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The highly polymorphic genes of the major histocompatibility complex (MHC) play a key role in adaptive immunity. Divergent allele advantage, a mechanism of balancing selection, is proposed to contribute to their exceptional polymorphism. It assumes that MHC genotypes with more divergent alleles allow for broader antigen-presentation to immune effector cells, by that increasing immunocompetence. However, the direct correlation between pairwise sequence divergence and the corresponding repertoire of bound peptides has not been studied systematically across different MHC genes. Here, we investigated this relationship for five key classical human MHC genes (human leukocyte antigen; HLA-A, -B, -C, -DRB1, and -DQB1), using allele-specific computational binding prediction to 118,097 peptides derived from a broad range of human pathogens. For all five human MHC genes, the genetic distance between two alleles of a heterozygous genotype was positively correlated with the total number of peptides bound by these two alleles. In accordance with the major antigen-presentation pathway of MHC class I molecules, HLA-B and HLA-C alleles showed particularly strong correlations for peptides derived from intracellular pathogens. Intriguingly, this bias coincides with distinct protein compositions between intra- and extracellular pathogens, possibly suggesting adaptation of MHC I molecules to present specifically intracellular peptides. Eventually, we observed significant positive correlations between an allele’s average divergence and its population frequency. Overall, our results support the divergent allele advantage as a meaningful quantitative mechanism through which pathogen-mediated selection leads to the evolution of MHC diversity.

Functional diversity of the highly polymorphic human leukocyte antigen class I ( HLA -I) genes underlies successful immunologic control of both infectious disease and cancer. The divergent allele advantage hypothesis dictates that an HLA -I genotype with two alleles with sequences that are more divergent enables presentation of more diverse immunopeptidomes 1 – 3 . However, the effect of sequence divergence between HLA -I alleles—a quantifiable measure of HLA -I evolution—on the efficacy of immune checkpoint inhibitor (ICI) treatment for cancer remains unknown. In the present study the germline HLA-I evolutionary divergence (HED) of patients with cancer treated with ICIs was determined by quantifying the physiochemical sequence divergence between HLA -I alleles of each patient’s genotype. HED was a strong determinant of survival after treatment with ICIs. Even among patients fully heterozygous at HLA -I, patients with an HED in the upper quartile respond better to ICIs than patients with a low HED. Furthermore, HED strongly impacts the diversity of tumor, viral and self-immunopeptidomes and intratumoral T cell receptor clonality. Similar to tumor mutation burden, HED is a fundamental metric of diversity at the major histocompatibility complex–peptide complex, which dictates ICI efficacy. The data link divergent HLA allele advantage to immunotherapy efficacy and unveil how ICI response relies on the evolved efficiency of HLA -mediated immunity. The degree of sequence divergence between patient MHC class I alleles influences the response to immune checkpoint blockade therapy independently of tumor mutational burden.

Central players of the adaptive immune system are the groups of proteins encoded in the major histocompatibility complex (MHC), which shape the immune response against pathogens and tolerance to self-peptides. The corresponding genomic region is of particular interest, as it harbors more disease associations than any other region in the human genome, including associations with infectious diseases, autoimmune disorders, cancers, and neuropsychiatric diseases. Certain MHC molecules can bind to a much wider range of epitopes than others, but the functional implication of such an elevated epitope-binding repertoire has remained largely unclear. It has been suggested that by recognizing more peptide segments, such promiscuous MHC molecules promote immune response against a broader range of pathogens. If so, the geographical distribution of MHC promiscuity level should be shaped by pathogen diversity. Three lines of evidence support the hypothesis. First, we found that in pathogen-rich geographical regions, humans are more likely to carry highly promiscuous MHC class II DRB1 alleles. Second, the switch between specialist and generalist antigen presentation has occurred repeatedly and in a rapid manner during human evolution. Third, molecular positions that define promiscuity level of MHC class II molecules are especially diverse and are under positive selection in human populations. Taken together, our work indicates that pathogen load maintains generalist adaptive immune recognition, with implications for medical genetics and epidemiology.

Pathogen-mediated balancing selection is regarded as a key driver of host immunogenetic diversity. A hallmark for balancing selection in humans is the heterozygote advantage at genes of the human leukocyte antigen (HLA), resulting in improved HIV-1 control. However, the actual mechanism of the observed heterozygote advantage is still elusive. HLA heterozygotes may present a broader array of antigenic viral peptides to immune cells, possibly resulting in a more efficient cytotoxic T-cell response. Alternatively, heterozygosity may simply increase the chance to carry the most protective HLA alleles, as individual HLA alleles are known to differ substantially in their association with HIV-1 control. Here, we used data from 6,311 HIV-1-infected individuals to explore the relative contribution of quantitative and qualitative aspects of peptide presentation in HLA heterozygote advantage against HIV. Screening the entire HIV-1 proteome, we observed that heterozygous individuals exhibited a broader array of HIV-1 peptides presented by their HLA class I alleles. In addition, viral load was negatively correlated with the breadth of the HIV-1 peptide repertoire bound by an individual’s HLA variants, particularly at HLA-B. This suggests that heterozygote advantage at HLA-B is at least in part mediated by quantitative peptide presentation. We also observed higher HIV-1 sequence diversity among HLA-B heterozygous individuals, suggesting stronger evolutionary pressure from HLA heterozygosity. However, HLA heterozygotes were also more likely to carry certain HLA alleles, including the highly protective HLA-B*57:01 variant, indicating that HLA heterozygote advantage ultimately results from a combination of quantitative and qualitative effects in antigen presentation.

