Aging at Evolutionary Crossroads: Longitudinal Gene Co-expression Network Analyses of Proximal and Ultimate Causes of Aging in Bats

Abstract

How, when, and why do organisms, their tissues, and their cells age remain challenging issues, although researchers have identified multiple mechanistic causes of aging, and three major evolutionary theories have been developed to unravel the ultimate causes of organismal aging. A central hypothesis of these theories is that the strength of natural selection decreases with age. However, empirical evidence on when, why, and how organisms age is phylogenetically limited, especially in natural populations. Here, we developed generic comparisons of gene co-expression networks that quantify and dissect the heterogeneity of gene co-expression in conspecific individuals from different age-classes to provide topological evidence about some mechanical and fundamental causes of organismal aging. We applied this approach to investigate the complexity of some proximal and ultimate causes of aging phenotypes in a natural population of the greater mouse-eared bat Myotis myotis, a remarkably long-lived species given its body size and metabolic rate, with available longitudinal blood transcriptomes. M. myotis gene co-expression networks become increasingly fragmented with age, suggesting an erosion of the strength of natural selection and a general dysregulation of gene co-expression in aging bats. However, selective pressures remain sufficiently strong to allow successive emergence of homogeneous age-specific gene co-expression patterns, for at least 7 years. Thus, older individuals from long-lived species appear to sit at an evolutionary crossroad: as they age, they experience both a decrease in the strength of natural selection and a targeted selection for very specific biological processes, further inviting to refine a central hypothesis in evolutionary aging theories.

Keywords: antagonistic pleiotropy theory; disposable soma theory; evolution of aging; longitudinal transcriptomics; mutation accumulation theory.