Literature DB >> 24221205

Quantitative genetic variance associated with chromosomal markers in segregating populations.

J C Dekkers1, M R Dentine.   

Abstract

Use of chromosomal markers can accelerate genetic progress for quantitative traits in pedigree selection programs by providing early information on Mendelian segregation effects for individual progeny. Potential effectiveness of selection using markers is determined by the amount of additive genetic variance traced from parents to progeny by the markers. Theoretical equations for the amount of additive genetic variance associated with a marker were derived at the individual level and for a segregating population in joint linkage equilibrium. Factors considered were the number of quantitative trait loci linked to the marker, their individual effects, and recombination rates with the marker. Subsequently, the expected amount of genetic variance associated with a marker in a segregating population was derived. In pedigree selection programs in segregating populations, a considerable fraction of the genetic variance on a chromosome is expected to be associated with a marker located on that chromosome. For an average chromosome in the bovine, this fraction is approximately 40% of the Mendelian segregation variance contributed by the chromosome. The effects of interference and position of the marker on this expectation are relative small. Length of the chromosome has a large effect on the expected variance. Effectiveness of MAS is, however, greatly reduced by lack of polymorphism at the marker and inaccuracy of estimation of chromosome substitution effects. The size of the expected amount of genetic variance associated with a chromosomal marker indicates that, even when the marker is not the active locus, large chromosome substitution effects are not uncommon in segregating populations.

Entities:  

Year:  1991        PMID: 24221205     DOI: 10.1007/BF00215725

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  10 in total

1.  The Theoretical Values of Correlations between Relatives in Random Mating Populations.

Authors:  O Kempthorne
Journal:  Genetics       Date:  1955-03       Impact factor: 4.562

2.  Structural variation around prolactin gene linked to quantitative traits in an elite Holstein sire family.

Authors:  C M Cowan; M R Dentine; R L Ax; L A Schuler
Journal:  Theor Appl Genet       Date:  1990-05       Impact factor: 5.699

3.  An analytical model for the estimation of chromosome substitution effects in the offspring of individuals heterozygous at a segregating marker locus.

Authors:  M R Dentine; C M Cowan
Journal:  Theor Appl Genet       Date:  1990-06       Impact factor: 5.699

4.  Efficiency of marker-assisted selection in the improvement of quantitative traits.

Authors:  R Lande; R Thompson
Journal:  Genetics       Date:  1990-03       Impact factor: 4.562

5.  Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.

Authors:  E S Lander; D Botstein
Journal:  Genetics       Date:  1989-01       Impact factor: 4.562

6.  Individual-specific 'fingerprints' of human DNA.

Authors:  A J Jeffreys; V Wilson; S L Thein
Journal:  Nature       Date:  1985 Jul 4-10       Impact factor: 49.962

7.  Evidence for increased recombination near the human insulin gene: implication for disease association studies.

Authors:  A Chakravarti; S C Elbein; M A Permutt
Journal:  Proc Natl Acad Sci U S A       Date:  1986-02       Impact factor: 11.205

8.  Investigations on inheritance of quantitative characters in animals by gene markers I. Methods.

Authors:  H Geldermann
Journal:  Theor Appl Genet       Date:  1975-01       Impact factor: 5.699

9.  Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms.

Authors:  A H Paterson; E S Lander; J D Hewitt; S Peterson; S E Lincoln; S D Tanksley
Journal:  Nature       Date:  1988-10-20       Impact factor: 49.962

Review 10.  Construction of a genetic linkage map in man using restriction fragment length polymorphisms.

Authors:  D Botstein; R L White; M Skolnick; R W Davis
Journal:  Am J Hum Genet       Date:  1980-05       Impact factor: 11.025

  10 in total
  9 in total

1.  A molecular selection index method based on eigenanalysis.

Authors:  J Jesús Cerón-Rojas; Fernando Castillo-González; Jaime Sahagún-Castellanos; Amalio Santacruz-Varela; Ignacio Benítez-Riquelme; José Crossa
Journal:  Genetics       Date:  2008-08-20       Impact factor: 4.562

2.  Detection of putative quantitative trait loci in line crosses under infinitesimal genetic models.

Authors:  P M Visscher; C S Haley
Journal:  Theor Appl Genet       Date:  1996-10       Impact factor: 5.699

3.  Bayesian analysis of linkage between genetic markers and quantitative trait loci. I. Prior knowledge.

Authors:  I Hoeschele; P M Vanraden
Journal:  Theor Appl Genet       Date:  1993-02       Impact factor: 5.699

4.  RFLP variation and genealogical distance, multivariate distance, heterosis, and genetic variance in oats.

Authors:  H Moser; M Lee
Journal:  Theor Appl Genet       Date:  1994-03       Impact factor: 5.699

5.  Derivation of single-locus relationship coefficients conditional on marker information.

Authors:  H Simianer
Journal:  Theor Appl Genet       Date:  1994-07       Impact factor: 5.699

6.  Computer simulation of marker-assisted selection utilizing linkage disequilibrium.

Authors:  W Zhang; C Smith
Journal:  Theor Appl Genet       Date:  1992-04       Impact factor: 5.699

7.  Intersubspecific subcongenic mouse strain analysis reveals closely linked QTLs with opposite effects on body weight.

Authors:  Md Bazlur R Mollah; Akira Ishikawa
Journal:  Mamm Genome       Date:  2011-03-31       Impact factor: 2.957

8.  Ghost QTL and hotspots in experimental crosses: novel approach for modeling polygenic effects.

Authors:  Jonas Wallin; Małgorzata Bogdan; Piotr A Szulc; R W Doerge; David O Siegmund
Journal:  Genetics       Date:  2021-03-31       Impact factor: 4.562

9.  The statistical theory of linear selection indices from phenotypic to genomic selection.

Authors:  J Jesus Cerón-Rojas; Jose Crossa
Journal:  Crop Sci       Date:  2022-02-06       Impact factor: 2.763

  9 in total

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