Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.

Genes of the vertebrate major histocompatibility complex (MHC) are of great interest to biologists because of their important role in immunity and disease, and their extremely high levels of genetic diversity. Next generation sequencing (NGS) technologies are quickly becoming the method of choice fo...

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Autores principales:	William E Stutz, Daniel I Bolnick
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9081b319dcbd4a59901f3b689ee979dd
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spelling	oai:doaj.org-article:9081b319dcbd4a59901f3b689ee979dd2021-11-25T06:08:02ZStepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.1932-620310.1371/journal.pone.0100587https://doaj.org/article/9081b319dcbd4a59901f3b689ee979dd2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25036866/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Genes of the vertebrate major histocompatibility complex (MHC) are of great interest to biologists because of their important role in immunity and disease, and their extremely high levels of genetic diversity. Next generation sequencing (NGS) technologies are quickly becoming the method of choice for high-throughput genotyping of multi-locus templates like MHC in non-model organisms. Previous approaches to genotyping MHC genes using NGS technologies suffer from two problems:1) a "gray zone" where low frequency alleles and high frequency artifacts can be difficult to disentangle and 2) a similar sequence problem, where very similar alleles can be difficult to distinguish as two distinct alleles. Here were present a new method for genotyping MHC loci--Stepwise Threshold Clustering (STC)--that addresses these problems by taking full advantage of the increase in sequence data provided by NGS technologies. Unlike previous approaches for genotyping MHC with NGS data that attempt to classify individual sequences as alleles or artifacts, STC uses a quasi-Dirichlet clustering algorithm to cluster similar sequences at increasing levels of sequence similarity. By applying frequency and similarity based criteria to clusters rather than individual sequences, STC is able to successfully identify clusters of sequences that correspond to individual or similar alleles present in the genomes of individual samples. Furthermore, STC does not require duplicate runs of all samples, increasing the number of samples that can be genotyped in a given project. We show how the STC method works using a single sample library. We then apply STC to 295 threespine stickleback (Gasterosteus aculeatus) samples from four populations and show that neighboring populations differ significantly in MHC allele pools. We show that STC is a reliable, accurate, efficient, and flexible method for genotyping MHC that will be of use to biologists interested in a variety of downstream applications.William E StutzDaniel I BolnickPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 7, p e100587 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q William E Stutz Daniel I Bolnick Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.
description	Genes of the vertebrate major histocompatibility complex (MHC) are of great interest to biologists because of their important role in immunity and disease, and their extremely high levels of genetic diversity. Next generation sequencing (NGS) technologies are quickly becoming the method of choice for high-throughput genotyping of multi-locus templates like MHC in non-model organisms. Previous approaches to genotyping MHC genes using NGS technologies suffer from two problems:1) a "gray zone" where low frequency alleles and high frequency artifacts can be difficult to disentangle and 2) a similar sequence problem, where very similar alleles can be difficult to distinguish as two distinct alleles. Here were present a new method for genotyping MHC loci--Stepwise Threshold Clustering (STC)--that addresses these problems by taking full advantage of the increase in sequence data provided by NGS technologies. Unlike previous approaches for genotyping MHC with NGS data that attempt to classify individual sequences as alleles or artifacts, STC uses a quasi-Dirichlet clustering algorithm to cluster similar sequences at increasing levels of sequence similarity. By applying frequency and similarity based criteria to clusters rather than individual sequences, STC is able to successfully identify clusters of sequences that correspond to individual or similar alleles present in the genomes of individual samples. Furthermore, STC does not require duplicate runs of all samples, increasing the number of samples that can be genotyped in a given project. We show how the STC method works using a single sample library. We then apply STC to 295 threespine stickleback (Gasterosteus aculeatus) samples from four populations and show that neighboring populations differ significantly in MHC allele pools. We show that STC is a reliable, accurate, efficient, and flexible method for genotyping MHC that will be of use to biologists interested in a variety of downstream applications.
format	article
author	William E Stutz Daniel I Bolnick
author_facet	William E Stutz Daniel I Bolnick
author_sort	William E Stutz
title	Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.
title_short	Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.
title_full	Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.
title_fullStr	Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.
title_full_unstemmed	Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.
title_sort	stepwise threshold clustering: a new method for genotyping mhc loci using next-generation sequencing technology.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/9081b319dcbd4a59901f3b689ee979dd
work_keys_str_mv	AT williamestutz stepwisethresholdclusteringanewmethodforgenotypingmhclociusingnextgenerationsequencingtechnology AT danielibolnick stepwisethresholdclusteringanewmethodforgenotypingmhclociusingnextgenerationsequencingtechnology
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Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.

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