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ScienceDirect Human genome variability, natural selection and infectious diseases Matteo Fumagalli1 and Manuela Sironi2 The recent availability of large-scale sequencing DNA data allowed researchers to investigate how genomic variation is distributed among populations. While demographic factors explain genome-wide population genetic diversity levels, scans for signatures of natural selection pinpointed several regions under non-neutral evolution. Recent studies found an enrichment of immune-related genes subjected to natural selection, suggesting that pathogens and infectious diseases have imposed a strong selective pressure throughout human history. Pathogen-mediated selection often targeted regulatory sites of genes belonging to the same biological pathway. Results from these studies have the potential to identify mutations that modulate infection susceptibility by integrating a population genomic approach with molecular immunology data and large-scale functional annotations. Addresses 1 UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, United Kingdom 2 Bioinformatics – Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy Corresponding author: Fumagalli, Matteo ([email protected])
Current Opinion in Immunology 2014, 30:9–16 This review comes from a themed issue on Immunogenetics and transplantation Edited by Luis B Barreiro and Lluis Quintana-Murci
http://dx.doi.org/10.1016/j.coi.2014.05.001 0952-7915/# 2014 Published by Elsevier Ltd. All rights reserved.
Introduction Over the last couple of years, our understanding of human genetic diversity has dramatically increased. The introduction of high-throughput sequencing machines, along with the development of sophisticated analytical tools, has allowed researchers to obtain and analyze unprecedentedly large amount of DNA data [1,2]. Here we discuss how these datasets can be exploited to elucidate the role evolution and natural selection played in shaping the distribution of genetic diversity across human populations. We review currently employed methods to detect signatures of natural selection in the www.sciencedirect.com
human genome, and discuss notable examples of pathogen-driven selective pressure and their implications in terms of human immunology and infectious disease epidemiology.
Population genomic variability Whole-genome sequencing of multiple individuals led to the identification of common and rare genetic variants in the human genome. The 1000 Genomes Project (1000G) identified and characterized almost 40 millions Single Nucleotide Polymorphisms (SNPs) by DNA sequencing of more than 1000 individuals belonging to 15 different populations [3]. This study builds upon previous projects aiming at characterizing human genetic variation, such as the HapMap Consortium [4], the HGDP-CEPH Panel resource [5], and the NHLBI-Exome Sequencing Project [6]. These datasets can be analyzed to infer which factors shaped human genome diversity and phenotypic variation. Patterns of worldwide genetic variation are compatible with an origin of modern humans in Africa, followed by a series of expansions, bottlenecks, and migrations between populations [7,8]. The observation of an overall decay of genetic diversity along axes of migration [9], together with a negative correlation between nucleotide variation and geographical distance from Africa [5] (Figure 1), suggests that demographic events played a major role shaping worldwide patterns of human genetic diversity. More recently, availability of sequenced DNA from ancient humans [10,11] and archaic hominids [12,13] elucidated past admixture events and possible colonization routes. Nonetheless, during this period of migratory events, humans have been exposed to new environments, namely to different climate conditions, pathogens, and food availability, to which they have been forced to adapt, through the action of natural selection. Lactase persistence is one of the most notable examples of genetic adaptation, with a polymorphism promoting the expression of LCT, the gene encoding the enzyme lactase, being at high frequency in European populations and mostly absent elsewhere [14]. Another stunning case of natural selection in the human genome is represented by adaptation to high altitude in Tibetans. A SNP in EPAS1, a gene related to response to hypoxia and hemoglobin concentration, exhibits a dramatic difference in frequency between Tibetans and Han Chinese [15], despite the two populations being genetically close to Current Opinion in Immunology 2014, 30:9–16
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Figure 1
Decay of genetic diversity from Africa
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Decay of nucleotide diversity with geographical distance from central Africa. For each country, the average nucleotide diversity is plotted against the geographical distance from central Africa. We analyzed allele frequencies of more than 500 000 SNPs in 20 countries, using the HGDP-CEPH (http:// www.cephb.fr/en/hgdp) and HapMap (http://hapmap.ncbi.nlm.nih.gov/) databases. We calculated the shortest distance between each country and central Africa on landmass routes.
each other. Further examples of genes with strong evidence of being subjected to natural selection are reviewed and discussed in [16,17].
