Abstract
Simple SummaryGenes of the major histocompatibility complex (MHC) have been extensively used for estimation of genetic diversity in wild vertebrate populations on account of their exceptionally high polymorphism and key role in pathogen resistance. The complexity of the MHC region varies greatly, even between closely related species, and consequently influences the choice of genotyping strategy. Here, we compared and evaluated MHC genotyping in a single-locus species, the roe deer, and red deer, a species with multiple loci, by utilisation of molecular cloning and two high-throughput sequencing platforms (Illumina and Ion Torrent). For high-throughput data processing, we applied a web version of the Amplicon Sequencing Analysis Tools that analyses the first 5000 reads per sample as well as its locally installed script that analyses a total number of reads per sample, up to a maximum of 200,000. We observed genotype discrepancies only in red deer, with Illumina sequencing scoring the maximum number of detected alleles, regardless of the number of reads used for data analysis. This study facilitates the adoption of an optimal strategy for MHC genotyping in wild mammals that does not include complex bioinformatic analyses.Major histocompatibility complex (MHC) genes are widely recognised as valuable markers for wildlife genetic studies given their extreme polymorphism and functional importance in fitness-related traits. Newly developed genotyping methods, which rely on the use of next-generation sequencing (NGS), are gradually replacing traditional cloning and Sanger sequencing methods in MHC genotyping studies. Allele calling in NGS methods remains challenging due to extreme polymorphism and locus multiplication in the MHC coupled with allele amplification bias and the generation of artificial sequences. In this study, we compared the performance of molecular cloning with Illumina and Ion Torrent NGS sequencing in MHC-DRB genotyping of single-locus species (roe deer) and species with multiple DRB loci (red deer) in an attempt to adopt a reliable and straightforward method that does not require complex bioinformatic analyses. Our results show that all methods work similarly well in roe deer, but we demonstrate non-consistency in results across methods in red deer. With Illumina sequencing, we detected a maximum number of alleles in 10 red deer individuals (42), while other methods were somewhat less accurate as they scored 69–81% of alleles detected with Illumina sequencing.
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