Indications of strong adaptive population genetic structure in albacore tuna (Thunnus alalunga) in the southwest and central Pacific Ocean

Abstract

Albacore tuna (Thunnus alalunga) has a distinctly complex life history in which juveniles and adults separate geographically but at times inhabit the same spaces sequentially. The species also migrates long distances and presumably experiences varied regimes of physical stress over a lifetime. There are, therefore, many opportunities for population structure to arise based on stochastic differences or environmental factors that promote local adaptation. However, with the extent of mobility consistently demonstrated by tagged individuals, there is also a strong argument for panmixia within an ocean basin. It is important to confirm such assumptions from a population genetics standpoint for this species in particular because albacore is one of the principal market tuna species that sustains massive global fisheries and yet is also a slow‐growing temperate tuna. Consequently, we used 1,837 neutral SNP loci and 89 loci under potential selection to analyze population genetic structure among five sample groups collected from the western and central South Pacific. We found no evidence to challenge panmixia at neutral loci, but strong indications of structuring at adaptive loci. One population sample, from French Polynesia in 2004, was particularly differentiated. Unfortunately, the current study cannot infer whether the divergence is geographic or temporal, or possibly caused by sample distribution. We encourage future studies to include potentially adaptive loci and to continue fine‐scale observations within an ocean basin, and not to assume genome‐wide panmixia.

Adaptive markers distinguish North and South Pacific Albacore amid low population differentiation

“…To further assess the identity of the putatively adaptive loci, we also compared our genetic results with a previous RADseq study of Albacore (Anderson et al, 2019). We trimmed adapter sequences from their loci sequences and mapped them to the Pacific Bluefin genome contigs using the same BWA‐MEM method.…”

“…Genetic variation was analyzed using double‐digest restriction site‐associated DNA sequencing (ddRADseq; Peterson et al, 2012), and we tested for presumably neutral and putatively adaptive differences among potential populations. Like many studies of HMMS (e.g., Bernard et al, 2016; Brendtro et al, 2008; Grewe et al, 2015; Mamoozadeh et al, 2020), and most genetic studies of albacore (e.g., Albaina et al, 2013; Anderson et al, 2019), we were not able to link samples to separate spawning areas. Given this situation, we explicitly acknowledged that our sample areas do not necessarily represent separate populations, and we iteratively analyzed the ddRADseq data to avoid any a priori biases.…”

Population Structure, Genetic Connectivity, and Signatures of Local Adaptation of the Giant Black Tiger Shrimp (Penaeus monodon) throughout the Indo-Pacific Region

“…All shrimp samples were sequenced and genotyped using DArTseq TM technology, as previously described ( Kilian et al 2012 ; Anderson et al 2019 ; Vu et al 2020 ). Briefly, DArTSeq TM technology relies on a complexity reduction method in order to obtain genome sequences using next-generation sequencing technology.…”

“…For example, analysis of neutral genetic loci has been utilized for population structure determination ( Batista et al 2016 ; Segovia et al 2017 ; Woodings et al 2018 ), whereas outlier detection methods permit the separation of putatively adaptive (i.e., outlier) and neutral loci into two discrete datasets. Recent studies have demonstrated that outlier loci provide unique and useful insights into the genetic structure and management units of aquatic species that neutral loci often do not show ( Gagnaire et al 2015 ; Woodings et al 2018 ; Anderson et al 2019 ; Nowland et al 2019 ).…”

Rangewide Population Structure of the Clearnose Skate

“…Although the reported F ST values using the full data set were low, there was a statistically significant level of differentiation in pairwise comparisons between the SCGAFL samples and those from six other and more northern states, a pattern that was also seen using the outlier data set. Similarly low yet significant pairwise F ST values have been reported in other fish population studies, including Nassau Grouper Epinephelus striatus (F ST = 0.0023, P = 0.0039 and F ST = 0.002, P = 0.0140; Jackson et al 2014), Leopard Sharks Triakis semifasciata (F ST = 0.003, P = 0.026; Barker et al 2015), and South Pacific Albacore Thunnus alalunga using both neutral loci (F ST = 0.0027-0.0031, P < 0.0004) and outlier loci (F ST = 0.0157-0.0203, P < 0.0012) (Anderson et al 2019). We feel confident that the number of loci used in this study was sufficient to overcome the high signal-to-noise ratio often seen in marine organism F ST estimates but acknowledge that sample size and distribution may bias estimates (Waples 1998;Willing et al 2012).…”