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Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme

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TLDR
A detailed analysis of the evolving RNA populations in genotype space shows that cryptic variation allows a population to explore new genotypes that become adaptive only in a new environment, highlighting the positive role that robustness and epistasis can have in adaptive evolution.
Abstract
Cryptic variation is caused by the robustness of phenotypes to mutations Cryptic variation has no effect on phenotypes in a given genetic or environmental background, but it can have effects after mutations or environmental change Because evolutionary adaptation by natural selection requires phenotypic variation, phenotypically revealed cryptic genetic variation may facilitate evolutionary adaptation This is possible if the cryptic variation happens to be pre-adapted, or "exapted", to a new environment, and is thus advantageous once revealed However, this facilitating role for cryptic variation has not been proven, partly because most pertinent work focuses on complex phenotypes of whole organisms whose genetic basis is incompletely understood Here we show that populations of RNA enzymes with accumulated cryptic variation adapt more rapidly to a new substrate than a population without cryptic variation A detailed analysis of our evolving RNA populations in genotype space shows that cryptic variation allows a population to explore new genotypes that become adaptive only in a new environment Our observations show that cryptic variation contains new genotypes pre-adapted to a changed environment Our results highlight the positive role that robustness and epistasis can have in adaptive evolution

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Citations
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Structure and function of long noncoding RNAs in epigenetic regulation

TL;DR: This work focuses on the well-characterized ability for lncRNAs to function as epigenetic modulators, and suggests that lnc RNAs may be part of a broad epigenetic regulatory network.
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Cryptic genetic variation: evolution's hidden substrate

TL;DR: The empirical support for widespread CGV in natural populations is reviewed, including its potential role in emerging human diseases and the growing evidence of its contribution to evolution are reviewed.
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The role of mutational robustness in RNA virus evolution.

TL;DR: This Review discusses the strategies used by RNA viruses to deal with the increased mutational load and considers how this mutational robustness might influence viral evolution and pathogenesis.
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Evolutionary biochemistry: revealing the historical and physical causes of protein properties

TL;DR: This work articulate the paradigm of evolutionary biochemistry, which aims to dissect the physical mechanisms and evolutionary processes by which biological molecules diversified and to reveal how their physical architecture facilitates and constrains their evolution.
References
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Journal ArticleDOI

Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Journal ArticleDOI

A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

TL;DR: This work has used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches.
Journal ArticleDOI

A general method applicable to the search for similarities in the amino acid sequence of two proteins

TL;DR: A computer adaptable method for finding similarities in the amino acid sequences of two proteins has been developed and it is possible to determine whether significant homology exists between the proteins to trace their possible evolutionary development.
Journal ArticleDOI

Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences

TL;DR: Cd-hit-2d compares two protein datasets and reports similar matches between them; cd- Hit-est clusters a DNA/RNA sequence database and cd- hit-est-2D compares two nucleotide datasets.
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