Abstract
BackgroundSingle nucleotide polymorphisms (SNPs) are the most common form of genetic variability in the human genome and play a prominent role in the heritability of phenotypes. Especially rare alleles with frequencies less than 5% may exhibit a particularly strong influence on the development of complex diseases. The detection of rare alleles by standard DNA sequencing is time-consuming and cost-intensive. Here we discuss an alternative approach for a high throughput detection of rare mutations in large population samples using Ecotilling embedded in a collection of bioinformatic analysis tools. Ecotilling originally was introduced as TILLING for the screening for rare chemically induced mutations in plants and later adopted for human samples, showing an outstanding suitability for the detection of rare alleles in humans. An actual problem in the use of Ecotilling for large mutation screening projects in humans without bioinformatic support is represented by the lack of solutions to quickly yet comprehensively evaluate each newly found variation and place it into the correct genomic context.ResultsWe present an optimized strategy for the design, evaluation and interpretation of Ecotilling results by integrating several mostly freely available bioinformatic tools. A major focus of our investigations was the evaluation and meaningful economical combination of these software tools for the inference of different possible regulatory functions for each newly detected mutation.ConclusionOur streamlined procedure significantly facilitates the experimental design and evaluation of Ecotilling assays and strongly improves the decision process on prioritizing the newly found SNPs for further downstream analysis.
Highlights
Single nucleotide polymorphisms (SNPs) are the most common form of genetic variability in the human genome and play a prominent role in the heritability of phenotypes
Many of the current pre-screening technologies such as single strand conformational polymorphism analysis or gradient gel electrophoresis are laborious, target only relatively small portions of DNA or are not capable for high throughput
The basic step of Targeting Induced Local Lesions IN Genomes (TILLING) is the amplification of a region of interest of up to 1.5 kb using two primers labeled with different infrared fluorochromes, followed by heat-denaturation and slow cooling to allow the formation of heteroduplexes in the presence of heterozygous mutations
Summary
Single nucleotide polymorphisms (SNPs) are the most common form of genetic variability in the human genome and play a prominent role in the heritability of phenotypes. The detection of rare alleles by standard DNA sequencing is time-consuming and cost-intensive. We discuss an alternative approach for a high throughput detection of rare mutations in large population samples using Ecotilling embedded in a collection of bioinformatic analysis tools. Ecotilling originally was introduced as TILLING for the screening for rare chemically induced mutations in plants and later adopted for human samples, showing an outstanding suitability for the detection of rare alleles in humans. Several studies have shown that especially rare alleles with frequencies below 5% (referred to as "rare" alleles) may have a strong impact on quantitative traits and complex diseases [1,2,3,4,5,6]. BMC Genomics 2008, 9:510 http://www.biomedcentral.com/1471-2164/9/510 regions in large study populations with the aim to identify the contribution of rare mutation is time-consuming and cost-intensive. Techniques that allow an inexpensive but high throughput detection of rare mutations with high sensitivity are of high interest [13,15]
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