PoPoolation: A Toolbox for Population Genetic Analysis of Next Generation Sequencing Data from Pooled Individuals

Recent statistical analyses suggest that sequencing of pooled samples provides a cost effective approach to determine genome-wide population genetic parameters. Here we introduce PoPoolation, a toolbox specifically designed for the population genetic analysis of sequence data from pooled individuals. PoPoolation calculates estimates of θWatterson, θπ, and Tajima's D that account for the bias introduced by pooling and sequencing errors, as well as divergence between species. Results of genome-wide analyses can be graphically displayed in a sliding window plot. PoPoolation is written in Perl and R and it builds on commonly used data formats. Its source code can be downloaded from http://code.google.com/p/popoolation/. Furthermore, we evaluate the influence of mapping algorithms, sequencing errors, and read coverage on the accuracy of population genetic parameter estimates from pooled data

High resolution melting analysis for a rapid identification of heterozygous and homozygous sequence changes in the MUTYH gene

Background: MUTYH-associated polyposis (MAP) is an autosomal recessive form of intestinal polyposis predisposing to colorectal carcinoma. High resolution melting analysis (HRMA) is a mutation scanning method that allows detection of heterozygous sequence changes with high sensitivity, whereas homozygosity for a nucleotide change may not lead to significant curve shape or melting temperature changes compared to homozygous wildtype samples. Therefore, HRMA has been mainly applied to the detection of mutations associated with autosomal dominant or X-linked disorders, while applications to autosomal recessive conditions are less common. Methods: MUTYH coding sequence and UTRs were analyzed by both HRMA and sequencing on 88 leukocyte genomic DNA samples. Twenty-six samples were also examined by SSCP. Experiments were performed both with and without mixing the test samples with wild-type DNA. Results: The results show that all MUTYH sequence variations, including G > C and A > T homozygous changes, can be reliably identified by HRMA when a condition of artificial heterozygosity is created by mixing test and reference DNA. HRMA had a sensitivity comparable to sequencing and higher than SSCP. Conclusions: The availability of a rapid and inexpensive method for the identification of MUTYH sequence variants is relevant for the diagnosis of colorectal cancer susceptibility, since the MAP phenotype is highly variable

Deep Sequencing of the Nicastrin Gene in Pooled DNA, the Identification of Genetic Variants That Affect Risk of Alzheimer's Disease

Nicastrin is an obligatory component of the γ-secretase; the enzyme complex that leads to the production of Aβ fragments critically central to the pathogenesis of Alzheimer's disease (AD). Analyses of the effects of common variation in this gene on risk for late onset AD have been inconclusive. We investigated the effect of rare variation in the coding regions of the Nicastrin gene in a cohort of AD patients and matched controls using an innovative pooling approach and next generation sequencing. Five SNPs were identified and validated by individual genotyping from 311 cases and 360 controls. Association analysis identified a non-synonymous rare SNP (N417Y) with a statistically higher frequency in cases compared to controls in the Greek population (OR 3.994, CI 1.105–14.439, p = 0.035). This finding warrants further investigation in a larger cohort and adds weight to the hypothesis that rare variation explains some of genetic heritability still to be identified in Alzheimer's disease

Sequencing of high-complexity DNA pools for identification of nucleotide and structural variants in regions associated with complex traits

We have used targeted genomic sequencing of high-complexity DNA pools based on long-range PCR and deep DNA sequencing by the SOLiD technology. The method was used for sequencing of 286 kb from four chromosomal regions with quantitative trait loci (QTL) influencing blood plasma lipid and uric acid levels in DNA pools of 500 individuals from each of five European populations. The method shows very good precision in estimating allele frequencies as compared with individual genotyping of SNPs (r(2) = 0.95, P < 10(-16)). Validation shows that the method is able to identify novel SNPs and estimate their frequency in high-complexity DNA pools. In our five populations, 17% of all SNPs and 61% of structural variants are not available in the public databases. A large fraction of the novel variants show a limited geographic distribution, with 62% of the novel SNPs and 59% of novel structural variants being detected in only one of the populations. The large number of population-specific novel SNPs underscores the need for comprehensive sequencing of local populations in order to identify the causal variants of human traits

Functional characterization of a multi-cancer risk locus on chr5p15.33 reveals regulation of TERT by ZNF148

Genome wide association studies (GWAS) have mapped multiple independent cancer susceptibility loci to chr5p15.33. Here, we show that fine-mapping of pancreatic and testicular cancer GWAS within one of these loci (Region 2 in CLPTM1L) focuses the signal to nine highly correlated SNPs. Of these, rs36115365-C associated with increased pancreatic and testicular but decreased lung cancer and melanoma risk, and exhibited preferred protein-binding and enhanced regulatory activity. Transcriptional gene silencing of this regulatory element repressed TERT expression in an allele-specific manner. Proteomic analysis identifies allele-preferred binding of Zinc finger protein 148 (ZNF148) to rs36115365-C, further supported by binding of purified recombinant ZNF148. Knockdown of ZNF148 results in reduced TERT expression, telomerase activity and telomere length. Our results indicate that the association with chr5p15.33-Region 2 may be explained by rs36115365, a variant influencing TERT expression via ZNF148 in a manner consistent with elevated TERT in carriers of the C allele