Definition of Mafa-A and -B haplotypes in pedigreed cynomolgus macaques (Macaca fascicularis)

The major histocompatibility complex (MHC) class I B gene/allelic repertoire was investigated in a pedigreed population of cynomolgus macaques of mixed Indonesian/Malaysian origin. The Mafa-B alleles detected in this cohort are mostly specific for a given geographic area, and only a small number of alleles appears to be shared with other populations. This suggests the fast evolution of Mafa-B alleles due to adaptation to new environments. In contrast to humans, the B locus in Old World monkeys displays extensive copy number variation. The Mafa-B and previously defined -A gene combinations segregate in families and thus allowed the definition of extended haplotypes. In many cases it was possible to assign a particular Mafa-I allele to one of these Mafa-A/B haplotypes as well. The presence of a large number of stable haplotypes in this cohort of animals, which was pedigreed for up to eight generations, looks promising for developing discriminative MHC typing tools that are less cumbersome. Furthermore, the discovery of 53 unreported Mafa-B sequences expands the lexicon of alleles significantly, and may help in understanding the complex organisation of the macaque B region

Genomic plasticity of the MHC class I A region in rhesus macaques: extensive haplotype diversity at the population level as revealed by microsatellites

The Mamu-A genes of the rhesus macaque show different degrees of polymorphism, transcription level variation, and differential haplotype distribution. Per haplotype, usually one “major” transcribed gene is present, A1 (A7), in various combinations with “minor” genes, A2 to A6. In silico analysis of the physical map of a heterozygous animal revealed the presence of similar Mamu-A regions consisting of four duplication units, but with dissimilar positions of the A1 genes on both haplotypes, and in combination with different minor genes. Two microsatellites, D6S2854 and D6S2859, have been selected as potential tools to characterize this complex region. Subsequent analysis of a large breeding colony resulted in the description of highly discriminative patterns, displaying copy number variation in concert with microsatellite repeat length differences. Sequencing and segregation analyses revealed that these patterns are unique for each Mamu-A haplotype. In animals of Indian, Burmese, and Chinese origin, 19, 15, or 9 haplotypes, respectively, could be defined, illustrating the occurrence of differential block duplications and subsequent rearrangements by recombination. The haplotypes can be assigned to 12 unique combinations of genes (region configurations). Although most configurations harbor two transcribed A genes, one or three genes per haplotype are also present. Additionally, haplotypes lacking an A1 gene or with an A1 duplication appear to exist. The presence of different transcribed A genes/alleles in monkeys from various origins may have an impact on differential disease susceptibilities. The high-throughput microsatellite technique will be a valuable tool in animal selection for diverse biomedical research projects

NetMHCpan, a method for MHC class I binding prediction beyond humans.

Binding of peptides to major histocompatibility complex (MHC) molecules is the single most selective step in the recognition of pathogens by the cellular immune system. The human MHC genomic region (called HLA) is extremely polymorphic comprising several thousand alleles, each encoding a distinct MHC molecule. The potentially unique specificity of the majority of HLA alleles that have been identified to date remains uncharacterized. Likewise, only a limited number of chimpanzee and rhesus macaque MHC class I molecules have been characterized experimentally. Here, we present NetMHCpan-2.0, a method that generates quantitative predictions of the affinity of any peptide–MHC class I interaction. NetMHCpan-2.0 has been trained on the hitherto largest set of quantitative MHC binding data available, covering HLA-A and HLA-B, as well as chimpanzee, rhesus macaque, gorilla, and mouse MHC class I molecules. We show that the NetMHCpan-2.0 method can accurately predict binding to uncharacterized HLA molecules, including HLA-C and HLA-G. Moreover, NetMHCpan-2.0 is demonstrated to accurately predict peptide binding to chimpanzee and macaque MHC class I molecules. The power of NetMHCpan-2.0 to guide immunologists in interpreting cellular immune responses in large out-bred populations is demonstrated. Further, we used NetMHCpan-2.0 to predict potential binding peptides for the pig MHC class I molecule SLA-1*0401. Ninety-three percent of the predicted peptides were demonstrated to bind stronger than 500 nM. The high performance of NetMHCpan-2.0 for non-human primates documents the method's ability to provide broad allelic coverage also beyond human MHC molecules. The method is available at http://www.cbs.dtu.dk/services/NetMHCpan