Biology subjects

Drown, M.

Publications and source records attributed to Drown, M..

4 recordsLinked to original sources

bioRxiv2025

Epigenetic plasticity is a driver of heritable pollution tolerance in Atlantic killifish

Heritable epigenetic adaptation to environmental stressors is a compelling but highly contested possibility. Previously, we showed evidence of a generationally heritable epigenetic memory at the cytochrome P450 1a (cyp1a) gene in wild Atlantic killifish (Fundulus heteroclitus) with acquired tolerance to polycyclic aromatic hydrocarbons (PAHs). This memory leads to blunted induction of cyp1a by PAHs; this blunted response protects against PAH-induced cancer. Here, using Oxford Nanopore long-read sequencing in PAH-tolerant and -sensitive F. heteroclitus embryos, we show that PAH-tolerant embryos displayed reduced plasticity in DNA methylation response to PAH, as compared to PAH-sensitive embryos, that was not due to mutational loss of CpG sites. Notably, we observed population differences in DNA methylation of genes in pathways linked to the PAH tolerance phenotype, including aryl hydrocarbon receptor (ahr) and voltage-gated potassium channel signaling, as well as developmental processes and energy metabolism. Specifically, we observed PAH-induced loss of cyp1a gene body methylation in PAH-sensitive but not-tolerant embryos. We observed similar patterns at cyp1b1, cyp1c1, and the aryl hydrocarbon receptor repressor, ahrr, which show similarly blunted expression in response to PAH challenge. The reduced loss in genic methylation in tolerant embryos was correlated with greater induction of natural anti-sense RNA transcripts in cis (cis-NATs), which may regulate transcription of these genes. Our data support the existence of stable epigenetic responses to chronic environmental stressors in a natural experimental setting, with broad implications for natural or directed adaptation strategies for other populations.

genomics↗

bioRxiv2023

Trans-Acting Genotypes Drive mRNA Expression Affecting Metabolic And Thermal Tolerance Traits

AO_SCPLOWBSTRACTC_SCPLOWEvolutionary processes driving physiological trait variation depend on the underlying genomic mechanisms. Evolution of these mechanisms depends on whether traits are genetically complex (involving many genes) and how gene expression that impact the traits is converted to phenotype. Yet, genomic mechanisms that impact physiological traits are diverse and context dependent (e.g., vary by environment or among tissues), making them difficult to discern. Here we examine the relationships between genotype, mRNA expression, and physiological traits to discern the genetic complexity and whether the gene expression effecting the physiological traits is primarily cis or trans-acting. We use low-coverage whole genome sequencing and tissue specific mRNA expression among individuals to identify polymorphisms directly associated with physiological traits and expressed quantitative trait loci (eQTL) driving variation in six temperature specific physiological traits (standard metabolic rate, thermal tolerance, and four substrate specific cardiac metabolic rates). Not surprisingly, there were few, only five, SNPs directly associated with physiological traits. Yet, by focusing on a select set of mRNAs belonging to co-expression modules that explain up to 82% of temperature specific (12{degrees}C or 28{degrees}C) metabolism and thermal tolerance, we identified hundreds of significant eQTL for mRNA whose expression affects physiological traits. Surprisingly, most eQTL (97.4% for heart and 96.7% for brain) of eQTL were trans-acting. This could be due to higher effect size or greater importance of trans versus cis acting eQTLs for mRNAs that are central to co-expression modules. That is, we may have enhanced the identification of trans-acting factors by looking for SNPs associated with mRNAs in co-expression modules that are known to be correlated with the expression of 10s or 100s of other genes, and thus have identified eQTLs with widespread effects on broad gene expression patterns. Overall, these data indicate that the genomic mechanism driving physiological variation across environments is driven by trans-acting tissue specific mRNA expression. AO_SCPLOWUTHORC_SCPLOW SO_SCPLOWUMMARYC_SCPLOWIn the salt marsh killifish Fundulus heteroclitus there is amazingly large variation in physiological traits assumed to be under stabilizing selection, which should reduce their variation. To discern the heritability of this physiological variation we took an innovative approach to define the DNA variation that drives mRNA expression linked to physiological variation. This indirect approach revealed many DNA sequence variants associated with physiological variation via their effect on mRNA expression. Surprisingly, these changes were not in the mRNAs themselves, but in unlinked distant genes which regulate mRNA expression. That is, the vast majority (>95%) were trans-acting. This is surprising because trans-acting effects are found less often than DNA variants within or close to mRNA expression genes. Our results are likely related to the select subset of mRNAs across environments that are linked to physiological variation.

