Recent and Long-Term Selection Across Synonymous Sites in Drosophila ananassae

Choi, Jae Young; Aquadro, Charles F.

doi:10.1007/s00239-016-9753-9

Cited by 12 publications

(12 citation statements)

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“…The impact of synonymous mutations at the genome-wide level was also found in patterns of codon usage bias (syno-nymous codons are used at different frequencies) across genomes. Evidence from studies within and between species support the role of direct selection on synonymous sites in various genes (Choi and Aquadro 2016;DuMont et al 2004;Hershberg and Petrov 2009;Ran and Higgs 2010;Shah and Gilchrist 2011;Singh et al 2007;Sun et al 2016). A first piece of evidence for synonymous effects in the studied region of Hsp90 came from Bank et al (2014) who reported that one of the 15 mutations synonymous to the parental sequence had a significantly deleterious effect in 4 out of 6 environments ( Fig.…”

Section: Resultsmentioning

confidence: 95%

“…Firstly, mutations in an amino acid based fitness landscape are, by definition, non-synonymous. This neglects the accumulating evidence from both comparative and experimental studies that synonymous mutations (i.e., mutations that change the codon but not the encoded amino acid) can display non-negligible fitness effects (Agashe et al 2013;Bailey et al 2014;Bali and Bebok 2015;Choi and Aquadro 2016;Drummond and Wilke 2008;Firnberg et al 2014;Hunt et al 2014;Knöppel et al 2016;Kudla et al 2009;Lind et al 2010;Plotkin and Kudla 2011;Presnyak et al 2015;Sauna and Kimchi-Sarfaty 2011;Singh et al 2007;Zhou et al 2009). For example, recent studies have shown that synonymous mutations can affect the speed and accuracy of translation (Bali and Bebok 2015;Drummond and Wilke 2008;Plotkin and Kudla 2011;Saunders and Deane 2010) mRNA structure (O'Brien et al 2014;Presnyak et al 2015;Shabalina et al 2013) expression in response to environmental changes (Shabalina et al 2013) and that they are associated with several organismal malfunctions (Hunt et al 2014;Parmley and Hurst 2007).…”

Section: Introductionmentioning

confidence: 99%

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The fitness landscape of the codon space across environments

et al. 2018

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Fitness landscapes map the relationship between genotypes and fitness. However, most fitness landscape studies ignore the genetic architecture imposed by the codon table and thereby neglect the potential role of synonymous mutations. To quantify the fitness effects of synonymous mutations and their potential impact on adaptation on a fitness landscape, we use a new software based on Bayesian Monte Carlo Markov Chain methods and re-estimate selection coefficients of all possible codon mutations across 9 amino acid positions in Saccharomyces cerevisiae Hsp90 across 6 environments. We quantify the distribution of fitness effects of synonymous mutations and show that it is dominated by many mutations of small or no effect and few mutations of larger effect. We then compare the shape of the codon fitness landscape across amino acid positions and environments, and quantify how the consideration of synonymous fitness effects changes the evolutionary dynamics on these fitness landscapes. Together these results highlight a possible role of synonymous mutations in adaptation and indicate the potential mis-inference when they are neglected in fitness landscape studies.

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Section: Resultsmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

The fitness landscape of the codon space across environments

et al. 2018

View full text Add to dashboard Cite

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“…The impact of synonymous mutations at the genome-wide level was also found in patterns of codon usage bias (synonymous codons are used at different frequencies) across genomes. Evidence from studies within and between species support the role of direct selection on synonymous sites in various genes (DuMont et al, 2004;Singh et al, 2007;Hershberg and Petrov, 2009;Ran and Higgs, 2010;Shah and Gilchrist, 2011;Choi and Aquadro, 2016;Sun et al, 2016). A first piece of evidence for synonymous effects in the studied region of Hsp90 came from Bank et al (2014), who reported that one of the 15 mutations synonymous to the parental sequence had a significantly deleterious effect in 4 out of 6 environments ( Fig.…”

