Neutral and Selective Processes Shape MHC Diversity in Roe Deer in Slovenia

AmpliSAS and AmpliHLA: Web Server and Local Tools for MHC Typing of Non-model Species and Human Using NGS Data

AmpliSAS and AmpliHLA are tools for automatic genotyping of MHC genes from high-throughput sequencing data. AmpliSAS is designed specifically to analyze amplicon sequencing data from non-model species and it is able to perform de novo genotyping without any previous knowledge of the reference alleles. AmpliHLA is a human specific version; it performs HLA typing by comparing sequenced variants against human reference alleles from the IMGT/HLA database. Both tools are available in AmpliSAT web-server as well as scripts for local/server installation. Here we describe the installation and deployment of AmpliSAS and AmpliHLA Perl scripts and dependencies on a local or a server computer. We will show how to run them in the command line using as examples four genotyping protocols: the first two use amplicon sequencing data to genotype the MHC genes of a passerine bird and human respectively; the third and fourth present the HLA typing of a human cell line starting from RNA and exome sequencing data respectively.

Neutral Forces and Balancing Selection Interplay to Shape the Major Histocompatibility Complex Spatial Patterns in the Striped Hamster in Inner Mongolia: Suggestive of Broad-Scale Local Adaptation

BACKGROUND

The major histocompatibility complex (MHC) plays a key role in the adaptive immune response to pathogens due to its extraordinary polymorphism. However, the spatial patterns of MHC variation in the striped hamster remain unclear, particularly regarding the relative contribution of the balancing selection in shaping MHC spatial variation and diversity compared to neutral forces.

METHODS

In this study, we investigated the immunogenic variation of the striped hamster in four wild populations in Inner Mongolia which experience a heterogeneous parasitic burden. Our goal was to identify local adaptation by comparing the genetic structure at the MHC with that at seven microsatellite loci, taking into account neutral processes.

RESULTS

We observed significant variation in parasite pressure among sites, with parasite burden showing a correlation with temperature and precipitation. Molecular analysis revealed a similar co-structure between MHC and microsatellite loci. We observed lower genetic differentiation at MHC loci compared to microsatellite loci, and no correlation was found between the two.

CONCLUSIONS

Overall, these results suggest a complex interplay between neutral evolutionary forces and balancing selection in shaping the spatial patterns of MHC variation. Local adaptation was not detected on a small scale but may be applicable on a larger scale.

Performance Comparison of Different Approaches in Genotyping MHC-DRB: The Contrast between Single-Locus and Multi-Locus Species

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.