genetics↗

bioRxiv2022

mRNA expression explains metabolic and thermal physiology

Quantifying mRNA expression, which is heritable and physiologically inducible, reveals biologically important networks and pathways underlying complex traits. Here, we quantify mRNA expression in Fundulus heteroclitus, a small teleost fish, among three populations acclimated to 12{degrees}C and 28{degrees}C and relate it to variation in six, complex, physiological traits (whole animal metabolism (WAM), critical thermal maximum (CTmax), and four substrate specific cardiac metabolic rates (CaM)). Although 366 heart mRNAs and 528 brain mRNAs had significant differential expression between the two acclimation temperatures, none of the mRNA acclimation responses were shared across all three populations in any tissue. Yet, within an acclimation temperature across all three populations, weighted gene co-expression network analyses show that mRNA expression patterns explained WAM, CTmax, and CaM trait variation. These analyses revealed 9 significant heart MEs (first principal component of module expression) and 4 significant brain MEs. Heart MEs explained variation in WAM, CTmax, and two of the four substrate specific cardiac metabolic rates at 12{degrees}C, and CTmax at 28C. In contrast, brain MEs explained CTmax and WAM at 28{degrees}C but not at 12{degrees}C. Combining MEs as multiple correlations, 82% of variation in WAM at 12{degrees}C was explained by four heart MEs, 80% of variation in fatty-acid CaM at 12{degrees}C was explained by three heart MEs, and 72% of variation in CTmax at 28{degrees}C was explained by three brain MEs. These MEs were enriched for Kyoto Encyclopedia of Genes and Genomes (KEGG) terms related to specific metabolic pathways, suggesting that they represent biologically relevant pathways. Together these data suggest that mRNA co-expression explains complex traits; moreover, physiological traits are more reliant on heart expression at 12{degrees}C and brain expression at 28{degrees}C. Author SummaryDespite an abundance of genomic data, the molecular and genetic underpinnings of complex traits remain poorly understood. To better understand the molecular basis of complex traits, we used heart and brain mRNA expression to explain complex traits- physiological responses to temperature- in individuals collected from three saltmarsh fish (Fundulus heteroclitus) populations acclimated to 12{degrees}C and 28{degrees}C. We found that while physiological traits did not differ among populations, the mRNAs important for acclimation responses were >88% unique to a single population and differed between heart and brain tissues. We also found tissue specific co-expressed mRNAs that explain up to 82% of complex traits including whole animal metabolism, upper thermal tolerance, and substrate specific cardiac metabolism measured at 12{degrees}C or 28{degrees}C acclimation conditions. Notably, sets of co-expressed mRNAs related to these traits are enriched for molecular pathways affecting metabolism, giving insight into the molecular underpinnings of these traits.

genetics↗

bioRxiv2020

An Innovative Setup for High-Throughput Respirometry of Small Aquatic Animals

AO_SCPLOWBSTRACTC_SCPLOWMetabolic rate is often measured as a phenotype in evolutionary genetics studies because it impacts organismal fitness, is repeatable and heritable, and is responsive to numerous environmental variables. Despite a wide body of literature about metabolic rates, key questions remain unanswered: 1) why do individuals from the same population exhibit up to three fold differences in metabolic rate, 2) how does metabolic rate change during an individuals lifetime, and 3) what metabolic rate is advantageous in a specific environment? Current low throughput approaches to measure metabolic rate make it difficult to answer these and other relevant ecological and evolutionary questions that require a much larger sample size. Here we describe a scalable high-throughput intermittent flow respirometer (HIFR) design and use it to measure the metabolic rates of 20 aquatic animals simultaneously while reducing equipment costs and time by more than 50%.

physiology↗