View Program - 2022 Population, Evolutionary, and Quantitative Genetics Conference

Biotic and abiotic factors determine organismal survival and success in their habitat. Temperature is one of the most important abiotic factors defining metabolism and species range. It is nearly universally true that ectotherms from warmer environments have evolved lower metabolic rates than those from colder environments. This broad phylogenetic convergence and common physiological and biochemical mechanisms underlying temperature adaptation suggest strong selection that should reduce interindividual variation. Yet, there are few studies characterizing variation in physiological traits, or defining the nucleotide variation driving it. To investigate variation in temperature response, six traits were measured in 250 Fundulus heteroclitus individuals collected across a non-clinal thermal mosaic of habitats, with up to an 8°C difference. Traits included whole-animal metabolic rate (MO₂) and Critical Thermal Maximum (CTmax) measured in the same individuals at both 12°C and 28°C, and 4 substrate-specific cardiac metabolic rates measured at either 12°C or 28°C. Here we focus on the thermal sensitivity (defined as the Q₁₀; change in trait value for every 10°C increase in temperature) of MO₂ and CTmax. Among and within populations we observed high phenotypic variation in these traits. Variation in thermal sensitivity ranged from a Q₁₀~1 (same trait value at 12°C and 28°C) to a Q₁₀>3 (~6-fold difference between temperatures). Much of this variation is within a population, yet up to 10% is associated with habitat temperature. To further understand the genomic basis of variation in these traits, we developed a sequencing technique, Extended Exome Capture sequencing (EXECseq) that targets regions of the genome likely under selection. EXECseq uses expressed RNA probes to capture large genic fragments, including exons and cis-regulatory regions. RNA probes were generated using numerous tissues exposed to heat and oxygen stress to produce a large pool of expressed genes. This method was used to sequence all individuals at 10X coverage across over 10,000 genes at a lower cost than whole-genome sequencing, and greater genome coverage than other reduced representation methods, and >80% of reads fell within genic regions. Using a multivariate analysis of this genomic data and phenotypic data, we can understand how individuals within and among these populations respond to temperature and provide insights into the genetic basis of the high variation in thermal sensitivity.

The Genomics of Highly Variable Physiological Response to Temperature