A worldwide survey of genome sequence variation provides insight into the evolutionary history of the honeybee Apis mellifera

Wållberg, Andreas; Fan, Han; Wellhagen, Gustaf; Dahle, Bjørn; Kawata, Masakado; Haddad, Nizar; Simões, Zilá Luz Paulino; Allsopp, Michael H.; Kandemi̇r, İrfan; Rúa, Pilar De la; Pirk, Christian Walter Werner; Webster, Matthew T.

doi:10.1038/ng.3077

Cited by 283 publications

(437 citation statements)

References 55 publications

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“…In particular, because PSMC is applied to a single diploid genome, it has been used to infer population size histories in numerous species for which one or more genome sequences are available, in many cases finding support for large changes in population size (Groenen et al 2012;Albert et al 2013;Prado-Martinez et al 2013;Zhan et al 2013;Freedman et al 2014;Green et al 2014;Wallberg et al 2014;Auton et al 2015;Lamichhaney et al 2015). Our findings suggest that natural selection may alter the shape of, and inflate the degree of change in, these inferred histories.…”

Section: Discussionmentioning

confidence: 80%

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

2016

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The availability of large-scale population genomic sequence data has resulted in an explosion in efforts to infer the demographic histories of natural populations across a broad range of organisms. As demographic events alter coalescent genealogies, they leave detectable signatures in patterns of genetic variation within and between populations. Accordingly, a variety of approaches have been designed to leverage population genetic data to uncover the footprints of demographic change in the genome. The vast majority of these methods make the simplifying assumption that the measures of genetic variation used as their input are unaffected by natural selection. However, natural selection can dramatically skew patterns of variation not only at selected sites, but at linked, neutral loci as well. Here we assess the impact of recent positive selection on demographic inference by characterizing the performance of three popular methods through extensive simulation of data sets with varying numbers of linked selective sweeps. In particular, we examined three different demographic models relevant to a number of species, finding that positive selection can bias parameter estimates of each of these models-often severely. We find that selection can lead to incorrect inferences of population size changes when none have occurred. Moreover, we show that linked selection can lead to incorrect demographic model selection, when multiple demographic scenarios are compared. We argue that natural populations may experience the amount of recent positive selection required to skew inferences. These results suggest that demographic studies conducted in many species to date may have exaggerated the extent and frequency of population size changes.KEYWORDS population genetics; positive selection; demographic inference T HE widespread availability of population genomic data has spurred a new generation of studies aimed at understanding the histories of natural populations from a host of model and nonmodel organisms alike. In particular, genomescale variation data allows for inference of demographic factors such as population size changes, the timing and ordering of population splits, migration rates between populations, and the founding of admixed populations (Pool et al. 2010;Pickrell and Pritchard 2012;Sousa and Hey 2013). Such efforts can refine our picture of demographic events inferred from the archaeological record (e.g., Fagundes et al. 2007;Goebel et al. 2008), or reveal such events in species where no archaeological data are available, and can aid conservation efforts by complementing census data (e.g., Hájková et al. 2007;Garrick et al. 2015).Population genomic data sets are well suited for this task simply because demographic changes leave their mark on patterns of genetic variation. Recent population growth, for example, will result in an excess of rare variation compared to equilibrium expectations (Fu 1997), while population contraction will result in an excess of intermediate frequency alleles (Maruyama and Fuerst 198...

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Section: Discussionmentioning

confidence: 80%

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

2016

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“…This was an expected result because M and C are the most divergent of the four lineages (Wallberg et al., 2014). The top enriched GO terms of the genes marked by those SNPs were associated with numerous genes related to regulation of expression, which is essential for the versatility and adaptability of a species for short‐ and long‐term environmental changes (López‐Maury, Marguerat, & Bahler, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…The top enriched GO terms of the genes marked by those SNPs were associated with numerous genes related to regulation of expression, which is essential for the versatility and adaptability of a species for short‐ and long‐term environmental changes (López‐Maury, Marguerat, & Bahler, 2008). This is consistent with the complex evolutionary history of A. mellifera and its numerous subspecies, which have adapted to the diversity of habitats and climates in its large distributional range (Harpur et al., 2014; Wallberg et al., 2014). …”

