Driven by co-evolution with pathogens, host immunity continuously adapts to optimize defence against pathogens within a given environment. Recent advances in genetics, genomics and transcriptomics have enabled a more detailed investigation into how immunogenetic variation shapes the diversity of immune responses seen across domestic and wild animal species. However, a deeper understanding of the diverse molecular mechanisms that shape immunity within and among species is still needed to gain insight into-and generate evolutionary hypotheses on-the ultimate drivers of immunological differences. Here, we discuss current advances in our understanding of molecular evolution underpinning jawed vertebrate immunity. First, we introduce the immunome concept, a framework for characterizing genes involved in immune defence from a comparative perspective, then we outline how immune genes of interest can be identified. Second, we focus on how different selection modes are observed acting across groups of immune genes and propose hypotheses to explain these differences. We then provide an overview of the approaches used so far to study the evolutionary heterogeneity of immune genes on macro and microevolutionary scales. Finally, we discuss some of the current evidence as to how specific pathogens affect the evolution of different groups of immune genes. This review results from the collective discussion on the current key challenges in evolutionary immunology conducted at the ESEB 2021 Online Satellite Symposium: Molecular evolution of the vertebrate immune system, from the lab to natural populations.

• Keywords
• MHC, adaptation, adaptive immunity, evolutionary immunology, genomics, host-parasite interactions, immunogenetics, innate immunity, molecular evolution, vertebrates,
• MeSH
• Adaptive Immunity * genetics   MeSH
• Biological Evolution * MeSH
• Evolution, Molecular MeSH
• Vertebrates genetics   MeSH
• Immunity, Innate genetics   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Research Support, N.I.H., Extramural MeSH

Retinoic acid-inducible gene I (RIG-I) and melanoma differentiation-associated protein 5 (MDA5) are key RNA virus sensors belonging to the RIG-I-like receptor (RLR) family. The activation of the RLR inflammasome leads to the establishment of antiviral state, mainly through interferon-mediated signaling. The evolutionary dynamics of RLRs has been studied mainly in mammals, where rare cases of RLR gene losses were described. By in silico screening of avian genomes, we previously described two independent disruptions of MDA5 in two bird orders. Here, we extend this analysis to approximately 150 avian genomes and report 16 independent evolutionary events of RIG-I inactivation. Interestingly, in almost all cases, these inactivations are coupled with genetic disruptions of RIPLET/RNF135, an ubiquitin ligase RIG-I regulator. Complete absence of any detectable RIG-I sequences is unique to several galliform species, including the domestic chicken (Gallus gallus). We further aimed to determine compensatory evolution of MDA5 in RIG-I-deficient species. While we were unable to show any specific global pattern of adaptive evolution in RIG-I-deficient species, in galliforms, the analyses of positive selection and surface charge distribution support the hypothesis of some compensatory evolution in MDA5 after RIG-I loss. This work highlights the dynamic nature of evolution in bird RNA virus sensors.

• Keywords
• avian genome, gene loss, innate immunity, viral sensors,
• MeSH
• Antiviral Agents MeSH
• DEAD Box Protein 58 genetics   metabolism   MeSH
• Immunity, Innate MeSH
• Birds virology   MeSH
• RNA Helicases MeSH
• RNA Viruses * physiology   MeSH
• RNA * MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antiviral Agents MeSH
• DEAD Box Protein 58 MeSH
• RNA Helicases MeSH
• RNA * MeSH

