A haplotype method detects diverse scenarios of local adaptation from genomic sequence variation

Identifying genomic targets of population‐specific positive selection is a major goal in several areas of basic and applied biology. However, it is unclear how often such selection should act on new mutations versus standing genetic variation or recurrent mutation, and furthermore, favoured alleles may either become fixed or remain variable in the population. Very few population genetic statistics are sensitive to all of these modes of selection. Here, we introduce and evaluate the Comparative Haplotype Identity statistic (χ_MD), which assesses whether pairwise haplotype sharing at a locus in one population is unusually large compared with another population, relative to genomewide trends. Using simulations that emulate human and Drosophila genetic variation, we find that χ_MD is sensitive to a wide range of selection scenarios, and for some very challenging cases (e.g. partial soft sweeps), it outperforms other two‐population statistics. We also find that, as with F_ST, our haplotype approach has the ability to detect surprisingly ancient selective sweeps. Particularly for the scenarios resembling human variation, we find that χ_MD outperforms other frequency‐ and haplotype‐based statistics for soft and/or partial selective sweeps. Applying χ_MD and other between‐population statistics to published population genomic data from D. melanogaster, we find both shared and unique genes and functional categories identified by each statistic. The broad utility and computational simplicity of χ_MD will make it an especially valuable tool in the search for genes targeted by local adaptation.     

Whole‐genome resequencing uncovers molecular signatures of natural and sexual selection in wild bighorn sheep

The identification of genes influencing fitness is central to our understanding of the genetic basis of adaptation and how it shapes phenotypic variation in wild populations. Here, we used whole‐genome resequencing of wild Rocky Mountain bighorn sheep (Ovis canadensis) to >50‐fold coverage to identify 2.8 million single nucleotide polymorphisms (SNPs) and genomic regions bearing signatures of directional selection (i.e. selective sweeps). A comparison of SNP diversity between the X chromosome and the autosomes indicated that bighorn males had a dramatically reduced long‐term effective population size compared to females. This probably reflects a long history of intense sexual selection mediated by male–male competition for mates. Selective sweep scans based on heterozygosity and nucleotide diversity revealed evidence for a selective sweep shared across multiple populations at RXFP2, a gene that strongly affects horn size in domestic ungulates. The massive horns carried by bighorn rams appear to have evolved in part via strong positive selection at RXFP2. We identified evidence for selection within individual populations at genes affecting early body growth and cellular response to hypoxia; however, these must be interpreted more cautiously as genetic drift is strong within local populations and may have caused false positives. These results represent a rare example of strong genomic signatures of selection identified at genes with known function in wild populations of a nonmodel species. Our results also showcase the value of reference genome assemblies from agricultural or model species for studies of the genomic basis of adaptation in closely related wild taxa.     

Genomic signatures of adaptation to Sahelian and Soudanian climates in sorghum landraces of Senegal

Uncovering the genomic basis of climate adaptation in traditional crop varieties can provide insight into plant evolution and facilitate breeding for climate resilience. In the African cereal sorghum (Sorghum bicolor L. [Moench]), the genomic basis of adaptation to the semiarid Sahelian zone versus the subhumid Soudanian zone is largely unknown. To address this issue, we characterized a large panel of 421 georeferenced sorghum landrace accessions from Senegal and adjacent locations at 213,916 single‐nucleotide polymorphisms (SNPs) using genotyping‐by‐sequencing. Seven subpopulations distributed along the north‐south precipitation gradient were identified. Redundancy analysis found that climate variables explained up to 8% of SNP variation, with climate collinear with space explaining most of this variation (6%). Genome scans of nucleotide diversity suggest positive selection on chromosome 2, 4, 5, 7, and 10 in durra sorghums, with successive adaptation during diffusion along the Sahel. Putative selective sweeps were identified, several of which colocalize with stay‐green drought tolerance (Stg) loci, and a priori candidate genes for photoperiodic flowering and inflorescence morphology. Genome‐wide association studies of photoperiod sensitivity and panicle compactness identified 35 and 13 associations that colocalize with a priori candidate genes, respectively. Climate‐associated SNPs colocalize with Stg3a, Stg1, Stg2, and Ma6 and have allelic distribution consistent with adaptation across Sahelian and Soudanian zones. Taken together, the findings suggest an oligogenic basis of adaptation to Sahelian versus Soudanian climates, underpinned by variation in conserved floral regulatory pathways and other systems that are less understood in cereals.     

