AI Article Synopsis

  • Many regulatory networks exhibit partially redundant enhancers, which have typically been thought to stem from sequence duplication, but some may arise through independent evolution.
  • Research indicates that 31% of redundant enhancer pairs in humans and 17% in mice evolved independently via different transposons, challenging the idea that redundancy is counterproductive to natural selection.
  • Redundant enhancers likely enhance gene expression and tissue specificity, suggesting that despite their redundancy, they play a beneficial role in the robustness and adaptability of mammalian regulatory networks.

Article Abstract

Many regulatory networks appear to involve partially redundant enhancers. Traditionally, such enhancers have been hypothesized to originate mainly by sequence duplication. An alternative model postulates that they arise independently, through convergent evolution. This mechanism appears to be counterintuitive to natural selection: Redundant sequences are expected to either diverge and acquire new functions or accumulate mutations and become nonfunctional. Nevertheless, we show that at least 31% of the redundant enhancer pairs in the human genome (and 17% in the mouse genome) indeed originated in this manner. Specifically, for virtually all transposon-derived redundant enhancer pairs, both enhancer partners have evolved independently, from the exaptation of two different transposons. In addition to conferring robustness to the system, redundant enhancers could provide an evolutionary advantage by fine-tuning gene expression. Consistent with this hypothesis, we observed that the target genes of redundant enhancers exhibit higher expression levels and tissue specificity as compared with other genes. Finally, we found that although enhancer redundancy appears to be an intrinsic property of certain mammalian regulatory networks, the corresponding enhancers are largely species-specific. In other words, the redundancy in these networks is most likely a result of convergent evolution.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093719PMC
http://dx.doi.org/10.1093/gbe/evaa004DOI Listing

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