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Steven A McCarroll,
Finny G Kuruvilla,
Joshua M Korn,
Simon Cawley,
James Nemesh,
Alec Wysoker,
Michael H Shapero,
Paul I W de Bakker,
Julian B Maller,
Andrew Kirby, [......],
Patrick J Collins,
Robert Handsaker,
Steve Lincoln,
Marcia Nizzari, John Blume,
Keith W Jones,
Rich Rava,
Mark J Daly,
Stacey B Gabriel,
David Altshuler
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ABSTRACT: Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.
Nature Genetics 09/2008; 40(10):1166-74. · 35.53 Impact Factor
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Jernej Ule,
Aljaz Ule,
Joanna Spencer,
Alan Williams,
Jing-Shan Hu,
Melissa Cline,
Hui Wang,
Tyson Clark,
Claire Fraser,
Matteo Ruggiu,
Barry R Zeeberg,
David Kane,
John N Weinstein, John Blume,
Robert B Darnell
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ABSTRACT: Alternative RNA splicing greatly increases proteome diversity and may thereby contribute to tissue-specific functions. We carried out genome-wide quantitative analysis of alternative splicing using a custom Affymetrix microarray to assess the role of the neuronal splicing factor Nova in the brain. We used a stringent algorithm to identify 591 exons that were differentially spliced in the brain relative to immune tissues, and 6.6% of these showed major splicing defects in the neocortex of Nova2-/- mice. We tested 49 exons with the largest predicted Nova-dependent splicing changes and validated all 49 by RT-PCR. We analyzed the encoded proteins and found that all those with defined brain functions acted in the synapse (34 of 40, including neurotransmitter receptors, cation channels, adhesion and scaffold proteins) or in axon guidance (8 of 40). Moreover, of the 35 proteins with known interaction partners, 74% (26) interact with each other. Validating a large set of Nova RNA targets has led us to identify a multi-tiered network in which Nova regulates the exon content of RNAs encoding proteins that interact in the synapse.
Nature Genetics 09/2005; 37(8):844-52. · 35.53 Impact Factor
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ABSTRACT: MOTIVATION: Many or most mammalian genes undergo alternative splicing, generating a variety of transcripts from a single gene. New information on splice variation is becoming available through technology for measuring expression levels of several exons or splice junctions per gene. We have developed a statistical method, ANalysis Of Splice VAriation (ANOSVA) to detect alternative splicing from expression data. Since ANOSVA requires no transcript information, it can be applied when the level of annotation is poor. When validated against spiked clone data, it generated no false positives and few false negatives. We demonstrated ANOSVA with data from a prototype mouse alternative splicing array, run against normal adult tissues, yielding a set of genes with evidence of tissue-specific splice variation. AVAILABILITY: The results are available at the supplementary information site. SUPPLEMENTARY INFORMATION: The results are available at the supplementary information site https://bioinfo.affymetrix.com/Papers/ANOSVA/
Bioinformatics 07/2005; 21 Suppl 1:i107-15. · 5.47 Impact Factor
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Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, Detroit, MI, USA, 25-29 June 2005; 01/2005
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Biocomputing 2004, Proceedings of the Pacific Symposium, Hawaii, USA, 6-10 January 2004; 01/2004