Limited Evidence for Classic Selective Sweeps in African Populations

While hundreds of loci have been identified as reflecting strong-positive selection in human populations, connections between candidate loci and specific selective pressures often remain obscure. This study investigates broader patterns of selection in African populations, which are underrepresented despite their potential to offer key insights into human adaptation. We scan for hard selective sweeps using several haplotype and allele-frequency statistics with a data set of nearly 500,000 genome-wide single-nucleotide polymorphisms in 12 highly diverged African populations that span a range of environments and subsistence strategies. We find that positive selection does not appear to be a strong determinant of allele-frequency differentiation among these African populations. Haplotype statistics do identify putatively selected regions that are shared across African populations. However, as assessed by extensive simulations, patterns of haplotype sharing between African populations follow neutral expectations and suggest that tails of the empirical distributions contain false-positive signals. After highlighting several genomic regions where positive selection can be inferred with higher confidence, we use a novel method to identify biological functions enriched among populations’ empirical tail genomic windows, such as immune response in agricultural groups. In general, however, it seems that current methods for selection scans are poorly suited to populations that, like the African populations in this study, are affected by ascertainment bias and have low levels of linkage disequilibrium, possibly old selective sweeps, and potentially reduced phasing accuracy. Additionally, population history can confound the interpretation of selection statistics, suggesting that greater care is needed in attributing broad genetic patterns to human adaptation.     

Discovery of Ongoing Selective Sweeps within Anopheles Mosquito Populations Using Deep Learning

Identification of partial sweeps, which include both hard and soft sweeps that have not currently reached fixation, provides crucial information about ongoing evolutionary responses. To this end, we introduce partialS/HIC, a deep learning method to discover selective sweeps from population genomic data. partialS/HIC uses a convolutional neural network for image processing, which is trained with a large suite of summary statistics derived from coalescent simulations incorporating population-specific history, to distinguish between completed versus partial sweeps, hard versus soft sweeps, and regions directly affected by selection versus those merely linked to nearby selective sweeps. We perform several simulation experiments under various demographic scenarios to demonstrate partialS/HIC’s performance, which exhibits excellent resolution for detecting partial sweeps. We also apply our classifier to whole genomes from eight mosquito populations sampled across sub-Saharan Africa by the Anopheles gambiae 1000 Genomes Consortium, elucidating both continent-wide patterns as well as sweeps unique to specific geographic regions. These populations have experienced intense insecticide exposure over the past two decades, and we observe a strong overrepresentation of sweeps at insecticide resistance loci. Our analysis thus provides a list of candidate adaptive loci that may be relevant to mosquito control efforts. More broadly, our supervised machine learning approach introduces a method to distinguish between completed and partial sweeps, as well as between hard and soft sweeps, under a variety of demographic scenarios. As whole-genome data rapidly accumulate for a greater diversity of organisms, partialS/HIC addresses an increasing demand for useful selection scan tools that can track in-progress evolutionary dynamics.     

The genomic basis of adaptation to high‐altitude habitats in the eastern honey bee (Apis cerana)

The eastern honey bee (Apis cerana) is of central importance for agriculture in Asia. It has adapted to a wide variety of environmental conditions across its native range in southern and eastern Asia, which includes high‐altitude regions. eastern honey bees inhabiting mountains differ morphologically from neighbouring lowland populations and may also exhibit differences in physiology and behaviour. We compared the genomes of 60 eastern honey bees collected from high and low altitudes in Yunnan and Gansu provinces, China, to infer their evolutionary history and to identify candidate genes that may underlie adaptation to high altitude. Using a combination of F_ST‐based statistics, long‐range haplotype tests and population branch statistics, we identified several regions of the genome that appear to have been under positive selection. These candidate regions were strongly enriched for coding sequences and had high haplotype homozygosity and increased divergence specifically in highland bee populations, suggesting they have been subjected to recent selection in high‐altitude habitats. Candidate loci in these genomic regions included genes related to reproduction and feeding behaviour in honey bees. Functional investigation of these candidate loci is necessary to fully understand the mechanisms of adaptation to high‐altitude habitats in the eastern honey bee.     