Genomic signatures of natural selection Detecting loci in the human genome that have been targeted by natural selection has a two-fold importance. Firstly, we can infer which selective events have shaped genome diversity most, and learn about past evolutionary events that characterized human history. Secondly, loci under natural selection are more likely to harbor functional variants, and therefore can be prioritized in screenings for association with susceptibility or resistance to diseases and infections. Indeed, genetic variants that are favorable to the carrier tend to increase in frequency in the population (a process known as positive selection), while deleterious mutations tend to be eliminated (negative selection). Current Opinion in Immunology 2014, 30:9–16
Comparing orthologous genes among primate species is an effective approach to detect positive selection acting over long evolutionary timescales. On the other hand, comparing genetic variation within human populations may shed light onto more recent adaptive events. Such rapid selective pressures can shift allele frequencies of SNPs in proximity of the selected allele, causing a local reduction of nucleotide diversity (a phenomenon known as selective sweep). Various parameters, including the strength of selection, time of onset of the beneficial mutation, current allele frequency of targeted variant, and recombination rate, affect the extent of genetic variation reduction around the selected site (Figure 2). Over the last years, many genome-wide scans for selection have been performed by looking at regions with a reduction of haplotype diversity and increased homozygosity [18,19,20]. Power to detect selection can be gained www.sciencedirect.com
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Figure 2
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Reduction of haplotype diversity around a site under positive selection. Levels of haplotype diversity along 300 kb regions are shown for different values of selection coefficient and current allele frequency of selected allele. Dotted line shows the location of the site under positive selection. We simulated 80 chromosomes using the software msms (http://www.mabs.at/ewing/msms) assuming a constant population size model and realistic values for human mutation rate, recombination rate, and effective population size. For each scenario, we computed a regressed line across 200 simulations. Scaled haplotype diversity was calculated with the nSL statistic [19], which measures the ratio of diversity between haplotypes carrying the derived allele and haplotypes carrying the ancestral allele. We performed a sliding window analysis and recorded the minimum value of nSL for each 20 kb window.
by investigating allelic or haplotypic differentiation between populations, through derivation of fixation index statistics (F ST, e.g. [21,22]) or more complex metrics [23,24]. Commonly used methods to detect selection in the genome are reviewed and described in [25,26]. A promising approach to increase the sensitivity of selection scans is to combine multiple methods. The Composite of Multiple Signals (CMS) metric combines several independent statistics into a unique score [27]. CMS has been used to identify roughly 100 putatively adaptive changes in the human genome, which could be then characterized through functional experiments [28]. In 2011, Hernandez and coworkers suggested that classic selective sweeps were rare events in recent human www.sciencedirect.com
evolution [29]. Since populations shared a common history, it is likely that mutations already present in the population become advantageous in a new environment. Selection from standing variation leaves complex and cryptic genomic features [30], which can be detected through simulations-based techniques [31]. Correlating population allele frequencies with environmental variables is an additional strategy to identify patterns of local adaptation [32]. Several human traits are distributed according to geographical clines, and may reflect the specific environmental conditions that acted as selective pressure. For instance, Prugnolle and coworkers firstly showed that alleles frequencies at HLA class I genes correlate with pathogen diversity, suggesting pathogen-driven selection acting on immune-related Current Opinion in Immunology 2014, 30:9–16
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genes [33]. Several methods have been proposed to point out variants that correlate with environments, correcting for the neutral effects of human demography [34,35,36]. Lastly, balancing selection is a process that maintains variation within populations, when heterozygotes have a selective advantage over homozygotes, the fitness of an allele is related to its frequency in the population, or different alleles are favored in changing environments. Genome-wide scans for balancing selection highlighted regions with increased levels of polymorphisms and intermediate allele frequency variants [37], and the presence of shared SNPs between humans and chimpanzee [38]. Empirical methods can be used to distinguish between the effects of neutral demographic factors on patterns of genetic variation and the action of natural selection on targeted loci. This approach takes advantage of the fact that while demography affects the whole genome, natural selection affects variation at single targeted regions. Ranked lists of candidate loci under selection can then be subjected to analysis for enriched biological processes. Alternatively, demographic models that incorporate realistic histories for human evolution [8] can be exploited to calculate the expected amount of genetic variation under neutrality. Genome-wide scans for signatures of natural selection in the human genome pinpointed several biological pathways (e.g. metabolism, pigmentation, and immune system) enriched with genes under non-neutral evolution, reflecting genetic adaptation to environments and lifestyle. Nonetheless, several recent studies have confirmed an old hypothesis whereby infectious agents have exerted an exceptionally strong selective pressure on human populations and contributed to the current genetic diversity at many genes (e.g. [39]).
