Integrated detection and population-genetic analysis of SNPs and copy number variation

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.

Copy number variation in patients with cervical artery dissection

“…We filtered our findings against CNVs detected by high-density platforms (4500 000 SNPs) in Caucasian individuals. [15][16][17] Many patients' CNVs that were absent from all analyzed controls showed some overlap with rare CNVs listed in the database of genomic variants (DGV). However, the value of DGV for CNV interpretation is limited, as DGV contains non-validated CNVs and many CNVs with overestimated lengths.…”

“…In the second step, we compared the rare CNVs detected in our patient samples with published CNVs in 2402 Caucasian healthy subjects (HapMap project, n ¼ 90; CHOP database, n ¼ 1327; and a recent CNV population study, n ¼ 985). [15][16][17] Rare CNVs that were detected among CeAD-patients but were absent from own control subjects, and from the aforementioned data sets were considered as CeAD-associated.…”

Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms

“…[35], and McCarroll et al . [4,36] demonstrated that common indels are in high LD with nearby SNPs, our results revealed that both low frequency and common indels can be reliably tagged by nearby SNPs (Figure 2a). OMNI and HapMap panels ably tag > 70% of common indels, while OMNI tags > 50% of low-frequency indels (Table S4 in Additional file 1) in all populations.…”

“…Perhaps of greater interest due to the impact on disease phenotypes by low frequency variants [33-36], we explored imputation of low frequency alleles from 1000G SNPs. We found that SNPTools ably imputed heterozygous low frequency alleles.…”

Gene expression changes in normal haematopoietic cells

“…81,82 These cutting edge technologies have rapidly advanced our understanding of how genomic changes impact expression, identifying thousands of new polymorphisms and promoter loci. 78,83,84 Currently, there are a number of different techniques to examine DNA methylation and histone marks -two major epigenetic mechanisms for controlling transcription. DNA methylation changes were first examined using restriction enzyme digest/PCR assays.…”