Soft Shoulders Ahead: Spurious Signatures of Soft and Partial Selective Sweeps Result from Linked Hard Sweeps

Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of “soft shoulders” underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.     

Signatures of soft sweeps across the Dt1 locus underlying determinate growth habit in soya bean [Glycine max (L.) Merr.]

Determinate growth habit is an agronomically important trait associated with domestication in soya bean. Previous studies have demonstrated that the emergence of determinacy is correlated with artificial selection on four nonsynonymous mutations in the Dt1 gene. To better understand the signatures of the soft sweeps across the Dt1 locus and track the origins of the determinate alleles, we examined patterns of nucleotide variation in Dt1 and the surrounding genomic region of approximately 800 kb. Four local, asymmetrical hard sweeps on four determinate alleles, sized approximately 660, 120, 220 and 150 kb, were identified, which constitute the soft sweeps for the adaptation. These variable‐sized sweeps substantially reflected the strength and timing of selection and indicated that the selection on the alleles had been completed rapidly within half a century. Statistics of EHH, iHS, H12 and H2/H1 based on haplotype data had the power to detect the soft sweeps, revealing distinct signatures of extensive long‐range LD and haplotype homozygosity, and multiple frequent adaptive haplotypes. A haplotype network constructed for Dt1 and a phylogenetic tree based on its extended haplotype block implied independent sources of the adaptive alleles through de novo mutations or rare standing variation in quick succession during the selective phase, strongly supporting multiple origins of the determinacy. We propose that the adaptation of soya bean determinacy is guided by a model of soft sweeps and that this model might be indispensable during crop domestication or evolution.     

Genomewide patterns of variation in genetic diversity are shared among populations,species and higher‐order taxa

Genomewide screens of genetic variation within and between populations can reveal signatures of selection implicated in adaptation and speciation. Genomic regions with low genetic diversity and elevated differentiation reflective of locally reduced effective population sizes (N_e) are candidates for barrier loci contributing to population divergence. Yet, such candidate genomic regions need not arise as a result of selection promoting adaptation or advancing reproductive isolation. Linked selection unrelated to lineage‐specific adaptation or population divergence can generate comparable signatures. It is challenging to distinguish between these processes, particularly when diverging populations share ancestral genetic variation. In this study, we took a comparative approach using population assemblages from distant clades assessing genomic parallelism of variation in N_e. Utilizing population‐level polymorphism data from 444 resequenced genomes of three avian clades spanning 50 million years of evolution, we tested whether population genetic summary statistics reflecting genomewide variation in N_e would covary among populations within clades, and importantly, also among clades where lineage sorting has been completed. All statistics including population‐scaled recombination rate (ρ), nucleotide diversity (π) and measures of genetic differentiation between populations (F_ST, PBS, d_xy) were significantly correlated across all phylogenetic distances. Moreover, genomic regions with elevated levels of genetic differentiation were associated with inferred pericentromeric and subtelomeric regions. The phylogenetic stability of diversity landscapes and stable association with genomic features support a role of linked selection not necessarily associated with adaptation and speciation in shaping patterns of genomewide heterogeneity in genetic diversity.     

Adaptation in isolated populations: when does it happen and when can we tell?

Isolated populations with novel phenotypes present an exciting opportunity to uncover the genetic basis of ecologically significant adaptation, and genomic scans have often, but not always, led to candidate genes directly related to an adaptive phenotype. However, in many cases these populations were established by a severe bottleneck, which can make identifying targets of selection problematic. Here, we simulate severe bottlenecks and subsequent selection on standing variation, mimicking adaptation after establishment of a new small population, such as an island or an artificial selection experiment. Using simulations of single loci under positive selection and population genetics theory, we examine how population size and age of the population isolate affect the ability of outlier scans for selection to identify adaptive alleles using both single‐site measures and haplotype structure. We find and explain an optimal combination of selection strength, starting frequency, and age of the adaptive allele, which we refer to as a Goldilocks zone, where adaptation is likely to occur and yet the adaptive variants are most likely to derive from a single ancestor (a ‘hard’ selective sweep); in this zone, four commonly used statistics detect selection with high power. Real‐world examples of both island colonization and experimental evolution studies are discussed. Our study provides concrete considerations to be made before embarking on whole‐genome sequencing of differentiated populations.     

