, numerous RNA-binding proteins, and an enormously intricate network of interactions among them, increasing the opportunity for exposure to mutations and misregulation that cause disease. The discovery of disease-causing mutations in RNAs is yielding a wealth of new therapeutic targets, and the growing understanding of RNA biology and chemistry is providing new RNA-based tools for developing therapeutics.

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QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data

Stefano Colella, Christopher Yau, Jennifer Taylor … (2007)

Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray™ SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. Other parameters are set via maximum marginal likelihood to prior training data of known structure. QuantiSNP provides probabilistic quantification of state classifications and significantly improves the accuracy of segmental aneuploidy identification and mapping, relative to existing analytical tools (Beadstudio, Illumina), as demonstrated by validation of breakpoint boundaries. QuantiSNP identified both novel and validated CNVs. QuantiSNP was developed using BeadArray™ SNP data but it can be adapted to other platforms and we believe that the OB-HMM framework has widespread applicability in genomic research. In conclusion, QuantiSNP is a novel algorithm for high-resolution CNV/aneuploidy detection with application to clinical genetics, cancer and disease association studies.