| Precision and high-resolution mapping of quantitative trait loci by use of recurrent selection, backcross or intercross schemes. | |
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MedLine Citation:
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PMID: 12072485 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Dissecting quantitative genetic variation into genes at the molecular level has been recognized as the greatest challenge facing geneticists in the twenty-first century. Tremendous efforts in the last two decades were invested to map a wide spectrum of quantitative genetic variation in nearly all important organisms onto their genome regions that may contain genes underlying the variation, but the candidate regions predicted so far are too coarse for accurate gene targeting. In this article, the recurrent selection and backcross (RSB) schemes were investigated theoretically and by simulation for their potential in mapping quantitative trait loci (QTL). In the RSB schemes, selection plays the role of maintaining the recipient genome in the vicinity of the QTL, which, at the same time, are rapidly narrowed down over multiple generations of backcrossing. With a high-density linkage map of DNA polymorphisms, the RSB approach has the potential of dissecting the complex genetic architecture of quantitative traits and enabling the underlying QTL to be mapped with the precision and resolution needed for their map-based cloning to be attempted. The factors affecting efficiency of the mapping method were investigated, suggesting guidelines under which experimental designs of the RSB schemes can be optimized. Comparison was made between the RSB schemes and the two popular QTL mapping methods, interval mapping and composite interval mapping, and showed that the scenario of genomic distribution of QTL that was unlocked by the RSB-based mapping method is qualitatively distinguished from those unlocked by the interval mapping-based methods. |
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Authors:
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Z W Luo; Chung-I Wu; M J Kearsey |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S. |
Journal Detail:
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Title: Genetics Volume: 161 ISSN: 0016-6731 ISO Abbreviation: Genetics Publication Date: 2002 Jun |
Date Detail:
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Created Date: 2002-06-19 Completed Date: 2003-01-10 Revised Date: 2009-11-19 |
Medline Journal Info:
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Nlm Unique ID: 0374636 Medline TA: Genetics Country: United States |
Other Details:
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Languages: eng Pagination: 915-29 Citation Subset: IM |
Affiliation:
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School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, England. z.luo@bham.ac.uk |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Animals Chromosome Mapping / methods* Computer Simulation Crosses, Genetic Data Interpretation, Statistical Genetic Variation Humans Inbreeding Models, Genetic Quantitative Trait Loci* Reproducibility of Results Selection, Genetic |
| Comments/Corrections | |
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