Optimum spacing of genetic markers for determining linkage between marker loci and quantitative trait loci

1994 ◽  
Vol 89-89 (2-3) ◽  
pp. 351-357 ◽  
Author(s):  
A. Darvasi ◽  
M. Soller
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Optimum Spacing ◽  
Trait Loci ◽  
Marker Loci

Role of genetic markers in fisheries and aquaculture: useful tools or stamp collecting?

1998 ◽  
Vol 55 (7) ◽  
pp. 1553-1563 ◽  
Author(s):  
Moira M Ferguson ◽  
Roy G Danzmann
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Family Relationships ◽  
Quantitative Trait ◽  
Genome Structure ◽  
Restriction Endonuclease Analysis ◽  
Randomly Amplified Polymorphic Dna ◽  
Trait Loci ◽  
Marker Loci

We comment on the role of genetic markers in fisheries and aquaculture with a view to the future. Our goal is to encourage researchers to evaluate the molecular markers they need to deploy and shift their thinking away from analyses of stock structure towards more aggressive pursuit of questions related to genome structure and function. Examples illustrate that no one marker type is appropriate for all applications. Choice should be based on the evolutionary genetic attributes of both the species and the marker loci themselves. We evaluate three relatively new marker types: mitochondrial DNA (mtDNA) sequences, randomly amplified polymorphic DNA, and hypervariable nuclear loci. We conclude that (i) sequences of mtDNA do not necessarily detect greater polymorphism than restriction endonuclease analysis, (ii) the technical ease of randomly amplified polymorphic DNA is offset by questionable repeatability, and (iii) simulations illustrate that even new marker systems with large numbers of alleles need not detect differences among closely related yet significantly differentiated populations. Increasing the number of alleles per locus did not increase the probability of detecting significant differences. Finally, we consider the roles of genetic markers in helping to determine family relationships in pooled lots of fishes and locate genes that control an organism's phenotype (quantitative trait loci). We discuss how knowledge of quantitative trait loci can help us to understand the basis of individual differences in performance.

Markers, maps and the detection of trait loci

1996 ◽  
Vol 1996 ◽  
pp. 50-50
Author(s):  
C.S. Haley
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Coat Colour ◽  
Combined Effects ◽  
Potential Interest ◽  
Naturally Occurring ◽  
Trait Loci ◽  
Modern Breeding

Naturally occurring genetic variation is the basis for differences in performance and appearance between and within different breeds and lines of livestock. In a few instances (e.g. coat colour, polling) the genes (or loci) which control the variation between animals and breeds have a large enough effect to be individually recognisable. For many traits, however, the combined effects of many different genes act together to control quantitative differences between breeds and individuals within breeds (hence such genes are often referred to as quantitative trait loci or QTLs). Thus the dramatic successes of modern breeding result from generations of selection which has produced accumulated changes at a number of different loci. The genome contains up to 100,000 different genes and identifying those which contribute to variation in traits of interest is a difficult task. One first step is to identify regions of the genome containing loci of potential interest through their linkage to genetic markers.

Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment

1996 ◽  
Vol 92 (8) ◽  
pp. 998-1002 ◽  
Author(s):  
J. I. Weller ◽  
G. R. Wiggans ◽  
P. M. VanRaden ◽  
M. Ron
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Canonical Transformation ◽  
Quantitative Trait ◽  
Trait Loci

scholarly journals The contribution of quantitative trait loci and neutral marker loci to the genetic variances and covariances among quantitative traits in random mating populations.

Genetics ◽  
1995 ◽  
Vol 139 (1) ◽  
pp. 445-455 ◽  
Author(s):  
A Ruiz ◽  
A Barbadilla
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Random Mating ◽  
Unbiased Estimation ◽  
Limited Information ◽  
Trait Loci ◽  
Marker Loci ◽  
Neutral Marker ◽  
Variance Explained

Abstract Using Cockerham's approach of orthogonal scales, we develop genetic models for the effect of an arbitrary number of multiallelic quantitative trait loci (QTLs) or neutral marker loci (NMLs) upon any number of quantitative traits. These models allow the unbiased estimation of the contributions of a set of marker loci to the additive and dominance variances and covariances among traits in a random mating population. The method has been applied to an analysis of allozyme and quantitative data from the European oyster. The contribution of a set marker loci may either be real, when the markers are actually QTLs, or apparent, when they are NMLs that are in linkage disequilibrium with hidden QTLs. Our results show that the additive and dominance variances contributed by a set of NMLs are always minimum estimates of the corresponding variances contributed by the associated QTLs. In contrast, the apparent contribution of the NMLs to the additive and dominance covariances between two traits may be larger than, equal to or lower than the actual contributions of the QTLs. We also derive an expression for the expected variance explained by the correlation between a quantitative trait and multilocus heterozygosity. This correlation explains only a part of the genetic variance contributed by the markers, i.e., in general, a combination of additive and dominance variances and, thus, provides only very limited information relative to the method supplied here.

scholarly journals Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Genetics ◽  
1987 ◽  
Vol 116 (1) ◽  
pp. 113-125
Author(s):  
M D Edwards ◽  
C W Stuber ◽  
J F Wendel
Keyword(s):  
Quantitative Trait Loci ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Gene Action ◽  
Individual Plant ◽  
Gene Effects ◽  
Individual Gene ◽  
Trait Loci ◽  
Marker Loci

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.

A Program to Detect Linkage between Genetic Markers and Nonadditive Quantitative Trait Loci

1991 ◽  
Vol 82 (5) ◽  
pp. 435-435 ◽  
Author(s):  
E. A. Carbonell ◽  
T. M. Gerig
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Trait Loci

scholarly journals Fine mapping of quantitative trait loci using selected overlapping recombinant chromosomes, in an interspecies cross of tomato.

Genetics ◽  
1990 ◽  
Vol 124 (3) ◽  
pp. 735-742 ◽  
Author(s):  
A H Paterson ◽  
J W DeVerna ◽  
B Lanini ◽  
S D Tanksley
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Soluble Solids ◽  
Domestic Species ◽  
Substitution Mapping ◽  
Solids Concentration ◽  
Small Fruit ◽  
Trait Loci ◽  
Soluble Solids Concentration

Abstract Quantitative trait loci (QTLs) have been mapped to small intervals along the chromosomes of tomato (Lycopersicon esculentum), by a method we call substitution mapping. The size of the interval to which a QTL can be mapped is determined primarily by the number and spacing of previously mapped genetic markers in the region surrounding the QTL. We demonstrate the method using tomato genotypes carrying chromosomal segments from Lycopersicon chmielewskii, a wild relative of tomato with high soluble solids concentration but small fruit and low yield. Different L. chmielewskii chromosomal segments carrying a common restriction fragment length polymorphism were identified, and their regions of overlap determined using all available genetic markers. The effect of these chromosomal segments on soluble solids concentration, fruit mass, yield, and pH, was determined in the field. Many overlapping chromosomal segments had very different phenotypic effects, indicating QTLs affecting the phenotype(s) to lie in intervals of as little as 3 cM by which the segments differed. Some associations between different traits were attributed to close linkage between two or more QTLs, rather than pleiotropic effects of a single QTL: in such cases, recombination should separate desirable QTLs from genes with undesirable effects. The prominence of such trait associations in wide crosses appears partly due to infrequent reciprocal recombination between heterozygous chromosomal segments flanked by homozygous regions. Substitution mapping is particularly applicable to gene introgression from wild to domestic species, and generally useful in narrowing the gap between linkage mapping and physical mapping of QTLs.

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