ISI Web of Knowledge Take the next step  
Web of Science®
 
Previous Record (inactive) Record 1  of  1 Next Record (inactive)
Record from Web of Science®
HIGH-RESOLUTION OF QUANTITATIVE TRAITS INTO MULTIPLE LOCI VIA INTERVAL MAPPING
Author(s): JANSEN RC, STAM P
Source: GENETICS    Volume: 136    Issue: 4    Pages: 1447-1455    Published: APR 1994  
Times Cited: 439     References: 17     
Abstract: A very general method is described for multiple linear regression of a quantitative phenotype on genotype [putative quantitative trait loci (QTLs) and markers] in segregating generations obtained from line crosses. The method exploits two features, (a) the use of additional parental and F-1 data, which fixes the joint QTL effects and the environmental error, and (b) the use of markers as cofactors, which reduces the genetic background noise. As a result, a significant increase of QTL detection power is achieved in comparison with conventional QTL mapping. The core of the method is the completion of any missing genotypic (QTL and marker) observations, which is embedded in a general and simple expectation maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. The method is described in detail for the analysis of an F-2 generation. Because of the generality of the approach, it is easily applicable to other generations, such as backcross progenies and recombinant inbred lines. An example is presented in which multiple QTLs for plant height in tomato are mapped in an F-2 progeny, using additional data from the parents and their F-1 progeny.
Document Type: Article
Language: English
Reprint Address: JANSEN, RC (reprint author), CPRO, DLO, DEPT POPULAT BIOL, POB 16, 6700 AA WAGENINGEN, NETHERLANDS
Addresses:
1. AGR UNIV WAGENINGEN, DEPT GENET, 6703 AH WAGENINGEN, NETHERLANDS
Publisher: GENETICS, 428 EAST PRESTON ST, BALTIMORE, MD 21202
Subject Category: Genetics & Heredity
IDS Number: NB821
ISSN: 0016-6731
Previous Record (inactive) Record 1  of  1 Next Record (inactive)
Record from Web of Science®
  
Thomson Reuters Logo