Literature DB >> 24197463

Estimating the locations and the sizes of the effects of quantitative trait loci using flanking markers.

O Martínez1, R N Curnow.   

Abstract

The use of information from flanking markers to estimate the position and size of the effect of a quantitative trait locus (QTL) lying between two markers is shown to be affected by QTLs lying in neighbouring regions of the chromosome. In some situations the effects of two QTLs lying outside the flanked region are reinforced in such a way that a 'ghost' QTL may be mistakenly identified as a real QTL. These problems are discussed in the framework of a backcross using a regression model as the analytical tool to present the theoretical results. Regression models that use information obtained from three or more nearby markers are shown to be useful in separating the effects of QTLs in neighbouring regions. A simulated data set exemplifies the problem and is analysed by the interval mapping method as well as by the regression model.

Year:  1992        PMID: 24197463     DOI: 10.1007/BF00222330

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


  10 in total

1.  Maximum likelihood estimation of linkage between a marker gene and a quantitative trait locus. II. Application to backcross and doubled haploid populations.

Authors:  Z W Luo; M J Kearsey
Journal:  Heredity (Edinb)       Date:  1991-02       Impact factor: 3.821

2.  A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

Authors:  C S Haley; S A Knott
Journal:  Heredity (Edinb)       Date:  1992-10       Impact factor: 3.821

3.  Detection of linkage between quantitative trait loci and restriction fragment length polymorphisms using inbred lines.

Authors:  S P Simpson
Journal:  Theor Appl Genet       Date:  1989-06       Impact factor: 5.699

4.  Using molecular markers to map multiple quantitative trait loci: models for backcross, recombinant inbred, and doubled haploid progeny.

Authors:  S J Knapp
Journal:  Theor Appl Genet       Date:  1991-03       Impact factor: 5.699

5.  Mapping quantitative trait loci using molecular marker linkage maps.

Authors:  S J Knapp; W C Bridges; D Birkes
Journal:  Theor Appl Genet       Date:  1990-05       Impact factor: 5.699

6.  Maximum likelihood estimation of linkage between a marker gene and a quantitative locus.

Authors:  Z W Luo; M J Kearsey
Journal:  Heredity (Edinb)       Date:  1989-12       Impact factor: 3.821

7.  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

8.  Maximum likelihood techniques for the mapping and analysis of quantitative trait loci with the aid of genetic markers.

Authors:  J I Weller
Journal:  Biometrics       Date:  1986-09       Impact factor: 2.571

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

10.  Estimation of recombination parameters between a quantitative trait locus (QTL) and two marker gene loci.

Authors:  J Jensen
Journal:  Theor Appl Genet       Date:  1989-11       Impact factor: 5.699

  10 in total
  78 in total

1.  Statistical methods for QTL mapping in cereals.

Authors:  Christine A Hackett
Journal:  Plant Mol Biol       Date:  2002 Mar-Apr       Impact factor: 4.076

2.  Using advanced intercross lines for high-resolution mapping of HDL cholesterol quantitative trait loci.

Authors:  Xiaosong Wang; Isabelle Le Roy; Edwige Nicodeme; Renhua Li; Richard Wagner; Christina Petros; Gary A Churchill; Stephen Harris; Ariel Darvasi; Jorge Kirilovsky; Pierre L Roubertoux; Beverly Paigen
Journal:  Genome Res       Date:  2003-06-12       Impact factor: 9.043

3.  Using the noninformative families in family-based association tests: a powerful new testing strategy.

Authors:  Christoph Lange; Dawn DeMeo; Edwin K Silverman; Scott T Weiss; Nan M Laird
Journal:  Am J Hum Genet       Date:  2003-09-18       Impact factor: 11.025

4.  Duplicate marker loci can result in incorrect locus orders on linkage maps.

Authors:  M Frisch; M Quint; T Lübberstedt; A E Melchinger
Journal:  Theor Appl Genet       Date:  2004-02-14       Impact factor: 5.699

5.  QTL mapping under truncation selection in homozygous lines derived from biparental crosses.

Authors:  Albrecht E Melchinger; Elena Orsini; Chris C Schön
Journal:  Theor Appl Genet       Date:  2011-11-01       Impact factor: 5.699

6.  Use of contiguous congenic strains in analyzing compound QTLs.

Authors:  John P Rapp; Bina Joe
Journal:  Physiol Genomics       Date:  2011-11-22       Impact factor: 3.107

7.  Multivariate whole genome average interval mapping: QTL analysis for multiple traits and/or environments.

Authors:  Arūnas P Verbyla; Brian R Cullis
Journal:  Theor Appl Genet       Date:  2012-06-13       Impact factor: 5.699

8.  Conditions under which genome-wide association studies will be positively misleading.

Authors:  Alexander Platt; Bjarni J Vilhjálmsson; Magnus Nordborg
Journal:  Genetics       Date:  2010-09-02       Impact factor: 4.562

9.  Mapping of epistatic quantitative trait loci in four-way crosses.

Authors:  Xiao-Hong He; Hongde Qin; Zhongli Hu; Tianzhen Zhang; Yuan-Ming Zhang
Journal:  Theor Appl Genet       Date:  2010-09-09       Impact factor: 5.699

10.  Complex genetic effects in quantitative trait locus identification: a computationally tractable random model for use in F(2) populations.

Authors:  Daisy Zimmer; Manfred Mayer; Norbert Reinsch
Journal:  Genetics       Date:  2010-10-18       Impact factor: 4.562

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