Population genetics of Galeorhinus galeus, Carcharhinus brachyurus and Rhinobatos annulatus- implications for regional fisheries and elasmobranch conservation

Thesis (PhDAgric)--Stellenbosch University, 2016.ENGLISH ABSTRACT: Elasmobranchs (sharks, skates and rays) are highly exploited world-wide and more vulnerable than most teleosts due to their life history traits (e.g. late age at maturity, low fecundity and slow growth). Most elasmobranchs are either targeted by commercial fisheries or unintentionally taken as bycatch in mixed-species fisheries. Among these, the tope shark Galeorhinus galeus, the copper shark Carcharhinus brachyurus and the southern African endemic lesser sandshark Rhinobatos annulatus, are targeted globally and locally in demersal, pelagic and recreational fisheries. Across the Southern Hemisphere, the International Union for the Conservation of Nature (IUCN) categorizes both the tope and copper sharks as “vulnerable” while the lesser sandshark as “data deficient” within its region of endemism. Information is urgently needed on their regional genetic structure and diversity to help delineate management units (MUs) for better fisheries monitoring and conserving local biodiversity. Regional and local population genetic structure of these species was assessed using previously optimised cross-species microsatellite panels and/or the mitochondrial NADH2 and NADH4 genes. Patterns of evolutionary and demographic history were inferred using coalescent and Bayesian statistical methods. For G. galeus, the data showed a lack of contemporary gene flow and deep historical divergence across the Southern Hemisphere. Two geographically distinct mitochondrial clades were recovered, one including the Atlantic and Indo-Pacific collections (ARG, SA and AUS) and one comprising the Pacific samples (NZ and CHI) as well as single divergent haplotype restricted to South Africa. Nuclear data also revealed large population subdivisions (FST = 0.050 to 0.333, P 0.05), with some degree of genetic structure between the Atlantic and Indian Ocean samples. The east coast samples of Port Elizabeth were significantly differentiated from the rest (FST = 0.023 to 0.091, P > 0.05). For C. brachyurus, estimates of pairwise population differentiation were significant (average FST = 0.031, P = 0.000) indicating some degree of gene flow between sampling sites while the sub-structuring observed at Strandfontein indicated the existence of a possible distinct, more admixed group of individuals. Neither AMOVA (FCT = -0.011, P = 1.000) nor Bayesian clustering analyses indicated genetic discontinuity or significant population structure across the Atlantic/Indian boundary. Although the ND4 results also alluded to historical dispersal across this boundary, the population of Mossel Bay harboured four highly divergent haplotypes, indicating that this region might be a potential nursery site for C. brachyurus. The genetic diversity and genetic connectivity of R. annulatus was inferred using cross-amplified polymorphic microsatellite loci across the Agulhas bioregion that coincides with the warm temperate biogeographical province of South Africa. Significant genetic differentiation was observed over a small sampling range (FST = 0.016 to 0.094, P < 0.050) implying that the species might be highly structured throughout its entire geographical range. Overall effective population size for R. annulatus was very low (Ne = 106) and not in accordance to the abundance proposed for the species. As this is the first regional assessment for all three of these species, the findings of this study could have immediate implications for the regional management and conservation of commercial and recreational sharks.AFRIKAANS OPSOMMING: Geen opsomming beskikbaa

Population genetics of Southern Hemisphere tope shark (<i>Galeorhinus galeus</i>) : Intercontinental divergence and constrained gene flow at different geographical scales

