Limits...
Using neutral, selected, and hitchhiker loci to assess connectivity of marine populations in the genomic era.

Gagnaire PA, Broquet T, Aurelle D, Viard F, Souissi A, Bonhomme F, Arnaud-Haond S, Bierne N - Evol Appl (2015)

Bottom Line: We highlight several issues that limit the effectiveness of methods based on neutral markers when there is virtually no genetic differentiation among samples.We argue that the increased ability to apply the concepts of cline analyses will improve dispersal inferences across physical and ecological barriers that reduce connectivity locally.We contend that one of the most promising applications of population genomics is the use of outlier loci to delineate relevant conservation units and related eco-geographic features across which connectivity can be measured.

View Article: PubMed Central - PubMed

Affiliation: Université de Montpellier Montpellier, France ; CNRS - Institut des Sciences de l'Evolution, UMR 5554 UM-CNRS-IRD-EPHE, Station Méditerranéenne de l'Environnement Littoral Sète, France.

ABSTRACT
Estimating the rate of exchange of individuals among populations is a central concern to evolutionary ecology and its applications to conservation and management. For instance, the efficiency of protected areas in sustaining locally endangered populations and ecosystems depends on reserve network connectivity. The population genetics theory offers a powerful framework for estimating dispersal distances and migration rates from molecular data. In the marine realm, however, decades of molecular studies have met limited success in inferring genetic connectivity, due to the frequent lack of spatial genetic structure in species exhibiting high fecundity and dispersal capabilities. This is especially true within biogeographic regions bounded by well-known hotspots of genetic differentiation. Here, we provide an overview of the current methods for estimating genetic connectivity using molecular markers and propose several directions for improving existing approaches using large population genomic datasets. We highlight several issues that limit the effectiveness of methods based on neutral markers when there is virtually no genetic differentiation among samples. We then focus on alternative methods based on markers influenced by selection. Although some of these methodologies are still underexplored, our aim was to stimulate new research to test how broadly they are applicable to nonmodel marine species. We argue that the increased ability to apply the concepts of cline analyses will improve dispersal inferences across physical and ecological barriers that reduce connectivity locally. We finally present how neutral markers hitchhiking with selected loci can also provide information about connectivity patterns within apparently well-mixed biogeographic regions. We contend that one of the most promising applications of population genomics is the use of outlier loci to delineate relevant conservation units and related eco-geographic features across which connectivity can be measured.

No MeSH data available.


Related in: MedlinePlus

The demographic parameters values behind weak FST values. (A) Because of the nonlinear relationship between FST and Nem in the island model, genetic differentiation (FST, in color scale) rapidly shrinks as the per-generation number of migrants (Nem) increases. (B) At equilibrium, weak to  genetic differentiation is expected for small (Ne = 103) and highly connected (m = 10−1) populations, but also for large (Ne = 107) and demographically independent (m = 10−5) populations.
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fig01: The demographic parameters values behind weak FST values. (A) Because of the nonlinear relationship between FST and Nem in the island model, genetic differentiation (FST, in color scale) rapidly shrinks as the per-generation number of migrants (Nem) increases. (B) At equilibrium, weak to genetic differentiation is expected for small (Ne = 103) and highly connected (m = 10−1) populations, but also for large (Ne = 107) and demographically independent (m = 10−5) populations.

Mentions: The majority of marine species, however, display combinations of life history traits (e.g. high fecundity, large population sizes, high dispersal potential often combined to complex life cycles) that produce weak patterns of genetic differentiation or even no differentiation at all (Ward et al. 1994; Waples 1998; Palumbi 2003; Hedgecock et al. 2007). A lack of genetic differentiation may result from a range of situations spanning from nearly complete demographic independence among large-sized populations to the existence of a unique panmictic population (Palumbi 2003; Waples and Gaggiotti 2006; Waples et al. 2008) (Fig. 1). Spatial genetic homogeneity may thus hide a large diversity of scenarios with regard to the contemporary rates of demographic exchanges among groups of individuals inhabiting different parts of a species range. This is of particular concern because the per-generation number of migrants, which is sufficient to lead to apparent genetic panmixia, may not be high enough to ensure demographic connectivity and rescue effects (Waples 1998; Lowe and Allendorf 2010). This discrepancy between the objective of inferring demographic connectivity for conservation biology and management purposes and the limitations inherent to most population genetic approaches has motivated several reviews in the field (Waples and Gaggiotti 2006; Broquet and Petit 2009; Hellberg 2009; Lowe and Allendorf 2010). Our goal here is not to provide a new synthesis of existing methods to infer connectivity, which have been thoroughly addressed in those reviews. We rather aim at considering the new perspectives offered by the increasing number of markers in population genomic studies, with a special focus on the use of loci influenced by selection. The rapid spread of next-generation sequencing (NGS)-based genotyping methods in the molecular ecologists' toolbox has considerably enhanced our ability to identify and characterize genetic variation from population samples (Davey et al. 2011). Still, it remains unclear which approaches will benefit the most from this massive amount of sequence data. One direct benefit of analyzing thousands of markers is an increased precision in measuring genetic differentiation and a higher statistical power to detect small genetic differences among populations (Waples 1998). However, populations with large effective sizes, high migration rates or both may remain virtually undifferentiated, and thus, multiplying neutral markers in such cases may still fail to reveal the current level of demographic connectivity.


