Single nucleotide polymorphism genotypes for the Australian blackspot shark and the milk shark in Northern Australian waters

Charles Darwin University and the Northern Territory (NT) Department of Industry, Tourism and Trade (DITT) Fisheries Division used genetic data to investigate the population structure of two small tropical shark species (Milk Shark [Rhizoprionodon acutus] and Australian Blackspot Shark [Carcharhinus coatesi]), which are caught as bycatch from commercial fisheries in the NT.

The aim of this study was to gain information on the genetic stock structure to inform the future management of these two species in the NT. This project was conducted in parallel with a PhD project investigating the biology and ecology of both species for applications to fisheries management. There is motivation by the NT Government to develop these two shark species into a commercial product. This project used genetic analysis to understand the patterns of connectivity of populations of these two shark species in NT waters and adjacent regions, including Northern Western Australia and Papua New Guinea.

Background

These two shark species that are captured as bycatch in the NT Demersal Trawl fishery have the potential to be developed into a byproduct to add value to that fishery. A sustainable commercial harvest of these two species could greatly reduce the waste from fisheries, where they are currently abundant and caught in relatively large numbers. We address current knowledge gaps in biological information about populations of R. acutus and C. coatesi to inform the potential development of a byproduct fishery for these two species in the NT.

Aims

Our research aimed to:

·         identify the genetic population structure for R. acutus and C. coatesi in NT waters

·         develop capacity for genetic research and monitoring of shark species in the NT

·         provide baseline information on genetic structure to inform potential genetic monitoring of these species, including initial estimates of effective population size.

Methods

We used single-nucleotide polymorphism genetic analyses to measure genetic structure among R. acutus and C. coatesi samples obtained from commercial trawl fishing in NT waters between May 2018 and November 2019. Our aim was to determine whether the two species each occur as a single population in NT waters or as a set of discrete populations that may warrant separate monitoring and management. We also analysed samples of these species from Western Australia and Papua New Guinea to provide broader context for the degree of genetic differentiation among the samples from different regions in the NT.

Our secondary aim was to provide a baseline for deciding whether genetic estimates of effective population size could be used to monitor trends in abundance of these species, and whether samples from across the NT could be combined for the genetic estimation of effective population size for this purpose.

Results

Genetic data from R. acutus and C. coatesi strongly suggest that each species exists as a single, highly connected population in the NT. Genetic differentiation among the sampling locations for each species was low, and genetic clustering analyses provided strong support for a single population of each species in the region. Sharks of both species captured within a single location (within 50 km of one another) were more genetically related than those further apart; however, this does not constitute evidence for multiple, spatially discrete populations of either species in NT waters. Preliminary applications of effective population size estimators were used, but further work is needed to determine if these can be used to indicate trends in abundance.

Implications for relevant stakeholders

The immediate implications of our research are for fisheries scientists and managers from NT DITT. Our results indicate that these two shark species can be monitored and managed in the NT under the assumption that each species occurs as a single population in this region. Further information relevant to shorter-term movements of individuals may refine management strategies for the two species.

Our research has potential implications for commercial fishers, particularly from the Demersal Trawl Fishery and Australia Bay Seafoods company. Currently, those implications are indirect, as the information from our research will flow through to the industry by contributing to the information required to develop a byproduct fishery for the two species, mitigating bycatch and increasing economic return.

Recommendations

Future research could develop genetic methods, such as effective population size or close-kin mark-recapture, for population monitoring. Comparing the genetic data against other data that indicate individual movement patterns on shorter timescales would help develop a holistic understanding of shark movement and population connectivity to inform sustainable harvest strategies.
Methods
The two datasets presented here include single nucleotide polymorphism (SNP data for the milk shark (Rhizoprionodon acutus) and the Australian blackspot shark (Carcarhinus coatesi) generated by Diversity Arrays Pty Ltd using the DArTSeq method. DArTSeq (Kilian et al 2012) involves an initial step of ‘genome reduction’ to subset a small fraction of the genome of each individual for high-throughput sequencing, followed by bioinformatics analysis to identify DNA sequences containing single nucleotide positions that vary among individuals within and among populations. The DArTSeq protocols for Carcharhinus and Rhizoprionodon are available for future projects via Diversity Arrays. 

Using the DArTSeq protocol, 196 individual R. acutus  and 634 individual C. coatesi sampled were genotyped. The samples came from sharks that were collected in Northern Territory (Australia) waters between May 2018 and November 2019 and from three additional regions including Western Australia (Pilbara and Kimberley regions) and Papua New Guinea.

Sampling locations of individuals and full unfilltered SNP genotypes are included in the dataset.

Kilian, A., Wenzl, P., Huttner, E., Carling, J., Xia, L., Blois, H., Caig, V., Heller-Uszynska, K., Jaccoud, D., & Hopper, C. (2012). Diversity arrays technology: A generic genome profiling technology on open platforms. In Data production and analysis in population genomics (pp. 67–89). Springer.