Three of the commonly used multilocus DNA marker systems in evolutionary, taxonomic, ecological, phylogenetic, and genetic studies are RFLPs, RAPDs, and AFLPs (DeYoung and Honeycutt 2005; Behura 2006; Agarwal et al. 2008). All these markers generate banding patterns that are scored for variation. In all three markers, the detected variation is caused by either point mutation within recognition sequences as well as insertions and/or deletions between the recognition sites, which may lead to an underestimation of genetic variation (DeYoung and Honeycutt 2005). Since none of the described multilocus markers is specific to a certain target organism DNA, there is a risk of false variation generated by contaminations (Sunnucks 2000). Furthermore, dominance of some of the markers (RAPD and AFLP) does not allow for a detection of alleles.
Depending on the sampling strategy, these markers can cover a wide spatial range, allowing for a detailed fine scale analysis of population structure between individuals, especially with AFLPs (Meudt and Clarke 2007), up to taxonomically and spatially coarse studies (e.g., Despres et al. 2003). While RFLP, RAPD, or AFLP are unsuitable to estimate mutation rates or alike, and are thus inappropriate for temporal studies (i.e., evolutionary), they provide a detailed image of the present species or population genetic state.
2.4.1 RFLP: Restriction Fragment Length Polymorphism
Restriction fragment length polymorphisms (Botstein et al. 1980) are highly polymorphic, co-dominantly inherited markers based on the use of restriction enzymes which can be applied as single and multilocus probes with the banding patterns resulting from multilocus probes.
The technique generates highly reproducible banding patterns and is characterized by a high heritability (Lowe et al. 2004; Semagn et al. 2006; Agarwal et al.
2008). It is used in areas such as population and conservation genetics, diversity (e.g., Apostolidis et al. 2008), phylogenetics (e.g., Hu et al. 2008), linkage mapping (e.g., Tanksley et al. 1989), or cultivar identification (e.g., Busti et al. 2004), though their main application is within human genetics (Weising et al. 2005). As RFLPs require relatively large amounts of DNA, they have recently been replaced by PCR-RFLPs or AFLP analyses in most ecological studies.
2.4.2 RAPD: Random Amplified Polymorphic DNA
The dominant marker system RAPD, introduced by Williams et al. (1990), is based on arbitrarily amplifying DNA sequences during PCR, without prior knowledge of the organism sequence, using 10 nucleotide primers (Lowe et al. 2004, Weising et al. 2005). One of the main problems associated with RAPDs is their susceptibility to changes in reaction conditions leading to reproducibility problems (Jones et al. 1997; Agarwal et al. 2008; Assmann et al. 2007). Due to these problems, some peer-reviewed journals (e.g., Molecular Ecology) have recently changed their policy and publish RAPD data only in exceptional cases.
RAPDs have been used in many fields, among them are studies on population and conservation genetics (e.g., Kim et al. 2008), phylogenetics (e.g., Simmons et al. 2007), and linkage mapping (e.g., Sun et al. 2008).
2.4.3 AFLP: Amplified Fragment Length Polymorphism
AFLPs are dominant markers based on a combination of the RFLP and PCR techniques and were developed by Vos et al. (1995). Also, they do not require any previous sequence information and are based on the digestion of DNA by restriction enzymes and adapter ligation (resulting in universal primer binding sites), with two subsequent PCRs using specific primers. AFLPs are highly reproducible (Meudt and Clarke 2007; Agarwal et al. 2008) and primers can be combined to yield a large set of combinations, though this may also lead to a clustering of markers with certain restriction enzymes (Keim et al. 1997; Young et al. 1999; Saal and Wricke 2002).
AFLPs find wide application in studies on population genetics, diversity, and differentiation (e.g., Abbott et al. 2008; Tang et al. 2008), phylogenetics and taxonomy (e.g., Brouat et al. 2004; Schenk et al. 2008), hybridization (e.g., Volkova et al. 2008), linkage, gene, and genome mapping (e.g., Olmstead et al. 2008; Radoev et al. 2008), assignments (e.g., Yang et al. 2008) and kinship (e.g., Hardy et al. 2006). Although they are dominant markers, the large number of loci gives them a high statistical power (Meudt and Clarke 2007). Therefore, they are well suited for intraspecific studies (distinguishing between closely related individuals), where many loci are necessary (i.e., high genomic heterogeneity, low genetic variability), in polyploids, and in systems with hybridization occurring (Meudt and Clarke 2007).
Table 1 Advantages, disadvantages and different features of microsatellites, Allozymes, mtDNA, RFLPs, RAPDs, and AFLPs
DNA amount required
Medium costs (l)No sequence information needed(4) High reproducibility &
reliability (4) Easy & safe protocol
(4)Low costs (4, 8) Many enzyme systems (4) Suited for polyploids (4)
Constant mutation rates (11) Available primers Neutral and selective regions (6) Inherited maternally (7) Detection of nucleotide
DNA and organelle DNA polymorphisms (4) Phylogenetic analysis (4) High repeatability (1, 2, 4)
High start-up costs (1,4) Species-specific primer pairs (4) PCR-based problems (5)
Underestimation of genetic variation (4) Not sure whether neutral or not (10) Limited to extant populations (10) Only forzen or fresh samples (10) Little practical value for population genetic studies (8) Expensive
Labor intensive use (1.4)
High start-up costs (1,4) Comparability between studies difficult (4)
High Medium (1,
Low costs (1,4) Easy use (1, 4) No sequence information needed(4) Medium costs (l)No sequence information needed(4) High reproducibility & reliability (4)
Low-intermediate reproducibility (1,2) Extensive criticism, see (4)
Initially difficult to set up (1 /Technically demanding (4) Relatively high amounts of DNA needed (4)
Abbreviations: 1= Semagn et al. 2006; 2= Agarwal et al. 2008; 3= Sunnucks 2000; 4= Lowe et al. 2004; 5= Selkoe and Toonen 2006; 6= Wan et al. 2004; 7= Behura 2006; 8= Zhang and Hewitt 2003 ;~9= DeYoung and Honeycutt 2005; 10= van der Bank et al. 2001; 11= Lushai et al. 2003
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