Quantitative trait loci: individual gene effects on quantitative characters

ABSTRACT Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17–20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800–1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.

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Modeling Epistasis of Quantitative Trait Loci Using Cockerham's Model

Genetics ◽

10.1093/genetics/160.3.1243 ◽

2002 ◽

Vol 160 (3) ◽

pp. 1243-1261 ◽

Cited By ~ 19

Author(s):

Chen-Hung Kao ◽

Zhao-Bang Zeng

Keyword(s):

Quantitative Trait Loci ◽

Qtl Mapping ◽

Quantitative Trait ◽

Genetic Variance ◽

Genetic Model ◽

Linkage Equilibrium ◽

Gene Effects ◽

Multiple Loci ◽

Trait Loci ◽

Orthogonal Property

AbstractWe use the orthogonal contrast scales proposed by Cockerham to construct a genetic model, called Cockerham's model, for studying epistasis between genes. The properties of Cockerham's model in modeling and mapping epistatic genes under linkage equilibrium and disequilibrium are investigated and discussed. Because of its orthogonal property, Cockerham's model has several advantages in partitioning genetic variance into components, interpreting and estimating gene effects, and application to quantitative trait loci (QTL) mapping when compared to other models, and thus it can facilitate the study of epistasis between genes and be readily used in QTL mapping. The issues of QTL mapping with epistasis are also addressed. Real and simulated examples are used to illustrate Cockerham's model, compare different models, and map for epistatic QTL. Finally, we extend Cockerham's model to multiple loci and discuss its applications to QTL mapping.

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Quantitative Trait Loci for Maternal Performance for Offspring Survival in Mice

Genetics ◽

10.1093/genetics/162.3.1341 ◽

2002 ◽

Vol 162 (3) ◽

pp. 1341-1353 ◽

Cited By ~ 1

Author(s):

Andréa C Peripato ◽

Reinaldo A de Brito ◽

Ty T Vaughn ◽

L Susan Pletscher ◽

Sergio R Matioli ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Inbred Mouse ◽

Relative Size ◽

Interval Mapping ◽

Mouse Strains ◽

Offspring Survival ◽

Gene Effects ◽

Trait Loci ◽

Maternal Performance

Abstract Maternal performance refers to the effect that the environment provided by mothers has on their offspring’s phenotypes, such as offspring survival and growth. Variations in maternal behavior and physiology are responsible for variations in maternal performance, which in turn affects offspring survival. In our study we found females that failed to nurture their offspring and showed abnormal maternal behaviors. The genetic architecture of maternal performance for offspring survival was investigated in 241 females of an F2 intercross of the SM/J and LG/J inbred mouse strains. Using interval-mapping methods we found two quantitative trait loci (QTL) affecting maternal performance at D2Mit17 + 6 cM and D7Mit21 + 2 cM on chromosomes 2 and 7, respectively. In a two-way genome-wide epistasis scan we found 15 epistatic interactions involving 23 QTL distributed across all chromosomes except 12, 16, and 17. These loci form several small sets of interacting QTL, suggesting a complex set of mechanisms operating to determine maternal performance for offspring survival. Taken all together and correcting for the large number of significant factors, QTL and their interactions explain almost 35% of the phenotypic variation for maternal performance for offspring survival in this cross. This study allowed the identification of many possible candidate genes, as well as the relative size of gene effects and patterns of gene action affecting maternal performance in mice. Detailed behavior observation of mothers from later generations suggests that offspring survival in the first week is related to maternal success in building nests, grooming their pups, providing milk, and/or manifesting aggressive behavior against intruders.

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Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.90.23.10972 ◽

1993 ◽

Vol 90 (23) ◽

pp. 10972-10976 ◽

Cited By ~ 672

Author(s):

Z B Zeng

Keyword(s):

Regression Analysis ◽

Quantitative Trait Loci ◽

Qtl Mapping ◽

Multiple Regression Analysis ◽

Multiple Regression ◽

Quantitative Trait ◽

Genetic Background ◽

Test Statistic ◽

Gene Effects ◽

Trait Loci

It is now possible to use complete genetic linkage maps to locate major quantitative trait loci (QTLs) on chromosome regions. The current methods of QTL mapping (e.g., interval mapping, which uses a pair or two pairs of flanking markers at a time for mapping) can be subject to the effects of other linked QTLs on a chromosome because the genetic background is not controlled. As a result, mapping of QTLs can be biased, and the resolution of mapping is not very high. Ideally when we test a marker interval for a QTL, we would like our test statistic to be independent of the effects of possible QTLs at other regions of the chromosome so that the effects of QTLs can be separated. This test statistic can be constructed by using a pair of markers to locate the testing position and at the same time using other markers to control the genetic background through a multiple regression analysis. Theory is developed in this paper to explore the idea of a conditional test via multiple regression analysis. Various properties of multiple regression analysis in relation to QTL mapping are examined. Theoretical analysis indicates that it is advantageous to construct such a testing procedure for mapping QTLs and that such a test can potentially increase the precision of QTL mapping substantially.

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