Abstract

Genetic datasets of tens of markers have been superseded through next-generation sequencing technology with genome-wide datasets of thousands of markers. Genomic datasets improve our power to detect low population structure and identify adaptive divergence. The increased population-level knowledge can inform the conservation management of endangered species, such as the blue whale (Balaenoptera musculus). In Australia, there are two known feeding aggregations of the pygmy blue whale (B. m. brevicauda) which have shown no evidence of genetic structure based on a small dataset of 10 microsatellites and mtDNA. Here, we develop and implement a high-resolution dataset of 8294 genome-wide filtered single nucleotide polymorphisms, the first of its kind for blue whales. We use these data to assess whether the Australian feeding aggregations constitute one population and to test for the first time whether there is adaptive divergence between the feeding aggregations. We found no evidence of neutral population structure and negligible evidence of adaptive divergence. We propose that individuals likely travel widely between feeding areas and to breeding areas, which would require them to be adapted to a wide range of environmental conditions. This has important implications for their conservation as this blue whale population is likely vulnerable to a range of anthropogenic threats both off Australia and elsewhere.

Highlights

  • Next-generation sequencing has brought about an orders-of-magnitude increase in the number of DNA markers feasible for studies of non-model organisms

  • We can assess with confidence whether putative populations that have shown no population structure based on traditional ‘previous-generation sequencing’ genetic datasets might have low, but biologically relevant, population structure

  • A series of analyses found no evidence of neutral structure, strongly suggesting that whales from these aggregations are a single genetic population

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Summary

Introduction

Next-generation sequencing has brought about an orders-of-magnitude increase in the number of DNA markers feasible for studies of non-model organisms. Genome-wide datasets boost the power of traditional analyses that use small numbers of neutral loci to evaluate population structure, and allow the investigation of the small proportion of loci in the genome that exhibit ecologically relevant adaptation [1,2,3]. We can assess with confidence whether putative populations that have shown no population structure based on traditional ‘previous-generation sequencing’ genetic datasets might have low, but biologically relevant, population structure. Genotyping-by-sequencing datasets have been used recently to resolve such low population structure [4,5,6]. These datasets may be used to detect adaptive divergence even when there is negligible neutral differentiation [7,8]. Such adaptive divergence should be taken into account when making management decisions, such as when delineating units for conservation [9]

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