Literature DB >> 31934856

Rank orders and signed interactions in evolutionary biology.

Kristina Crona1.   

Abstract

Rank orders have been studied in evolutionary biology for almost a hundred years. Constraints on the order in which mutations accumulate are known from cancer drug treatment, and order constraints for species invasions are important in ecology. However, current theory on rank orders in biology is somewhat fragmented. Here, we show how our previous work on inferring genetic interactions from comparative fitness data (Crona et al., 2017) is related to an influential approach to rank orders based on sign epistasis. Our approach depends on order perturbations that indicate interactions. We apply our results to malaria parasites and find that order perturbations beyond sign epistasis are prevalent in the antimalarial drug-resistance landscape. This finding agrees with the observation that reversed evolution back to the ancestral type is difficult. Another application concerns the adaptation of bacteria to a methanol environment.
© 2020, Crona.

Entities:  

Keywords:  epistasis; evolutionary biology; evolutionary predictability; malaria; rank orders; sign epistasis

Mesh:

Substances:

Year:  2020        PMID: 31934856      PMCID: PMC7000213          DOI: 10.7554/eLife.51004

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


  13 in total

1.  Diminishing returns epistasis among beneficial mutations decelerates adaptation.

Authors:  Hsin-Hung Chou; Hsuan-Chao Chiu; Nigel F Delaney; Daniel Segrè; Christopher J Marx
Journal:  Science       Date:  2011-06-03       Impact factor: 47.728

2.  Reciprocal sign epistasis is a necessary condition for multi-peaked fitness landscapes.

Authors:  Frank J Poelwijk; Sorin Tănase-Nicola; Daniel J Kiviet; Sander J Tans
Journal:  J Theor Biol       Date:  2010-12-16       Impact factor: 2.691

Review 3.  Perspective: Sign epistasis and genetic constraint on evolutionary trajectories.

Authors:  Daniel M Weinreich; Richard A Watson; Lin Chao
Journal:  Evolution       Date:  2005-06       Impact factor: 3.694

4.  Computational Complexity as an Ultimate Constraint on Evolution.

Authors:  Artem Kaznatcheev
Journal:  Genetics       Date:  2019-03-04       Impact factor: 4.562

5.  MOLECULAR EVOLUTION OVER THE MUTATIONAL LANDSCAPE.

Authors:  John H Gillespie
Journal:  Evolution       Date:  1984-09       Impact factor: 3.694

Review 6.  Empirical fitness landscapes and the predictability of evolution.

Authors:  J Arjan G M de Visser; Joachim Krug
Journal:  Nat Rev Genet       Date:  2014-06-10       Impact factor: 53.242

7.  The peaks and geometry of fitness landscapes.

Authors:  Kristina Crona; Devin Greene; Miriam Barlow
Journal:  J Theor Biol       Date:  2012-10-02       Impact factor: 2.691

8.  Estimating the predictability of cancer evolution.

Authors:  Sayed-Rzgar Hosseini; Ramon Diaz-Uriarte; Florian Markowetz; Niko Beerenwinkel
Journal:  Bioinformatics       Date:  2019-07-15       Impact factor: 6.937

9.  A pivot mutation impedes reverse evolution across an adaptive landscape for drug resistance in Plasmodium vivax.

Authors:  C Brandon Ogbunugafor; Daniel Hartl
Journal:  Malar J       Date:  2016-01-25       Impact factor: 2.979

10.  Inferring genetic interactions from comparative fitness data.

Authors:  Kristina Crona; Alex Gavryushkin; Devin Greene; Niko Beerenwinkel
Journal:  Elife       Date:  2017-12-20       Impact factor: 8.140

View more
  2 in total

1.  Relation Between the Number of Peaks and the Number of Reciprocal Sign Epistatic Interactions.

Authors:  Raimundo Saona; Fyodor A Kondrashov; Ksenia A Khudiakova
Journal:  Bull Math Biol       Date:  2022-06-17       Impact factor: 3.871

2.  Predictable properties of fitness landscapes induced by adaptational tradeoffs.

Authors:  Suman G Das; Susana Ol Direito; Bartlomiej Waclaw; Rosalind J Allen; Joachim Krug
Journal:  Elife       Date:  2020-05-19       Impact factor: 8.140

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.