Variability among individuals is generated at the gene expression level

• Main Authors: Peck, Lloyd S., Thorne, Michael A. S., Hoffman, Joseph I., Morley, Simon A., Clark, Melody S.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Figshare 2016
• Subjects: Environmental Science; Ecology; FOS Biological sciences; Antarctic; Nacella; Antarc*
• Online Access: https://dx.doi.org/10.6084/m9.figshare.c.3307842; https://figshare.com/collections/Variability_among_individuals_is_generated_at_the_gene_expression_level/3307842

Selection acts on individuals, specifically on their differences. To understand adaptation and responses to change therefore requires knowledge of how variation is generated and distributed across traits. Variation occurs on different biological scales, from genetic through physiological to morphological, yet it is unclear which of these carries the most variability. For example, if individual variation is mainly generated by differences in gene expression, variability should decrease progressively from coding genes to morphological traits, whereas if post-translational and epigenetic effects increase variation, the opposite should occur. To test these predictions, we compared levels of variation among individuals in various measures of gene expression, physiology (including activity), and morphology in two abundant and geographically widespread Antarctic molluscs, the clam Laternula elliptica and the limpet Nacella concinna . Direct comparisons among traits as diverse as heat shock protein QPCR assays, whole transcription profiles, respiration rates, burying rate, shell length, and ash-free dry mass were made possible through the novel application of an established metric, the Wentworth Scale. In principle, this approach could be extended to analyses of populations, communities, or even entire ecosystems. We found consistently greater variation in gene expression than morphology, with physiological measures falling in between. This suggests that variability is generated at the gene expression level. These findings have important implications for refining current biological models and predictions of how biodiversity may respond to climate change.