Literature DB >> 18854970

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

Alizera Navabi1, D E Mather, J Bernier, D M Spaner, G N Atlin.   

Abstract

Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18854970     DOI: 10.1007/s00122-008-0904-2

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


  13 in total

1.  Maximum likelihood analysis of quantitative trait loci under selective genotyping.

Authors:  S Xu; C Vogl
Journal:  Heredity (Edinb)       Date:  2000-05       Impact factor: 3.821

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

Authors:  A Gallais; L Moreau; A Charcosset
Journal:  Theor Appl Genet       Date:  2006-12-13       Impact factor: 5.699

Review 3.  Segregation distorters.

Authors:  T W Lyttle
Journal:  Annu Rev Genet       Date:  1991       Impact factor: 16.830

4.  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

5.  Advanced backcross QTL analysis: a method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into elite breeding lines.

Authors:  S D Tanksley; J C Nelson
Journal:  Theor Appl Genet       Date:  1996-02       Impact factor: 5.699

6.  The effects of selective genotyping on estimates of proportion of recombination between linked quantitative trait loci.

Authors:  J Z Lin; K Ritland
Journal:  Theor Appl Genet       Date:  1996-12       Impact factor: 5.699

7.  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

8.  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

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

Review 10.  Mapping quantitative trait loci using linkage disequilibrium: marker- versus trait-based methods.

Authors:  Albert Tenesa; Peter M Visscher; Andrew D Carothers; Sara A Knott
Journal:  Behav Genet       Date:  2005-03       Impact factor: 2.805

View more
  24 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.  Impact of selective genotyping in the training population on accuracy and bias of genomic selection.

Authors:  Yusheng Zhao; Manje Gowda; Friedrich H Longin; Tobias Würschum; Nicolas Ranc; Jochen C Reif
Journal:  Theor Appl Genet       Date:  2012-04-06       Impact factor: 5.699

3.  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

4.  Molecular mapping of aluminium resistance loci based on root re-growth and Al-induced fluorescent signals (callose accumulation) in lentil (Lens culinaris Medikus).

Authors:  Chandan Kumar Singh; Dharmendra Singh; Ram Sewak Singh Tomar; Sourabh Karwa; K C Upadhyaya; Madan Pal
Journal:  Mol Biol Rep       Date:  2018-09-14       Impact factor: 2.316

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.  Fine mapping QTL for drought resistance traits in rice (Oryza sativa L.) using bulk segregant analysis.

Authors:  Arvindkumar Shivaji Salunkhe; R Poornima; K Silvas Jebakumar Prince; P Kanagaraj; J Annie Sheeba; K Amudha; K K Suji; A Senthil; R Chandra Babu
Journal:  Mol Biotechnol       Date:  2011-09       Impact factor: 2.695

7.  Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis.

Authors:  Ramaiah Venuprasad; C O Dalid; M Del Valle; D Zhao; M Espiritu; M T Sta Cruz; M Amante; A Kumar; G N Atlin
Journal:  Theor Appl Genet       Date:  2009-10-17       Impact factor: 5.699

8.  Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents.

Authors:  Mehrzad Eskandari; Elroy R Cober; Istvan Rajcan
Journal:  Theor Appl Genet       Date:  2012-11-29       Impact factor: 5.699

9.  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

10.  QTL mapping for haploid male fertility by a segregation distortion method and fine mapping of a key QTL qhmf4 in maize.

Authors:  Jiaojiao Ren; Penghao Wu; Xiaolong Tian; Thomas Lübberstedt; Shaojiang Chen
Journal:  Theor Appl Genet       Date:  2017-04-07       Impact factor: 5.699

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.