Literature DB >> 9503632

QTL analysis in plants; where are we now?

M J Kearsey1, A G Farquhar.   

Abstract

We have briefly reviewed the methods currently available for QTL analysis in segregating populations and summarized some of the conclusions arising from such analyses in plant populations. We show that the analytical methods locate QTL with poor precision (10-30 cM), unless the heritability of an individual QTL is high. Also the estimates of the QTL effects, particularly the dominance effects tend to be inflated because only large estimates are significant. Estimates of numbers of QTL per trait are generally low (< 8) for individual trials. This may suggest that there are few QTL but probably reflects the power of the methods. There is no large correlation between the numbers of QTL found and the amount of the variation explained. Of those cases where dominance is measurable, dominance ratios are often > 1, but seldom significantly greater. These latter cases need further analysis. Many QTL map close to candidate genes, and there is growing evidence from synteny studies of corresponding chromosome regions carrying similar QTL in different species. However, unreliability of QTL location may suggest false candidates.

Mesh:

Year:  1998        PMID: 9503632     DOI: 10.1046/j.1365-2540.1998.00500.x

Source DB:  PubMed          Journal:  Heredity (Edinb)        ISSN: 0018-067X            Impact factor:   3.821


  108 in total

1.  Sex and adaptation in a changing environment.

Authors:  D Waxman; J R Peck
Journal:  Genetics       Date:  1999-10       Impact factor: 4.562

2.  Marker pair selection for mapping quantitative trait loci.

Authors:  H P Piepho; H G Gauch
Journal:  Genetics       Date:  2001-01       Impact factor: 4.562

3.  Genetic and nongenetic bases for the L-shaped distribution of quantitative trait loci effects.

Authors:  B Bost; D de Vienne; F Hospital; L Moreau; C Dillmann
Journal:  Genetics       Date:  2001-04       Impact factor: 4.562

4.  Quantitative trait loci: a meta-analysis.

Authors:  B Goffinet; S Gerber
Journal:  Genetics       Date:  2000-05       Impact factor: 4.562

5.  Bias in estimates of quantitative-trait-locus effect in genome scans: demonstration of the phenomenon and a method-of-moments procedure for reducing bias.

Authors:  David B Allison; Jose R Fernandez; Moonseong Heo; Shankuan Zhu; Carol Etzel; T Mark Beasley; Christopher I Amos
Journal:  Am J Hum Genet       Date:  2002-02-08       Impact factor: 11.025

6.  Modeling linkage disequilibrium between a polymorphic marker locus and a locus affecting complex dichotomous traits in natural populations.

Authors:  Z W Luo; C I Wu
Journal:  Genetics       Date:  2001-08       Impact factor: 4.562

7.  Large upward bias in estimation of locus-specific effects from genomewide scans.

Authors:  H H Göring; J D Terwilliger; J Blangero
Journal:  Am J Hum Genet       Date:  2001-10-09       Impact factor: 11.025

8.  Statistical methods for QTL mapping in cereals.

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

9.  Mixed model association scans of multi-environmental trial data reveal major loci controlling yield and yield related traits in Hordeum vulgare in Mediterranean environments.

Authors:  J Comadran; J R Russell; A Booth; A Pswarayi; S Ceccarelli; S Grando; A M Stanca; N Pecchioni; T Akar; A Al-Yassin; A Benbelkacem; H Ouabbou; J Bort; F A van Eeuwijk; W T B Thomas; I Romagosa
Journal:  Theor Appl Genet       Date:  2011-01-30       Impact factor: 5.699

10.  Genetic mapping and QTL analysis of fiber-related traits in cotton ( Gossypium).

Authors:  M Mei; N H Syed; W Gao; P M Thaxton; C W Smith; D M Stelly; Z J Chen
Journal:  Theor Appl Genet       Date:  2003-09-25       Impact factor: 5.699

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.