Molecular evolution of genes in avian genomes

Nam K, Mugal C, Nabholz B, Schielzeth H, Wolf JBW, Backström N, Künstner A, Balakrishnan CN, Heger A, Ponting CP, Clayton DF, et al. (2010)
Genome Biology 11(6): R68.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Nam, Kiwoong; Mugal, Carina; Nabholz, Benoit; Schielzeth, HolgerUniBi ; Wolf, Jochen BW; Backström, Niclas; Künstner, Axel; Balakrishnan, Christopher N; Heger, Andreas; Ponting, Chris P; Clayton, David F; Ellegren, Hans
Abstract / Bemerkung
Background: Obtaining a draft genome sequence of the zebra finch (Taeniopygia guttata), the second bird genome to be sequenced, provides the necessary resource for whole-genome comparative analysis of gene sequence evolution in a non-mammalian vertebrate lineage. To analyze basic molecular evolutionary processes during avian evolution, and to contrast these with the situation in mammals, we aligned the protein-coding sequences of 8,384 1:1 orthologs of chicken, zebra finch, a lizard and three mammalian species. Results: We found clear differences in the substitution rate at fourfold degenerate sites, being lowest in the ancestral bird lineage, intermediate in the chicken lineage and highest in the zebra finch lineage, possibly reflecting differences in generation time. We identified positively selected and/or rapidly evolving genes in avian lineages and found an overrepresentation of several functional classes, including anion transporter activity, calcium ion binding, cell adhesion and microtubule cytoskeleton. Conclusions: Focusing specifically on genes of neurological interest and genes differentially expressed in the unique vocal control nuclei of the songbird brain, we find a number of positively selected genes, including synaptic receptors. We found no evidence that selection for beneficial alleles is more efficient in regions of high recombination; in fact, there was a weak yet significant negative correlation between ω and recombination rate, which is in the direction predicted by the Hill-Robertson effect if slightly deleterious mutations contribute to protein evolution. These findings set the stage for studies of functional genetics of avian genes.
Erscheinungsjahr
2010
Zeitschriftentitel
Genome Biology
Band
11
Ausgabe
6
Art.-Nr.
R68
ISSN
1465-6906
Page URI
https://pub.uni-bielefeld.de/record/2496087

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Nam K, Mugal C, Nabholz B, et al. Molecular evolution of genes in avian genomes. Genome Biology. 2010;11(6): R68.
Nam, K., Mugal, C., Nabholz, B., Schielzeth, H., Wolf, J. B. W., Backström, N., Künstner, A., et al. (2010). Molecular evolution of genes in avian genomes. Genome Biology, 11(6), R68. doi:10.1186/gb-2010-11-6-r68
Nam, Kiwoong, Mugal, Carina, Nabholz, Benoit, Schielzeth, Holger, Wolf, Jochen BW, Backström, Niclas, Künstner, Axel, et al. 2010. “Molecular evolution of genes in avian genomes”. Genome Biology 11 (6): R68.
Nam, K., Mugal, C., Nabholz, B., Schielzeth, H., Wolf, J. B. W., Backström, N., Künstner, A., Balakrishnan, C. N., Heger, A., Ponting, C. P., et al. (2010). Molecular evolution of genes in avian genomes. Genome Biology 11:R68.
Nam, K., et al., 2010. Molecular evolution of genes in avian genomes. Genome Biology, 11(6): R68.
K. Nam, et al., “Molecular evolution of genes in avian genomes”, Genome Biology, vol. 11, 2010, : R68.
Nam, K., Mugal, C., Nabholz, B., Schielzeth, H., Wolf, J.B.W., Backström, N., Künstner, A., Balakrishnan, C.N., Heger, A., Ponting, C.P., Clayton, D.F., Ellegren, H.: Molecular evolution of genes in avian genomes. Genome Biology. 11, : R68 (2010).
Nam, Kiwoong, Mugal, Carina, Nabholz, Benoit, Schielzeth, Holger, Wolf, Jochen BW, Backström, Niclas, Künstner, Axel, Balakrishnan, Christopher N, Heger, Andreas, Ponting, Chris P, Clayton, David F, and Ellegren, Hans. “Molecular evolution of genes in avian genomes”. Genome Biology 11.6 (2010): R68.

