19 research outputs found

    Exome-wide assessment of isolated biliary atresia: A report from the National Birth Defects Prevention Study using child–parent trios and a case–control design to identify novel rare variants

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    The etiology of biliary atresia (BA) is unknown, but recent studies suggest a role for rare protein-altering variants (PAVs). Exome sequencing data from the National Birth Defects Prevention Study on 54 child–parent trios, one child–mother duo, and 1513 parents of children with other birth defects were analyzed. Most (91%) cases were isolated BA. We performed (1) a trio-based analysis to identify rare de novo, homozygous, and compound heterozygous PAVs and (2) a case–control analysis using a sequence kernel-based association test to identify genes enriched with rare PAVs. While we replicated previous findings on PKD1L1, our results do not suggest that recurrent de novo PAVs play important roles in BA susceptibility. In fact, our finding in NOTCH2, a disease gene associated with Alagille syndrome, highlights the difficulty in BA diagnosis. Notably, IFRD2 has been implicated in other gastrointestinal conditions and warrants additional study. Overall, our findings strengthen the hypothesis that the etiology of BA is complex

    Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

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    A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved
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