Flight‐induced changes in gene expression in the Glanville fritillary butterfly

Kvist, Jouni; Mattila, Anniina L. K.; Somervuo, Panu; Ahola, Virpi; Koskinen, Patrik; Paulín, Lars; Salmela, Leena; Fountain, Toby; Rastas, Pasi; Ruokolainen, Annukka; Taipale, Minna; Holm, Liisa; Auvinen, Petri; Lehtonen, Rainer; Frilander, Mikko J.; Hanski, Ilkka

doi:10.1111/mec.13359

Cited by 34 publications

(42 citation statements)

References 82 publications

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“…It is also possible that any beneficial effects from genes linked with the outlier loci were swamped by accumulation of deleterious mutations (6,43,44) and general loss of heterozygosity and fitness (45). In the Glanville fritillary, flight metabolic rate is significantly and positively correlated with genome-wide heterozygosity, a proxy of individual inbreeding (46), with a 30% fitness reduction in a small (N e ∼100) population that has remained completely isolated for at least 75 y (9). As another example, habitat fragmentation due to climate-induced range contraction has eroded genetic diversity in an alpine mammal species (47), likely reducing the adaptive potential of the species and increasing the risk of inbreeding (48).…”

Section: Discussionmentioning

confidence: 99%

“…The genomic resources for the Glanville fritillary include the published genome (33), a high-density linkage map (59), and two RNAseq datasets (32,46), which were used to create a SNP panel using the KASP genotyping platform (LGC Genomics) for large-scale genotyping (Dataset S3). Markers were selected on the basis of previous studies (32,34,46,60), in which candidate genes were associated with flight and dispersal traits or were significantly differentially expressed after an experimental flight treatment. Putatively neutral SNPs were selected from the noncoding regions of the genome (SI Appendix).…”

Section: Methodsmentioning

confidence: 99%

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Predictable allele frequency changes due to habitat fragmentation in the Glanville fritillary butterfly

Fountain

Nieminen

Sirén

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Describing the evolutionary dynamics of now extinct populations is challenging, as their genetic composition before extinction is generally unknown. The Glanville fritillary butterfly has a large extant metapopulation in the Åland Islands in Finland, but declined to extinction in the nearby fragmented southwestern (SW) Finnish archipelago in the 20th century. We genotyped museum samples for 222 SNPs across the genome, including SNPs from candidate genes and neutral regions. SW Finnish populations had significantly reduced genetic diversity before extinction, and their allele frequencies gradually diverged from those in contemporary Åland populations over 80 y. We identified 15 outlier loci among candidate SNPs, mostly related to flight, in which allele frequencies have changed more than the neutral expectation. At outlier loci, allele frequencies in SW Finland shifted in the same direction as newly established populations deviated from old local populations in contemporary Åland. Moreover, outlier allele frequencies in SW Finland resemble those in fragmented landscapes as opposed to continuous landscapes in the Baltic region. These results indicate selection for genotypes associated with good colonization capacity in the highly fragmented landscape before the extinction of the populations. Evolutionary response to habitat fragmentation may have enhanced the viability of the populations, but it did not save the species from regional extinction in the face of severe habitat loss and fragmentation. These results highlight a potentially common situation in changing environments: evolutionary changes are not strong enough to fully compensate for the direct adverse effects of environmental change and thereby rescue populations from extinction.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Predictable allele frequency changes due to habitat fragmentation in the Glanville fritillary butterfly

Fountain

Nieminen

Sirén

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Three separate criteria were used to select the panel of SNP markers. Markers from candidate genes relating to flight or dispersal traits, or genes that were differentially expressed after an experimental flight treatment were selected on the basis of previous studies (n = 184; (Saastamoinen, Ikonen, Wong, Lehtonen, & Hanski, 2013;Somervuo et al, 2014;de Jong, Wong, Lehtonen, & Hanski, 2014;Kvist et al, 2015). Putatively neutral SNPs (n = 40) from noncoding regions of the genome were also selected, with the remaining 44 SNPs chosen to ensure that all chromosomes were represented, based on linkage map information (Rastas, Paulin, Hanski, Lehtonen, & Auvinen, 2013).…”