The selective pressure exerted by infections The history of human societies is punctuated by records of deadly epidemics. The Black Death of the 14th century killed approximately 50 million people in Europe and Asia, and the Spanish flu of 1918–1919, which likely represented the deadliest pandemic recorded in history, killed an estimated 50–100 million people throughout the world [40]. Events of such proportion are thought to be typical of large, highly interconnected modern societies, and possibly appeared only after the Neolithic transition. Nonetheless, pathogens that establish life-long infections, sexually transmitted agents, as well as a plethora of parasites daunted pre-agricultural societies. Indeed, humans have been infected with Helicobacter pylori for at least 88 000–116 000 years [41] and the pattern of genetic diversity for H. pylori strains mirrors that observed in human populations, indicating an intimate host–pathogen association [42]. Likewise, the Mycobacterium tuberculosis complex (MBTC), which caused 20% of all human deaths Current Opinion in Immunology 2014, 30:9–16
in the Western world between the 17th and 19th centuries, emerged about 70 000 years ago in Africa, accompanied human migrations throughout the planet, and expanded as a consequence of increased human population density in the Neolithic [43]. In line with these observations, several reports have indicated that both genes directly involved in immune response and, more generally, loci encoding proteins that interact with microbial components (e.g. erythrocyte surface molecules that modulate binding of Plasmodium) have been targeted by natural selection in human populations (see [44] for a comprehensive review). In particular, population genetics approaches have been instrumental in dissecting the evolutionary history and genetic diversity spectrum at innate immunity receptors and effectors, which represent the foremost line of defense against infections. Toll-like receptors (TLRs), for example, experienced selective constraint both in human [45] and in great ape populations [46], with endosomal TLRs evolving under the strongest purifying selection in our species [45]. Although with different strength, purifying also shaped genetic diversity at molecular adaptors that transduce TLR signaling [47], as well as at RIG-I-like [48], NOD-like [49], and AIM2-like receptors [50]. Nonetheless, extensive analyses (see [51] for an exhaustive review) revealed that instances of selective sweeps could also be detected at these loci either worldwide (e.g. at MYD88 and SARM1) or in specific populations (e.g. at IFIH1, NLRP14, and the TLR10-TLR1-TLR6 gene cluster) [45,47,48,49,52], indicating complex evolutionary scenarios and candidate genetic modulators of immunologic phenotypes. Similarly, Manry et al. [53] provided a thorough analysis of interferon (IFN) genes in human populations; their analysis revealed distinct evolutionary scenarios, with some IFN genes being strongly constrained (e.g. IFNG) and others accumulating nonsense and missense variants at high frequency (e.g. IFNA10, IFNE). Interestingly, the Authors were also able to detect variants targeted by positive selection in Asian and European populations at IL28B, IL28A, and IL29. Providing strong evidence for the conundrum that selected variants modulate infectious disease phenotypes, the selected polymorphisms described by Manry et al. [53] in IL28B have been associated with the spontaneous clearance of HCV [54]. Instances of selective sweeps restricted to one or few populations clearly point to locally exerted selective pressure – for e the presence of specific pathogens in a given geographic location. Recently, populations with different genetic ancestry such as Europeans and Rroma, exposed to the same environment for at least 1000 years, were shown to display signals of convergent evolution at immune response genes [55]. Specifically, the TLR1/ TLR6/TLR10 gene cluster accounted for one of the strongest signals and the authors suggested that bubonic www.sciencedirect.com
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Figure 3
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Schematic representation of MHC I antigen processing and presentation. Molecules involved in APC (antigen presenting cell)-T cell interaction are also shown. Pathway components are designated using official gene names (excluding MHC I and T cell receptor, TCR) and color-coded according to their selective pattern in humans. Genes showing signatures of selective sweeps are shown in red, whereas balancing selection targets are depicted in orange. Genes are shown in green if no selection signals were detected or reported.
