MHC genotyping of non-model organisms using next-generation sequencing: a new methodology to deal with artefacts and allelic dropout

Abstract

BackgroundThe Major Histocompatibility Complex (MHC) is the most important genetic marker to study patterns of adaptive genetic variation determining pathogen resistance and associated life history decisions. It is used in many different research fields ranging from human medical, molecular evolutionary to functional biodiversity studies. Correct assessment of the individual allelic diversity pattern and the underlying structural sequence variation is the basic requirement to address the functional importance of MHC variability. Next-generation sequencing (NGS) technologies are likely to replace traditional genotyping methods to a great extent in the near future but first empirical studies strongly indicate the need for a rigorous quality control pipeline. Strict approaches for data validation and allele calling to distinguish true alleles from artefacts are required.ResultsWe developed the analytical methodology and validated a data processing procedure which can be applied to any organism. It allows the separation of true alleles from artefacts and the evaluation of genotyping reliability, which in addition to artefacts considers for the first time the possibility of allelic dropout due to unbalanced amplification efficiencies across alleles. Finally, we developed a method to assess the confidence level per genotype a-posteriori, which helps to decide which alleles and individuals should be included in any further downstream analyses. The latter method could also be used for optimizing experiment designs in the future.ConclusionsCombining our workflow with the study of amplification efficiency offers the chance for researchers to evaluate enormous amounts of NGS-generated data in great detail, improving confidence over the downstream analyses and subsequent applications.

Large-scale genotyping of highly polymorphic loci by next-generation sequencing: how to overcome the challenges to reliably genotype individuals?

“…During post-processing, the differentiation of artifacts and PCR chimeras from true alleles has proven to be challenging (Babik et al, 2009;Babik, 2010;Zagalska-Neubauer et al, 2010;Huchard et al, 2012; Sommer et al, 2013). The absence of artifacts and PCR chimeras after removing singletons in our study could be the result of multiples causes.…”

“…Variability of coverage per amplicon is a well-known issue when using NGS and can result from the use of suboptimal primers (Sommer et al, 2013) or from the presence of homopolymer regions in the tags (Huse et al, 2007). However, our marmot-specific primers were carefully designed (Kuduk et al, 2012) and the tags we used (provided in the Supplementary Table S1) were designed to minimize this problem, which was confirmed after sequencing (the number of homopolymers in the tags was not found to affect the obtained coverage per amplicon).…”

“…Assignation of variants with indels allows to increase the evidence that the most frequent variant present in a given amplicon is a true allele (Stutz and Bolnick, 2014). This procedure could be especially useful when true alleles are represented by a few reads due to a lower sequencing efficiency relative to other alleles (Sommer et al, 2013).…”

“…Moreover, ampliconbased NGS techniques are highly suitable to genotype genes with high allelic diversity and provide a viable method to obtain an accurate genotyping of all copies for genes characterized by a variable number of copies (that is, with copy-number variation; Babik, 2010;Promerová et al, 2012). Indeed, amplicon-based NGS techniques have been widely used to genotype individuals at a wide range of highly polymorphic functional loci such as the major histocompatibility complex (MHC) in rodents (Babik et al, 2009;Galan et al, 2010;Sommer et al, 2013), primates , carnivores (Oomen et al, 2013), birds Sepil et al, 2012;Dunn et al, 2013) and fish (Herdegen et al, 2014;Lighten et al, 2014b); the CYP7B1 and SPG7 genes involved in the hereditary spastic paraplegia in humans (Schlipf et al, 2011); toll-like receptor genes in New Zealand robin (Petroica australis; Grueber et al, 2012); and the S locus receptor kinase gene involved in plant selfincompatibility in rock cress (Arabidopsis sp. ; Jørgensen et al, 2012).…”

“…The second and very recent approach (Stutz and Bolnick, 2014;Lighten et al, 2014b), rather than applying frequency or similarity criteria to determine whether a given variant is an allele or not, groups variants into clusters based on the similarity of the corresponding sequences and then identify alleles on a cluster by cluster basis rather than on a variant by variant basis. Both these approaches suffer from validation over a very limited number of samples using cloning or duplicate PCRs of the same samples (generally o30 samples, but see Sommer et al, 2013 for a counter example).…”