Detecting selection signatures in three Iranian sheep breeds

The objective of genome mapping is to achieve valuable insight into the connection between gene variants (genotype) and observed traits (phenotype). Part of that objective is to understand the selective forces that have operated on a population. Finding links between genotype–phenotype changes makes it possible to identify selective sweeps by patterns of genetic variation and linkage disequilibrium. Based on Illumina 50KSNP chip data, two approaches, XP‐EHH (cross‐population extend haplotype homozygosity) and F_ST (fixation index), were carried out in this research to identify selective sweeps in the genome of three Iranian local sheep breeds: Baluchi (n = 86), Lori‐Bakhtiari (n = 45) and Zel (n = 45). Using both methods, 93 candidate genomic regions were identified as harboring putative selective sweeps. Bioinformatics analysis of the genomic regions showed that signatures of selection related to multiple candidate genes, such as HOXB9, HOXB13, ACAN, NPR2, TRIL, AOX1, CSF2, GHR, TNS2, SPAG8, HINT2, ALS2, AAAS, RARG, SYCP2, CAV1, PPP1R3D, PLA2G7, TTLL7 and C20orf10, that play a role in skeletal system and tail, sugar and energy metabolisms, growth, reproduction, immune and nervous system traits. Our findings indicated diverse genomic selection during the domestication of Iranian sheep breeds.     

Evolutionary genomics of Culex pipiens: global and local adaptations associated with climate,life-history traits and anthropogenic factors

We present the first genome-wide study of recent evolution in Culex pipiens species complex focusing on the genomic extent, functional targets and likely causes of global and local adaptations. We resequenced pooled samples of six populations of C. pipiens and two populations of the outgroup Culex torrentium. We used principal component analysis to systematically study differential natural selection across populations and developed a phylogenetic scanning method to analyse admixture without haplotype data. We found evidence for the prominent role of geographical distribution in shaping population structure and specifying patterns of genomic selection. Multiple adaptive events, involving genes implicated with autogeny, diapause and insecticide resistance were limited to specific populations. We estimate that about 5–20% of the genes (including several histone genes) and almost half of the annotated pathways were undergoing selective sweeps in each population. The high occurrence of sweeps in non-genic regions and in chromatin remodelling genes indicated the adaptive importance of gene expression changes. We hypothesize that global adaptive processes in the C. pipiens complex are potentially associated with South to North range expansion, requiring adjustments in chromatin conformation. Strong local signature of adaptation and emergence of hybrid bridge vectors necessitate genomic assessment of populations before specifying control agents.     

Adaptive divergence along environmental gradients in a climate‐change‐sensitive mammal

In the face of predicted climate change, a broader understanding of biotic responses to varying environments has become increasingly important within the context of biodiversity conservation. Local adaptation is one potential option, yet remarkably few studies have harnessed genomic tools to evaluate the efficacy of this response within natural populations. Here, we show evidence of selection driving divergence of a climate‐change‐sensitive mammal, the American pika (Ochotona princeps), distributed along elevation gradients at its northern range margin in the Coast Mountains of British Columbia (BC), Canada. We employed amplified‐fragment‐length‐polymorphism‐based genomic scans to conduct genomewide searches for candidate loci among populations inhabiting varying environments from sea level to 1500 m. Using several independent approaches to outlier locus detection, we identified 68 candidate loci putatively under selection (out of a total 1509 screened), 15 of which displayed significant associations with environmental variables including annual precipitation and maximum summer temperature. These candidate loci may represent important targets for predicting pika responses to climate change and informing novel approaches to wildlife conservation in a changing world.     

