Abstract
Much work has been done on the evolutionary divergence of duplicated genes in protein coding regions. However, this remains a partial view, and little is known how duplicated genes diverge in non-coding regions, which can play an important role in the evolutionary preservation of duplicated genes. Here we compared the evolutionary rates of different parts of of duplicated genes in the human and mouse genomes, including 5’-UTRs, coding regions, 3’-UTRs, and 500 bps upstream and downstram of the untranslated regions. Results show that compared to orthologous genes, the ratios of the genetic distance of noncoding regions such as UTRs and upstream and downstream regions vs. synonymous substitutions tend to be smaller in paralogous genes, suggesting that synonymous substitutions benefit more greatly from relaxed selective constraints than noncoding regions. Moreover, we also examined the most frequent types of rate comparison among different genic regions in both orthologs and paralogs and found that the ranks of the most frequent types of rate comparison differ little between human paralogs and mouse paralogs, but differ greatly from those in orthologs, suggesting that duplication enables changes of evolutionary dynamics along different parts of genes. We also classified duplicated genes into three categories based on their chromosomal locations, tandem duplicates, intra-chromosomal duplicates, and inter-chromosomal duplicates. Results show that in both the human and mouse, selective constraint (measured by K a /K s ) on intra-chromosomal duplicates tends to be much lower than that on tandem duplicates, which in turn is significantly lower than that on inter-chromosomal duplicates. This shows that genomic location is an important factor in determining the evolutionary divergence of duplicated genes.
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References
Ohno, S.: Evolution by gene duplication. Springer, New York (1970)
Conant, G.C., Wagner, A.: Asymmetric sequence divergence of duplicate genes. Genome. Res. 13(9), 2052–2058 (2003)
Cusack, B.P., Wolfe, K.H.: Not born equal: increased rate asymmetry in relocated and retrotransposed rodent gene duplicates. Mol. Biol. Evol. 24(3), 679–686 (2007)
Makalowski, W., Boguski, M.S.: Evolutionary parameters of the transcribed mammalian genome: An analysis of 2,820 orthologous rodent and human sequences. Proc. Natl. Acad. Sci. USA 95(16), 9407–9412 (1998)
Huang, X., Chao, K.M.: A generalized global alignment algorithm. Bioinformatics 19(2), 228–233 (2003)
Kimura, M.: A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16(2), 111–120 (1980)
Yang, Z.: PAML: A program package for phylogenetic analysis by maximum likelihood. Comput. Appl. Biosci. 13(5), 555–556 (1997)
Guo, Y., Jamison, D.C.: The distribution of SNPs in human gene regulatory regions. BMC Genomics 6, 140 (2005)
Hirsh, A.E., Fraser, H.B., Wall, D.P.: Adjusting for selection on synonymous sites in estimates of evolutionary distance. Mol. Biol. Evol. 22(1), 174–177 (2005)
Shoja, V., Zhang, L.: A roadmap of tandemly arrayed genes in the genomes of human, mouse, and rat. Mol. Biol. Evol. 23(11), 2134–2141 (2006)
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© 2008 Springer-Verlag Berlin Heidelberg
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Pan, D., Zhang, L. (2008). A Holistic View of Evolutionary Rates in Paralogous and Orthologous Genes. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_116
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DOI: https://doi.org/10.1007/978-3-540-85984-0_116
Publisher Name: Springer, Berlin, Heidelberg
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