Multiplexed resequencing analysis to identify rare variants in pooled DNA with barcode indexing using next-generation sequencer

Mitsui, Jun; Fukuda, Yoko; Azuma, Kyo; Tozaki, Hirokazu; Ishiura, Hiroyuki; Takahashi, Yūji; Goto, Jun; Tsuji, Shoji

doi:10.1038/jhg.2010.46

Cited by 13 publications

(12 citation statements)

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“…For example one cannot test for an association under different models, or look at gene-gene or gene-environment interactions. An alternative approach gaining popularity is the use indexed libraries [3], [23], [24] and combinational pooling strategies [25], [26]. Although at present there are limitations to the number of samples that can feasibly be pooled, taking into account the cost and time constraints of preparing a library for each sample.…”

Section: Discussionmentioning

confidence: 99%

“…However, it is increasingly recognised that rare variants have a role in complex disease. An example in neurodegenerative disease is the glucocerebrosidase gene (GBA) in Parkinson's disease, individuals homozygous for mutations in this gene present with the Mendelian disorder Gaucher disease, while individuals heterozygous for the same mutations have an increased risk for Parkinson disease [3], [4] The cumulative frequency of GBA mutations in Parkinson disease cases can be as high as 9.0% compared to less than 0.5% in controls. Such variants are not included on commercial genotyping arrays but are only detected through re-sequencing approaches.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2011

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2011

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“…However, some studies have suggested that the genetic variants for common diseases could have a wide spectrum of frequencies, ranging from rare to common, and that rare variants could exhibit a relatively large genetic effect (for example, odds ratio greater than 2). [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] For example, in 2008, Stefansson et al 10 found that three rare deletions were associated with schizophrenia with the odds ratios of 2.7, 11.5 and 14.8, respectively. Some authors have proposed novel methods to detect associations with multiple rare variants for common diseases.…”

Section: Introductionmentioning

confidence: 99%

Evaluating rare variants under two-stage design

Pan

Yue

et al. 2012

J Hum Genet

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Current genome-wide association studies (GWAS) focusing on relatively common single-nucleotide polymorphisms (SNPs) usually adopt a cost-effective multi-staged design in which a proportion of the total samples are genotyped using a commercial SNP array with a reasonably good coverage of the whole genome at the initial stage, and a list of promising SNPs are further genotyped and evaluated on the remaining samples at the second stage. This staged design in principal can also be used for the study of rare genetic variants at the genome-wide scale, but the statistical methods developed for evaluating the relatively common SNPs under the staged design are not appropriate for rare variants due to the invalidity of large sample theorems. Here, we develop a new statistical framework that aims to evaluate rare variants under two-staged (or multi-staged) design. By extensive computer simulations, we evaluate the empirical type I error rate and power of the proposed procedures. A real example from two recent case-control rheumatoid arthritis genetic association studies is also used to demonstrate the performances of the proposed methods. Keywords: case-control study; GWAS; rare variants; two-staged design INTRODUCTION Current wave of genome-wide association studies (GWAS) focusing on relatively common single-nucleotide polymorphisms (SNPs) (minor allele frequency (MAF)45%) have successfully identified hundreds of loci associated with risk of various diseases. To date, more than 5900 SNPs have been reported to be associated with different diseases (http://www.genome.gov/gwastudies/). However, some studies have suggested that the genetic variants for common diseases could have a wide spectrum of frequencies, ranging from rare to common, and that rare variants could exhibit a relatively large genetic effect (for example, odds ratio greater than 2). 1-15 For example, in 2008, Stefansson et al. 10 found that three rare deletions were associated with schizophrenia with the odds ratios of 2.7, 11.5 and 14.8, respectively. Some authors have proposed novel methods to detect associations with multiple rare variants for common diseases. [16][17][18][19][20] Current GWAS with common SNPs usually adopt a cost-effective staged design in which a proportion of the available sample are genotyped using a commercially available SNP array with a reasonable coverage of the whole genome at the initial stage, and a list of promising SNPs with P-values less than a given threshold are further genotyped on the rest of the samples at the second stage. [21][22][23][24] For data analysis, it is generally more powerful to use the joint analysis strategy that combines the statistics from two stages for the final evaluation of the association evidence comparing with the replication-based analysis that only uses the statistic from the second stage. [24][25][26] In principle, this staged design can be used for future GWAS or candidate gene association studies focusing on rare genetic variants. However, the analysis of rare variant under such a multi-sta...

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“…Fixed arrays will be just as informative as resequencing approaches would be where the information content of the dataset is limited by the frequency of recombination rather than by the detection of rare alleles. Furthermore, array-based analysis can be readily followed up by more targeted, sequencing-based approaches to identify rare alleles in genomic regions or germplasm accessions of interest (Mitsui et al 2010) With rapid changes in technology and computational resources, the two-step paradigm of SNP-discovery followed by SNP-detection is rapidly merging into a single, sequencebased process of simultaneous SNP discovery and detection (Craig et al 2008, Cronn et al 2008, Huang et al 2009. Once this becomes economically and logistically feasible for the rice community, direct sequencing will undoubtedly replace the use of fixed arrays.…”

Section: Advantages and Disadvantages Of Fixed Snp Assaysmentioning

confidence: 99%

Development of genome-wide SNP assays for rice

et al. 2010

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Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation in eukaryotic genomes. SNPs may be functionally responsible for specific traits or phenotypes, or they may be informative for tracing the evolutionary history of a species or the pedigree of a variety. As genetic markers, SNPs are rapidly replacing simple sequence repeats (SSRs) because they are more abundant, stable, amenable to automation, efficient, and increasingly cost-effective. The integration of high throughput SNP genotyping capability promises to accelerate genetic gain in a breeding program, but also imposes a series of economic, organizational and technical hurdles. To begin to address these challenges, SNP-based resources are being developed and made publicly available for broad application in rice research. These resources include large SNP datasets, tools for identifying informative SNPs for targeted applications, and a suite of custom-designed SNP assays for use in marker-assisted and genomic selection, association and QTL mapping, positional cloning, pedigree analysis, variety identification and seed purity testing. SNP resources also make it possible for breeders to more efficiently evaluate and utilize the wealth of natural variation that exists in both wild and cultivated germplasm with the aim of improving the productivity and sustainability of agriculture.

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Multiplexed resequencing analysis to identify rare variants in pooled DNA with barcode indexing using next-generation sequencer

Cited by 13 publications

References 11 publications

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

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

Evaluating rare variants under two-stage design

Development of genome-wide SNP assays for rice

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