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plague might have represented the underlying pressure [55]. Likewise, Karlsson et al. [56] performed a genome-wide scan of natural selection in a Bangladeshi population living in the Ganges River Delta region, where Vibrio cholerae infection is thought to have represented an extremely strong selective pressure for millennia. Their CMS approach revealed a number of selective sweep candidates with enrichment for potassium channel genes involved in chloride secretion and for nuclear factor kB (NF-kB) signaling components [56]. Similarly to the IFN analysis [53], this study provides a nice example of the complementary between evolutionary genetics and infectious disease epidemiology: the Authors show that a number of the positively selected variants do confer increased resistance to cholera infection (or associate with a milder disease). Interestingly, Karlsson et al. [56] also noted an overlap between genes selected by V. cholerae and those involved in inflammatory bowel disease (IBD). Other studies reported that a proportion of IBD loci represented targets of pathogen-driven selection [57,58,59], suggesting that adaptation to infection contributed to the shaping of genetic diversity at loci that participate in systemic and mucosal immunity, resulting in the spread or maintenance of IBD susceptibility loci. Similar considerations might apply to other immunemediated diseases [44,60,61,62], indicating that the long interaction between humans and their pathogens has implications for traits and diseases not directly related to infection. Also, the Karlsson et al.’s study [56] epitomizes the concept whereby different genes may be targeted by the same selective pressure because they impinge on a common molecular pathway, the NF-kB signaling pathway in the case of cholera. Recently, Daub et al. [63] have applied an F ST- and pathway-based approach to search for signals of polygenic adaptation. In line with the idea that pathogens represented a major selective pressure for human populations, the authors found that most pathways enriched for selection signals are directly or indirectly involved in immune response. Other authors [60,64] have recently analyzed pathways or gene sets of central importance to immune response such as T-cell activation and antigen processing and presentation. By combining different selection tests, Forni et al. [60,64] found signals to be pervasive in these pathways and to be accounted for by both balancing and positive selection (Figure 3). In several cases a continuum was also noted, with the same genes having been targeted by selection both during mammalian evolution and in the more recent history of humans, indicating their long-lasting interaction with pathogens. Forni and coworkers made use of the low-coverage 1000G data, allowing fine mapping of selection signals [60,64]. Current Opinion in Immunology 2014, 30:9–16
Although they identified some nonsynonymous variants to represent selection targets, most detected signals were located in noncoding regions with a likely regulatory function. A similar observation has been reported by Grossman et al. [28], who applied the CMS test to the 1000G data. The authors identified missense SNPs as selection targets (including one in TLR5 that affects the response to bacterial flagellin), but most signals were noncoding and likely regulatory in nature. Overall, these analyses indicate that regulatory changes played a pivotal role in recent human evolution and most likely involved a number of immune response loci. Forni and Grossman integrated their selection signals with large-scale functional annotations of regulatory regions and eQTL data, but a proportion of selected variants remained uncharacterized [28,60,64]. Very recently, two groups [65,66] exposed human monocyte/dendritic cells to bacterial or viral stimuli and identified context-specific eQTLs. Their analyses detected hundreds of stimulus-regulated genes and revealed that many regulatory variants display functionality only after stimulation. Also, a number of context-specific eQTLs were associated to autoimmune or infectious disease loci identified by genome-wide association studies.
Conclusions The context-specific eQTLs mentioned above, as well as other variants that will hopefully emerge from similar approaches in different immune cell types, clearly represent extremely good candidates as genetic modulators of susceptibility to infection and as natural selection targets, possibly accounting for some of the still unexplained selection signals. Indeed, integration of different sets of large-scale genomic data and of distinct analysis methodologies holds the promise to shed light on the past, present and future scenarios of human-pathogen interactions.
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51. Quintana-Murci L, Clark AG: Population genetic tools for dissecting innate immunity in humans. Nat Rev Immunol 2013, 13:280-293. A comprehensive review on the evolutionary forces shaping innate immune response genes with several useful insights for epidemiological and clinical immunology.
62. Raj T, Kuchroo M, Replogle JM, Raychaudhuri S, Stranger BE, De Jager PL: Common risk alleles for inflammatory diseases are targets of recent positive selection. Am J Hum Genet 2013, 92:517-529.
