7 Genomic Approaches in Aquaculture and Fisheries
253
associated exchange of genetic material (gene flow) among populations. Population
genetic theory predicts that the level of genetic divergence among populations is
positively correlated with the degree of reproductive isolation. For most species the
“genetic distance” (F st
1 ) is below 3%. As such, subtle genomic variation is the rule
more than the exception (e.g. European eel: Maes et al. 2006; bluefin tuna Rooker
et al. 2007; Atlantic herring: Ruzzante et al. 2006), although cases of relatively
strong genetic differentiation have been documented (e.g. in Atlantic cod, Nielsen
et al. 2003; Atlantic killifish, Duvernell et al. 2008). Accordingly, population genetics of marine fish has constantly been hovering on the brink of detection of a true
signal of population differentiation (Waples 1998). The statistical power for inferring population structure in marine fish can be improved by using large samples
of individuals and checking for temporal stability. In many cases, however, strong
inferences of the mere occurrence of population structure or the relationships among
putative populations cannot be made with the limited number of genetic markers
commonly employed at present. For example, Koskinen et al. (2004) found that the
median number of genetic markers (nuclear microsatellites or SSR) was only six!
The theoretical recommended number for unambiguous determination of relationships and distance among populations is at least 30 but could reach several hundreds
(see Takezaki and Nei 1996, Pollock et al. 1998). In practice, Koskinen et al. (2004)
showed that increasing the number of microsatellite genetic markers from 6 to 17
provided a massive improvement of the power for determining the correct genetic
relationships. Obviously, a switch to genomic methods, where hundreds of markers
are commonly employed, might revolutionize the field of research. An additional
problem relates to determining the evolutionary properties of the genetic markers employed. State of the art genetic markers such as microsatellites are a priori
assumed to represent neutral genomic variation, i.e. not subject to direct or hitchhiking selection. Recent cases have shown that microsatellites subject to selection
are not uncommon in population genetic studies of fish (Nielsen et al. 2006, Larsson
et al. 2007). Accordingly, demographic inferences on migration rates and population sizes based on “neutral” population genetic theory are expected to be biased.
In contrast, scanning the genome using multiple genetic markers spread throughout the genome would allow a statistical evaluation of the evolutionary dynamics of
individual marker loci (Beaumont and Nichols 1996, Schlötterer 2002) enabling the
establishment of a neutral baseline applicable for providing demographic inferences
(Luikart et al. 2003). Markers subject to selection on the other hand could be used
for inferring local adaptations to specific environmental conditions experienced by
local populations (see next paragraph).
Although we are aware of many ongoing studies using large genomic datasets
for inferring population structure of marine fish, the number of published studies is
relatively scarce. As in many other fields of fisheries science, salmonid research is
1 F st is the proportion of the total genetic variance which can be ascribed to population differences.
F st can attain values between 1, when populations are completely isolated, and 0 when there is no
apparent reproductive isolation among samples. Intermediate values represent different levels of
migration among populations.
253
associated exchange of genetic material (gene flow) among populations. Population
genetic theory predicts that the level of genetic divergence among populations is
positively correlated with the degree of reproductive isolation. For most species the
“genetic distance” (F st
1 ) is below 3%. As such, subtle genomic variation is the rule
more than the exception (e.g. European eel: Maes et al. 2006; bluefin tuna Rooker
et al. 2007; Atlantic herring: Ruzzante et al. 2006), although cases of relatively
strong genetic differentiation have been documented (e.g. in Atlantic cod, Nielsen
et al. 2003; Atlantic killifish, Duvernell et al. 2008). Accordingly, population genetics of marine fish has constantly been hovering on the brink of detection of a true
signal of population differentiation (Waples 1998). The statistical power for inferring population structure in marine fish can be improved by using large samples
of individuals and checking for temporal stability. In many cases, however, strong
inferences of the mere occurrence of population structure or the relationships among
putative populations cannot be made with the limited number of genetic markers
commonly employed at present. For example, Koskinen et al. (2004) found that the
median number of genetic markers (nuclear microsatellites or SSR) was only six!
The theoretical recommended number for unambiguous determination of relationships and distance among populations is at least 30 but could reach several hundreds
(see Takezaki and Nei 1996, Pollock et al. 1998). In practice, Koskinen et al. (2004)
showed that increasing the number of microsatellite genetic markers from 6 to 17
provided a massive improvement of the power for determining the correct genetic
relationships. Obviously, a switch to genomic methods, where hundreds of markers
are commonly employed, might revolutionize the field of research. An additional
problem relates to determining the evolutionary properties of the genetic markers employed. State of the art genetic markers such as microsatellites are a priori
assumed to represent neutral genomic variation, i.e. not subject to direct or hitchhiking selection. Recent cases have shown that microsatellites subject to selection
are not uncommon in population genetic studies of fish (Nielsen et al. 2006, Larsson
et al. 2007). Accordingly, demographic inferences on migration rates and population sizes based on “neutral” population genetic theory are expected to be biased.
In contrast, scanning the genome using multiple genetic markers spread throughout the genome would allow a statistical evaluation of the evolutionary dynamics of
individual marker loci (Beaumont and Nichols 1996, Schlötterer 2002) enabling the
establishment of a neutral baseline applicable for providing demographic inferences
(Luikart et al. 2003). Markers subject to selection on the other hand could be used
for inferring local adaptations to specific environmental conditions experienced by
local populations (see next paragraph).
Although we are aware of many ongoing studies using large genomic datasets
for inferring population structure of marine fish, the number of published studies is
relatively scarce. As in many other fields of fisheries science, salmonid research is
1 F st is the proportion of the total genetic variance which can be ascribed to population differences.
F st can attain values between 1, when populations are completely isolated, and 0 when there is no
apparent reproductive isolation among samples. Intermediate values represent different levels of
migration among populations.