Development of microsatellite markers in the Sparidae and their application in population genetics of the hottentot seabream around South Africa

By defining the degree of genetic spatial variation of populations, inferences can be made about what biological and environmental factors influence the genetic divergence and biogeography of marine species (Cowen et al. 2006). The marine environment is extensive, covering over 70 percent of the earth’s surface and contain highly diverse habitats (Avise 1998; Chopelet et al. 2009). These habitats are not always continuous and may be patchy (e.g. kelp beds) and variable (Gratwicke & Speight 2005). The interactions of individuals (life-history traits) of a species within and between patchy habitats leads to a specific degree of genetic diversity and population structure that can be identified (Chopelet et al. 2009). Marine species are often characterised by specific life-history traits such as high fecundity, numerous pelagic eggs and larvae, mobility and longevity which contribute to high levels of gene flow counterbalancing spatial heterogeneity of habitats (Avise 1998; Hauser & Carvalho 2008). These life-history traits coupled with homogenous transient habitats (allowing dispersal between habitats) that have limited physical barriers lead to a general lack of highly divergent populations at a regional scale. This is however not always the case for all organisms with several marine fish having been identified with population structure on local and regional scales (González et al. 2008; Narum et al. 2008; Nielsen et al. 2009). Population genetics plays a major role in the management and the conservation of commercial marine fish as the statistical approaches allow for the identification of the number of stocks that may need to be conserved separately. Marine fish are harvested in large quantities and this has led to overexploitation (Carvalho & Hauser 1998). By over-harvesting, genetic diversity may be lost which has wider implications as this decreases the ability of the species to adapt (Fenberg & Roy 2008). Also marine fish are one of the last wild sources of protein and as the stocks become depleted it has far reaching implications on the people who rely on it as a food source and income (Ryman et al. 1995). The correct management and conservation required to maintain the sustainability of this resource starts with the improvement of knowledge of the population biology of the targeted species.

South Africa has a wide range of marine fish species due to the diverse geological and oceanographic features which provide a number of habitats along the coast. One of the most prevalent and diverse fish families along the South African coast is the Sparidae. This family is of economic importance to the line fishery and many of these species are considered vulnerable or endangered due to a combination of overfishing and life-history traits. Two species of particular interest are the hottentot seabream (Pachymetopon blochii) and white steenbras (Lithognathus lithognathus). Both species are endemic to southern Africa and are considered vulnerable to overexploitation.

This study reports the development of microsatellite markers for both the above mentioned species using the Fast Isolation by AFLP of Sequences Containing Repeats (FIASCO) developed by Zane et al. (2002). Nine polymorphic markers were identified in each of these species. Nineteen markers (fifteen newly developed and four from other sparids) were used as a panel on eleven economically important sparids, to test microsatellite cross-species amplification. From this study twelve adequate polymorphic loci were identified for the white steenbras (applied in a population genetic study by a PhD student associated with SAIAB) and fourteen in the hottentot seabream which were applied in this dissertation. We were also able to identify a number of polymorphic loci for the other sparids (Fig. 1). It was concluded that the sparids do not show a negative correlation between genetic distance and microsatellite amplification success and polymorphism.

Fig. 1 Summary of the number of microsatellites that amplification (A) and were polymorphic (P) in the different sparid species included in this study.

The study further investigated the population genetic structure of the hottentot seabream. Pachymetopon blochii is an endemic, demersal sparid occurring along the west coast of southern Africa, found mainly in kelp beds and rocky outcrops (Heemstra & Heemstra 2004). This species is targeted by line fisheries and is considered vulnerable due to its slow growth and sedentary adults. Two hypotheses are considered in this study, the first being that the eggs and larvae remain in the habitats where the adults are found and this would lead to less gene flow between geographically separated habitats (hypothesis of isolation). Alternatively the eggs and larvae could be transported by the inshore currents which would lead to a single population identified along the west coast of South Africa (hypothesis of panmixia). The main aim of this study was to investigate which of these two hypotheses best explains the population connectivity in the hottentot seabream.

For this purpose, the spatial and temporal genetic variation of this species along the South African west coast was assessed. Fourteen highly polymorphic loci were genotyped for 288 individuals across nine locations sampled in 2001 and in 189 samples from six locations in 2009 (Fig. 2). Individual-based statistical analyses suggested the presence of one population along the coast. The effective population size was estimated to be relatively small (~ 9989 individuals). Weak spatial structure was identified between the sampling locations from 2009 using Factorial Correspondence Analysis (FCA), Analysis of Molecular Variance (AMOVA) and Spatial Autocorrelation (SAC). Between the 2001 sampling locations no significant spatial structure was identified. Temporal variation was identified between the two sampling years. This was likely due to “larval genetic patchiness” which led to variations in the observed population structure across different years. In conclusion, one population of the hottentot seabream was identified along the coast of South Africa with weak spatial and temporal variation between years, which is likely due to the larval dispersal and mortality mediated through the oceanographic features along the west coast.

Fig. 2 Map of the locations sampled along the coast of South Africa in 2001 and 2009. The 2001 sampling locations are indicated in blue and the 2009 sampling locations in red. The inset shows a map of Africa (google maps; orange line indicates the west coast of southern Africa where the hottentot is distributed) and an image of the hottentot seabream.