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Gene regulatory divergence is thought to play an important role in adaptation, yet its extent and underlying mechanisms remain largely elusive for local adaptation with gene flow. Local adaptation is widespread in marine species despite generally high connectivity and is often associated with tightly linked genomic architectures, such as chromosomal inversions. To investigate gene regulatory evolution under gene flow and the role of inversions 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 temperatures. We found substantial divergence in gene expression and thermal plasticity between populations, with up to 31% of genes being differentially expressed. Reduced thermal plasticity, temperature-dependent gene misexpression, and the disruption of coexpression networks in hybrids point toward a role of regulatory incompatibilities in local adaptation, particularly under colder temperatures. Chromosomal inversions show an accumulation of regulatory incompatibilities but are not consistently enriched for differentially expressed genes. Together, these results suggest that gene regulation can diverge substantially among populations despite gene flow, partly due to the accumulation of temperature-dependent regulatory incompatibilities within inversions. [ABSTRACT FROM AUTHOR]

Northern sand lance (Ammodytes dubius) are essential forage fish in most offshore, temperate-to-polar waters on the Northwest Atlantic shelf (NWA), but their population structure and genetic separation from the American sand lance (A. americanus) remain unresolved. We assembled a reference genome for A. dubius (first in the Ammodytidae) and then used low-coverage whole genome sequencing on 262 specimens collected across the species distribution (Mid-Atlantic Bight to Greenland) to quantify genetic differentiation between geographic regions based on single nucleotide polymorphisms. We found strong separation between A. dubius from locations north and south of the Scotian Shelf, largely due to massive genetic differentiation spanning most of chromosomes 21 and 24. Genetic distance increased with geographic distance in the smaller southern cluster but not in the larger northern cluster, where genetic homogeneity appeared across large geographic distances (>103 km). The two genetic clusters coincide with a clear break in winter sea surface temperature, suggesting that differential offspring survival, rather than limited transport, causes a break in realized connectivity. Nuclear and mitochondrial DNA both clearly delineated A. dubius from A. americanus , thereby confirming a species boundary through spatial niche partitioning into inshore (A. americanus) and offshore (A. dubius) sand lance species on the NWA. [ABSTRACT FROM AUTHOR]

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 (QTL) 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 more 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 QTL affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of these parameters can affect allele frequency dynamics at the QTL 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 QTL 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 when designing and interpreting 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. [ABSTRACT FROM AUTHOR]