Major gene detection for fusiform rust resistance using segregation analysis and linkage analysis in loblolly pine
Abstract (Summary)
Li, Hua. Major gene detection for fusiform rust resistance using segregation analysis and
linkage analysis in loblolly pine. (Under the direction of Dr. Bailian Li and Dr. Henry
Amerson)
Fusiform rust, a disease caused by Cronartium quercuum f.sp. fusiforme , is the most
economically important disease for loblolly pine (Pinus taeda L.) in the southern U.S.
Identification and breeding of loblolly pines that are genetically resistant to fusiform rust
are important for successful establishment of commercial plantations. This research
developed a new analytical approach to detect major genes for rust resistance using
complex segregation analysis in a diallel progeny population. Molecular markers were
examined for association with the potential rust resistance genes.
Loblolly pines from a six-parent half-diallel mating were planted in a randomized
complete block field design at four test sites. Rust infection (gall presence / absence) was
recorded annually through age 8. Time trends and genetic differences for rust infection
were analyzed based on a polygenic model using a Bayesian logistic approach. For
genetic control of rust infection among families, the parental general combining ability
(GCA) due to additive effect was much more important than specific combining ability
(SCA) due to none-additive effect in full-sib combinations. Large genetic differences
among parents and full-sib families were found for rust infection. Among six parents,
parent A showed consistent low infection rates over time and across four sites, which
indicated high genetic resistance to fusiform rust due to strong polygenic effects and / or
major gene effects.
A Bayesian analysis of a threshold model was developed and used to make inference
about a mixed inheritance model (MIM) that included both polygenic effects and major
gene effects. The MIM was compared with a pure polygenic model. Marginalizations
were achieved by means of Gibbs sampler. A parent block sampling has been
implemented to improve mixing. Results showed that the MIM was a better model to
explain the inheritance of rust-resistance than the pure polygenic model in the diallel
population. A large major gene variance component (around 40-50%) indicated the
existence of major genes for rust resistance. The major genes would be most likely
associated with parent A because it was estimated to have the highest probability carrying
two resistance alleles and predicted to have the highest GCA effect for rust resistance
among the six parents.
Bulk segregate analyses and marker / trait co-segregation analyses were used to search
for major resistance genes. When the progeny of parent A × F showed an intermediate
rust infection level with single spore inoculum, additional RAPD markers were found to
be linked with the Fr2 locus in parent A. An improved map (framework linkage map ) of
the Fr2 linkage group was developed. An effort to define another resistance locus in
parent A, using progeny of cross A by F inoculated with an intermediate spore density,
with mixed gall inoculum was not successful. This may be due to the complexity of
suspected multiple gene interaction effects in parent A and unknown pathogen virulence
composition. Two mixed inocula with extremely high spore density were used to
inoculate the diallel progeny population of 12 crosses. Progeny from the cross of parent E
by A showed 75% rust infection. The interaction of two pairs of complementary genes
was proposed to explain the observed 75% infection based on a gene-for-gene
hypothesis. This two-gene model was not confirmed with molecular markers used in this
study. Nevertheless, results of this study provided strong statistical and more molecular
evidence to support that the parent A is carrying multiple rust resistance genes.
Bibliographical Information:
Advisor:
School:North Carolina State University
School Location:USA - North Carolina
Source Type:Master's Thesis
Keywords:north carolina state university
ISBN:
Date of Publication: