86
M.S. Clark et al.
produce similar results to those by Vasemägi et al. (2005), which in their case did
not directly shed light on the physiological basis of local adaptation. This could
possibly be improved if EST-SSRs were only used from ESTs that matched known
genes. This would improve our knowledge of how physiological regulation shapes
a given phenotype and/or pattern of habitat distribution. However, this can dramatically decrease the number of such markers available for population studies, reducing
the benefit of genomics in providing ecological and population tools. In consequence, functional information should not be an a priori prerequisite for choosing
EST-SSR markers.
3.2.1.2 Differentiating Selective and Demographic Effects
One challenge when studying the genetic basis of adaptation is that the pattern
of variation produced by genetic hitch-hiking or selective sweeps may also be the
result of demographic changes. Therefore a common approach in population genetics studies is to analyse a very large number of unlinked loci (the so-called “genome
scan” method; see Luikart et al. 2003, Storz 2005) in an attempt to disentangle
selective and demographic effects (see also Teshima et al. 2006). As stated by, e.g.,
Wenne et al. (2007), the outlier loci in genome scans – i.e. loci that do not statistically conform to the neutral theory – offer the potential for the generation of
informative markers which are suited for specific questions raised in management
scenarios of marine species. According to the theory first developed by MaynardSmith and Haigh (1974), outlier loci are most likely the causal loci, but are either
physically linked or in linkage disequilibrium (LD) with the site(s) that undergo
or have undergone selection. The extent of LD between the marker locus and the
functionally relevant mutation involved in one ecological adaptation can vary dramatically across the genome and also between study systems. This will be affected
by population history, mating system, recombination rate, the age of the selected
allele, the strength of selection and many other factors (Nordborg and Tavare 2002).
Several marker types can be used for genome scans such as anonymous microsatellites (amphibian: Bonin et al. 2006), SNPs (man: Akey et al. 2002), or a combination
of several markers (cf. Chinook salmon: Smith et al. 2007). Dominant (see Bensch
et al. 2002) AFLP (Vos et al. 1995) markers are also appropriate tools for carrying
out such analyses as these can be produced at a moderate cost and with no previous
genomic knowledge.
3.2.1.3 Identifying Adaptive Traits
The use of molecular markers, such as anonymous microsatellites, EST-SSRs and
AFLPs, is not necessarily the best approach for addressing all ecological issues. This
is because they are mostly neutral and do not enable the understanding of fitness differences among wild individuals that could drive adaptation in a given environment.
Generally, it is not known if they are associated with a gene and, even if this is
known, the role(s) of such an associated gene in metabolic/gene network(s) can be
very obscure in a wide range of marine organisms. The continued development of
M.S. Clark et al.
produce similar results to those by Vasemägi et al. (2005), which in their case did
not directly shed light on the physiological basis of local adaptation. This could
possibly be improved if EST-SSRs were only used from ESTs that matched known
genes. This would improve our knowledge of how physiological regulation shapes
a given phenotype and/or pattern of habitat distribution. However, this can dramatically decrease the number of such markers available for population studies, reducing
the benefit of genomics in providing ecological and population tools. In consequence, functional information should not be an a priori prerequisite for choosing
EST-SSR markers.
3.2.1.2 Differentiating Selective and Demographic Effects
One challenge when studying the genetic basis of adaptation is that the pattern
of variation produced by genetic hitch-hiking or selective sweeps may also be the
result of demographic changes. Therefore a common approach in population genetics studies is to analyse a very large number of unlinked loci (the so-called “genome
scan” method; see Luikart et al. 2003, Storz 2005) in an attempt to disentangle
selective and demographic effects (see also Teshima et al. 2006). As stated by, e.g.,
Wenne et al. (2007), the outlier loci in genome scans – i.e. loci that do not statistically conform to the neutral theory – offer the potential for the generation of
informative markers which are suited for specific questions raised in management
scenarios of marine species. According to the theory first developed by MaynardSmith and Haigh (1974), outlier loci are most likely the causal loci, but are either
physically linked or in linkage disequilibrium (LD) with the site(s) that undergo
or have undergone selection. The extent of LD between the marker locus and the
functionally relevant mutation involved in one ecological adaptation can vary dramatically across the genome and also between study systems. This will be affected
by population history, mating system, recombination rate, the age of the selected
allele, the strength of selection and many other factors (Nordborg and Tavare 2002).
Several marker types can be used for genome scans such as anonymous microsatellites (amphibian: Bonin et al. 2006), SNPs (man: Akey et al. 2002), or a combination
of several markers (cf. Chinook salmon: Smith et al. 2007). Dominant (see Bensch
et al. 2002) AFLP (Vos et al. 1995) markers are also appropriate tools for carrying
out such analyses as these can be produced at a moderate cost and with no previous
genomic knowledge.
3.2.1.3 Identifying Adaptive Traits
The use of molecular markers, such as anonymous microsatellites, EST-SSRs and
AFLPs, is not necessarily the best approach for addressing all ecological issues. This
is because they are mostly neutral and do not enable the understanding of fitness differences among wild individuals that could drive adaptation in a given environment.
Generally, it is not known if they are associated with a gene and, even if this is
known, the role(s) of such an associated gene in metabolic/gene network(s) can be
very obscure in a wide range of marine organisms. The continued development of