FROM PHENOTYPE VIA QTL TO VIRTUAL PHENOTYPE IN MICROSERIS (ASTERACEAE) - PREDICTIONS FROM MULTILOCUS MARKER GENOTYPES

Citation
K. Bachmann et Ej. Hombergen, FROM PHENOTYPE VIA QTL TO VIRTUAL PHENOTYPE IN MICROSERIS (ASTERACEAE) - PREDICTIONS FROM MULTILOCUS MARKER GENOTYPES, New phytologist, 137(1), 1997, pp. 9-18
Citations number
34
Categorie Soggetti
Plant Sciences
Journal title
ISSN journal
0028646X
Volume
137
Issue
1
Year of publication
1997
Pages
9 - 18
Database
ISI
SICI code
0028-646X(1997)137:1<9:FPVQTV>2.0.ZU;2-H
Abstract
Microseris douglasii (DC.) Sch.-Bip. and M. bigelovii (Gray) Sch.-Bip. are two small annual autogamous species of Compositae with nearly non -overlapping distribution ranges in Western North America. Specificall y, M. bigelovii occurs directly along the Pacific coast, whilst M. dou glasii has an inland distribution including patches of serpentine soil . Both species are variable, and artificial hybrids between them vary widely in fertility depending on the individual parents. Segregating o ffspring of one hybrid (strain H27) is being used to analyse the genet ic basis of characters differentiating the two species by QTL mapping with RAPDS and ALFPs as molecular markers. Technical problems with map ping dominant markers in a wide cross will be briefly listed and QTL a nalysis will be discussed. For the genetic analysis of physiological c haracters, the precise definition of the characters is crucial and the methods of scoring or measuring phenotypes in different environments eventually require more time and effort than the molecular characteriz ation. We are establishing recombinant inbred lines to provide materia l for more complex physiological analyses requiring several plants per genotype. An increasing number of characters is being studied in this cross, and the possibility of shared pleiotropic QTLs is high. The po tential number of QTL genotypes by far exceeds the number of actual ge notypes in these lines. We are characterizing the gene interactions as closely as possible and making quantitative genetic models to predict the genotypes corresponding to all possible genotypes. These predicti ons are converted via computer modelling into an increasingly realisti c three-dimensional representation of the growing plant useful for a s imulation of plant evolution.