In vertebrates, cannabinoids modulate neuroimmune interactions through two cannabinoid receptors (CNRs) conservatively expressed in the brain (CNR1, syn. CB1) and in the periphery (CNR2, syn. CB2). Our comparative genomic analysis indicates several evolutionary losses in the CNR2 gene that is involved in immune regulation. Notably, we show that the CNR2 gene pseudogenized in all parrots (Psittaciformes). This CNR2 gene loss occurred because of chromosomal rearrangements. Our positive selection analysis suggests the absence of any specific molecular adaptations in parrot CNR1 that would compensate for the CNR2 loss in the modulation of the neuroimmune interactions. Using transcriptomic data from the brains of birds with experimentally induced sterile inflammation we highlight possible functional effects of such a CNR2 gene loss. We compare the expression patterns of CNR and neuroinflammatory markers in CNR2-deficient parrots (represented by the budgerigar, Melopsittacus undulatus and five other parrot species) with CNR2-intact passerines (represented by the zebra finch, Taeniopygia guttata). Unlike in passerines, stimulation with lipopolysaccharide resulted in neuroinflammation in the parrots linked with a significant upregulation of expression in proinflammatory cytokines (including interleukin 1 beta (IL1B) and 6 (IL6)) in the brain. Our results indicate the functional importance of the CNR2 gene loss for increased sensitivity to brain inflammation.

• Keywords
• avian immunology, cannabinoid receptor pseudogenization, cannabinoid receptors, gene loss, neural inflammation, neuroimmunology,
• MeSH
• Parrots * genetics   MeSH
• Receptors, Cannabinoid MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Receptors, Cannabinoid MeSH

Penguins (Sphenisciformes) are an iconic order of flightless, diving seabirds distributed across a large latitudinal range in the Southern Hemisphere. The extensive area over which penguins are endemic is likely to have fostered variation in pathogen pressure, which in turn will have imposed differential selective pressures on the penguin immune system. At the front line of pathogen detection and response, the Toll-like receptors (TLRs) provide insight into host evolution in the face of microbial challenge. TLRs respond to conserved pathogen-associated molecular patterns and are frequently found to be under positive selection, despite retaining specificity for defined agonist classes. We undertook a comparative immunogenetics analysis of TLRs for all penguin species and found evidence of adaptive evolution that was largely restricted to the cell surface-expressed TLRs, with evidence of positive selection at, or near, key agonist-binding sites in TLR1B, TLR4, and TLR5. Intriguingly, TLR15, which is activated by fungal products, appeared to have been pseudogenized multiple times in the Eudyptes spp., but a full-length form was present as a rare haplotype at the population level. However, in vitro analysis revealed that even the full-length form of Eudyptes TLR15 was nonfunctional, indicating an ancestral cryptic pseudogenization prior to its eventual disruption multiple times in the Eudyptes lineage. This unusual pseudogenization event could provide an insight into immune adaptation to fungal pathogens such as Aspergillus, which is responsible for significant mortality in wild and captive bird populations.

• Keywords
• Toll-like receptors, avian immunology, host–pathogen interaction, immunogenetics, pseudogenization, wildlife disease,
• MeSH
• Evolution, Molecular MeSH
• Selection, Genetic MeSH
• Spheniscidae * genetics   MeSH
• Toll-Like Receptors genetics   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Toll-Like Receptors MeSH

Two key cytosolic receptors belonging to the retinoic acid-inducible gene I (RIG-I)-like receptor (RLR) family sense the viral RNA-derived danger signals: RIG-I and melanoma differentiation-associated protein 5 (MDA5). Their activation establishes an antiviral state by downstream signaling that ultimately activates interferon-stimulated genes (ISGs). While in rare cases RIG-I gene loss has been detected in mammalian and avian species, most notably in the chicken, MDA5 pseudogenization has only been detected once in mammals. We have screened over a hundred publicly available avian genome sequences and describe an independent disruption of MDA5 in two unrelated avian lineages, the storks (Ciconiiformes) and the rallids (Gruiformes). The results of our RELAX analysis confirmed the absence of negative selection in the MDA5 pseudogene. In contrast to our prediction, we have shown, using multiple dN/dS-based approaches, that the MDA5 loss does not appear to have resulted in any compensatory evolution in the RIG-I gene, which may partially share its ligand-binding specificity. Together, our results indicate that the MDA5 pseudogenization may have important functional effects on immune responsiveness in these two avian clades.