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Brain architecture and social complexity in modern and ancient birds.
Burish MJ, Kueh HY, Wang SS., Brain Behav. Evol. 63(2), 2003
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The ongoing adaptive evolution of ASPM and Microcephalin is not explained by increased intelligence.
Mekel-Bobrov N, Posthuma D, Gilbert SL, Lind P, Gosso MF, Luciano M, Harris SE, Bates TC, Polderman TJ, Whalley LJ, Fox H, Starr JM, Evans PD, Montgomery GW, Fernandes C, Heutink P, Martin NG, Boomsma DI, Deary IJ, Wright MJ, de Geus EJ, Lahn BT., Hum. Mol. Genet. 16(6), 2007
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NMDA receptor trafficking in synaptic plasticity and neuropsychiatric disorders.
Lau CG, Zukin RS., Nat. Rev. Neurosci. 8(6), 2007
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Hippocampal specialization of food-storing birds.
Krebs JR, Sherry DF, Healy SD, Perry VH, Vaccarino AL., Proc. Natl. Acad. Sci. U.S.A. 86(4), 1989
PMID: 2919184

AUTHOR UNKNOWN, 1996
Blockade of NMDA receptors during song model exposure impairs song development in juvenile zebra finches.
Aamodt SM, Nordeen EJ, Nordeen KW., Neurobiol Learn Mem 65(1), 1996
PMID: 8673412
Androgens modulate NMDA receptor-mediated EPSCs in the zebra finch song system.
White SA, Livingston FS, Mooney R., J. Neurophysiol. 82(5), 1999
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Comparisons of dN/dS are time dependent for closely related bacterial genomes.
Rocha EP, Smith JM, Hurst LD, Holden MT, Cooper JE, Smith NH, Feil EJ., J. Theor. Biol. 239(2), 2005
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Quantitative prediction of molecular clock and ka/ks at short timescales.
Peterson GI, Masel J., Mol. Biol. Evol. 26(11), 2009
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Nonlinear dynamics of nonsynonymous (dN) and synonymous (dS) substitution rates affects inference of selection.
Wolf JB, Kunstner A, Nam K, Jakobsson M, Ellegren H., Genome Biol Evol 1(), 2009
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The evolutionary advantage of recombination.
Felsenstein J., Genetics 78(2), 1974
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Reduced efficacy of selection in regions of the Drosophila genome that lack crossing over.
Haddrill PR, Halligan DL, Tomaras D, Charlesworth B., Genome Biol. 8(2), 2007
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Evolution of protein-coding genes in Drosophila.
Larracuente AM, Sackton TB, Greenberg AJ, Wong A, Singh ND, Sturgill D, Zhang Y, Oliver B, Clark AG., Trends Genet. 24(3), 2008
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Comparative recombination rates in the rat, mouse, and human genomes.
Jensen-Seaman MI, Furey TS, Payseur BA, Lu Y, Roskin KM, Chen CF, Thomas MA, Haussler D, Jacob HJ., Genome Res. 14(4), 2004
PMID: 15059993
Absence of the TAP2 human recombination hotspot in chimpanzees.
Ptak SE, Roeder AD, Stephens M, Gilad Y, Paabo S, Przeworski M., PLoS Biol. 2(6), 2004
PMID: 15208713
Comparison of fine-scale recombination rates in humans and chimpanzees.
Winckler W, Myers SR, Richter DJ, Onofrio RC, McDonald GJ, Bontrop RE, McVean GA, Gabriel SB, Reich D, Donnelly P, Altshuler D., Science 308(5718), 2005
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The rise and fall of a human recombination hot spot.
Jeffreys AJ, Neumann R., Nat. Genet. 41(5), 2009
PMID: 19349985
A common sequence motif associated with recombination hot spots and genome instability in humans.
Myers S, Freeman C, Auton A, Donnelly P, McVean G., Nat. Genet. 40(9), 2008
PMID: 19165926
Biomart
AUTHOR UNKNOWN, 0
InParanoid 6: eukaryotic ortholog clusters with inparalogs.
Berglund AC, Sjolund E, Ostlund G, Sonnhammer EL., Nucleic Acids Res. 36(Database issue), 2007
PMID: 18055500
PAML 4: phylogenetic analysis by maximum likelihood.
Yang Z., Mol. Biol. Evol. 24(8), 2007
PMID: 17483113
A direct approach to false discovery rates.
AUTHOR UNKNOWN, 2002
GOstat: find statistically overrepresented Gene Ontologies within a group of genes.
Beissbarth T, Speed TP., Bioinformatics 20(9), 2004
PMID: 14962934
Controlling the false discovery rate: a practical and powerful approach to multiple testing.
AUTHOR UNKNOWN, 1995
OMIM Database
AUTHOR UNKNOWN, 0
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