A new computational method for the detection of horizontal gene transfer events.
In recent years, the increase in the amounts of available genomic data has made it easier to appreciate the extent by which organisms increase their genetic diversity through horizontally transferred genetic material. Such transfers have the potential to give rise to extremely dynamic genomes where a significant proportion of their coding DNA has been contributed by external sources. Because of the impact of these horizontal transfers on the ecological and pathogenic character of the recipient organisms, methods are continuously sought that are able to computationally determine which of the genes of a given genome are products of transfer events. In this paper, we introduce and discuss a novel computational method for identifying horizontal transfers that relies on a gene's nucleotide composition and obviates the need for knowledge of codon boundaries. In addition to being applicable to individual genes, the method can be easily extended to the case of clusters of horizontally transferred genes. With the help of an extensive and carefully designed set of experiments on 123 archaeal and bacterial genomes, we demonstrate that the new method exhibits significant improvement in sensitivity when compared to previously published approaches. In fact, it achieves an average relative improvement across genomes of between 11 and 41% compared to the Codon Adaptation Index method in distinguishing native from foreign genes. Our method's horizontal gene transfer predictions for 123 microbial genomes are available online at http://cbcsrv.watson.ibm.com/HGT/.
Tsirigos
Aristotelis
A
New York University, Computer Science New York, NY 10021, USA.
Rigoutsos
Isidore
I
D000465:Algorithms; D001435:Bacteriophages / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D022761:Gene Transfer, Horizontal; D019766:Genes, Archaeal; D005798:Genes, Bacterial; D005814:Genes, Viral; D023281:Genomics / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*
Genome Res. 1998 Nov;8(11):1154-71
9847079
Nature. 2000 May 18;405(6784):299-304
10830951
Plant Physiol. 1998 Sep;118(1):9-17
9733521
Genome Res. 1999 Jul;9(7):608-28
10413400
Trends Biochem Sci. 1992 Dec;17(12):489-93
1471257
Science. 1995 Feb 10;267(5199):897-9
7846533
Proc Natl Acad Sci U S A. 1998 Aug 4;95(16):9413-7
9689094
Genome Res. 1999 Aug;9(8):689-710
10447505
Mol Microbiol. 1997 Aug;25(4):619-37
9379893
Science. 2003 Mar 28;299(5615):2071-4
12663927
Annu Rev Genet. 1999;33:351-97
10690412
J Mol Biol. 1996 Oct 4;262(4):459-72
8893856
J Theor Biol. 1985 Jan 21;112(2):333-43
2984477
Mol Microbiol. 1998 Sep;29(6):1341-55
9781873
Science. 1999 Jun 25;284(5423):2124-9
10381871
J Exp Med. 1979 Feb 1;149(2):297-326
33226
Nat Genet. 2004 Jul;36(7):760-6
15208628
FEMS Microbiol Lett. 2001 Jul 24;201(2):187-91
11470360
Science. 2003 Nov 28;302(5650):1569-71
14645850
Proc Natl Acad Sci U S A. 1999 Aug 3;96(16):9184-9
10430917
Trends Genet. 1995 Jul;11(7):283-90
7482779
Microbiol Mol Biol Rev. 2000 Mar;64(1):202-36
10704480
J Bacteriol. 1997 Jun;179(12):3899-913
9190805
Curr Opin Genet Dev. 1999 Dec;9(6):649-56
10607611
J Mol Evol. 2002 Mar;54(3):365-75
11847562
Genome Res. 2001 Aug;11(8):1404-9
11483581
Annu Rev Genet. 1994;28:237-61
7893125
Curr Opin Genet Dev. 1998 Dec;8(6):630-6
9914200
J Mol Biol. 1991 Dec 20;222(4):851-6
1762151
Curr Opin Genet Dev. 1999 Dec;9(6):678-87
10607615
Curr Biol. 1998 Mar 12;8(6):R209-11
9512414
Trends Genet. 2000 Dec;16(12):529-33
11102698
EMBO J. 1992 Apr;11(4):1309-16
1339343
Nature. 1999 May 27;399(6734):323-9
10360571
Annu Rev Microbiol. 2001;55:709-42
11544372
Nucleic Acids Res. 2003 Jan 1;31(1):187-9
12519978
Trends Genet. 1998 Nov;14(11):442-4
9825671
Proc Natl Acad Sci U S A. 1999 Mar 30;96(7):3801-6
10097118
Int J Syst Evol Microbiol. 2002 May;52(Pt 3):777-87
12054238
Mol Biol Evol. 1985 Jan;2(1):13-34
3916708