Section: Discussionmentioning

confidence: 99%

Developing reduced SNP assays from whole‐genome sequence data to estimate introgression in an organism with complex genetic patterns, the Iberian honeybee (Apis mellifera iberiensis)

Henriques

Parejo

Vignal

et al. 2018

Evolutionary Applications

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The most important managed pollinator, the honeybee (Apis mellifera L.), has been subject to a growing number of threats. In western Europe, one such threat is large‐scale introductions of commercial strains (C‐lineage ancestry), which is leading to introgressive hybridization and even the local extinction of native honeybee populations (M‐lineage ancestry). Here, we developed reduced assays of highly informative SNPs from 176 whole genomes to estimate C‐lineage introgression in the most diverse and evolutionarily complex subspecies in Europe, the Iberian honeybee (Apis mellifera iberiensis). We started by evaluating the effects of sample size and sampling a geographically restricted area on the number of highly informative SNPs. We demonstrated that a bias in the number of fixed SNPs (FST = 1) is introduced when the sample size is small (N ≤ 10) and when sampling only captures a small fraction of a population's genetic diversity. These results underscore the importance of having a representative sample when developing reliable reduced SNP assays for organisms with complex genetic patterns. We used a training data set to design four independent SNP assays selected from pairwise FST between the Iberian and C‐lineage honeybees. The designed assays, which were validated in holdout and simulated hybrid data sets, proved to be highly accurate and can be readily used for monitoring populations not only in the native range of A. m. iberiensis in Iberia but also in the introduced range in the Balearic islands, Macaronesia and South America, in a time‐ and cost‐effective manner. While our approach used the Iberian honeybee as model system, it has a high value in a wide range of scenarios for the monitoring and conservation of potentially hybridized domestic and wildlife populations.

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“…Drones are of particular interest since variation in physiological parameters, such as weight have direct effects on flight ability and sperm quantity (Jarolimek and Otis, 2001;Schlüns et al 2003). Indeed, male competition appears particularly high in African honeybee populations (Wallberg et al 2014). Slight variations in the damage caused by parasitism can have large and direct effects on their competitiveness and hence on their fitness (Jandricic and Otis, 2003).…”

Section: Introductionmentioning

confidence: 99%

Resistance rather than tolerance explains survival of savannah honeybees (Apis mellifera scutellata) to infestation by the parasitic mite Varroa destructor

et al. 2015

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SUMMARYVarroa destructor is considered the most damaging parasite affecting honeybees (Apis mellifera L.). However, some honeybee populations such as the savannah honeybee (A. m. scutellata) can survive mite infestation without treatment. It is unclear if survival is due to resistance mechanisms decreasing parasite reproduction or to tolerance mechanisms decreasing the detrimental effects of mites on the host. This study investigates both aspects by quantifying the reproductive output of V. destructor and its physiological costs at the individual host level. Costs measured were not consistently lower when compared to susceptible honeybee populations, indicating a lack of tolerance. In contrast, reproduction of V. destructor mites was distinctly lower than in susceptible populations. There was a higher proportion of infertile individuals and the reproductive success of fertile mites was lower than measured to date, even in surviving populations. Our results suggest that survival of savannah honeybees is based on resistance rather than tolerance to this parasite. We identified traits that may be useful for breeding programs aimed at increasing the survival of susceptible populations. African honeybees may have benefited from a lack of human interference, allowing natural selection to shape a population of honeybees that is more resistant to Varroa mite infestation.2

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A worldwide survey of genome sequence variation provides insight into the evolutionary history of the honeybee Apis mellifera

Cited by 283 publications

References 55 publications

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

Developing reduced SNP assays from whole‐genome sequence data to estimate introgression in an organism with complex genetic patterns, the Iberian honeybee (Apis mellifera iberiensis)

Resistance rather than tolerance explains survival of savannah honeybees (Apis mellifera scutellata) to infestation by the parasitic mite Varroa destructor

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