• Keywords
• avian genome, gene loss, innate immunity, viral sensors,
• MeSH
• DEAD Box Protein 58 chemistry   genetics   immunology   MeSH
• Gene Deletion * MeSH
• Phylogeny MeSH
• Humans MeSH
• Models, Molecular MeSH
• Immunity, Innate MeSH
• Pseudogenes MeSH
• Avian Proteins chemistry   genetics   immunology   MeSH
• Birds classification   genetics   immunology   MeSH
• Amino Acid Sequence MeSH
• Sequence Alignment MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DEAD Box Protein 58 MeSH
• Avian Proteins MeSH

Immune genes show remarkable levels of adaptive variation shaped by pathogen-mediated selection. Compared to humans, however, population polymorphism in animals has been understudied. To provide an insight into immunogenetic diversity in birds, we sequenced complete protein-coding regions of all Toll-like receptor (TLR) genes with direct orthology between mammals and birds (TLR3, TLR4, TLR5 and TLR7) in 110 domestic chickens from 25 breeds and compared their variability with a corresponding human dataset. Chicken TLRs (chTLRs) exhibit on average nine-times higher nucleotide diversity than human TLRs (hTLRs). Increased potentially functional non-synonymous variability is found in chTLR ligand-binding ectodomains. While we identified seven sites in chTLRs under positive selection and found evidence for convergence between alleles, no selection or convergence was detected in hTLRs. Up to six-times more alleles were identified in fowl (70 chTLR4 alleles vs. 11 hTLR4 alleles). In chTLRs, high numbers of alleles are shared between the breeds and the allelic frequencies are more equal than in hTLRs. These differences may have an important impact on infectious disease resistance and host-parasite co-evolution. Though adaptation through high genetic variation is typical for acquired immunity (e.g. MHC), our results show striking levels of intraspecific polymorphism also in poultry innate immune receptors.

• MeSH
• Gene Frequency MeSH
• Genetic Variation * MeSH
• Chickens * MeSH
• Humans MeSH
• Sequence Analysis, DNA MeSH
• Toll-Like Receptors genetics   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH
• Names of Substances
• Toll-Like Receptors MeSH

Toll-like receptors (TLRs) are key sensor molecules in vertebrates triggering initial phases of immune responses to pathogens. The avian TLR family typically consists of ten receptors, each adapted to distinct ligands. To understand the complex evolutionary history of each avian TLR, we analyzed all members of the TLR family in the whole genome assemblies and target sequence data of 63 bird species covering all major avian clades. Our results indicate that gene duplication events most probably occurred in TLR1 before synapsids diversified from sauropsids. Unlike mammals, ssRNA-recognizing TLR7 has duplicated independently in several avian taxa, while flagellin-sensing TLR5 has pseudogenized multiple times in bird phylogeny. Our analysis revealed stronger positive, diversifying selection acting in TLR5 and the three-domain TLRs (TLR10 [TLR1A], TLR1 [TLR1B], TLR2A, TLR2B, TLR4) that face the extracellular space and bind complex ligands than in single-domain TLR15 and endosomal TLRs (TLR3, TLR7, TLR21). In total, 84 out of 306 positively selected sites were predicted to harbor substitutions dramatically changing the amino acid physicochemical properties. Furthermore, 105 positively selected sites were located in the known functionally relevant TLR regions. We found evidence for convergent evolution acting between birds and mammals at 54 of these sites. Our comparative study provides a comprehensive insight into the evolution of avian TLR genetic variability. Besides describing the history of avian TLR gene gain and gene loss, we also identified candidate positions in the receptors that have been likely shaped by direct molecular host-pathogen coevolutionary interactions and most probably play key functional roles in birds.

• Keywords
• adaptive evolution, amino acid physicochemical properties, convergence, pattern recognition receptors, positive selection, pseudogene,
• MeSH
• Gene Duplication * MeSH
• Evolution, Molecular * MeSH
• Pseudogenes MeSH
• Birds genetics   MeSH
• Amino Acid Sequence MeSH
• Selection, Genetic * MeSH
• Toll-Like Receptors genetics   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Comparative Study MeSH
• Names of Substances
• Toll-Like Receptors MeSH

