Inferring the shape of global epistasis

Otwinowski, Jakub; McCandlish, David M.; Plotkin, Joshua B.

doi:10.1101/278630

Cited by 8 publications

(10 citation statements)

References 64 publications

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“…They might result from mechanistic coupling between nucleotide pairs. Alternatively, they could result from nonlinearities in the relationship between PSI and some intermediate non-epistatic phenotype (e.g., U1 snRNP-5’ss binding energy), a phenomenon known as “global epistasis.” More sophisticated quantitative modeling (e.g., along the lines of Otwinowski et al 2018) might help distinguish between these possibilities in the future.…”

Section: Resultsmentioning

confidence: 99%

Quantitative Activity Profile and Context Dependence of All Human 5′ Splice Sites

2018

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Pre-mRNA splicing is an essential step in the expression of most human genes. Mutations at the 5' splice site (5'ss) frequently cause defective splicing and disease due to interference with the initial recognition of the exon-intron boundary by U1 small nuclear ribonucleoprotein (snRNP), a component of the spliceosome. Here, we use a massively parallel splicing assay (MPSA) in human cells to quantify the activity of all 32,768 unique 5'ss sequences (NNN/GYNNNN) in three different gene contexts. Our results reveal that although splicing efficiency is mostly governed by the 5'ss sequence, there are substantial differences in this efficiency across gene contexts. Among other uses, these MPSA measurements facilitate the prediction of 5'ss sequence variants that are likely to cause aberrant splicing. This approach provides a framework to assess potential pathogenic variants in the human genome and streamline the development of splicing-corrective therapies.

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Section: Resultsmentioning

confidence: 99%

Quantitative Activity Profile and Context Dependence of All Human 5′ Splice Sites

2018

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“…2016 ; Steinberg and Ostermeier 2016 ; Wu et al. 2016 ), combined with new methods for using these measurements to parameterize fitness functions ( Sailer and Harms 2017 ; Otwinowski, McCandlish, and Plotkin 2018 ). Perhaps some day such truly realistic models might be useful for phylogenetic inference.…”

Section: Discussionmentioning

confidence: 99%

Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence

Hilton

Bloom

2018

Virus Evolution

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Molecular phylogenetics is often used to estimate the time since the divergence of modern gene sequences. For highly diverged sequences, such phylogenetic techniques sometimes estimate surprisingly recent divergence times. In the case of viruses, independent evidence indicates that the estimates of deep divergence times from molecular phylogenetics are sometimes too recent. This discrepancy is caused in part by inadequate models of purifying selection leading to branch-length underestimation. Here we examine the effect on branch-length estimation of using models that incorporate experimental measurements of purifying selection. We find that models informed by experimentally measured site-specific amino-acid preferences estimate longer deep branches on phylogenies of influenza virus hemagglutinin. This lengthening of branches is due to more realistic stationary states of the models, and is mostly independent of the branch-length extension from modeling site-to-site variation in amino-acid substitution rate. The branch-length extension from experimentally informed site-specific models is similar to that achieved by other approaches that allow the stationary state to vary across sites. However, the improvements from all of these site-specific but time homogeneous and site independent models are limited by the fact that a protein’s amino-acid preferences gradually shift as it evolves. Overall, our work underscores the importance of modeling site-specific amino-acid preferences when estimating deep divergence times—but also shows the inherent limitations of approaches that fail to account for how these preferences shift over time.

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“…However, it would be interesting to allow for stronger artificial selection to significantly impact the standing variation and the structure of the phenotypic covariance within a population over time. Indeed, allowing a population to rapidly collapse as it approaches a desired target is a common strategy in evolutionary optimization algorithms [46]-a strategy that could accelerate the design of new functions with directed molecular evolution.…”

Section: Discussionmentioning

confidence: 99%

Optimal evolutionary control for artificial selection on molecular phenotypes

Nourmohammad

Eksin

2019

Preprint

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Controlling an evolving population is an important task in modern molecular genetics, including in directed evolution to improve the activity of molecules and enzymes, breeding experiments in animals and in plants, and in devising public health strategies to suppress evolving pathogens. An optimal intervention to direct evolution should be designed by considering its impact over an entire stochastic evolutionary trajectory that follows. As a result, a seemingly suboptimal intervention at a given time can be globally optimal as it can open opportunities for desirable actions in the future. Here, we propose a feedback control formalism to devise globally optimal artificial selection protocol to direct the evolution of molecular phenotypes. We show that artificial selection should be designed to counter evolutionary tradeoffs among multi-variate phenotypes to avoid undesirable outcomes in one phenotype by imposing selection on another. Control by artificial selection is challenged by our ability to predict molecular evolution. We develop an information theoretical framework and show that molecular time-scales for evolution under natural selection can inform how to monitor a population to acquire sufficient predictive information for an effective intervention with artificial selection. Our formalism opens a new avenue for devising optimal artificial selection for directed evolution of molecular functions.

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Inferring the shape of global epistasis

Cited by 8 publications

References 64 publications

Quantitative Activity Profile and Context Dependence of All Human 5′ Splice Sites

Quantitative Activity Profile and Context Dependence of All Human 5′ Splice Sites

Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence

Optimal evolutionary control for artificial selection on molecular phenotypes

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