The tope shark (Galeorhinus galeus Linnaeus, 1758) is a temperate, coastal hound shark found in the Atlantic and Indo-Pacific oceans. In this study, the population structure of Galeorhinus galeus was determined across the entire Southern Hemisphere, where the species is heavily targeted by commercial fisheries, as well as locally, along the South African coastline. Analysis was conducted on a total of 185 samples using 19 microsatellite markers and a 671 bp fragment of the NADH dehydrogenase subunit 2 (ND2) gene. Across the Southern Hemisphere, three geographically distinct clades were recovered, including one from South America (Argentina, Chile), one from Africa (all the South African collections) and an Australia-New Zealand clade. Nuclear data revealed significant population subdivisions (FST = 0.192 to 0.376, p<0.05) indicating limited gene flow for tope sharks across ocean basins. Marked population connectivity was however evident across the Indian Ocean based on Bayesian clustering analysis. More locally in South Africa, F-statistics and multivariate analysis supported moderate to high gene flow across the Atlantic/ Indian Ocean boundary (FST = 0.035 to 0.044, p<0.05), with exception of samples from Struisbaai and Port Elizabeth which differed significantly from the rest. Discriminant and Bayesian clustering analysis indicated admixture in all sampling populations, decreasing from west to east, corroborating possible restriction to gene flow across regional oceanographic barriers. Mitochondrial sequence data recovered seven haplotypes (h = 0.216, π = 0.001) for South Africa, with one major haplotype shared by 87% of the individuals and at least one private haplotype for each sampling location except Port Elizabeth. As with many other coastal shark species with cosmopolitan distribution, this study confirms the lack of both historical dispersal and inter-oceanic gene flow while also implicating contemporary factors such as oceanic currents and thermal fronts to drive local genetic structure of G. galeus on a smaller spatial scale.Facultad de Ciencias Naturales y Muse

Implementation of molecular markers for triticale cultivar identification and marker-assisted selection

Thesis (MSc)--Stellenbosch University, 2012.Triticale is an amphidiploid that consists of wheat (A and B) and rye (R) genomes. This cereal is fast becoming important on a commercial basis and warrants further assessment for the better management and breeding of the hybrid. The assessment of the genetic diversity among the wheat and rye genomes within triticale can be obtained by using molecular markers developed in both donor genomes. Simple sequence repeats markers (SSRs) and amplified fragment length markers (AFLPs) have been previously used to assess the genetic diversity among triticale lines. SSRs are highly polymorphic markers that are abundant and which have been shown to be highly transferable between species in previous studies while AFLP markers are known to generate plenty of data as they cover so many loci. Thus, the aim of this study was to develop a marker system suitable to assess the genetic diversity and relationships of advanced breeding material (and cultivars) of the Stellenbosch University’s Plant Breeding Laboratory (SU-PBL). Therefore, both AFLP and SSR markers were initially analysed using eight triticale cultivars (with known pedigrees) to facilitate cultivar identification. Fourty-two AFLP primer combinations and 86 SSR markers were used to assess the genetic diversity among the Elite triticale cultivars. The AFLP primer combinations generated under average polymorphism information content (PIC) values. Furthermore, these markers generated neighbour-joining (NJ) and unweighted pair group method with arithmetic average (UPGMA) dendograms that displayed relationships that did not correspond with the available pedigree information. Therefore, this marker system was found not to be suitable. A set of 86 SSRs previously identified in both wheat and rye, was used to test the genetic diversity among the eight cultivars. The markers developed in wheat achieved 84% transferability while those developed in rye achieved 79.3% transferability. A subset of SSR markers was able to distinguish the cultivars, and correctly identify them by generating NJ and UPGMA dendograms that exhibited relationships that corroborated the available pedigree data. This panel of markers was therefore chosen as the most suitable for the assessment of the advanced breeding material. The panel of seven SSR markers was optimised for semi-automated analysis and was used to screen and detect the genetic diversity among 306 triticale entries in the F6, Senior and Elite phases of the SU-PBL triticale breeding programme. An average PIC value of 0.65 was detected and moderate genetic variation was observed. NJ and UPGMA dendograms generated showed no clear groupings. However, the panel of markers managed to accurately identify all cultivars within the breeding program. The marker panel developed in this study is being used to routinely distinguish among the advanced breeding material within the SU-PBL triticale breeding programme and as a tool in molecular-assisted backcross

Population genetics of Southern Hemisphere tope shark (<i>Galeorhinus galeus</i>): Intercontinental divergence and constrained gene flow at different geographical scales