The major histocompatibility complex (MHC), coding for antigen presenting molecules of the adaptive immune system, represents one of the most polymorphic regions in the vertebrate genome. The exceptional polymorphism, which is potentially maintained by balancing selection under host-parasite coevolution, comprises excessive sequence divergence among alleles as well as ancient allelic lineages that predate species divergence (trans-species polymorphism). Here, the mechanisms that are proposed to maintain such sequence divergence and ancient lineages are investigated. Established computational antigen-binding prediction algorithms, which are based on empirical databases, are employed to determine the overlap in bound antigens among individual MHC class IIB alleles. The results show that genetically more divergent allele pairs experience less overlap and thus present a broader range of potential antigens. These findings support the divergent allele advantage hypothesis and furthermore suggest an evolutionary advantage explaining the maintenance of divergent allelic lineages, that is, trans-species polymorphism. In addressing a quantitative rather than qualitative aspect of MHC alleles, these insights highlight a new direction for future research on MHC evolution.

The patterns of genomic divergence during ecological speciation are shaped by a combination of evolutionary forces. Processes such as genetic drift, local reduction of gene flow around genes causing reproductive isolation, hitchhiking around selected variants, variation in recombination and mutation rates are all factors that can contribute to the heterogeneity of genomic divergence. On the basis of 60 fully sequenced three-spined stickleback genomes, we explore these different mechanisms explaining the heterogeneity of genomic divergence across five parapatric lake and river population pairs varying in their degree of genetic differentiation. We find that divergent regions of the genome are mostly specific for each population pair, while their size and abundance are not correlated with the extent of genome-wide population differentiation. In each pair-wise comparison, an analysis of allele frequency spectra reveals that 25-55% of the divergent regions are consistent with a local restriction of gene flow. Another large proportion of divergent regions (38-75%) appears to be mainly shaped by hitchhiking effects around positively selected variants. We provide empirical evidence that alternative mechanisms determining the evolution of genomic patterns of divergence are not mutually exclusive, but rather act in concert to shape the genome during population differentiation, a first necessary step towards ecological speciation.

The genes of the major histocompatibility complex are the most polymorphic genes in vertebrates, with more than 1,000 alleles described in human populations. How this polymorphism is maintained, however, remains an evolutionary puzzle. Major histocompatibility complex genes have a crucial function in the adaptive immune system by presenting parasite-derived antigens to T lymphocytes. Because of this function, varying parasite-mediated selection has been proposed as a major evolutionary force for maintaining major histocompatibility complex polymorphism. A necessary prerequisite of such a balancing selection process is rapid major histocompatibility complex allele frequency shifts resulting from emerging selection by a specific parasite. Here we show in six experimental populations of sticklebacks, each exposed to one of two different parasites, that only those major histocompatibility complex alleles providing resistance to the respective specific parasite increased in frequency in the next host generation. This result demonstrates experimentally that varying parasite selection causes rapid adaptive evolutionary changes, thus facilitating the maintenance of major histocompatibility complex polymorphism. In vertebrates parasite-mediated selection is thought to maintain polymorphism in MHC genes where specific resistance MHC alleles increase under emerging selection. Here, experimental evidence is shown from six stickleback fish populations that varying parasite selection helps maintain MHC polymorphism.

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Structural and functional variability of human leukocyte antigen (HLA) is the foundation for competent adaptive immune responses against pathogen and tumor antigens as it assures the breadth of the presented immune-peptidome, theoretically sustaining an efficient and diverse T cell response. This variability is presumably the result of the continuous selection by pathogens, which over the course of evolution shaped the adaptive immune system favoring the assortment of a hyper-polymorphic HLA system able to elaborate efficient immune responses. Any genetic alteration affecting this diversity may lead to pathological processes, perturbing antigen presentation capabilities, T-cell reactivity and, to some extent, natural killer cell functionality. A highly variable germline HLA genotype can convey immunogenetic protection against infections, be associated with tumor surveillance or influence response to anti-neoplastic treatments. In contrast, somatic aberrations of HLA loci, rearranging the original germline configuration, theoretically decreasing its variability, can facilitate mechanisms of immune escape that promote tumor growth and immune resistance. The purpose of the present review is to provide a unified and up-to-date overview of the pathophysiological consequences related to the perturbations of the genomic heterogeneity of HLA complexes and their impact on human diseases, with a special focus on cancer.