Genomics of invasion: diversity and selection in introduced populations of monkeyflowers (Mimulus guttatus)

Global trade and travel is irreversibly changing the distribution of species around the world. Because introduced species experience drastic demographic events during colonization and often face novel environmental challenges from their native range, introduced populations may undergo rapid evolutionary change. Genomic studies provide the opportunity to investigate the extent to which demographic, historical and selective processes shape the genomic structure of introduced populations by analysing the signature that these processes leave on genomic variation. Here, we use next‐generation sequencing to compare genome‐wide relationships and patterns of diversity in native and introduced populations of the yellow monkeyflower (Mimulus guttatus). Genome resequencing data from 10 introduced populations from the United Kingdom (UK) and 12 native M. guttatus populations in North America (NA) demonstrated reduced neutral genetic diversity in the introduced range and showed that UK populations are derived from a geographic region around the North Pacific. A selective‐sweep analysis revealed site frequency changes consistent with selection on five of 14 chromosomes, with genes in these regions showing reduced silent site diversity. While the target of selection is unknown, genes associated with flowering time and biotic and abiotic stresses were located within the swept regions. The future identification of the specific source of origin of introduced UK populations will help determining whether the observed selective sweeps can be traced to unsampled native populations or occurred since dispersal across the Atlantic. Our study demonstrates the general potential of genome‐wide analyses to uncover a range of evolutionary processes affecting invasive populations.     

Signatures of local adaptation in lowland and highland teosintes from whole‐genome sequencing of pooled samples

Spatially varying selection triggers differential adaptation of local populations. Here, we mined the determinants of local adaptation at the genomewide scale in the two closest maize wild relatives, the teosintes Zea mays ssp parviglumis and ssp. mexicana. We sequenced 120 individuals from six populations: two lowland, two intermediate and two highland populations sampled along two altitudinal gradients. We detected 8 479 581 single nucleotide polymorphisms (SNPs) covered in the six populations with an average sequencing depth per site per population ranging from 17.0× to 32.2×. Population diversity varied from 0.10 to 0.15, and linkage disequilibrium decayed very rapidly. We combined two differentiation‐based methods, and correlation of allele frequencies with environmental variables to detect outlier SNPs. Outlier SNPs displayed significant clustering. From clusters, we identified 47 candidate regions. We further modified a haplotype‐based method to incorporate genotype uncertainties in haplotype calling, and applied it to candidate regions. We retrieved evidence for selection at the haplotype level in 53% of our candidate regions, and in 70% of the cases the same haplotype was selected in the two lowland or the two highland populations. We recovered a candidate region located within a previously characterized inversion on chromosome 1. We found evidence of a soft sweep at a locus involved in leaf macrohair variation. Finally, our results revealed frequent colocalization between our candidate regions and loci involved in the variation of traits associated with plant–soil interactions such as root morphology, aluminium and low phosphorus tolerance. Soil therefore appears to be a major driver of local adaptation in teosintes.     

Genome‐wide evidence for divergent selection between populations of a major agricultural pathogen

The genetic and environmental homogeneity in agricultural ecosystems is thought to impose strong and uniform selection pressures. However, the impact of this selection on plant pathogen genomes remains largely unknown. We aimed to identify the proportion of the genome and the specific gene functions under positive selection in populations of the fungal wheat pathogen Zymoseptoria tritici. First, we performed genome scans in four field populations that were sampled from different continents and on distinct wheat cultivars to test which genomic regions are under recent selection. Based on extended haplotype homozygosity and composite likelihood ratio tests, we identified 384 and 81 selective sweeps affecting 4% and 0.5% of the 35 Mb core genome, respectively. We found differences both in the number and the position of selective sweeps across the genome between populations. Using a XtX‐based outlier detection approach, we identified 51 extremely divergent genomic regions between the allopatric populations, suggesting that divergent selection led to locally adapted pathogen populations. We performed an outlier detection analysis between two sympatric populations infecting two different wheat cultivars to identify evidence for host‐driven selection. Selective sweep regions harboured genes that are likely to play a role in successfully establishing host infections. We also identified secondary metabolite gene clusters and an enrichment in genes encoding transporter and protein localization functions. The latter gene functions mediate responses to environmental stress, including interactions with the host. The distinct gene functions under selection indicate that both local host genotypes and abiotic factors contributed to local adaptation.     

