Biology subjects

Therkildsen, N. O.

Publications and source records attributed to Therkildsen, N. O..

4 recordsLinked to original sources

bioRxiv2022

Temperature-dependent gene regulatory divergence underlies local adaptation with gene flow in the Atlantic silverside

Gene regulatory divergence is thought to play an important role in adaptation, yet its extent and underlying mechanisms remain largely elusive under scenarios of local adaptation with gene flow. Local adaptation is widespread in marine species despite generally high connectivity and often associated with tightly-linked genomic architectures, such as chromosomal inversions. To investigate gene regulatory evolution under gene flow and the role of discrete genomic regions associated with local adaptation to a steep thermal gradient, we generated RNA-seq data from Atlantic silversides (Menidia menidia) from two locally adapted populations and their F1 hybrids, reared under two different temperatures. We found substantial divergence in gene expression and thermal plasticity, with up to 31% of genes being differentially expressed, and primarily trans-rather than cis-regulatory divergence between populations, despite ongoing gene flow. Substantially reduced thermal plasticity, temperature-dependent gene misexpression and the disruption of co-expression networks in hybrids point toward a role of regulatory incompatibilities in maintaining local adaptation, particularly under colder temperatures, which appear more challenging for this species. Adaptive chromosomal inversions seem to play an important role in gene regulatory divergence through the accumulation of regulatory incompatibilities but are not consistently enriched for divergently regulated genes. Together, these results highlight that gene regulation can diverge substantially among populations connected by strong gene flow in marine environments, partly due to the accumulation of temperature-dependent regulatory incompatibilities within inversions.

evolutionary biology↗

bioRxiv2021

Comparative linkage mapping uncovers massive chromosomal inversions that suppress recombination between locally adapted fish populations

The role of recombination in genome evolution has long been studied in theory, but until recently empirical investigations had been limited to a small number of model species. Here we compare the recombination landscape and genome collinearity between two populations of the Atlantic silverside (Menidia menidia), a small fish distributed across the steep latitudinal climate gradient of the North American Atlantic coast. Using ddRADseq, we constructed separate linkage maps for locally adapted populations from New York and Georgia and their inter-population lab cross. First, we used one of the linkage maps to improve the current silverside genome assembly by anchoring three large unplaced scaffolds to two chromosomes. Second, we estimated sex-specific recombination rates, finding 2.75-fold higher recombination rates in females than males--one of the most extreme examples of heterochiasmy in a fish. While recombination occurs relatively evenly across female chromosomes, it is restricted to only the terminal ends of male chromosomes. Furthermore, comparisons of female linkage maps revealed suppressed recombination along several massive chromosomal inversions spanning nearly 16% of the genome and segregating between locally adapted populations. Finally, we discerned significantly higher recombination rates across chromosomes in the northern population. In addition to providing valuable resources for ongoing evolutionary and comparative genomic studies, our findings represent a striking example of structural variation that impacts recombination between adaptively divergent populations, providing empirical support for theorized genomic mechanisms facilitating adaptation despite gene flow.

evolutionary biology↗

bioRxiv2020

Chromosome-level assembly of the Atlantic silverside genome reveals extreme levels of sequence diversity and structural genetic variation

The levels and distribution of standing genetic variation in a genome can provide a wealth of insights about the adaptive potential, demographic history, and genome structure of a population or species. As structural variants are increasingly associated with traits important for adaptation and speciation, investigating both sequence and structural variation is essential for wholly tapping this potential. Using a combination of shotgun sequencing, 10X Genomics linked reads and proximity-ligation data (Chicago and Hi-C), we produced and annotated a chromosome-level genome assembly for the Atlantic silverside (Menidia menidia) - an established ecological model for studying the phenotypic effects of natural and artificial selection - and examined patterns of genomic variation across two individuals sampled from different populations with divergent local adaptations. Levels of diversity varied substantially across each chromosome, consistently being highly elevated near the ends (presumably near telomeric regions) and dipping to near zero around putative centromeres. Overall, our estimate of the genome-wide average heterozygosity in the Atlantic silverside is the highest reported for a fish, or any vertebrate, to date (1.32-1.76% depending on inference method and sample). Furthermore, we also found extreme levels of structural variation, affecting ~23% of the total genome sequence, including multiple large inversions (> 1 Mb and up to 12.6 Mb) associated with previously identified haploblocks showing strong differentiation between locally adapted populations. These extreme levels of standing genetic variation are likely associated with large effective population sizes and may help explain the remarkable adaptive divergence among populations of the Atlantic silverside.

genomics↗

bioRxiv2019

The Effects of Quantitative Trait Architecture on Detection Power in Artificial Selection Experiments

Evolve and resequence (E&R) experiments, in which artificial selection is imposed on organisms in a controlled environment, are becoming an increasingly accessible tool for studying the genetic basis of adaptation. Previous work has assessed how different experimental design parameters affect the power to detect the quantitative trait loci (QTLs) that underlie adaptive responses in such experiments, but so far there has been little exploration of how this power varies with the genetic architecture of the evolving traits. In this study, we use forward simulation to build a realistic model of an E&R experiment in which a quantitative polygenic trait experiences a short, but strong, episode of truncation selection. We study the expected power for QTL detection in such an experiment and how this power is influenced by different aspects of trait architecture, including the number of QTLs affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of the above parameters can affect allele frequency dynamics at the QTLs and linked loci in complex and often unintuitive ways, and thus influence our power to detect them. One consequence of this is that existing detection methods based on models of independent selective sweeps at individual QTLs often have lower detection power than a simple measurement of allele frequency differences before and after selection. Our findings highlight the importance of taking trait architecture into account in designing studies of molecular adaptation with temporal data. We provide a customizable modeling framework that will enable researchers to easily simulate E&R experiments with different trait architectures and parameters tuned to their specific study system, allowing for assessment of expected detection power and optimization of experimental design.

evolutionary biology↗