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The genetic population structure of Lake Tanganyika's Lates species flock, an endemic radiation of pelagic top predators

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Zenodo2021-12-20 更新2026-05-25 收录
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Data associated with the manuscript "The genetic population structure of Lake Tanganyika’s Lates species flock, an endemic radiation of pelagic top predators," where we investigate the genetic population structure of the four endemic <em>Lates </em>species in Lake Tanganyika. <strong>Abstract</strong>: Life history traits are important in shaping gene flow within species and can thus determine whether a species exhibits genetic homogeneity or population structure across its range. Understanding genetic connectivity plays a crucial role in species conservation decisions, and genetic connectivity is an important component of modern fisheries management in fishes exploited for human consumption. In this study, we investigated the population genetics of four endemic <em>Lates</em> species of Lake Tanganyika (<em>Lates stappersii</em>, <em>L. microlepis</em>, <em>L. mariae</em> and <em>L. angustifrons</em>), using reduced-representation genomic sequencing methods. We find the four species to be strongly differentiated from one another, with no evidence for contemporary admixture. We also find evidence for high levels of genetic structure within <em>L. mariae</em>, with the majority of individuals from the most southern sampling site forming a genetic group distinct from the individuals at other sampling sites<em>.</em> We find evidence for much weaker structure within the other three species, <em>L. stappersii,</em> <em>L. microlepis</em>, and <em>L. angustifrons</em>, although small and unbalanced sample sizes and imprecise geographic sampling locations may hinder our ability to detect weak population structure. We call for further research into the origins of the genetic differentiation that we observe in these four species, particularly that of <em>L. mariae</em>, which may be important for the conservation and management of this species. Code associated with the analysis of these data can be found on GitHub at https://github.com/jessicarick/lates-popgen.

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2021-12-20
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