7.1 Reviewers report 1
Eugene V. Koonin, NCBI, NLM, NIH, Bethesda, MD 20894, United States
The idea of this paper is as brilliant as it is pretty obvious...in retrospect. A novel solution is offered to the old enigma of the evolution of complex features in proteins that require two or more mutations (emergence of a disulphide bond is a straightforward example). Whitehead et al. propose that selection for such traits could be facilitated by phenotypic mutations (errors of transcription and, especially, translation). Due to phenotypic mutations, rare variants of proteins will emerge that are "pre-adapted" to accommodate the second, beneficial mutation, yielding the complex, adaptive trait, even if transiently. Simply put, for the case of a disulfide bond, one cysteine appears as a result of a phenotypic mutation and the other one due to a genotypic mutation. The result will be that, for a while, the cell will have in its possession the protein molecule with a disulfide bond. Thus, "pre-adaptation" owing to phenotypic mutation would promote fixation of the second mutation which will be beneficial even without the first one – if the selective advantage of the complex trait is high enough (the ultimate situation that helps understanding is that this trait is essential for survival). The actual fixation of the complex trait, then, requires only one (the first) mutation and is thus greatly facilitated. Mathematical modeling described in the paper shows that, if the selective advantage of the complex trait, i.e., the selection coefficient for the second mutation, is high enough, this look-ahead effect becomes realistic under the experimentally determined mistranslation rates. Obviously, the realization of the look-ahead effect will depend on a variety of factors including the overall translation fidelity, the local context of the codon involved, the stability of the protein etc. This allows a number of rather straightforward experimental tests of the model.
From my perspective, this is a genuinely important work that introduces a new and potentially major mechanism of evolution and, in a sense, overturns the old adage of evolution having no foresight. It seems like, even if non-specifically and unwittingly, some foresight might be involved. At a more general conceptual level, this work is important in that it puts together, within a single conceptual framework, the evolutionary effects of genotypic and phenotypic mutations. There is much more to investigate here!
I would like to mention a rather general biological implication. It seems obvious enough that, under conditions of stress (e.g., amino acid starvation, heat shock etc), when translation fidelity drops, the look-ahead effect will be enhanced. Thus, this could be a general and crucial mechanism of adaptation during evolution.
Author response: We would like to thank Eugene Koonin for his enthusiastic and positive review.
7.2 Reviewers report 2
Subhajyoti De, MRC Laboratory of Molecular Biology Hills Road, Cambridge CB2 2QH, United Kingdom
I have read the revised manuscript, and have found that all points raised by the referees were fully addressed. The work is rigorous and very interesting, and I believe, will make a significant contribution in the field. I'll be happy to consider it for publication.
Author response: We would like to thank Subhajyoti De for feedback that improved the original manuscript, and the subsequent positive review.
7.3 Reviewers report 3
David Krakauer, Santa Fe Institute, United States
In this paper the authors demonstrate how phenotypic variation arising through errors in development (e.g. transcription and translation), can, when building on (amplifying) genetic variation, accelerate the fixation rate of neutral alleles. By assuming that neutral alleles are genetically closer to an optimum genotype than a mutation-free wild-type, this can also reduce the time required to reach the optimum. The result is illustrated through stochastic simulation and some limiting-case analytical approximations.
This is an interesting paper that is technically rigorous, and correct in many of the conclusions that it reaches. The paper is now much improved as it now includes specific reference to the almost identical, Baldwin effect. As the authors correctly state, many of papers on the Baldwin effect emphasize learning, but a significant fraction explore the role of random ontogenetic variation on evolutionary dynamics, and a few, explicitly consider the adaptive value of errors in transcription and translation on the exploration of fitness landscapes. It is not yet clear how important the differences are between treating Baldwin effects in terms of individual ontogenetic programs versus population level dynamics. In both cases, the key insight is that random variation is capable of generating a more effective gradient for population dynamics.
I think it worthwhile therefore to give a brief review of this mechanism and a little of its literature.