Section: Effect Of Synonymous Mutations On the Topography And The Dynmentioning

confidence: 94%

“…This neglects the accumulating evidence from both comparative and experimental studies that synonymous mutations (i.e., mutations that change the codon but not the encoded amino-acid) can display non-negligible fitness effects (Singh et al, 2007;Drummond and Wilke, 2008;Kudla et al, 2009;Zhou et al, 2009;Lind et al, 2010;Plotkin and Kudla, 2011;Sauna and Kimchi-Sarfaty, 2011;Agashe et al, 2013;Bailey et al, 2014;Firnberg et al, 2014;Hunt et al, 2014;Bali and Bebok, 2015;Presnyak et al, 2015;Agashe et al, 2016;Choi and Aquadro, 2016;Knöppel et al, 2016). For example, recent studies have shown that synonymous mutations can affect the speed and accuracy of translation (Drummond and Wilke, 2008;Saunders and Deane, 2010;Plotkin and Kudla, 2011;Bali and Bebok, 2015), mRNA structure (Shabalina et al, 2013;O'Brien et al, 2014;Presnyak et al, 2015), expression in response to environmental changes (Shabalina et al, 2013), and that they are associated with several organismal malfunctions (Parmley and Hurst, 2007;Hunt et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

The fitness landscape of the codon space across environments

Fragata

Matuszweski

Schmitz

et al. 2018

Preprint

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“…Chamary and Hurst 2005;Lynch 2007;Zeng and Charlesworth 2010a;Lawrie et al 2013;Choi and Aquadro 2016;Jackson et al 2017), and 2) the DFE is not assumed to follow a specific parameterized distribution, such as the widely-used gamma distribution.Our results demonstrate that it is possible to jointly infer the deleterious DFE and past demographic changes using an ABC framework, by including various summary statistics capturing aspects of the SFS, linkage disequilibrium and divergence, compared between coding and flanking non-coding sequences. Ancestral population sizes and the frequency of the most deleterious classes of the DFE are estimated with relatively low accuracy, whereas the current population sizes and the neutral mutation class are estimated with high accuracy.…”

mentioning

confidence: 99%

Towards an evolutionarily appropriate null model: jointly inferring demography and purifying selection

Johri

Charlesworth

Jensen

2019

Preprint

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The question of the relative evolutionary roles of adaptive and non-adaptive processes has been a central debate in population genetics for nearly a century. While advances have been made in the theoretical development of the underlying models, and statistical methods for estimating their parameters from large-scale genomic data, a framework for an appropriate null model remains elusive. A model incorporating evolutionary processes known to be in constant operationgenetic drift (as modulated by the demographic history of the population) and purifying selection -is lacking. Without such a null model, the role of adaptive processes in shaping within-and between-population variation may not be accurately assessed. Here, we investigate how population size changes and the strength of purifying selection affect patterns of variation at neutral sites near functional genomic components. We propose a novel statistical framework for jointly inferring the contribution of the relevant selective and demographic parameters. By means of extensive performance analyses, we quantify the utility of the approach, identify the most important statistics for parameter estimation, and compare the results with existing methods. Finally, we re-analyze genome-wide population-level data from a Zambian population of Drosophila melanogaster, and find that it has experienced a much slower rate of population growth than was inferred when the effects of purifying selection were neglected. Our approach represents an appropriate null model, against which the effects of positive selection can be assessed. and Aquadro 2016; Jackson et al. 2017), and which can result in serious mis-inference (Matsumoto et al. 2016). In applying this approach to genome-wide data from a Zambian population of Drosophila melanogaster, our results show that this population has experienced a very mild 1.2-fold growth in size, considerably less than previous estimates which did not correct for the BGS-induced skew of the SFS (e.g., Ragsdale and Gutenkunst 2017; Kapopoulou et al. 2018). In addition, we estimate that ~25% of all mutations in exons are effectively neutral in this population, and find little evidence for wide-spread selection on synonymous sites. METHODS Simulations:The discrete generation simulation package SLiM 3.1 (Haller and Messer 2019) was used to simulate a functional element of length L, which is flanked by neutral non-functional regions. The functional region experiencing purifying selection is described by a DFE that is modeled as a discrete distribution with four bins (Figure 1a) representing effectively neutral (g < 1), weakly deleterious (1 £ g < 10), moderately deleterious (10 £ g < 100), and strongly deleterious (100 £ g < 10000) classes of mutations, where g = 2Nes. Semi-dominance is assumed, so that the fitness of mutant heterozygotes is exactly intermediate between the values for the two homozygotes (a dominance coefficient, h, of 0.5). Fitness effects are assumed to follow a uniform distribution within each of the four bins. In order to inf...

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Recent and Long-Term Selection Across Synonymous Sites in Drosophila ananassae

Cited by 12 publications

References 88 publications

The fitness landscape of the codon space across environments

The fitness landscape of the codon space across environments

The fitness landscape of the codon space across environments

Towards an evolutionarily appropriate null model: jointly inferring demography and purifying selection

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