Parameters of proteome evolution from histograms of amino-acid sequence identities of paralogous proteins

Center for Models of Life, Niels Bohr Institute, Blegdamsvej 17, DK-2100 Copenhagen Ø, Denmark.
Biology Direct (Impact Factor: 4.66). 02/2007; 2(1):32. DOI: 10.1186/1745-6150-2-32
Source: PubMed


Background: The evolution of the full repertoire of proteins encoded in a given genome is mostly driven by gene duplications, deletions, and sequence modifications of existing proteins. Indirect information about relative rates and other intrinsic parameters of these three basic processes is contained in the proteome-wide distribution of sequence identities of pairs of paralogous proteins. Results: We introduce a simple mathematical framework based on a stochastic birth-and-death model that allows one to extract some of this information and apply it to the set of all pairs of paralogous proteins in H. pylori, E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens. It was found that the histogram of sequence identities p generated by an all-to-all alignment of all protein sequences encoded in a genome is well fitted with a power-law form ∼ p−γ with the value of the exponent γ around 4 for the majority of organisms used in this study. This implies that the intra-protein variability of substitution rates is best described by the Gamma-distribution with the exponent α ≈ 0.33. Different features of the shape of such histograms allow us to quantify the ratio between the genome-wide average deletion/duplication rates and the amino-acid substitution rate. 1 Conclusions: We separately measure the short-term (“raw”) duplication and deletion rates r ∗ dup, r ∗ del which

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Available from: Sergei S Maslov
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    • "However, inclusion of paralogous sequences can potentially introduce noises in generating protein sequence conservation profiles since, compared with orthologs, protein paralogs are more likely to diverge in sequence and in cellular functions. On average the amino acid sequence identity between paralogous protein pairs is only 30% (Axelsen et al., 2007). "
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    ABSTRACT: The recent advances in genome sequencing have revealed an abundance of non-synonymous polymorphisms among human individuals; subsequently it is of immense interest and importance to predict whether such substitutions are functional neutral or have deleterious effects. The accuracy of such prediction algorithms depends on the quality of the multiple sequence alignment, which is used to infer how an amino acid substitution is tolerated at a given position. Due to the scarcity of orthologous protein sequences in the past, the existing prediction algorithms all include sequences of protein paralogs in the alignment, which can dilute the conservation signal and affect prediction accuracy. However we believe that, with the sequencing of a large number of mammalian genomes, it is now feasible to include only protein orthologs in the alignment and improve the prediction performance. We have developed a novel prediction algorithm, named SNPdryad, which only includes protein orthologs in building a multiple sequence alignment. Among many other innovations, SNPdryad uses different conservation scoring schemes and uses Random Forest as a classifier. We have tested SNPdryad on several datasets. We found that SNPdryad consistently outperformed other methods in several performance metrics, which is attributed to the exclusion of paralogous sequence. We have run SNPdryad on the complete human proteome, generating prediction scores for all the possible amino acid substitutions. The algorithm and the prediction results can be accessed from the website:
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    • "Of the 848 gene products in YPD, we found 581 paralogous pairs using BLASTP with E-value cutoff of 10-10 [14,26]. For the YPD network 132 of these paralogous pairs are at distance l = 2. "
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