Interactions between markers can be caused by the dominance effect of quantitative trait loci.
F(2) populations are commonly used in genetic studies of animals and plants. For simplicity, most quantitative trait locus or loci (QTL) mapping methods have been developed on the basis of populations having two distinct genotypes at each polymorphic marker or gene locus. In this study, we demonstrate that dominance can cause the interactions between markers and propose an inclusive linear model that includes marker variables and marker interactions so as to completely control both additive and dominance effects of QTL. The proposed linear model is the theoretical basis for inclusive composite-interval QTL mapping (ICIM) for F(2) populations, which consists of two steps: first, the best regression model is selected by stepwise regression, which approximately identifies markers and marker interactions explaining both additive and dominance variations; second, the interval mapping approach is applied to the phenotypic values adjusted by the regression model selected in the first step. Due to the limited mapping population size, the large number of variables, and multicollinearity between variables, coefficients in the inclusive linear model cannot be accurately determined in the first step. Interval mapping is necessary in the second step to fine tune the QTL to their true positions. The efficiency of including marker interactions in mapping additive and dominance QTL was demonstrated by extensive simulations using three QTL distribution models with two population sizes and an actual rice F(2) population.
Zhang
Luyan
L
School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China.
Li
Huihui
H
Li
Zhonglai
Z
Wang
Jiankang
J
D000483:Alleles; D005819:Genetic Markers / Q000235:genetics*; D005828:Genetics, Population; D005838:Genotype; D016014:Linear Models; D040641:Quantitative Trait Loci
D005819:Genetic Markers
Genetics. 1999 Jul;152(3):1203-16
10388834
Genetics. 2006 Jul;173(3):1693-703
16624924
Genetics. 2006 Aug;173(4):2269-82
16702423
Proc Natl Acad Sci U S A. 1997 Aug 19;94(17):9226-31
11038567
Genetics. 2004 Jun;167(2):989-99
15238547
Nat Rev Genet. 2002 Jan;3(1):43-52
11823790
Genetics. 1994 Mar;136(3):1195-207
8005424
Genetics. 2001 Jan;157(1):433-44
11139523
Genetics. 2001 Nov;159(3):1351-64
11729175
Genetics. 2001 Sep;159(1):371-87
11560912
Genetics. 2003 Jul;164(3):1129-38
12871920
Theor Appl Genet. 2008 Jan;116(2):243-60
17985112
Genetics. 2007 May;176(1):611-23
17339210
Proc Natl Acad Sci U S A. 2003 Mar 4;100(5):2574-9
12604771
Genetics. 2007 Jan;175(1):361-74
17110476
Genetics. 1989 Jan;121(1):185-99
2563713
Trends Genet. 2002 Jun;18(6):301-7
12044359
Theor Appl Genet. 1994 Oct;89(2-3):305-12
24177846
Genetics. 2009 Mar;181(3):1077-86
19104078
Theor Appl Genet. 1992 Dec;85(4):480-8
24197463
Heredity (Edinb). 1992 Oct;69(4):315-24
16718932
Nat Rev Genet. 2001 Jan;2(1):11-20
11253063
Genetics. 1996 Oct;144(2):805-16
8889541
Nat Rev Genet. 2002 Jan;3(1):11-21
11823787
Genetics. 2005 Mar;169(3):1711-25
15654105
Genetics. 1994 Apr;136(4):1457-68
8013918
Genetics. 1991 Jan;127(1):181-97
1673106
Genetics. 1995 Jul;140(3):1111-27
7672582
Genetics. 2000 May;155(1):391-405
10790412