Inferring Genetic Interactions from Comparative Fitness Data

Overview

Journal Elife

Specialty Biology

Date 2017 Dec 21

PMID 29260711

Citations 14

Authors

Kristina Crona

Alex Gavryushkin

Devin Greene

Niko Beerenwinkel

Affiliations

Soon will be listed here.

Abstract

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite , the fungus , and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

Citing Articles

Resolving discrepancies between chimeric and multiplicative measures of higher-order epistasis.

Chitra U, Arnold B, Raphael B Nat Commun. 2025; 16(1):1711.

PMID: 39962081 PMC: 11833126. DOI: 10.1038/s41467-025-56986-5.

Synthetic lethality and the minimal genome size problem.

Rahiminejad S, De Sanctis B, Pevzner P, Mushegian A mSphere. 2024; 9(7):e0013924.

PMID: 38904396 PMC: 11288024. DOI: 10.1128/msphere.00139-24.

Master regulators of biological systems in higher dimensions.

Eble H, Joswig M, Lamberti L, Ludington W Proc Natl Acad Sci U S A. 2023; 120(51):e2300634120.

PMID: 38096409 PMC: 10743376. DOI: 10.1073/pnas.2300634120.

A fast lasso-based method for inferring higher-order interactions.

Elmes K, Heywood A, Huang Z, Gavryushkin A PLoS Comput Biol. 2022; 18(12):e1010730.

PMID: 36580499 PMC: 9833600. DOI: 10.1371/journal.pcbi.1010730.

Exploring the expanse between theoretical questions and experimental approaches in the modern study of evolvability.

Draghi J, Ogbunugafor C J Exp Zool B Mol Dev Evol. 2022; 340(1):8-17.

PMID: 35451559 PMC: 10083935. DOI: 10.1002/jez.b.23134.

References

Sanjuan R, Moya A, Elena S . The distribution of fitness effects caused by single-nucleotide substitutions in an RNA virus. Proc Natl Acad Sci U S A. 2004; 101(22):8396-401. PMC: 420405. DOI: 10.1073/pnas.0400146101. View

Bonhoeffer S, Chappey C, Parkin N, Whitcomb J, Petropoulos C . Evidence for positive epistasis in HIV-1. Science. 2004; 306(5701):1547-50. DOI: 10.1126/science.1101786. View

Sanjuan R, Cuevas J, Moya A, Elena S . Epistasis and the adaptability of an RNA virus. Genetics. 2005; 170(3):1001-8. PMC: 1451175. DOI: 10.1534/genetics.105.040741. View

Weinreich D, Watson R, Chao L . Perspective: Sign epistasis and genetic constraint on evolutionary trajectories. Evolution. 2005; 59(6):1165-74. View

Moore J, Gilbert J, Tsai C, Chiang F, Holden T, Barney N . A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. J Theor Biol. 2006; 241(2):252-61. DOI: 10.1016/j.jtbi.2005.11.036. View

Weinreich D, Delaney N, DePristo M, Hartl D . Darwinian evolution can follow only very few mutational paths to fitter proteins. Science. 2006; 312(5770):111-4. DOI: 10.1126/science.1123539. View

Segal M, Barbour J, Grant R . Relating HIV-1 sequence variation to replication capacity via trees and forests. Stat Appl Genet Mol Biol. 2006; 3:Article2. DOI: 10.2202/1544-6115.1031. View

Bershtein S, Segal M, Bekerman R, Tokuriki N, Tawfik D . Robustness-epistasis link shapes the fitness landscape of a randomly drifting protein. Nature. 2006; 444(7121):929-32. DOI: 10.1038/nature05385. View

Poon A, Chao L . Functional origins of fitness effect-sizes of compensatory mutations in the DNA bacteriophage phiX174. Evolution. 2006; 60(10):2032-43. View

10.

Poelwijk F, Kiviet D, Weinreich D, Tans S . Empirical fitness landscapes reveal accessible evolutionary paths. Nature. 2007; 445(7126):383-6. DOI: 10.1038/nature05451. View

11.

Huggins P, Pachter L, Sturmfels B . Toward the human genotope. Bull Math Biol. 2007; 69(8):2723-35. DOI: 10.1007/s11538-007-9244-7. View

12.

Hallgrimsdottir I, Yuster D . A complete classification of epistatic two-locus models. BMC Genet. 2008; 9:17. PMC: 2289835. DOI: 10.1186/1471-2156-9-17. View

13.

Orr H . Fitness and its role in evolutionary genetics. Nat Rev Genet. 2009; 10(8):531-9. PMC: 2753274. DOI: 10.1038/nrg2603. View

14.

Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear E, Sevier C . The genetic landscape of a cell. Science. 2010; 327(5964):425-31. PMC: 5600254. DOI: 10.1126/science.1180823. View

15.

da Silva J, Coetzer M, Nedellec R, Pastore C, Mosier D . Fitness epistasis and constraints on adaptation in a human immunodeficiency virus type 1 protein region. Genetics. 2010; 185(1):293-303. PMC: 2870964. DOI: 10.1534/genetics.109.112458. View

16.

Sanjuan R . Mutational fitness effects in RNA and single-stranded DNA viruses: common patterns revealed by site-directed mutagenesis studies. Philos Trans R Soc Lond B Biol Sci. 2010; 365(1548):1975-82. PMC: 2880115. DOI: 10.1098/rstb.2010.0063. View

17.

Poelwijk F, Tanase-Nicola S, Kiviet D, Tans S . Reciprocal sign epistasis is a necessary condition for multi-peaked fitness landscapes. J Theor Biol. 2010; 272(1):141-4. DOI: 10.1016/j.jtbi.2010.12.015. View

18.

Wylie C, Shakhnovich E . A biophysical protein folding model accounts for most mutational fitness effects in viruses. Proc Natl Acad Sci U S A. 2011; 108(24):9916-21. PMC: 3116435. DOI: 10.1073/pnas.1017572108. View

19.

Khan A, Dinh D, Schneider D, Lenski R, Cooper T . Negative epistasis between beneficial mutations in an evolving bacterial population. Science. 2011; 332(6034):1193-6. DOI: 10.1126/science.1203801. View

20.

Franke J, Klozer A, de Visser J, Krug J . Evolutionary accessibility of mutational pathways. PLoS Comput Biol. 2011; 7(8):e1002134. PMC: 3158036. DOI: 10.1371/journal.pcbi.1002134. View