Section: Dna Extraction and Genotypingmentioning

confidence: 99%

Inferring dispersal across a fragmented landscape using reconstructed families in the Glanville fritillary butterfly

Fountain

Husby

Nonaka

et al. 2017

Evolutionary Applications

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Dispersal is important for determining both species ecological processes, such as population viability, and its evolutionary processes, like gene flow and local adaptation. Yet obtaining accurate estimates in the wild through direct observation can be challenging or even impossible, particularly over large spatial and temporal scales. Genotyping many individuals from wild populations can provide detailed inferences about dispersal. We therefore utilized genomewide marker data to estimate dispersal in the classic metapopulation of the Glanville fritillary butterfly (Melitaea cinxia L.), in the Åland Islands in SW Finland. This is an ideal system to test the effectiveness of this approach due to the wealth of information already available covering dispersal across small spatial and temporal scales, but lack of information at larger spatial and temporal scales. We sampled three larvae per larval family group from 3732 groups over a six‐year period and genotyped for 272 SNPs across the genome. We used this empirical data set to reconstruct cases where full‐sibs were detected in different local populations to infer female effective dispersal distance, that is, dispersal events directly contributing to gene flow. On average this was one kilometre, closely matching previous dispersal estimates made using direct observation. To evaluate our power to detect full‐sib families, we performed forward simulations using an individual‐based model constructed and parameterized for the Glanville fritillary metapopulation. Using these simulations, 100% of predicted full‐sibs were correct and over 98% of all true full‐sib pairs were detected. We therefore demonstrate that even in a highly dynamic system with a relatively small number of markers, we can accurately reconstruct full‐sib families and for the first time make inferences on female effective dispersal. This highlights the utility of this approach in systems where it has previously been impossible to obtain accurate estimates of dispersal over both ecological and evolutionary scales.

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“…Loci included in each analysis were Pgi , 34 neutral markers, and four additional markers previously identified as being outliers in fragmented vs. continuous landscapes or from flight induced gene expression differences (Kvist et al. ; Fountain et al. ).…”

Section: Methodsmentioning

confidence: 99%

Landscape permeability and individual variation in a dispersal-linked gene jointly determine genetic structure in the Glanville fritillary butterfly

2018

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There is now clear evidence that species across a broad range of taxa harbor extensive heritable variation in dispersal. While studies suggest that this variation can facilitate demographic outcomes such as range expansion and invasions, few have considered the consequences of intraspecific variation in dispersal for the maintenance and distribution of genetic variation across fragmented landscapes. Here, we examine how landscape characteristics and individual variation in dispersal combine to predict genetic structure using genomic and spatial data from the Glanville fritillary butterfly. We used linear and latent factor mixed models to identify the landscape features that best predict spatial sorting of alleles in the dispersal‐related gene phosphoglucose isomerase (Pgi). We next used structural equation modeling to test if variation in Pgi mediated gene flow as measured by Fst at putatively neutral loci. In a year when the population was recovering following a large decline, individuals with a genotype associated with greater dispersal ability were found at significantly higher frequencies in populations isolated by water and forest, and these populations showed lower levels of genetic differentiation at neutral loci. These relationships disappeared in the next year when metapopulation density was high, suggesting that the effects of individual variation are context dependent. Together our results highlight that (1) more complex aspects of landscape structure beyond just the configuration of habitat can be important for maintaining spatial variation in dispersal traits and (2) that individual variation in dispersal plays a key role in maintaining genetic variation across fragmented landscapes.

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Flight‐induced changes in gene expression in the Glanville fritillary butterfly

Cited by 34 publications

References 82 publications

Predictable allele frequency changes due to habitat fragmentation in the Glanville fritillary butterfly

Predictable allele frequency changes due to habitat fragmentation in the Glanville fritillary butterfly

Inferring dispersal across a fragmented landscape using reconstructed families in the Glanville fritillary butterfly

Landscape permeability and individual variation in a dispersal-linked gene jointly determine genetic structure in the Glanville fritillary butterfly

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