52. Fumagalli M, Cagliani R, Riva S, Pozzoli U, Biasin M, Piacentini L, Comi GP, Bresolin N, Clerici M, Sironi M: Population genetics of IFIH1: ancient population structure, local selection and implications for susceptibility to type 1 diabetes. Mol Biol Evol 2010, 27:2555-2566. 53. Manry J, Laval G, Patin E, Fornarino S, Itan Y, Fumagalli M, Sironi M, Tichit M, Bouchier C, Casanova JL et al.: Evolutionary genetic dissection of human interferons. J Exp Med 2011, 208:2747-2759. A population genetics study of IFN genes in humans, which describes distinct evolutionary trajectories for different IFN types and provides clues on the genetic determinants of antiviral response. 54. Thomas DL, Thio CL, Martin MP, Qi Y, Ge D, O’Huigin C, Kidd J, Kidd K, Khakoo SI, Alexander G et al.: Genetic variation in IL28B and spontaneous clearance of hepatitis C virus. Nature 2009, 461:798-801. 55. Laayouni H, Oosting M, Luisi P, Ioana M, Alonso S, Ricano Ponce I, Trynka G, Zhernakova A, Plantinga TS, Cheng SC et al.:
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63. Daub JT, Hofer T, Cutivet E, Dupanloup I, Quintana-Murci L, Robinson-Rechavi M, Excoffier L: Evidence for polygenic adaptation to pathogens in the human genome. Mol Biol Evol 2013, 30:1544-1558. 64. Forni D, Cagliani R, Tresoldi C, Pozzoli U, De Gioia L, Filippi G, Riva S, Menozzi G, Colleoni M, Biasin M et al.: An evolutionary analysis of antigen processing and presentation across different timescales reveals pervasive selection. PLoS Genet 2014, 10:e1004189. 65. Fairfax BP, Humburg P, Makino S, Naranbhai V, Wong D, Lau E, Jostins L, Plant K, Andrews R, McGee C, Knight JC: Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 2014, 343:1246949. Identification of context-specific eQTLs in monocytes. 66. Lee MN, Ye C, Villani AC, Raj T, Li W, Eisenhaure TM, Imboywa SH, Chipendo PI, Ran FA, Slowikowski K et al.: Common genetic variants modulate pathogen-sensing responses in human dendritic cells. Science 2014, 343:1246980. Identification of context-specific eQTLs in dendritic cells.
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ScienceDirect Human genome variability, natural selection and infectious diseases Matteo Fumagalli1 and Manuela Sironi2 The recent availability of large-scale sequencing DNA data allowed researchers to investigate how genomic variation is distributed among populations. While demographic factors explain genome-wide population genetic diversity levels, scans for signatures of natural selection pinpointed several regions under non-neutral evolution. Recent studies found an enrichment of immune-related genes subjected to natural selection, suggesting that pathogens and infectious diseases have imposed a strong selective pressure throughout human history. Pathogen-mediated selection often targeted regulatory sites of genes belonging to the same biological pathway. Results from these studies have the potential to identify mutations that modulate infection susceptibility by integrating a population genomic approach with molecular immunology data and large-scale functional annotations. Addresses 1 UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, United Kingdom 2 Bioinformatics – Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy Corresponding author: Fumagalli, Matteo ([email protected])
Current Opinion in Immunology 2014, 30:9–16 This review comes from a themed issue on Immunogenetics and transplantation Edited by Luis B Barreiro and Lluis Quintana-Murci
http://dx.doi.org/10.1016/j.coi.2014.05.001 0952-7915/# 2014 Published by Elsevier Ltd. All rights reserved.
Introduction Over the last couple of years, our understanding of human genetic diversity has dramatically increased. The introduction of high-throughput sequencing machines, along with the development of sophisticated analytical tools, has allowed researchers to obtain and analyze unprecedentedly large amount of DNA data [1,2]. Here we discuss how these datasets can be exploited to elucidate the role evolution and natural selection played in shaping the distribution of genetic diversity across human populations. We review currently employed methods to detect signatures of natural selection in the www.sciencedirect.com
human genome, and discuss notable examples of pathogen-driven selective pressure and their implications in terms of human immunology and infectious disease epidemiology.
Population genomic variability Whole-genome sequencing of multiple individuals led to the identification of common and rare genetic variants in the human genome. The 1000 Genomes Project (1000G) identified and characterized almost 40 millions Single Nucleotide Polymorphisms (SNPs) by DNA sequencing of more than 1000 individuals belonging to 15 different populations [3]. This study builds upon previous projects aiming at characterizing human genetic variation, such as the HapMap Consortium [4], the HGDP-CEPH Panel resource [5], and the NHLBI-Exome Sequencing Project [6]. These datasets can be analyzed to infer which factors shaped human genome diversity and phenotypic variation. Patterns of worldwide genetic variation are compatible with an origin of modern humans in Africa, followed by a series of expansions, bottlenecks, and migrations between populations [7,8]. The observation of an overall decay of genetic diversity along axes of migration [9], together with a negative correlation between nucleotide variation and geographical distance from Africa [5] (Figure 1), suggests that demographic events played a major role shaping worldwide patterns of human genetic diversity. More recently, availability of sequenced DNA from ancient humans [10,11] and archaic hominids [12,13] elucidated past admixture events and possible colonization routes. Nonetheless, during this period of migratory events, humans have been exposed to new environments, namely to different climate conditions, pathogens, and food availability, to which they have been forced to adapt, through the action of natural selection. Lactase persistence is one of the most notable examples of genetic adaptation, with a polymorphism promoting the expression of LCT, the gene encoding the enzyme lactase, being at high frequency in European populations and mostly absent elsewhere [14]. Another stunning case of natural selection in the human genome is represented by adaptation to high altitude in Tibetans. A SNP in EPAS1, a gene related to response to hypoxia and hemoglobin concentration, exhibits a dramatic difference in frequency between Tibetans and Han Chinese [15], despite the two populations being genetically close to Current Opinion in Immunology 2014, 30:9–16
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Figure 1
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Decay of nucleotide diversity with geographical distance from central Africa. For each country, the average nucleotide diversity is plotted against the geographical distance from central Africa. We analyzed allele frequencies of more than 500 000 SNPs in 20 countries, using the HGDP-CEPH (http:// www.cephb.fr/en/hgdp) and HapMap (http://hapmap.ncbi.nlm.nih.gov/) databases. We calculated the shortest distance between each country and central Africa on landmass routes.