Genomic analysis of a migratory divide reveals candidate genes for migration and implicates selective sweeps in generating islands of differentiation

Differential gene flow, reductions in diversity following linked selection and/or features of the genome can structure patterns of genomic differentiation during the process of speciation. Possible sources of reproductive isolation are well studied between coastal and inland subspecies groups of Swainson's thrushes, with differences in seasonal migratory behaviour likely playing a key role in reducing hybrid fitness. We assembled and annotated a draft reference genome for this species and generated whole‐genome shotgun sequence data for populations adjacent to the hybrid zone between these groups. We documented substantial genomewide heterogeneity in relative estimates of genetic differentiation between the groups. Within population diversity was lower in areas of high relative differentiation, supporting a role for selective sweeps in generating this pattern. Absolute genetic differentiation was reduced in these areas, further suggesting that recurrent selective sweeps in the ancestral population and/or between divergent populations following secondary contact likely occurred. Relative genetic differentiation was also higher near centromeres and on the Z chromosome, suggesting that features of the genome also contribute to genomewide heterogeneity. Genes linked to migratory traits were concentrated in islands of differentiation, supporting previous suggestions that seasonal migration is under divergent selection between Swainson's thrushes. Differences in migratory behaviour likely play a central role in the speciation of many taxa; we developed the infrastructure here to permit future investigations into the role several candidate genes play in reducing gene flow between not only Swainson's thrushes but other species as well.     

The genomic footprint of climate adaptation in Chironomus riparius

The gradual heterogeneity of climatic factors poses varying selection pressures across geographic distances that leave signatures of clinal variation in the genome. Separating signatures of clinal adaptation from signatures of other evolutionary forces, such as demographic processes, genetic drift and adaptation, to nonclinal conditions of the immediate local environment is a major challenge. Here, we examine climate adaptation in five natural populations of the harlequin fly Chironomus riparius sampled along a climatic gradient across Europe. Our study integrates experimental data, individual genome resequencing, Pool‐Seq data and population genetic modelling. Common‐garden experiments revealed significantly different population growth rates at test temperatures corresponding to the population origin along the climate gradient, suggesting thermal adaptation on the phenotypic level. Based on a population genomic analysis, we derived empirical estimates of historical demography and migration. We used an F_ST outlier approach to infer positive selection across the climate gradient, in combination with an environmental association analysis. In total, we identified 162 candidate genes as genomic basis of climate adaptation. Enriched functions among these candidate genes involved the apoptotic process and molecular response to heat, as well as functions identified in studies of climate adaptation in other insects. Our results show that local climate conditions impose strong selection pressures and lead to genomic adaptation despite strong gene flow. Moreover, these results imply that selection to different climatic conditions seems to converge on a functional level, at least between different insect species.     

SPEED OF ADAPTATION AND GENOMIC FOOTPRINTS OF HOST–PARASITE COEVOLUTION UNDER ARMS RACE AND TRENCH WARFARE DYNAMICS

Coevolution between hosts and their parasites is expected to follow a range of possible dynamics, the two extreme cases being called trench warfare (or Red Queen) and arms races. Long‐term stable polymorphism at the host and parasite coevolving loci is characteristic of trench warfare, and is expected to promote molecular signatures of balancing selection, while the recurrent allele fixation in arms races should generate selective sweeps. We compare these two scenarios using a finite size haploid gene‐for‐gene model that includes both mutation and genetic drift. We first show that trench warfare do not necessarily display larger numbers of coevolutionary cycles per unit of time than arms races. We subsequently perform coalescent simulations under these dynamics to generate sequences at both host and parasite loci. Genomic footprints of recurrent selective sweeps are often found, whereas trench warfare yield signatures of balancing selection only in parasite sequences, and only in a limited parameter space. Our results suggest that deterministic models of coevolution with infinite population sizes do not predict reliably the observed genomic signatures, and it may be best to study parasite rather than host populations to find genomic signatures of coevolution, such as selective sweeps or balancing selection.