Accurate detection and genotyping of SNPs utilizing population sequencing data.

Next generation sequencing technologies have made it possible to sequence targeted regions of the human genome in hundreds of individuals. Deep sequencing represents a powerful approach for the discovery of the complete spectrum of DNA sequence variants in functionally important genomic intervals. Current methods for SNP detection are designed to detect SNPs from single individual sequence datasets. Here we describe a novel method SNIP-Seq (Single Nucleotide polymorphism Identification from Population Sequence data) that leverages sequence data from a population of individuals to detect SNPs and assign genotypes to individuals. To evaluate our method, we utilized sequence data from a 200 kilobase region on chromosome 9p21 of the human genome. This region was sequenced in 48 individuals (5 sequenced in duplicate) using the Illumina GA platform. Using this dataset, we demonstrate that our method is highly accurate for detecting variants and can filter out false SNPs that are attributable to sequencing errors. The concordance of sequencing based genotype assignments between duplicate samples was 98.8%. The 200 kb region was independently sequenced to a high depth of coverage using two sequence pools containing the 48 individuals. Many of the novel SNPs identified by SNIP-Seq from the individual sequencing were validated by the pooled sequencing data and were subsequently confirmed by Sanger sequencing. We estimate that SNIP-Seq achieves a low false positive rate of ~2% improving upon the higher false positive rate for existing methods that do not utilize population sequence data. Collectively, these results suggest that analysis of population sequencing data is a powerful approach for the accurate detection of SNPs and the assignment of genotypes to individual samples.

from The Scripps Institute

Structural variation in the human genome.

Nat Rev Genet. 2006 Feb;7(2):85-97.

Feuk L, Carson AR, Scherer SW.

The Centre for Applied Genomics and Program in Genetics and Genomic Biology, The Hospital for Sick Children, Department of Molecular and Medical Genetics, University of Toronto, Ontario, Canada.

The first wave of information from the analysis of the human genome revealed SNPs to be the main source of genetic and phenotypic human variation. However, the advent of genome-scanning technologies has now uncovered an unexpectedly large extent of what we term ’structural variation’ in the human genome. This comprises microscopic and, more commonly, submicroscopic variants, which include deletions, duplications and large-scale copy-number variants – collectively termed copy-number variants or copy-number polymorphisms – as well as insertions, inversions and translocations. Rapidly accumulating evidence indicates that structural variants can comprise millions of nucleotides of heterogeneity within every genome, and are likely to make an important contribution to human diversity and disease susceptibility

Using Microsatellites and SNPs as Tools in Medical Genetic Diagnostics and Research