Literature DB >> 19407987

Efficiency gain of marker-assisted backcrossing by sequentially increasing marker densities over generations.

Vanessa Prigge1, Albrecht E Melchinger, Baldev S Dhillon, Matthias Frisch.   

Abstract

Expenses for marker assays are the major costs in marker-assisted backcrossing programs for the transfer of target genes from a donor into the genetic background of a recipient genotype. Our objectives were to (1) investigate the effect of employing sequentially increasing marker densities over backcross generations on the recurrent parent genome (RPG) recovery and the number of marker data points (MDP) required, and (2) determine optimum designs for attaining RPG thresholds of 93-98% with a minimum number of MDP. We simulated the introgression of one dominant target gene for genome models of sugar beet (Beta vulgaris L.) and maize (Zea mays L.) with varying marker distances of 5-80 cM and population sizes of 30-250 plants across BC(1) to BC(3) generations. Employing less dense maps in early backcross generations resulted in savings of over 50% in the number of required MDP compared with using a constant set of markers and was accompanied only by small reductions in the attained RPG values. The optimum designs were characterized by increasing marker densities and increasing population sizes in advanced generations for both genome models. We conclude that increasing simultaneously the marker density and the population size from early to advanced backcross generations results in gene introgression with a minimum number of required MDP.

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Year:  2009        PMID: 19407987     DOI: 10.1007/s00122-009-1013-6

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


  7 in total

1.  The length of the intact donor chromosome segment around a target gene in marker-assisted backcrossing.

Authors:  M Frisch; A E Melchinger
Journal:  Genetics       Date:  2001-03       Impact factor: 4.562

2.  Optimal positioning of markers to control genetic background in marker-assisted backcrossing.

Authors:  Bertrand Servin; F Hospital
Journal:  J Hered       Date:  2002 May-Jun       Impact factor: 2.645

3.  Using markers in gene introgression breeding programs.

Authors:  F Hospital; C Chevalet; P Mulsant
Journal:  Genetics       Date:  1992-12       Impact factor: 4.562

Review 4.  Selection in backcross programmes.

Authors:  Frédéric Hospital
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-07-29       Impact factor: 6.237

5.  Marker-based prediction of the parental genome contribution to inbred lines derived from biparental crosses.

Authors:  Matthias Frisch; Albrecht E Melchinger
Journal:  Genetics       Date:  2006-08-03       Impact factor: 4.562

6.  Variance of the parental genome contribution to inbred lines derived from biparental crosses.

Authors:  Matthias Frisch; Albrecht E Melchinger
Journal:  Genetics       Date:  2007-04-03       Impact factor: 4.562

7.  Marker-assisted introgression in backcross breeding programs.

Authors:  P M Visscher; C S Haley; R Thompson
Journal:  Genetics       Date:  1996-12       Impact factor: 4.562

  7 in total
  4 in total

1.  Power and false-positive rate in QTL detection with near-isogenic line libraries.

Authors:  K C Falke; M Frisch
Journal:  Heredity (Edinb)       Date:  2010-08-04       Impact factor: 3.821

2.  High-throughput genetic mapping of mutants via quantitative single nucleotide polymorphism typing.

Authors:  Sanzhen Liu; Hsin D Chen; Irina Makarevitch; Rebecca Shirmer; Scott J Emrich; Charles R Dietrich; W Brad Barbazuk; Nathan M Springer; Patrick S Schnable
Journal:  Genetics       Date:  2009-11-02       Impact factor: 4.562

3.  Selection strategies for marker-assisted backcrossing with high-throughput marker systems.

Authors:  Eva Herzog; Matthias Frisch
Journal:  Theor Appl Genet       Date:  2011-04-08       Impact factor: 5.699

4.  Fine mapping a major QTL for kernel number per row under different phosphorus regimes in maize (Zea mays L.).

Authors:  Guodong Zhang; Xiaopeng Wang; Bin Wang; Yanchen Tian; Meng Li; Yongxin Nie; Qingcai Peng; Zeli Wang
Journal:  Theor Appl Genet       Date:  2013-03-15       Impact factor: 5.699

  4 in total

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