each other. Further examples of genes with strong evidence of being subjected to natural selection are reviewed and discussed in [16,17].
Genomic signatures of natural selection Detecting loci in the human genome that have been targeted by natural selection has a two-fold importance. Firstly, we can infer which selective events have shaped genome diversity most, and learn about past evolutionary events that characterized human history. Secondly, loci under natural selection are more likely to harbor functional variants, and therefore can be prioritized in screenings for association with susceptibility or resistance to diseases and infections. Indeed, genetic variants that are favorable to the carrier tend to increase in frequency in the population (a process known as positive selection), while deleterious mutations tend to be eliminated (negative selection). Current Opinion in Immunology 2014, 30:9–16
Comparing orthologous genes among primate species is an effective approach to detect positive selection acting over long evolutionary timescales. On the other hand, comparing genetic variation within human populations may shed light onto more recent adaptive events. Such rapid selective pressures can shift allele frequencies of SNPs in proximity of the selected allele, causing a local reduction of nucleotide diversity (a phenomenon known as selective sweep). Various parameters, including the strength of selection, time of onset of the beneficial mutation, current allele frequency of targeted variant, and recombination rate, affect the extent of genetic variation reduction around the selected site (Figure 2). Over the last years, many genome-wide scans for selection have been performed by looking at regions with a reduction of haplotype diversity and increased homozygosity [18,19,20]. Power to detect selection can be gained www.sciencedirect.com
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Reduction of haplotype diversity around a site under positive selection. Levels of haplotype diversity along 300 kb regions are shown for different values of selection coefficient and current allele frequency of selected allele. Dotted line shows the location of the site under positive selection. We simulated 80 chromosomes using the software msms (http://www.mabs.at/ewing/msms) assuming a constant population size model and realistic values for human mutation rate, recombination rate, and effective population size. For each scenario, we computed a regressed line across 200 simulations. Scaled haplotype diversity was calculated with the nSL statistic [19], which measures the ratio of diversity between haplotypes carrying the derived allele and haplotypes carrying the ancestral allele. We performed a sliding window analysis and recorded the minimum value of nSL for each 20 kb window.
