ABSTRACT
Currently, developing genetic linkage map mostly use the derived-populations from crossing of two homogenous parents, which only covers limited genetic diversity and is inappropriate for some species, such as tobacco with lower diversity in genome. It is very general that there are no sufficient polymorphic markers to construct linkage map and ineffective to conduct marker-assisted selection (MAS) and quantitative trait locus (QTL) mapping based on lower density linkage map. This study proposed a method for developing genetic linkage map based on a four-way cross population. Computer simulation was conducted to investigate the feasibility and effectiveness of the method and a supporting program was designed. The main procedures and features of the proposed method were summarized as follows: 1) estimating genetic distance of any paired markers based on maximum likelihood method; 2) splitting all markers into different groups (linkage group) by cluster analysis based on genetic distance of markers; 3) for each linkage group, two end markers were first determined, then the marker order could be determined by inserting other markers in appropriate position by distance analysis of any three neighboring markers. Monte Carlo simulation showed that the proposed method is feasible, effective, and applicable in other derived populations from crossing of two homogenous parents.
ABSTRACT
Most important agronomic and quality traits of crops are quantitative in nature. The genetic variations in such traits are usually controlled by sets of genes called quantitative trait loci (QTLs), and the interactions between QTLs and the environment. It is crucial to understand the genetic architecture of complex traits to design efficient strategies for plant breeding. In the present study, a new experimental design and the corresponding statistical method are presented for QTL mapping. The proposed mapping population is composed of double backcross populations derived from backcrossing both homozygous parents to DH (double haploid) or RI (recombinant inbreeding) lines separately. Such an immortal mapping population allows for across-environment replications, and can be used to estimate dominance effects, epistatic effects, and QTL-environment interactions, remedying the drawbacks of a single backcross population. In this method, the mixed linear model approach is used to estimate the positions of QTLs and their various effects including the QTL additive, dominance, and epistatic effects, and QTL-environment interaction effects (QE). Monte Carlo simulations were conducted to investigate the performance of the proposed method and to assess the accuracy and efficiency of its estimations. The results showed that the proposed method could estimate the positions and the genetic effects of QTLs with high efficiency.
