Cargando…
GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing
BACKGROUND: Tandem 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 indivi...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6048696/ https://www.ncbi.nlm.nih.gov/pubmed/30012093 http://dx.doi.org/10.1186/s12859-018-2282-3 |
_version_ | 1783340141957349376 |
---|---|
author | Ganesamoorthy, Devika Cao, Minh Duc Duarte, Tania Chen, Wenhan Coin, Lachlan |
author_facet | Ganesamoorthy, Devika Cao, Minh Duc Duarte, Tania Chen, Wenhan Coin, Lachlan |
author_sort | Ganesamoorthy, Devika |
collection | PubMed |
description | BACKGROUND: Tandem 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. We 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. RESULTS: We 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. CONCLUSIONS: The 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2282-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6048696 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60486962018-07-19 GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing Ganesamoorthy, Devika Cao, Minh Duc Duarte, Tania Chen, Wenhan Coin, Lachlan BMC Bioinformatics Methodology Article BACKGROUND: Tandem 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. We 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. RESULTS: We 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. CONCLUSIONS: The 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2282-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-16 /pmc/articles/PMC6048696/ /pubmed/30012093 http://dx.doi.org/10.1186/s12859-018-2282-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Ganesamoorthy, Devika Cao, Minh Duc Duarte, Tania Chen, Wenhan Coin, Lachlan GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing |
title | GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing |
title_full | GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing |
title_fullStr | GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing |
title_full_unstemmed | GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing |
title_short | GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing |
title_sort | gttr: bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6048696/ https://www.ncbi.nlm.nih.gov/pubmed/30012093 http://dx.doi.org/10.1186/s12859-018-2282-3 |
work_keys_str_mv | AT ganesamoorthydevika gttrbayesianestimationofabsolutetandemrepeatcopynumberusingsequencecaptureandhighthroughputsequencing AT caominhduc gttrbayesianestimationofabsolutetandemrepeatcopynumberusingsequencecaptureandhighthroughputsequencing AT duartetania gttrbayesianestimationofabsolutetandemrepeatcopynumberusingsequencecaptureandhighthroughputsequencing AT chenwenhan gttrbayesianestimationofabsolutetandemrepeatcopynumberusingsequencecaptureandhighthroughputsequencing AT coinlachlan gttrbayesianestimationofabsolutetandemrepeatcopynumberusingsequencecaptureandhighthroughputsequencing |