by investigating allelic or haplotypic differentiation between populations, through derivation of fixation index statistics (F ST, e.g. [21,22]) or more complex metrics [23,24]. Commonly used methods to detect selection in the genome are reviewed and described in [25,26]. A promising approach to increase the sensitivity of selection scans is to combine multiple methods. The Composite of Multiple Signals (CMS) metric combines several independent statistics into a unique score [27]. CMS has been used to identify roughly 100 putatively adaptive changes in the human genome, which could be then characterized through functional experiments [28]. In 2011, Hernandez and coworkers suggested that classic selective sweeps were rare events in recent human www.sciencedirect.com
evolution [29]. Since populations shared a common history, it is likely that mutations already present in the population become advantageous in a new environment. Selection from standing variation leaves complex and cryptic genomic features [30], which can be detected through simulations-based techniques [31]. Correlating population allele frequencies with environmental variables is an additional strategy to identify patterns of local adaptation [32]. Several human traits are distributed according to geographical clines, and may reflect the specific environmental conditions that acted as selective pressure. For instance, Prugnolle and coworkers firstly showed that alleles frequencies at HLA class I genes correlate with pathogen diversity, suggesting pathogen-driven selection acting on immune-related Current Opinion in Immunology 2014, 30:9–16
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genes [33]. Several methods have been proposed to point out variants that correlate with environments, correcting for the neutral effects of human demography [34,35,36]. Lastly, balancing selection is a process that maintains variation within populations, when heterozygotes have a selective advantage over homozygotes, the fitness of an allele is related to its frequency in the population, or different alleles are favored in changing environments. Genome-wide scans for balancing selection highlighted regions with increased levels of polymorphisms and intermediate allele frequency variants [37], and the presence of shared SNPs between humans and chimpanzee [38]. Empirical methods can be used to distinguish between the effects of neutral demographic factors on patterns of genetic variation and the action of natural selection on targeted loci. This approach takes advantage of the fact that while demography affects the whole genome, natural selection affects variation at single targeted regions. Ranked lists of candidate loci under selection can then be subjected to analysis for enriched biological processes. Alternatively, demographic models that incorporate realistic histories for human evolution [8] can be exploited to calculate the expected amount of genetic variation under neutrality. Genome-wide scans for signatures of natural selection in the human genome pinpointed several biological pathways (e.g. metabolism, pigmentation, and immune system) enriched with genes under non-neutral evolution, reflecting genetic adaptation to environments and lifestyle. Nonetheless, several recent studies have confirmed an old hypothesis whereby infectious agents have exerted an exceptionally strong selective pressure on human populations and contributed to the current genetic diversity at many genes (e.g. [39]).
The selective pressure exerted by infections The history of human societies is punctuated by records of deadly epidemics. The Black Death of the 14th century killed approximately 50 million people in Europe and Asia, and the Spanish flu of 1918–1919, which likely represented the deadliest pandemic recorded in history, killed an estimated 50–100 million people throughout the world [40]. Events of such proportion are thought to be typical of large, highly interconnected modern societies, and possibly appeared only after the Neolithic transition. Nonetheless, pathogens that establish life-long infections, sexually transmitted agents, as well as a plethora of parasites daunted pre-agricultural societies. Indeed, humans have been infected with Helicobacter pylori for at least 88 000–116 000 years [41] and the pattern of genetic diversity for H. pylori strains mirrors that observed in human populations, indicating an intimate host–pathogen association [42]. Likewise, the Mycobacterium tuberculosis complex (MBTC), which caused 20% of all human deaths Current Opinion in Immunology 2014, 30:9–16
in the Western world between the 17th and 19th centuries, emerged about 70 000 years ago in Africa, accompanied human migrations throughout the planet, and expanded as a consequence of increased human population density in the Neolithic [43]. In line with these observations, several reports have indicated that both genes directly involved in immune response and, more generally, loci encoding proteins that interact with microbial components (e.g. erythrocyte surface molecules that modulate binding of Plasmodium) have been targeted by natural selection in human populations (see [44] for a comprehensive review). In particular, population genetics approaches have been instrumental in dissecting the evolutionary history and genetic diversity spectrum at innate immunity receptors and effectors, which represent the foremost line of defense against infections. Toll-like receptors (TLRs), for example, experienced selective constraint both in human [45] and in great ape populations [46], with endosomal TLRs evolving under the strongest purifying selection in our species [45]. Although with different strength, purifying also shaped genetic diversity at molecular adaptors that transduce TLR signaling [47], as well as at RIG-I-like [48], NOD-like [49], and AIM2-like receptors [50]. Nonetheless, extensive analyses (see [51] for an exhaustive review) revealed that instances of selective sweeps could also be detected at these loci either worldwide (e.g. at MYD88 and SARM1) or in specific populations (e.g. at IFIH1, NLRP14, and the TLR10-TLR1-TLR6 gene cluster) [45,47,48,49,52], indicating complex evolutionary scenarios and candidate genetic modulators of immunologic phenotypes. Similarly, Manry et al. [53] provided a thorough analysis of interferon (IFN) genes in human populations; their analysis revealed distinct evolutionary scenarios, with some IFN genes being strongly constrained (e.g. IFNG) and others accumulating nonsense and missense variants at high frequency (e.g. IFNA10, IFNE). Interestingly, the Authors were also able to detect variants targeted by positive selection in Asian and European populations at IL28B, IL28A, and IL29. Providing strong evidence for the conundrum that selected variants modulate infectious disease phenotypes, the selected polymorphisms described by Manry et al. [53] in IL28B have been associated with the spontaneous clearance of HCV [54]. Instances of selective sweeps restricted to one or few populations clearly point to locally exerted selective pressure – for e the presence of specific pathogens in a given geographic location. Recently, populations with different genetic ancestry such as Europeans and Rroma, exposed to the same environment for at least 1000 years, were shown to display signals of convergent evolution at immune response genes [55]. Specifically, the TLR1/ TLR6/TLR10 gene cluster accounted for one of the strongest signals and the authors suggested that bubonic www.sciencedirect.com
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Figure 3
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Schematic representation of MHC I antigen processing and presentation. Molecules involved in APC (antigen presenting cell)-T cell interaction are also shown. Pathway components are designated using official gene names (excluding MHC I and T cell receptor, TCR) and color-coded according to their selective pattern in humans. Genes showing signatures of selective sweeps are shown in red, whereas balancing selection targets are depicted in orange. Genes are shown in green if no selection signals were detected or reported.
