Biology subjects

Brachmann, M. K.

Publications and source records attributed to Brachmann, M. K..

3 recordsLinked to original sources

bioRxiv2025

Parallel adaptation to geothermally-warmed habitats due to common structural variation and functional developmental pathways

Climate change is causing rapid increases in temperature which drives genomic changes tied to adaptation. However, predicting the outcomes of climate change presents challenges as the anticipated conditions have yet to be experienced by natural populations. Modelling and lab experiments suggest that natural populations will experience shifts in life history, physiology, phenology, and ecology, but the underlying genomic mechanisms involved are unknown. However, some contemporary natural populations experience habitat warming through geothermal activity and can provide valuable insights into evolutionary responses. Geothermally warmed habitats should impose strong selection on ectotherms compared to ambient habitats as they increase metabolic demands, alter developmental processes, and offer novel ecological conditions. We leveraged Icelandic threespine sticklebacks (Gasterosteus aculeatus) from populations that have adaptively diverged along a geothermal/ambient habitat axis. We obtained 173,485 single nucleotide polymorphisms (SNPs) across four independent instances of population divergence using whole genome sequencing. While the majority of genomic differentiation between geothermal/ambient ecotypes was non-parallel, the MAPK signalling pathway appeared across all ecotype pairs. We also identified a putative inversion located on chromosome XXI which appears to drive parallel genomic differentiation between geothermal and ambient ecotypes. Candidate genes within the putative inversion correspond to metabolic adaptations, including regulation of appetite and fat content. Appetite level showed strong heritable divergence between ecotypes, while the rate of weight loss during starvation and fat levels differed between ecotypes. Overall, both polygenic adaptation and parallel structural variation appeared to be key genomic mechanisms for adaptation to geothermally warmed environments. While allelic divergence was largely unique across populations, it resulted in similar functional phenotypic outcomes. Thus, structural and allelic variation both operate to facilitate adaptation to warming environments. Therefore, while management from a genomic perspective will play a role in mitigating the effects of climate change, this study suggests that consideration of functional molecular pathways will be key to conservation but with precise changes being difficult to predict due to the highly polygenic nature of thermal adaptation.

evolutionary biology↗

bioRxiv2022

Whole genome sequencing reveals fine-scale climate associated adaptive divergence near the range limits of a temperate reef fish.

Adaptation to ocean climate is increasingly recognized as an important driver of diversity in marine species despite the lack of physical barriers to dispersal and the presence of pelagic stages in many taxa. A robust understanding of the genomic and ecological processes involved in structuring populations is lacking for most marine species, often hindering management and conservation action. Cunner (Tautogolabrus adspersus), is a temperate reef fish that displays both pelagic early life history stages and strong site-associated homing as adults; the species is also presently of interest for use as a cleaner fish in salmonid aquaculture in Atlantic Canada. Here we produce a chromosome-level genome assembly for cunner and characterize spatial population structure throughout Atlantic Canada using whole genome resequencing. The genome assembly spanned 0.72 Gbp and resolved 24 chromosomes; whole genome resequencing of 803 individuals from 20 locations spanning from Newfoundland to New Jersey identified approximately 11 million genetic variants. Principal component analysis revealed four distinct regional groups in Atlantic Canada, including three near the range edge in Newfoundland. Pairwise FST and selection scans revealed consistent signals of differentiation and selection at discrete genomic regions including adjacent peaks on chromosome 10 recurring across multiple pairwise comparisons (i.e., FST 0.5-0.75). Redundancy analysis suggested significant association of environmental variables related to benthic temperature and oxygen range with genomic structure, again highlighting the previously identified region on chromosome 10. Our results suggest that climate associated adaptation in this temperate reef fish drives regional diversity despite high early life history dispersal potential.

genomics↗

bioRxiv2022

Genomic and machine learning-based screening of aquaculture associated introgression into at-risk wild North American Atlantic salmon (Salmo salar) populations.

The negative genetic impacts of gene flow from domestic to wild populations can be dependent on the degree of domestication and exacerbated by the magnitude of pre-existing genetic differences between wild populations and the domestication source. Recent evidence of European ancestry within North American aquaculture Atlantic salmon (Salmo salar) has elevated the potential impact of escaped farmed salmon on often at-risk wild North American salmon populations. Here we compare the ability of single nucleotide polymorphism (SNP) and microsatellite (SSR) marker panels of different sizes (7-SSR, 100-SSR, and 220K-SNP) to detect introgression of European genetic information into North American wild and aquaculture populations. Linear regression comparing admixture predictions for a set of individuals common to the three data sets showed that the 100-SSR panel and 7-SSR panels replicated the full 220K-SNP-based admixture estimates with low accuracy (r2 of 0.64 and 0.49 respectively). Additional tests explored the effects of individual sample size and marker number, which revealed that ~300 randomly selected SNPs could replicate the 220K-SNP admixture predictions with greater than 95% fidelity. We designed a custom SNP panel (301-SNP) for European admixture detection in future monitoring work and then developed and tested a Python package, SalmonEuAdmix (https://github.com/CNuge/SalmonEuAdmix), that uses a deep neural network to make de novo estimates of individuals European admixture proportion without the need to conduct complete admixture analysis utilizing baseline samples. The results demonstrate the mobilization of targeted SNP panels and machine learning in support of at-risk species conservation and management.

genomics↗