Literature DB >> 9465409

Mapping quantitative trait loci with dominant and missing markers in various crosses from two inbred lines.

C Jiang1, Z B Zeng.   

Abstract

Dominant phenotype of a genetic marker provides incomplete information about the marker genotype of an individual. A consequence of using this incomplete information for mapping quantitative trait loci (QTL) is that the inference of the genotype of a putative QTL flanked by a marker with dominant phenotype will depend on the genotype or phenotype of the next marker. This dependence can be extended further until a marker genotype is fully observed. A general algorithm is derived to calculate the probability distribution of the genotype of a putative QTL at a given genomic position, conditional on all observed marker phenotypes in the region with dominant and missing marker information for an individual. The algorithm is implemented for various populations stemming from two inbred lines in the context of mapping QTL. Simulation results show that if only a proportion of markers contain missing or dominant phenotypes, QTL mapping can be almost as efficient as if there were no missing information in the data. The efficiency of the analysis, however, may decrease substantially when a very large proportion of markers contain missing or dominant phenotypes and a genetic map has to be reconstructed first on the same data as well. So it is important to combine dominant markers with codominant markers in a QTL mapping study.

Mesh:

Substances:

Year:  1997        PMID: 9465409     DOI: 10.1023/a:1018394410659

Source DB:  PubMed          Journal:  Genetica        ISSN: 0016-6707            Impact factor:   1.082


  76 in total

1.  Multiple interval mapping for quantitative trait loci.

Authors:  C H Kao; Z B Zeng; R D Teasdale
Journal:  Genetics       Date:  1999-07       Impact factor: 4.562

2.  Construction of a genetic linkage map in tetraploid species using molecular markers.

Authors:  Z W Luo; C A Hackett; J E Bradshaw; J W McNicol; D Milbourne
Journal:  Genetics       Date:  2001-03       Impact factor: 4.562

3.  Multipoint mapping of viability and segregation distorting loci using molecular markers.

Authors:  C Vogl; S Xu
Journal:  Genetics       Date:  2000-07       Impact factor: 4.562

4.  Interval mapping of quantitative trait loci in autotetraploid species.

Authors:  C A Hackett; J E Bradshaw; J W McNicol
Journal:  Genetics       Date:  2001-12       Impact factor: 4.562

5.  Detection of closely linked multiple quantitative trait loci using a genetic algorithm.

Authors:  R Nakamichi; Y Ukai; H Kishino
Journal:  Genetics       Date:  2001-05       Impact factor: 4.562

6.  Mapping unexplored genomes: a genetic linkage map of the Hawaiian cricket Laupala.

Authors:  Y M Parsons; K L Shaw
Journal:  Genetics       Date:  2002-11       Impact factor: 4.562

7.  Mapping quantitative trait loci in F2 incorporating phenotypes of F3 progeny.

Authors:  Yuan-Ming Zhang; Shizhong Xu
Journal:  Genetics       Date:  2004-04       Impact factor: 4.562

8.  A unified Markov chain Monte Carlo framework for mapping multiple quantitative trait loci.

Authors:  Nengjun Yi
Journal:  Genetics       Date:  2004-06       Impact factor: 4.562

9.  Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences.

Authors:  P K Sabadin; M Malosetti; M P Boer; F D Tardin; F G Santos; C T Guimarães; R L Gomide; C L T Andrade; P E P Albuquerque; F F Caniato; M Mollinari; G R A Margarido; B F Oliveira; R E Schaffert; A A F Garcia; F A van Eeuwijk; J V Magalhaes
Journal:  Theor Appl Genet       Date:  2012-05       Impact factor: 5.699

10.  Toward a better understanding of the genomic region harboring Fusarium head blight resistance QTL Qfhs.ndsu-3AS in durum wheat.

Authors:  Xianwen Zhu; Shaobin Zhong; Shiaoman Chao; Yong Qiang Gu; Shahryar F Kianian; Elias Elias; Xiwen Cai
Journal:  Theor Appl Genet       Date:  2015-09-18       Impact factor: 5.699

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.