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plague might have represented the underlying pressure [55]. Likewise, Karlsson et al. [56] performed a genome-wide scan of natural selection in a Bangladeshi population living in the Ganges River Delta region, where Vibrio cholerae infection is thought to have represented an extremely strong selective pressure for millennia. Their CMS approach revealed a number of selective sweep candidates with enrichment for potassium channel genes involved in chloride secretion and for nuclear factor kB (NF-kB) signaling components [56]. Similarly to the IFN analysis [53], this study provides a nice example of the complementary between evolutionary genetics and infectious disease epidemiology: the Authors show that a number of the positively selected variants do confer increased resistance to cholera infection (or associate with a milder disease). Interestingly, Karlsson et al. [56] also noted an overlap between genes selected by V. cholerae and those involved in inflammatory bowel disease (IBD). Other studies reported that a proportion of IBD loci represented targets of pathogen-driven selection [57,58,59], suggesting that adaptation to infection contributed to the shaping of genetic diversity at loci that participate in systemic and mucosal immunity, resulting in the spread or maintenance of IBD susceptibility loci. Similar considerations might apply to other immunemediated diseases [44,60,61,62], indicating that the long interaction between humans and their pathogens has implications for traits and diseases not directly related to infection. Also, the Karlsson et al.’s study [56] epitomizes the concept whereby different genes may be targeted by the same selective pressure because they impinge on a common molecular pathway, the NF-kB signaling pathway in the case of cholera. Recently, Daub et al. [63] have applied an F ST- and pathway-based approach to search for signals of polygenic adaptation. In line with the idea that pathogens represented a major selective pressure for human populations, the authors found that most pathways enriched for selection signals are directly or indirectly involved in immune response. Other authors [60,64] have recently analyzed pathways or gene sets of central importance to immune response such as T-cell activation and antigen processing and presentation. By combining different selection tests, Forni et al. [60,64] found signals to be pervasive in these pathways and to be accounted for by both balancing and positive selection (Figure 3). In several cases a continuum was also noted, with the same genes having been targeted by selection both during mammalian evolution and in the more recent history of humans, indicating their long-lasting interaction with pathogens. Forni and coworkers made use of the low-coverage 1000G data, allowing fine mapping of selection signals [60,64]. Current Opinion in Immunology 2014, 30:9–16
Although they identified some nonsynonymous variants to represent selection targets, most detected signals were located in noncoding regions with a likely regulatory function. A similar observation has been reported by Grossman et al. [28], who applied the CMS test to the 1000G data. The authors identified missense SNPs as selection targets (including one in TLR5 that affects the response to bacterial flagellin), but most signals were noncoding and likely regulatory in nature. Overall, these analyses indicate that regulatory changes played a pivotal role in recent human evolution and most likely involved a number of immune response loci. Forni and Grossman integrated their selection signals with large-scale functional annotations of regulatory regions and eQTL data, but a proportion of selected variants remained uncharacterized [28,60,64]. Very recently, two groups [65,66] exposed human monocyte/dendritic cells to bacterial or viral stimuli and identified context-specific eQTLs. Their analyses detected hundreds of stimulus-regulated genes and revealed that many regulatory variants display functionality only after stimulation. Also, a number of context-specific eQTLs were associated to autoimmune or infectious disease loci identified by genome-wide association studies.
Conclusions The context-specific eQTLs mentioned above, as well as other variants that will hopefully emerge from similar approaches in different immune cell types, clearly represent extremely good candidates as genetic modulators of susceptibility to infection and as natural selection targets, possibly accounting for some of the still unexplained selection signals. Indeed, integration of different sets of large-scale genomic data and of distinct analysis methodologies holds the promise to shed light on the past, present and future scenarios of human-pathogen interactions.
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