Back

Revisiting the genetics of Lake Constance Coregonids using lake-wide whole genome sequencing

Jacobs, A.; Roch, S.; Roberts, B.; Capstick, M.; Brinker, A.

2026-01-18 ecology
10.64898/2026.01.18.700192 bioRxiv
Show abstract

Anthropogenic pressures can have detrimental impacts on fish populations, with their effective management and conservation requiring accurate monitoring tools. Yet, this is not straightforward for closely-related, co-existing species that are difficult to distinguish using simple phenotypic or genetic approaches. Coregonids are of cultural and economic importance across Europe but have faced a multitude of pressures over the last century. Yet genomic management tools are lacking. In Lake Constance, a large pre-alpine lake, stocks have drastically collapsed due to a multitude of pressures, leading to a fishery closure. Here, we adopt a cost-effective, whole genome sequencing approach for lake-wide assessment of stock composition, spatial distribution and genetic diversity of highly admixed Lake Constance whitefish (Coregonus spp.). By sequencing 983 adult and larval genomes, we show that nearly 90% of the stock is made up by one of three species, the Gangfisch (C. macrophthalmus), and define the genetic relationship between Upper and Lower Lake Constance whitefish stocks. We also identified strong mixing between Gangfisch and Blaufelchen (C. wartmanni) on traditionally specific-specific spawning grounds, and detected strong admixture in larvae, with potentially drastic impacts on the effectiveness of hatchery supplementation and stocking. Despite the collapse and admixture, species still exhibit low to moderate levels of genetic diversity, maintain ecologically-relevant genetic differences, and seem to show differences in habitat use. Overall, we present a cost-effective, translatable tool for stock-wide sequencing and genetically-informed fisheries management, with our results calling for the re-evaluation of current management practices to avoid the potential genetic mixing between species.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Molecular Ecology Resources
161 papers in training set
Top 0.1%
18.0%
2
Scientific Reports
3102 papers in training set
Top 3%
13.9%
3
Nature Communications
4913 papers in training set
Top 30%
6.2%
4
PLOS ONE
4510 papers in training set
Top 33%
4.7%
5
Canadian Journal of Fisheries and Aquatic Sciences
14 papers in training set
Top 0.1%
3.5%
6
Evolutionary Applications
91 papers in training set
Top 0.3%
3.5%
7
Molecular Ecology
304 papers in training set
Top 2%
2.5%
50% of probability mass above
8
Communications Biology
886 papers in training set
Top 6%
2.0%
9
Frontiers in Marine Science
55 papers in training set
Top 0.5%
2.0%
10
Water Research
74 papers in training set
Top 0.8%
2.0%
11
Communications Earth & Environment
14 papers in training set
Top 0.4%
1.8%
12
Ecology and Evolution
232 papers in training set
Top 2%
1.8%
13
Frontiers in Ecology and Evolution
60 papers in training set
Top 2%
1.6%
14
Environmental DNA
49 papers in training set
Top 0.2%
1.6%
15
iScience
1063 papers in training set
Top 16%
1.6%
16
Metabarcoding and Metagenomics
12 papers in training set
Top 0.1%
1.6%
17
Global Change Biology
69 papers in training set
Top 1%
1.4%
18
Aquatic Conservation: Marine and Freshwater Ecosystems
12 papers in training set
Top 0.2%
1.4%
19
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 35%
1.4%
20
Journal of Fish Biology
14 papers in training set
Top 0.2%
1.4%
21
Science Advances
1098 papers in training set
Top 22%
1.3%
22
Peer Community Journal
254 papers in training set
Top 3%
1.2%
23
Methods in Ecology and Evolution
160 papers in training set
Top 2%
0.9%
24
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 5%
0.9%
25
Science of The Total Environment
179 papers in training set
Top 4%
0.9%
26
Global Ecology and Conservation
25 papers in training set
Top 0.9%
0.9%
27
Limnology and Oceanography: Methods
11 papers in training set
Top 0.3%
0.9%
28
Animals
20 papers in training set
Top 0.7%
0.9%
29
Conservation Letters
11 papers in training set
Top 0.4%
0.9%
30
Ecological Informatics
29 papers in training set
Top 0.7%
0.8%