<div><p>The tope shark (<i>Galeorhinus galeus</i> Linnaeus, 1758) is a temperate, coastal hound shark found in the Atlantic and Indo-Pacific oceans. In this study, the population structure of <i>Galeorhinus galeus</i> was determined across the entire Southern Hemisphere, where the species is heavily targeted by commercial fisheries, as well as locally, along the South African coastline. Analysis was conducted on a total of 185 samples using 19 microsatellite markers and a 671 bp fragment of the NADH dehydrogenase subunit 2 (<i>ND2</i>) gene. Across the Southern Hemisphere, three geographically distinct clades were recovered, including one from South America (Argentina, Chile), one from Africa (all the South African collections) and an Australia-New Zealand clade. Nuclear data revealed significant population subdivisions (F_ST = 0.192 to 0.376, p<0.05) indicating limited gene flow for tope sharks across ocean basins. Marked population connectivity was however evident across the Indian Ocean based on Bayesian clustering analysis. More locally in South Africa, F-statistics and multivariate analysis supported moderate to high gene flow across the Atlantic/Indian Ocean boundary (F_ST = 0.035 to 0.044, p<0.05), with exception of samples from Struisbaai and Port Elizabeth which differed significantly from the rest. Discriminant and Bayesian clustering analysis indicated admixture in all sampling populations, decreasing from west to east, corroborating possible restriction to gene flow across regional oceanographic barriers. Mitochondrial sequence data recovered seven haplotypes (<i>h</i> = 0.216, π = 0.001) for South Africa, with one major haplotype shared by 87% of the individuals and at least one private haplotype for each sampling location except Port Elizabeth. As with many other coastal shark species with cosmopolitan distribution, this study confirms the lack of both historical dispersal and inter-oceanic gene flow while also implicating contemporary factors such as oceanic currents and thermal fronts to drive local genetic structure of <i>G</i>. <i>galeus</i> on a smaller spatial scale.</p></div

Analysis of molecular variance (AMOVA) across South Africa of <i>Galeorhinus galeus</i> based on mtDNA <i>ND2</i> sequence and microsatellite data.

<p>Analysis of molecular variance (AMOVA) across South Africa of <i>Galeorhinus galeus</i> based on mtDNA <i>ND2</i> sequence and microsatellite data.</p

Analysis of molecular variance (AMOVA) across the Southern Hemisphere of <i>Galeorhinus galeus</i> based on mtDNA <i>ND2</i> sequence and microsatellite data.

<p>Analysis of molecular variance (AMOVA) across the Southern Hemisphere of <i>Galeorhinus galeus</i> based on mtDNA <i>ND2</i> sequence and microsatellite data.</p

Pairwise Φ_ST values for mtDNA (below diagonial) and pairwise F_ST values for microsatellite data (above diagonial) among sampling locations across the Southern Hemisphere (left) and South Africa (right).

<p>Pairwise Φ_ST values for mtDNA (below diagonial) and pairwise F_ST values for microsatellite data (above diagonial) among sampling locations across the Southern Hemisphere (left) and South Africa (right).</p

Sampling locations of <i>Galeorhinus galeus</i>.

<p>Map showing the major biogeographic barriers and oceanic currents across the Southern Hemisphere and South Africa. The main biogeographic barriers indicated by the dashed lines are the Eastern South Pacific Barrier (EPB) and the Mid-Atlantic Barrier (MAB). Sampling codes: Chile (CHI), Argentina (ARG), South Africa (SA), Australia (AUS), New Zealand (NZ); Robben Island (RI), False Bay (FB), Kleinmond (K), Agulhas Bank (AB), Struisbaai (SB) and Port Elizabeth (PE).</p

Cluster composition and population differentiation of <i>Galeorhinus galeus</i>.

<p>Scatterplots generated by the DAPC analysis for sampling populations from (A) the Southern Hemisphere and (B) South Africa respectively.</p

Individual cluster assignments generated from STRUCTURE analysis.

<p>This is illustrated by sampling location for K = 2 to K = 6 for both the Southern Hemisphere and the South African sampling populations.</p