Abstract

As a pacesetter for physiological processes, variation in metabolic rate can determine the shape of energetic trade-offs and thereby drive variation in life-history traits. In turn, such variation in metabolic performance and life-histories can have profound consequences for lifespan and lifetime fitness. Thus, the extent to which metabolic rate variation is due to phenotypic plasticity or fixed genetic differences among individuals or populations is likely to be shaped by natural selection. Here, we first present a generalized framework describing the central role of mitochondria in processes linking environmental, genomic, physiological, and aging variation. We then present a test of these relationships in an exemplary system: populations of garter snakes (Thamnophis elegans) exhibiting contrasting life-history strategies - fast-growing, early-reproducing, and fast-aging (FA) versus slow-growing, late-reproducing, and slow-aging (SA). Previous work has characterized divergences in mitochondrial function, reactive oxygen species processing, and whole-organism metabolic rate between these contrasting life-history ecotypes. Here, we report new data on cellular respiration and mitochondrial genomics and synthesize these results with previous work. We test hypotheses about the causes and implications of mitochondrial genome variation within this generalized framework. First, we demonstrate that snakes of the FA ecotype increase cellular metabolic rate across their lifespan, while the opposite pattern holds for SA snakes, implying that reduced energetic throughput is associated with a longer life. Second, we show that variants in mitochondrial genomes are segregating across the landscape in a manner suggesting selection on the physiological consequences of this variation in habitats varying in temperature, food availability, and rates of predation. Third, we demonstrate functional variation in whole-organism metabolic rate related to these mitochondrial genome sequence variants. With this synthesis of numerous datasets, we are able to further characterize how variation across levels of biological organization interact within this generalized framework and how this has resulted in the emergence of distinct life-history ecotypes that vary in their rates of aging and lifespan.

Full Text
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