Suchergebnisse

AbstractGenome-wide linkage analysis using multiple traits and statistical software packages is a tedious process which requires a significant amount of manual file manipulation. Different linkage analysis programs require different input file formats, making the task of analyzing data with multiple methods even more time-consuming. We have developed a software tool, AUTOGSCAN, that automates file formatting, the running of statistical analyses, and the summarizing of resulting statistics for whole genome scans with a push of a button, using several independent, and often idiosyncratic, statistical software packages such as MERLIN, SOLAR and GENEHUNTER. We also describe a program, ANALYZE, designed to run qualitative linkage analysis with several different statistical strategies and programs to efficiently screen for linkage and linkage disequilibrium for a given discrete trait. The ANALYZE program can also be used by AUTOGSCAN in a genome-wide sense.

AbstractThe amount of available DNA is often a limiting factor in pursuing genetic analyses of large-scale population cohorts. An association between higher DNA yield from blood and several phenotypes associated with inflammatory states has recently been demonstrated, suggesting that exclusion of samples with very low DNA yield may lead to biased results in statistical analyses. Whole genome amplification (WGA) could present a solution to the DNA concentration-dependent sample selection. The aim was to thoroughly assess WGA for samples with low DNA yield, using the multiply-primed rolling circle amplification method. Fifty-nine samples were selected with the lowest DNA yield (less than 7.5µg) among 799 samples obtained for one population cohort. The genotypes obtained from two replicate WGA samples and the original genomic DNA were compared by typing 24 single nucleotide polymorphisms (SNPs). Multiple genotype discrepancies were identified for 13 of the 59 samples. The largest portion of discrepancies was due to allele dropout in heterozygous genotypes in WGA samples. Pooling the WGA DNA replicates prior to genotyping markedly improved genotyping reproducibility for the samples, with only 7 discrepancies identified in 4 samples. The nature of discrepancies was mostly homozygote genotypes in the genomic DNA and heterozygote genotypes in the WGA sample, suggesting possible allele dropout in the genomic DNA sample due to very low amounts of DNA template. Thus, WGA is applicable for low DNA yield samples, especially if using pooled WGA samples. A higher rate of genotyping errors requires that increased attention be paid to genotyping quality control, and caution when interpreting results.

Genome-wide association analysis on monozygotic twin-pairs offers a route to discovery of gene–environment interactions through testing for variability loci associated with sensitivity to individual environment/lifestyle. We present a genome-wide scan of loci associated with intra-pair differences in serum lipid and apolipoprotein levels. We report data for 1,720 monozygotic female twin-pairs from GenomEUtwin project with 2.5 million SNPs, imputed or genotyped, and measured serum lipid fractions for both twins. We found one locus associated with intra-pair differences in high-density lipoprotein cholesterol,rs2483058in an intron ofSRGAP2, where twins carrying the C allele are more sensitive to environmental factors (P= 3.98 × 10−8). We followed up the association in further genotyped monozygotic twins (N= 1,261), which showed a moderate association for the variant (P= 0.200, same direction of an effect). In addition, we report a new association on the level of apolipoprotein A-II (P= 4.03 × 10−8).