Literature DB >> 17165081

Detection of marker-QTL associations by studying change in marker frequencies with selection.

A Gallais1, L Moreau, A Charcosset.   

Abstract

The value of selective genotyping for the detection of QTL has already been studied from a theoretical point of view but with the assumption of a negligible contribution (r2P) of the QTL to the phenotypic variance. For predicting change in gene frequency, we show that this assumption is only valid for r2P less than 0.05 and for a proportion selected higher than 1%. Therefore, we develop a study of the optimization of selective genotyping without assumption on QTL effect, with selection either of both tails (bidirectional genotyping or BSG) or only one tail (unidirectional genotyping or USG). For a given population size of phenotyped plants the optimal proportion selected for selective genotyping is around 30% for each tail. For the same investment as in ANOVA, by investing more in phenotyping than in genotyping when the cost ratio of genotyping to phenotyping is higher than 1, the optimal proportion selected appears to be between 10 and 20% for each tail. It is mainly affected by the cost ratio and decreases when the cost ratio increases. At this optimum, BSG is competitive with ANOVA, or even more powerful, when the cost ratio is higher than 1. USG can also be competitive when the cost ratio is higher than 2. Using experimental data from two populations of about 300 F4 inbred families of maize, it was verified that BSG at the optimum gives the same results as ANOVA or is better whereas USG is less powerful or equivalent.

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Year:  2006        PMID: 17165081     DOI: 10.1007/s00122-006-0467-z

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


  12 in total

1.  Exploiting selective genotyping to study genetic diversity of resistance to Fusarium head blight in barley.

Authors:  W J Wingbermuehle; C Gustus; K P Smith
Journal:  Theor Appl Genet       Date:  2004-07-15       Impact factor: 5.699

2.  Use of trial clustering to study QTL x environment effects for grain yield and related traits in maize.

Authors:  Laurence Moreau; Alain Charcosset; André Gallais
Journal:  Theor Appl Genet       Date:  2004-11-12       Impact factor: 5.699

3.  Trait-based analyses for the detection of linkage between marker loci and quantitative trait loci in crosses between inbred lines.

Authors:  R J Lebowitz; M Soller; J S Beckmann
Journal:  Theor Appl Genet       Date:  1987-02       Impact factor: 5.699

4.  Estimation of the contribution of quantitative trait loci (QTL) to the variance of a quantitative trait by means of genetic markers.

Authors:  A Charcosset; A Gallais
Journal:  Theor Appl Genet       Date:  1996-12       Impact factor: 5.699

5.  Selective genotyping for determination of linkage between a marker locus and a quantitative trait locus.

Authors:  A Darvasi; M Soller
Journal:  Theor Appl Genet       Date:  1992-11       Impact factor: 5.699

6.  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

7.  A generalized approach for estimating effective population size from temporal changes in allele frequency.

Authors:  R S Waples
Journal:  Genetics       Date:  1989-02       Impact factor: 4.562

8.  Allozyme Frequency Changes Associated with Selection for Increased Grain Yield in Maize (ZEA MAYS L.).

Authors:  C W Stuber; R H Moll; M M Goodman; H E Schaffer; B S Weir
Journal:  Genetics       Date:  1980-05       Impact factor: 4.562

9.  Selective DNA pooling for determination of linkage between a molecular marker and a quantitative trait locus.

Authors:  A Darvasi; M Soller
Journal:  Genetics       Date:  1994-12       Impact factor: 4.562

10.  Mapping salt-tolerance genes in tomato (Lycopersicon esculentum) using trait-based marker analysis.

Authors:  M R Foolad; R A Jones
Journal:  Theor Appl Genet       Date:  1993-10       Impact factor: 5.699

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  16 in total

1.  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

2.  Three EST-SSR markers associated with QTL for the growth of the clam Meretrix meretrix revealed by selective genotyping.

Authors:  Xia Lu; Hongxia Wang; Baozhong Liu; Jianhai Xiang
Journal:  Mar Biotechnol (NY)       Date:  2012-04-27       Impact factor: 3.619

3.  Selective genotyping and phenotyping strategies in a complex trait context.

Authors:  Saunak Sen; Frank Johannes; Karl W Broman
Journal:  Genetics       Date:  2009-01-19       Impact factor: 4.562

4.  QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses.

Authors:  Alizera Navabi; D E Mather; J Bernier; D M Spaner; G N Atlin
Journal:  Theor Appl Genet       Date:  2008-10-15       Impact factor: 5.699

5.  Genomic architecture of alpha-amylase activity in mature rye grain relative to that of preharvest sprouting.

Authors:  Piotr Masojć; Magdalena Wiśniewska; Anna Łań; Paweł Milczarski; Marcin Berdzik; Daniel Pędziwiatr; Magdalena Pol-Szyszko; Monika Gałęza; Radosław Owsianicki
Journal:  J Appl Genet       Date:  2011-01-12       Impact factor: 3.240

6.  Molecular mapping of major QTL conferring resistance to orange wheat blossom midge (Sitodiplosis mosellana) in Chinese wheat varieties with selective populations.

Authors:  Lijing Zhang; Miaomiao Geng; Zhe Zhang; Yue Zhang; Guijun Yan; Shumin Wen; Guiru Liu; Ruihui Wang
Journal:  Theor Appl Genet       Date:  2019-11-26       Impact factor: 5.699

7.  QTL mapping for grain yield-related traits in bread wheat via SNP-based selective genotyping.

Authors:  Li Yang; Dehui Zhao; Zili Meng; Kaijie Xu; Jun Yan; Xianchun Xia; Shuanghe Cao; Yubing Tian; Zhonghu He; Yong Zhang
Journal:  Theor Appl Genet       Date:  2019-12-16       Impact factor: 5.699

8.  Bidirectional selective genotyping approach for the identification of quantitative trait loci controlling earliness per se in winter rye (Secale cereale L.).

Authors:  Beata Myśków; Stefan Stojałowski
Journal:  J Appl Genet       Date:  2015-06-12       Impact factor: 3.240

9.  Genetic analysis carried out in population tails reveals diverse two-loci interactions as a basic factor of quantitative traits variation in rye.

Authors:  Piotr Masojć; Anna Bienias; Marcin Berdzik; Piotr Kruszona
Journal:  J Appl Genet       Date:  2015-10-08       Impact factor: 3.240

Review 10.  Bulked sample analysis in genetics, genomics and crop improvement.

Authors:  Cheng Zou; Pingxi Wang; Yunbi Xu
Journal:  Plant Biotechnol J       Date:  2016-04-28       Impact factor: 9.803

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