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1.
Mol Psychiatry ; 13(3): 302-12, 2008 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-17667963

RESUMO

We describe a multistage approach to identify single nucleotide polymorphisms (SNPs) associated with neuroticism, a personality trait that shares genetic determinants with major depression and anxiety disorders. Whole genome association with 452 574 SNPs was performed on DNA pools from approximately 2000 individuals selected on extremes of neuroticism scores from a cohort of 88 142 people from southwest England. The most significant SNPs were then genotyped on independent samples to replicate findings. We were able to replicate association of one SNP within the PDE4D gene in a second sample collected by our laboratory and in a family-based test in an independent sample; however, the SNP was not significantly associated with neuroticism in two other independent samples. We also observed an enrichment of low P-values in known regions of copy number variations. Simulation indicates that our study had approximately 80% power to identify neuroticism loci in the genome with odds ratio (OR)>2, and approximately 50% power to identify small effects (OR=1.5). Since we failed to find any loci accounting for more than 1% of the variance, the heritability of neuroticism probably arises from many loci each explaining much less than 1%. Our findings argue the need for much larger samples than anticipated in genetic association studies and that the biological basis of emotional disorders is extremely complex.


Assuntos
Genoma/fisiologia , Transtornos Neuróticos/genética , Polimorfismo de Nucleotídeo Único , Estudos de Coortes , Simulação por Computador , Nucleotídeo Cíclico Fosfodiesterase do Tipo 4/genética , Feminino , Frequência do Gene , Marcadores Genéticos/genética , Predisposição Genética para Doença , Genótipo , Humanos , Desequilíbrio de Ligação , Masculino , Programas de Rastreamento/métodos , Análise de Sequência com Séries de Oligonucleotídeos , Inventário de Personalidade
2.
Proc Natl Acad Sci U S A ; 101(26): 9734-9, 2004 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-15210992

RESUMO

Investigation of sequence variation in common inbred mouse strains has revealed a segmented pattern in which regions of high and low variant density are intermixed. Furthermore, it has been suggested that allelic strain distribution patterns also occur in well defined blocks and consequently could be used to map quantitative trait loci (QTL) in comparisons between inbred strains. We report a detailed analysis of polymorphism distribution in multiple inbred mouse strains over a 4.8-megabase region containing a QTL influencing anxiety. Our analysis indicates that it is only partly true that the genomes of inbred strains exist as a patchwork of segments of sequence identity and difference. We show that the definition of haplotype blocks is not robust and that methods for QTL mapping may fail if they assume a simple block-like structure.


Assuntos
Variação Genética/genética , Haplótipos/genética , Camundongos Endogâmicos/genética , Alelos , Animais , Ansiedade/genética , Camundongos , Repetições de Microssatélites/genética , Polimorfismo de Nucleotídeo Único/genética , Locos de Características Quantitativas/genética , Análise de Sequência de DNA
3.
Bioinformatics ; 17(11): 1084-9, 2001 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-11724740

RESUMO

MOTIVATION: Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semi-automatic or task specific automatic by using existing techniques from computer science and signal processing. Computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error. RESULTS: We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification. AVAILABILITY: The IDL source code of the software is available on request from jonathan.flint@well.ox.ac.uk


Assuntos
DNA/genética , DNA/isolamento & purificação , Eletroforese em Gel de Ágar/estatística & dados numéricos , Processamento de Imagem Assistida por Computador/estatística & dados numéricos , Software , Animais , Biologia Computacional , Marcadores Genéticos , Polimorfismo Genético , Análise de Sequência de DNA/estatística & dados numéricos , Design de Software
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