A differential equation model for functional mapping of a virus-cell dynamic system.
The dynamic pattern of viral load in a patient's body critically depends on the host's genes. For this reason, the identification of those genes responsible for virus dynamics, although difficult, is of fundamental importance to design an optimal drug therapy based on patients' genetic makeup. Here, we present a differential equation (DE) model for characterizing specific genes or quantitative trait loci (QTLs) that affect viral load trajectories within the framework of a dynamic system. The model is formulated with the principle of functional mapping, originally derived to map dynamic QTLs, and implemented with a Markov chain process. The DE-integrated model enhances the mathematical robustness of functional mapping, its quantitative prediction about the temporal pattern of genetic expression, and therefore its practical utilization and effectiveness for gene discovery in clinical settings. The model was used to analyze simulated data for viral dynamics, aimed to investigate its statistical properties and validate its usefulness. With an increasing availability of genetic polymorphic data, the model will have great implications for probing the molecular genetic mechanism of virus dynamics and disease progression.
Luo
Jiangtao
J
Department of Mathematics, University of Florida, Gainesville, FL 32611, USA.
Hager
William W
WW
Wu
Rongling
R
D002874:Chromosome Mapping; D003198:Computer Simulation / Q000706:statistics & numerical data; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D040641:Quantitative Trait Loci; D019562:Viral Load / Q000235:genetics*; D014777:Virus Diseases / Q000235:genetics*
Stat Appl Genet Mol Biol. 2009;8:Article 18
19341352
Nat Rev Genet. 2006 Mar;7(3):229-37
16485021
Nature. 1995 Jan 12;373(6510):123-6
7816094
Genetics. 1989 Jan;121(1):185-99
2563713
Genetics. 2004 Dec;168(4):2383-94
15371347
Genetics. 2002 Aug;161(4):1751-62
12196415
Genetics. 1994 Nov;138(3):963-71
7851788
Proc Natl Acad Sci U S A. 2008 Mar 25;105(12):4832-7
18362342
Genetics. 2002 Feb;160(2):779-92
11861578
Genetics. 2004 Mar;166(3):1541-51
15082567
Proc Natl Acad Sci U S A. 1997 Jun 24;94(13):6971-6
9192676
Biometrics. 2004 Sep;60(3):729-38
15339296
Nature. 2003 Dec 18;426(6968):789-96
14685227
Stat Med. 2006 Feb 15;25(3):495-511
16013038
Stat Med. 2006 Nov 30;25(22):3826-49
16435340
Proc Natl Acad Sci U S A. 2000 Jul 18;97(15):8193-5
10899988
Stat Appl Genet Mol Biol. 2005;4:Article33
16646852
Proc Natl Acad Sci U S A. 2000 Jul 5;97(14):7681-6
10884399
Nature. 1997 May 8;387(6629):188-91
9144290
Science. 1996 Mar 15;271(5255):1582-6
8599114
J Virol. 1997 Apr;71(4):3275-8
9060694
Stat Med. 2004 Oct 15;23(19):3033-51
15351959