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Sahar Parto

Publications and source records attributed to Sahar Parto.

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Molecular adaptation in Rubisco: discriminating between convergent evolution and positive selection using mechanistic and classical codon models

Rubisco (Ribulose-1, 5-biphosphate carboxylase/oxygenase) is the most important enzyme on earth, catalyzing the first step of CO2 fixation in photosynthesis. Its molecular adaptation to C4 photosynthetic pathway has attracted a lot of attention. C4 plants, which comprise less than 5% of land plants, have evolved more efficient photosynthesis compared to C3 plants. Interestingly, a large number of independent transitions from C3 to C4 phenotype have occurred. Each time, the Rubisco enzyme has been subject to similar changes in selective pressure, thus providing an excellent model for convergent evolution at the molecular level. Molecular adaptation is often identified with positive selection and is typically characterized by an elevated ratio of non-synonymous over synonymous substitution rates (dN/dS). However, convergent adaptation is expected to leave a different molecular signature, taking the form of repeated transitions toward identical or similar amino acids.\n\nHere, we use a previously introduced codon-based differential selection model to detect and quantify consistent patterns of convergent adaptation in Rubisco in Amaranthaceae. We further contrast the results thus obtained with those obtained under classical codon models based on the estimation of dN/dS. We find that the two classes of models tend to select distinct, although overlapping, sets of positions. This discrepancy in the results illustrates the conceptual difference between these models, while emphasizing the need to better discriminate between qualitatively different selective regimes, by using a broader class of codon models than those currently considered in molecular evolutionary studies.

Evolutionary Biology

Detecting consistent patterns of directional adaptation using differential selection codon models

BackgroundPhylogenetic codon models are often used to characterize the selective regimes acting on protein coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by explicitly modelling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions.\n\nResultsHere, we developed a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles.\n\nConclusionour differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

Bioinformatics