Targeted Genotyping of Variable Number Tandem Repeats with adVNTR

Bakhtiari, Mehrdad; Shleizer-Burko, Sharona; Gymrek, Melissa; Bansal, Vikas; Bafna, Vineet

doi:10.1101/221754

Cited by 17 publications

(27 citation statements)

References 60 publications

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“…Over the last several years, we and others have developed a series of tools for genome-wide genotyping of STRs [12,44,16,23] from short reads or targeted genotyping of VNTRs [4] from both short and long reads. These tools primarily rely on identifying reads that completely enclose the repeat of interest.…”

Section: Introductionmentioning

confidence: 99%

Profiling the genome-wide landscape of tandem repeat expansions

Mousavi

Shleizer-Burko

Gymrek

2018

Preprint

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Tandem Repeat (TR) expansions have been implicated in dozens of genetic diseases, including Huntington's Disease, Fragile X Syndrome, and hereditary ataxias. Furthermore, TRs have recently been implicated in a range of complex traits, including gene expression and cancer risk. While the human genome harbors hundreds of thousands of TRs, analysis of TR expansions has been mainly limited to known pathogenic loci. A major challenge is that expanded repeats are beyond the read length of most next-generation sequencing (NGS) datasets and are not profiled by existing genome-wide tools. We present GangSTR, a novel algorithm for genome-wide genotyping of both short and expanded TRs. GangSTR extracts information from paired-end reads into a unified model to estimate maximum likelihood TR lengths. We validate GangSTR on real and simulated data and show that GangSTR outperforms alternative methods in both accuracy and speed. We apply GangSTR to a deeply sequenced trio to profile the landscape of TR expansions in a healthy family and validate novel expansions using orthogonal technologies. Our analysis reveals that healthy individuals harbor dozens of long TR alleles not captured by current genome-wide methods. GangSTR will likely enable discovery of novel disease-associated variants not currently accessible from NGS.

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Section: Introductionmentioning

confidence: 99%

Profiling the genome-wide landscape of tandem repeat expansions

Mousavi

Shleizer-Burko

Gymrek

2018

Preprint

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“…In addition, we parsed out SV loci according to regions with a single SV across the samples and those with multiple different SVs and identified that 38,239 (59%) of our SV calls occur as single, unique events in the respective region and the rest 26,869 (41%) occur in regions with one or more nearby SVs ( Figure S1 ) . Recent evidence suggests that a significant fraction of novel SVs could be tandem repeats with variable lengths across the population 30,31 and we found that 49% of the singleton unique SVs are completely within the UCSC Genome Browser Tandem Repeat (TR) tracks while 93% of the clustered unique SVs are within TR tracks. Because regions with multiple variants will pose additional complexities for SV genotyping that are beyond the scope of the current version of Paragraph, we limited our LRGT to the 9,238 deletions and 10,870 insertions that are not confounded by the presence of a different nearby or overlapping SV (see Methods ).…”

Section: Construction Of a Long Read-based Ground Truthmentioning

confidence: 65%

Paragraph: A graph-based structural variant genotyper for short-read sequence data

Chen

Krusche

Dolzhenko

et al. 2019

Preprint

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Accurate detection and genotyping of structural variations (SVs) from short-read data is a long-standing area of development in genomics research and clinical sequencing pipelines. We introduce Paragraph, an accurate genotyper that models SVs using sequence graphs and SV annotations. We demonstrate the accuracy of Paragraph on whole-genome sequence data from three samples using long read SV calls as the truth set, and then apply Paragraph at scale to a cohort of 100 short-read sequenced samples of diverse ancestry. Our analysis shows that Paragraph has better accuracy than other existing genotypers and can be applied to population-scale studies.

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“…al. (2017) [29]. Briefly, VNTRTyper takes advantage of the long read sequencing to identify the number of repeat units in the TR regions.…”

Section: Methodsmentioning

confidence: 99%

GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing

Ganesamoorthy

Cao

Duarte

et al. 2018

Preprint

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BackgroundTandem repeats comprise significant proportion of the human genome including coding and regulatory regions. They are highly prone to repeat number variation and nucleotide mutation due to their repetitive and unstable nature, making them a major source of genomic variation between individuals. Despite recent advances in high throughput sequencing, analysis of tandem repeats in the context of complex diseases is still hindered by technical limitations.MethodsWe report a novel targeted sequencing approach, which allows simultaneous analysis of hundreds of repeats. We developed a Bayesian algorithm, namely – GtTR - which combines information from a reference long-read dataset with a short read counting approach to genotype tandem repeats at population scale. PCR sizing analysis was used for validation.ResultsWe used a PacBio long-read sequenced sample to generate a reference tandem repeat genotype dataset with on average 13% absolute deviation from PCR sizing results. Using this reference dataset GtTR generated estimates of VNTR copy number with accuracy within 95% high posterior density (HPD) intervals of 68% and 83% for capture sequence data and 200X WGS data respectively, improving to 87% and 94% with use of a PCR reference. We show that the genotype resolution increases as a function of depth, such that the median 95% HPD interval lies within 25%, 14%, 12% and 8% of the its midpoint copy number value for 30X, 200X WGS, 395X and 800X capture sequence data respectively. We validated nine targets by PCR sizing analysis and genotype estimates from sequencing results correlated well with PCR results.ConclusionsThe novel genotyping approach described here presents a new cost-effective method to explore previously unrecognized class of repeat variation in GWAS studies of complex diseases at the population level. Further improvements in accuracy can be obtained by improving accuracy of the reference dataset.

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Targeted Genotyping of Variable Number Tandem Repeats with adVNTR

Cited by 17 publications

References 60 publications

Profiling the genome-wide landscape of tandem repeat expansions

Profiling the genome-wide landscape of tandem repeat expansions

Paragraph: A graph-based structural variant genotyper for short-read sequence data

GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing

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