Data from: Family-assisted inference of the genetic architecture of MHC variation
Gaigher, Arnaud et al. (2016), Data from: Family-assisted inference of the genetic architecture of MHC variation, Dryad, Dataset, https://doi.org/10.5061/dryad.rm611
With their direct link to individual fitness, genes of the major histocompatibility complex (MHC) are a popular system to study the evolution of adaptive genetic diversity. However, owing to the highly dynamic evolution of the MHC region, the isolation, characterization and genotyping of MHC genes remain a major challenge. While high-throughput sequencing technologies now provide unprecedented resolution of the high allelic diversity observed at the MHC, in many species, it remains unclear (i) how alleles are distributed among MHC loci, (ii) whether MHC loci are linked or segregate independently and (iii) how much copy number variation (CNV) can be observed for MHC genes in natural populations. Here, we show that the study of allele segregation patterns within families can provide significant insights in this context. We sequenced two MHC class I (MHC-I) loci in 1267 European barn owls (Tyto alba), including 590 offspring from 130 families using Illumina MiSeq technology. Coupled with a high per-individual sequencing coverage (~3000×), the study of allele segregation patterns within families provided information on three aspects of the architecture of MHC-I variation in barn owls: (i) extensive sharing of alleles among loci, (ii) strong linkage of MHC-I loci indicating tandem architecture and (iii) the presence of CNV in the barn owl MHC-I. We conclude that the additional information that can be gained from high-coverage amplicon sequencing by investigating allele segregation patterns in families not only helps improving the accuracy of MHC genotyping, but also contributes towards enhanced analyses in the context of MHC evolutionary ecology.