A Synoptic Outline Of the Baldwin-Morgan-Osborn Effect
1. The essential insight of Baldwin and several other 19th century biologists (listed above) was to understand that phenotypic plasticity can have a direct effect on genetic evolution. In some cases, this can give rise to the appearance of Lamarckian inheritance, as selection on plastic phenotypes derived from a single genotype, can lead to the fixation of polymorphic sequences generating these phenotypes without plasticity.
2. The modern investigation of this effect is associated with the work of Hinton and Nowlan (1987) who showed that ontogenetic variability or plasticity, could lead to effective genetic optimization in neutral fitness landscapes.
3. This has been followed by numerous papers exploring complex landscapes, diverse models of plasticity, including learning, homeostasis, diffusion, and combinatorial sampling. See Turney (1996) for a review with an emphasis on computational approaches.
4. Ancel and Fontana (2000) (building on some more theoretical work by Ancel) demonstrated for RNA secondary structure, the crucial requirement that phenotypic plasticity and genetic polymorphism should exhibit a particular correlational structure for the Baldwin effect to be effective.
5. The most recent, and somewhat exhaustive analysis of the Baldwin effect has been conducted by Borenstein et al (2006) in fluctuating landscapes, exploring both directed and random phenotypic variation.
6. Krakauer and Sasaki (2002) demonstrated a "negative Baldwin effect" whereby developmental errors could amplify mildly deleterious mutations in finite populations, thereby leading to their effective purging.
Certainly the paper by Krakauer and Sasaki does not consider learning explicitly, but something much closer to the so called "look ahead effect" described by Whitehead et al, as it treats the ensemble of variant proteins generated by a single underlying sequence as a result of errors in transcription or translation. In both the Baldwin effect and the "look ahead" effect, genetically identical organisms generate phenotypically diverse populations. I think it an interesting subject for future work to establish the precise nature of any differences manifesting at the level of population dynamics, rather than at the incidental level, of mechanism.
Author response: We appreciate this correction of a large hole in our background literature. We have cited relevant literature about the Baldwin effect, and discussed the main differences between the look-ahead effect and the Baldwin effect. While on the surface the look-ahead effect is very similar to the Baldwin effect, crucially the Baldwin effect is about individual learning, whereas the look-ahead effect is about errors that always produce different proteins from a single gene, at a given rate. Thus, in our model there is little difference between individuals with the same genotype, as no learning is involved, as opposed to the Baldwin effect, where, due to learning, two organisms with identical genotypes can have very different phenotypes. Therefore, we believe that it is important to distinguish clearly between the cases with and without learning, and to use different terminology to emphasize this distinction.
I was somewhat confused by the remark that double mutations are neglected because they are very rare.
Firstly, double mutations should be allowed within the binomial model presented by the authors. Secondly, the statement is empirically false for many haploid genomes. Bonhoeffer and Nowak (1997) showed that in large populations double mutants are likely to exist at fairly high abundance.
Author response: We agree that for RNA-based viral genomes, which often have genomic mutation rates 1000 times greater than DNA-based organisms, double mutations occur frequently. Our model focused on DNA-based organisms, where double mutations are rare. If we wanted to apply our model to RNA viruses, we would have to include double mutations. However, the results from such a modification are obvious: If double mutations are frequent, the organism will happen upon the beneficial double mutation quickly and not require the look-ahead effect at all.
The treatment of deleterious mutations remains a little confusing. Presumably developmental noise can both amplify existing deleterious effects (e.g. cryptic genetic variation, sensu Gibson & Dworkin 2004) and contribute novel pathologies, orthogonal to those of the underlying transcript (e.g. gain of function mutations). This should be made an explicit, distributional property of the model rather than assuming a fixed background cost.
Author response: The explanation of how we treat deleterious mutations was extremely brief in our original draft, and we have expanded and clarified the respective paragraph. We believe that a more explicit, complex treatment of deleterious effects would detract from the main message the model in this work was meant to convey. We have added to the discussion how phenotypic mutations can amplify deleterious genotypic mutations. A more complete treatment of deleterious phenotypic mutations will be a topic of future work.