Genome-Wide Population Structure of Lake Whitefish (Coregonus clupeaformis) in a Subarctic Great Lake

IF 3.2 2区 生物学 Q1 EVOLUTIONARY BIOLOGY
Philippe Hénault, Raphaël Bouchard, David A. Boguski, Brendan K. Malley, Eric Normandeau, Charles Babin, Xavier Dallaire, Louis Bernatchez, Xinhua Zhu, Jean-Sébastien Moore
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Abstract

Advances in genomics have facilitated the delineation of fisheries management units, which can be challenging in systems such as large lakes, in which high gene flow tends to limit genetic structure. In Great Slave Lake, Lake Whitefish populations have supported an important commercial fishery since the mid-1940s. The genetic structure of Lake Whitefish, however, has never been assessed, preventing the implementation of population-specific monitoring. Using low-coverage whole-genome resequencing of 305 samples from 10 sampling locations, we identified eight genetically differentiated populations of Lake Whitefish in Great Slave Lake and its main tributary, the Slave River. In the lake, we observed elevated levels of genetic differentiation among putative spawning locations in environmentally heterogeneous sections of the Main Basin despite small geographic distances among sites. In contrast, we observed weak genetic structure between populations in the comparatively homogeneous East Arm despite large geographic distances. Our observations suggest that mechanisms such as spawning site fidelity, adfluvial migratory behaviour, or local adaptation might shape population structure in this system. Using genome-wide scans, we found multiple genomic regions of elevated differentiation, with some displaying patterns coherent with chromosomal inversions. These results highlight the potential role of chromosomal rearrangements in maintaining local adaptation in the face of gene flow in environmentally heterogeneous lakes. Overall, our study provides novel insights into the genetic structure of fish populations in vast, recently deglaciated lakes. Furthermore, our results highlight the power of genomic data for population delineation in systems with high gene flow. Lastly, our precise assessment of genetic structure will provide a baseline for the genetic monitoring of culturally and socio-economically important Lake Whitefish commercial fisheries in this subarctic Great Lake.

Abstract Image

亚北极五大湖湖泊白鱼的全基因组种群结构
基因组学的进步促进了渔业管理单位的划定,这在大型湖泊等系统中可能具有挑战性,在这些系统中,高基因流动往往会限制遗传结构。在大奴湖,自20世纪40年代中期以来,湖白鱼种群一直支持着一项重要的商业渔业。然而,湖泊白鱼的遗传结构从未被评估过,这阻碍了特定种群监测的实施。利用来自10个采样点的305个样本的低覆盖全基因组重测序,我们在大奴湖及其主要支流奴河中鉴定了8个遗传分化的湖白鱼种群。在湖泊中,我们观察到在主要盆地环境异质部分的假定产卵地点之间的遗传分化水平升高,尽管地点之间的地理距离较小。相比之下,尽管地理距离较远,但在相对均匀的东臂,我们观察到群体之间的遗传结构较弱。我们的观察表明,产卵地点保真度、河流迁徙行为或当地适应等机制可能会影响该系统中的种群结构。使用全基因组扫描,我们发现多个基因组区域分化升高,其中一些显示模式与染色体倒位一致。这些结果强调了染色体重排在面对环境异质湖泊基因流时维持局部适应的潜在作用。总的来说,我们的研究为最近冰川消融的巨大湖泊中鱼类种群的遗传结构提供了新的见解。此外,我们的研究结果强调了基因组数据在高基因流系统中种群描述的力量。最后,我们对遗传结构的精确评估将为这个亚北极大湖具有重要文化和社会经济意义的湖白鱼商业渔业的遗传监测提供基线。
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来源期刊
Evolutionary Applications
Evolutionary Applications 生物-进化生物学
CiteScore
8.50
自引率
7.30%
发文量
175
审稿时长
6 months
期刊介绍: Evolutionary Applications is a fully peer reviewed open access journal. It publishes papers that utilize concepts from evolutionary biology to address biological questions of health, social and economic relevance. Papers are expected to employ evolutionary concepts or methods to make contributions to areas such as (but not limited to): medicine, agriculture, forestry, exploitation and management (fisheries and wildlife), aquaculture, conservation biology, environmental sciences (including climate change and invasion biology), microbiology, and toxicology. All taxonomic groups are covered from microbes, fungi, plants and animals. In order to better serve the community, we also now strongly encourage submissions of papers making use of modern molecular and genetic methods (population and functional genomics, transcriptomics, proteomics, epigenetics, quantitative genetics, association and linkage mapping) to address important questions in any of these disciplines and in an applied evolutionary framework. Theoretical, empirical, synthesis or perspective papers are welcome.
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