Dataset Information

High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling.

ABSTRACT: Human individuals differ from one another at only approximately 0.1% of nucleotide positions, but these single nucleotide differences account for most heritable phenotypic variation. Large-scale efforts to discover and genotype human variation have been limited to common polymorphisms. However, these efforts overlook rare nucleotide changes that may contribute to phenotypic diversity and genetic disorders, including cancer. Thus, there is an increasing need for high-throughput methods to robustly detect rare nucleotide differences. Toward this end, we have adapted the mismatch discovery method known as Ecotilling for the discovery of human single nucleotide polymorphisms. To increase throughput and reduce costs, we developed a universal primer strategy and implemented algorithms for automated band detection. Ecotilling was validated by screening 90 human DNA samples for nucleotide changes in 5 gene targets and by comparing results to public resequencing data. To increase throughput for discovery of rare alleles, we pooled samples 8-fold and found Ecotilling to be efficient relative to resequencing, with a false negative rate of 5% and a false discovery rate of 4%. We identified 28 new rare alleles, including some that are predicted to damage protein function. The detection of rare damaging mutations has implications for models of human disease.

SUBMITTER: Till BJ

PROVIDER: S-EPMC1540726 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling.

Till Bradley J BJ Zerr Troy T Bowers Elisabeth E Greene Elizabeth A EA Comai Luca L Henikoff Steven S

Nucleic acids research 20060807 13

Human individuals differ from one another at only approximately 0.1% of nucleotide positions, but these single nucleotide differences account for most heritable phenotypic variation. Large-scale efforts to discover and genotype human variation have been limited to common polymorphisms. However, these efforts overlook rare nucleotide changes that may contribute to phenotypic diversity and genetic disorders, including cancer. Thus, there is an increasing need for high-throughput methods to robustl ...[more]

PMID: 16893952

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Project description:BackgroundInformation on polymorphic DNA in organelle genomes is essential for evolutionary and ecological studies. However, it is challenging to perform high-throughput investigations of chloroplast and mitochondrial DNA polymorphisms. In recent years, EcoTILLING stands out as one of the most universal, low-cost, and high-throughput reverse genetic methods, and the identification of natural genetic variants can provide much information about gene function, association mapping and linkage disequilibrium analysis and species evolution. Until now, no report exists on whether this method is applicable to organelle genomes and to what extent it can be used.Methodology/principal findingsTo address this problem, we adapted the CEL I-based heteroduplex cleavage strategy used in Targeting Induced Local Lesions in Genomes (TILLING) for the discovery of nucleotide polymorphisms in organelle genomes. To assess the applicability and accuracy of this technology, designated ORG-EcoTILLING, at different taxonomic levels, we sampled two sets of taxa representing accessions from the Brassicaceae with three chloroplast genes (accD, matK and rbcL) and one mitochondrial gene (atp6). The method successfully detected nine, six and one mutation sites in the accD, matK and rbcL genes, respectively, in 96 Brassica accessions. These mutations were confirmed by DNA sequencing, with 100% accuracy at both inter- and intraspecific levels. We also detected 44 putative mutations in accD in 91 accessions from 45 species and 29 genera of seven tribes. Compared with DNA sequencing results, the false negative rate was 36%. However, 17 SNPs detected in atp6 were completely identical to the sequencing results.Conclusions/significanceThese results suggest that ORG-EcoTILLING is a powerful and cost-effective alternative method for high-throughput genome-wide assessment of inter- and intraspecific chloroplast and mitochondrial DNA polymorphisms. It will play an important role in evolutionary and ecological biology studies, in identification of related genes associated with agronomic importance such as high yield and improved cytoplasmic quality, and for identifying mitochondrial point mutations responsible for diseases in humans and other animals.

Project description:A method of historical inference that accounts for ascertainment bias is developed and applied to single-nucleotide polymorphism (SNP) data in humans. The data consist of 84 short fragments of the genome that were selected, from three recent SNP surveys, to contain at least two polymorphisms in their respective ascertainment samples and that were then fully resequenced in 47 globally distributed individuals. Ascertainment bias is the deviation, from what would be observed in a random sample, caused either by discovery of polymorphisms in small samples or by locus selection based on levels or patterns of polymorphism. The three SNP surveys from which the present data were derived differ both in their protocols for ascertainment and in the size of the samples used for discovery. We implemented a Monte Carlo maximum-likelihood method to fit a subdivided-population model that includes a possible change in effective size at some time in the past. Incorrectly assuming that ascertainment bias does not exist causes errors in inference, affecting both estimates of migration rates and historical changes in size. Migration rates are overestimated when ascertainment bias is ignored. However, the direction of error in inferences about changes in effective population size (whether the population is inferred to be shrinking or growing) depends on whether either the numbers of SNPs per fragment or the SNP-allele frequencies are analyzed. We use the abbreviation "SDL," for "SNP-discovered locus," in recognition of the genomic-discovery context of SNPs. When ascertainment bias is modeled fully, both the number of SNPs per SDL and their allele frequencies support a scenario of growth in effective size in the context of a subdivided population. If subdivision is ignored, however, the hypothesis of constant effective population size cannot be rejected. An important conclusion of this work is that, in demographic or other studies, SNP data are useful only to the extent that their ascertainment can be modeled.

Dataset Information

High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling.

Publications

High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling.

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