Toll-like receptors (TLRs) are a cornerstone of vertebrate innate immunity. In this study, we identified orthologues of TLR4, TLR5 and TLR7 (representing both bacterial- and viral-sensing TLRs) in the grey partridge (Perdix perdix), a European Galliform game bird species. The phylogeny of all three TLR genes follows the known phylogeny of Galloanserae birds, placing grey partridge TLRs (PePeTLRs) in close proximity to their turkey and pheasant orthologues. The predicted proteins encoded by the PePeTLR genes were 843, 862-863 and 1,047 amino acids long, respectively, and clearly showed all TLR structural features. To verify functionality in these genes we mapped their tissue-expression profiles, revealing generally high PePeTLR4 and PePeTLR5 expression in the thymus and absence of PePeTLR4 and PePeTLR7 expression in the brain. Using 454 next-generation sequencing, we then assessed genetic variation within these genes for a wild grey partridge population in the Czech Republic, EU. We identified 11 nucleotide substitutions in PePeTLR4, eight in PePeTLR5 and six in PePeTLR7, resulting in four, four and three amino acid replacements, respectively. Given their locations and chemical features, most of these non-synonymous substitutions probably have a minor functional impact. As the intraspecific genetic variation of the three TLR genes was low, we assume that either negative selection or a bottleneck may have reduced TLR population variability in this species.

• MeSH
• Gene Expression MeSH
• Phylogeny MeSH
• Galliformes classification   genetics   MeSH
• Genetic Variation * MeSH
• Protein Conformation MeSH
• Evolution, Molecular MeSH
• Models, Molecular MeSH
• Organ Specificity MeSH
• Toll-Like Receptor 4 chemistry   genetics   MeSH
• Toll-Like Receptor 5 chemistry   genetics   MeSH
• Toll-Like Receptor 7 chemistry   genetics   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Toll-Like Receptor 4 MeSH
• Toll-Like Receptor 5 MeSH
• Toll-Like Receptor 7 MeSH

BACKGROUND: Toll-like receptors (TLR) are essential activators of the innate part of the vertebrate immune system. In this study, we analysed the interspecific variability of three TLR (bacterial-sensing TLR4 and TLR5 and viral-sensing TLR7) within the Galloanserae bird clade, investigated their phylogeny, assessed their structural conservation and estimated site-specific selection pressures. RESULTS: Physiochemical properties varied according to the TLR analysed, mainly with regards to the surface electrostatic potential distribution. The predicted ligand-binding features (mainly in TLR4 and TLR5) differed between the avian proteins and their fish and mammalian counterparts, but also varied within the Galloanserae birds. We identified 20 positively selected sites in the three TLR, among which several are topologically close to ligand-binding sites reported for mammalian and fish TLR. We described 26, 28 and 25 evolutionarily non-conservative sites in TLR4, TLR5 and TLR7, respectively. Thirteen of these sites in TLR4, and ten in TLR5 were located in functionally relevant regions. The variability appears to be functionally more conserved for viral-sensing TLR7 than for the bacterial-sensing TLR. Amino-acid positions 268, 270, 343, 383, 444 and 471 in TLR4 and 180, 183, 209, 216, 264, 342 and 379 in TLR5 are key candidates for further functional research. CONCLUSIONS: Host-pathogen co-evolution has a major effect on the features of host immune receptors. Our results suggest that avian and mammalian TLR may be differentially adapted to pathogen-derived ligand recognition. We have detected signatures of positive selection even within the Galloanserae lineage. To our knowledge, this is the first study to depict evolutionary pressures on Galloanserae TLR and to estimate the validity of current knowledge on TLR function (based on mammalian and chicken models) for non-model species of this clade.

• MeSH
• Anseriformes genetics   MeSH
• Galliformes genetics   MeSH
• Humans MeSH
• Evolution, Molecular * MeSH
• Mice MeSH
• Computer Simulation MeSH
• Sequence Analysis, Protein MeSH
• Protein Structure, Tertiary MeSH
• Toll-Like Receptor 4 genetics   MeSH
• Toll-Like Receptor 5 genetics   MeSH
• Toll-Like Receptor 7 genetics   MeSH
• Binding Sites MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Mice MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Toll-Like Receptor 4 MeSH
• Toll-Like Receptor 5 MeSH
• Toll-Like Receptor 7 MeSH