Using neutral, selected, and hitchhiker loci to assess connectivity of marine populations in the genomic era.

Gagnaire PA, Broquet T, Aurelle D, Viard F, Souissi A, Bonhomme F, Arnaud-Haond S, Bierne N - Evol Appl (2015)

The demographic parameters values behind weak FST values. (A) Because of the nonlinear relationship between FST and Nem in the island model, genetic differentiation (FST, in color scale) rapidly shrinks as the per-generation number of migrants (Nem) increases. (B) At equilibrium, weak to  genetic differentiation is expected for small (Ne = 103) and highly connected (m = 10−1) populations, but also for large (Ne = 107) and demographically independent (m = 10−5) populations.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4561567&req=5

fig01: The demographic parameters values behind weak FST values. (A) Because of the nonlinear relationship between FST and Nem in the island model, genetic differentiation (FST, in color scale) rapidly shrinks as the per-generation number of migrants (Nem) increases. (B) At equilibrium, weak to genetic differentiation is expected for small (Ne = 103) and highly connected (m = 10−1) populations, but also for large (Ne = 107) and demographically independent (m = 10−5) populations.
Mentions: The majority of marine species, however, display combinations of life history traits (e.g. high fecundity, large population sizes, high dispersal potential often combined to complex life cycles) that produce weak patterns of genetic differentiation or even no differentiation at all (Ward et al. 1994; Waples 1998; Palumbi 2003; Hedgecock et al. 2007). A lack of genetic differentiation may result from a range of situations spanning from nearly complete demographic independence among large-sized populations to the existence of a unique panmictic population (Palumbi 2003; Waples and Gaggiotti 2006; Waples et al. 2008) (Fig. 1). Spatial genetic homogeneity may thus hide a large diversity of scenarios with regard to the contemporary rates of demographic exchanges among groups of individuals inhabiting different parts of a species range. This is of particular concern because the per-generation number of migrants, which is sufficient to lead to apparent genetic panmixia, may not be high enough to ensure demographic connectivity and rescue effects (Waples 1998; Lowe and Allendorf 2010). This discrepancy between the objective of inferring demographic connectivity for conservation biology and management purposes and the limitations inherent to most population genetic approaches has motivated several reviews in the field (Waples and Gaggiotti 2006; Broquet and Petit 2009; Hellberg 2009; Lowe and Allendorf 2010). Our goal here is not to provide a new synthesis of existing methods to infer connectivity, which have been thoroughly addressed in those reviews. We rather aim at considering the new perspectives offered by the increasing number of markers in population genomic studies, with a special focus on the use of loci influenced by selection. The rapid spread of next-generation sequencing (NGS)-based genotyping methods in the molecular ecologists' toolbox has considerably enhanced our ability to identify and characterize genetic variation from population samples (Davey et al. 2011). Still, it remains unclear which approaches will benefit the most from this massive amount of sequence data. One direct benefit of analyzing thousands of markers is an increased precision in measuring genetic differentiation and a higher statistical power to detect small genetic differences among populations (Waples 1998). However, populations with large effective sizes, high migration rates or both may remain virtually undifferentiated, and thus, multiplying neutral markers in such cases may still fail to reveal the current level of demographic connectivity.

Bottom Line: We highlight several issues that limit the effectiveness of methods based on neutral markers when there is virtually no genetic differentiation among samples.We argue that the increased ability to apply the concepts of cline analyses will improve dispersal inferences across physical and ecological barriers that reduce connectivity locally.We contend that one of the most promising applications of population genomics is the use of outlier loci to delineate relevant conservation units and related eco-geographic features across which connectivity can be measured.

View Article: PubMed Central - PubMed

Affiliation: Université de Montpellier Montpellier, France ; CNRS - Institut des Sciences de l'Evolution, UMR 5554 UM-CNRS-IRD-EPHE, Station Méditerranéenne de l'Environnement Littoral Sète, France.

ABSTRACT
Estimating the rate of exchange of individuals among populations is a central concern to evolutionary ecology and its applications to conservation and management. For instance, the efficiency of protected areas in sustaining locally endangered populations and ecosystems depends on reserve network connectivity. The population genetics theory offers a powerful framework for estimating dispersal distances and migration rates from molecular data. In the marine realm, however, decades of molecular studies have met limited success in inferring genetic connectivity, due to the frequent lack of spatial genetic structure in species exhibiting high fecundity and dispersal capabilities. This is especially true within biogeographic regions bounded by well-known hotspots of genetic differentiation. Here, we provide an overview of the current methods for estimating genetic connectivity using molecular markers and propose several directions for improving existing approaches using large population genomic datasets. We highlight several issues that limit the effectiveness of methods based on neutral markers when there is virtually no genetic differentiation among samples. We then focus on alternative methods based on markers influenced by selection. Although some of these methodologies are still underexplored, our aim was to stimulate new research to test how broadly they are applicable to nonmodel marine species. We argue that the increased ability to apply the concepts of cline analyses will improve dispersal inferences across physical and ecological barriers that reduce connectivity locally. We finally present how neutral markers hitchhiking with selected loci can also provide information about connectivity patterns within apparently well-mixed biogeographic regions. We contend that one of the most promising applications of population genomics is the use of outlier loci to delineate relevant conservation units and related eco-geographic features across which connectivity can be measured.

No MeSH data available.


Related in: MedlinePlus