Linkage analysis of molecular markers and quantitative trait loci in populations of inbred backcross lines of Brassica napus L

Genetics. 1999 Oct;153(2):949-64. doi: 10.1093/genetics/153.2.949.

Abstract

Backcross populations are often used to study quantitative trait loci (QTL) after they are initially discovered in balanced populations, such as F(2), BC(1), or recombinant inbreds. While the latter are more powerful for mapping marker loci, the former have the reduced background genetic variation necessary for more precise estimation of QTL effects. Many populations of inbred backcross lines (IBLs) have been developed in plant and animal systems to permit simultaneous study and dissection of quantitative genetic variation introgressed from one source to another. Such populations have a genetic structure that can be used for linkage estimation and discovery of QTL. In this study, four populations of IBLs of oilseed Brassica napus were developed and analyzed to map genomic regions from the donor parent (a winter-type cultivar) that affect agronomic traits in spring-type inbreds and hybrids. Restriction fragment length polymorphisms (RFLPs) identified among the IBLs were used to calculate two-point recombination fractions and LOD scores through grid searches. This information allowed the enrichment of a composite genetic map of B. napus with 72 new RFLP loci. The selfed and hybrid progenies of the IBLs were evaluated during two growing seasons for several agronomic traits. Both pedigree structure and map information were incorporated into the QTL analysis by using a regression approach. The number of QTL detected for each trait and the number of effective factors calculated by using biometrical methods were of similar magnitude. Populations of IBLs were shown to be valuable for both marker mapping and QTL analysis.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Brassica / genetics*
  • Chromosome Mapping*
  • Crosses, Genetic
  • Genetic Markers
  • Models, Genetic
  • Models, Statistical
  • Quantitative Trait, Heritable*
  • Recombination, Genetic*

Substances

  • Genetic Markers