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Updated: Jul 29, 2025

Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat
Published on: September 20, 2016
Evolution of Metabolome and Transcriptome Supports a Hierarchical Organization of Adaptive Traits
Wei-Yun Lai1,2, Kathrin A Otte1,3, Christian Schlötterer1
1Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.
Abstract:
Most organismal phenotypes have a polygenic basis, which enables adaptive phenotypic responses on ecological time scales. While adaptive phenotypic changes are highly parallel in replicate populations, this does not apply to the contributing loci. In particular for small populations, the same phenotypic shift can be fueled by different sets of alleles at alternative loci (genetic redundancy). Although this phenomenon is empirically well supported, the molecular basis of the genetic redundancy is not yet understood. To fill this gap, we compared the heterogeneity of the evolutionary transcriptomic and metabolomic response in ten Drosophila simulans populations which evolved parallel high-level phenotypic changes in a novel temperature environment but used different allelic combinations of alternative loci. We showed that the metabolome evolved more parallel than the transcriptome, confirming a hierarchical organization of molecular phenotypes. Different sets of genes responded in each evolved population but led to the enrichment of similar biological functions and a consistent metabolic profile. Since even the metabolomic response was still highly heterogeneous across evolved populations, we propose that selection may operate on pathways/networks.
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Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
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