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Human Genome Assembly and Analysis on a Desktop Computer Using DNASTAR’s Prototype Pipeline

Filed under Bioinformatics, Genotyping by on October 7, 2010 at 9:00 pm no comments
SAN FRANCISCO - JULY 15: The Intel logo is se...
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This application note demonstrates an innovative approach to next-generation sequence assembly and analysis pipeline that will run on a desktop computer and produce a human genome sequence in a reasonable time frame.
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Genome-wide SNP genotyping study using pooled DNA to identify candidate markers mediating susceptibility to end-stage renal disease attributed to Type 1 diabetes.

Filed under Bioinformatics, Genotyping by on October 2, 2010 at 11:03 pm no comments
Sequenom genotyping chip
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Genome-wide SNP genotyping study using pooled DNA to identify candidate markers mediating susceptibility to end-stage renal disease attributed to Type 1 diabetes. Diabet Med. 2009 Nov;26(11):1090-8 Authors: Craig DW, Millis MP, DiStefano JK AIMS: Genetic factors play a major role in the progression of kidney disease in diabetes. To identify candidate single nucleotide polymorphisms (SNPs) with potential effects on susceptibility to end-stage renal disease (ESRD), we performed a whole genome association scan using pooled DNA from Caucasian individuals with Type 1 diabetes. METHODS: We utilized the Illumina Infinium II HumanHap 550 beadchip platform to genotype 555 352 SNPs in DNA pools comprised of 547 cases with ESRD and 549 control subjects with Type 1 diabetes duration > 20 years and no ESRD. Pooled probe intensity was used to predict mean allele frequency (MAF) for each locus. Individual genotyping was performed using the iPLEX assay in conjunction with the MassARRAY platform (Sequenom). RESULTS: We identified 2870 markers showing substantial differences in MAF (5.0-10.7%) between pools. To initiate validation of these findings, we genotyped 22 high-ranking markers in 462 individuals with ESRD and 470 unaffected control subjects selected from the genome-wide SNP genotyping study sample. We observed the strongest evidence for association between ESRD and rs1749824, located in the ZMIZ1 gene [OR = 1.47 (1.21-1.78) per copy of T allele; P = 8.1 x 10(-5)] and rs9298190, located in the musculin gene [OR = 1.56 (1.28-1.91) per copy of C allele; P = 1.6 x 10(-5)]. Evidence for nominal association with markers in or near the IRS2, TMPO, BID, KLRA1, ELMO1 and CNDP1 genes was also observed (P < or = 0.0006). CONCLUSIONS: These findings identify several novel loci which may contribute to ESRD susceptibility in individuals with Type 1 diabetes. PMID: 19929986 [PubMed - indexed for MEDLINE]
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High concordance of bovine single nucleotide polymorphism genotypes generated using two independent genotyping strategies.

Filed under Bioinformatics, Core facilities by on September 30, 2010 at 7:00 pm no comments
In this study, 263 Bos spp. samples were genotyped commercially for a total of 16 SNPs. Of the total possible 4,208 SNP genotypes, 4,179 SNP genotypes were generated, yielding a genotype call rate of 99.31% (standard deviation ± 0.93%). Between 110 and 263 samples were subsequently re-genotyped by us for all 16 markers using a custom-designed SNP genotyping platform, and of the possible 3,819 genotypes a total of 3,768 genotypes were generated (98.70% genotype call rate, SD ± 1.89%). A total of 3,744 duplicate genotypes were generated for both genotyping platforms, and comparison of the genotype calls for both methods revealed 3,741 concordant SNP genotype call rates (99.92% SNP genotype concordance rate). These data indicate that both genotyping methods used can provide livestock ge...

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A new, powerful tool for annotating single nucleotide variants and indels

Filed under Bioinformatics, Genotyping by on September 21, 2010 at 11:12 am no comments

New Tool For Annotating SNVs
Wang, Li, Hakonarson, Nucleic Acids Research
The University of Pennsylvania’s Hakon Hakonarson and his colleagues describe ANNOVAR, a tool that can “annotate single nucleotide variants and insertions/deletions,” and is capable of “examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1,000 Genomes Project and dbSNP,” the authors write. ANNOVAR can be run on a desktop computer, the team reports, and takes only four minutes to perform gene-based annotation and 15 to perform variants reduction on 4.7 million variants, “making it practical to handle hundreds of human genomes in a day.”

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