Ordering dominant markers in F2 populations

Abstract

Ordering dominant markers in F 2 populations is considered a difficult problem. The difficulties arise from the fact that recombinations cannot be observed directly from the data. In general, the multi-point maximum likelihood would be the appropriate criterion for ordering markers. This criterion takes into account all available information present in marker data. However, calculation of multi-point maximum likelihoods is very timedemanding, especially if the number of markers is large. In this paper, ordering markers by minimising the number of recombinations between adjacent markers is used as a simple alternative to multi-point maximum likelihood. Contrary to multi-point maximum likelihood, this method does not involve any probability assumptions about the occurrence of recombination events. Simulated data indicate that the minimum number of recombinations between adjacent markers is approximately a linear function of the map length obtained by multi-point maximum likelihood. As a consequence, it will lead to more or less the same optimum marker orders. Optimisation of marker orders with regard to the number of recombinations between adjacent markers is carried out by a modified form of simulated annealing. The reliability of the resulting marker orders is studied by generating marker orders that are plausible with the data using a Metropolis algorithm.

Linkage analysis between dominant and co-dominant makers in full-sib families of out-breeding species

“…Nowadays, this problem is receiving additional attention, as high-throughput genomic tools, such as the DNA microarray platform, have lead to the development of up-to-date genotyping procedures resulting in new dominant markers. Novel methods for mapping such markers circumventing this issue have been described ( Tan and Fu, 2007 ; Jansen, 2009 ). Nevertheless, in full-sib families of out-breeding species, dominant markers appear to be unimpeachable, if used together with co-dominant markers.…”

“…The first maximum likelihood estimators of recombination frequency for a variety of genetic situations in BC 1 and F 2 populations were developed in the early 1950's. For F 2 with dominant markers, Tan and Fu (2007) recently improved two-point estimates by taking averages from three-point maximum likelihood estimates, whereas Jansen (2009) developed another method for ordering dominant markers by minimizing the number of recombinations between adjacent markers, as a simple alternative to multi-point maximum likelihood. Three-point estimates of recombination frequencies were previously used by Ridout et al (1998) for out-breeding species.…”

Quantitative trait locus (QTL) analysis and fine-mapping for <i>Fusarium oxysporum</i> disease resistance in <i>Raphanus sativus</i> using GRAS-Di technology

“…Although the co-dominant derived map has sufficient marker density for QTL analysis, to construct a map with higher density of markers, we attempted to use the information of dominant markers together with the co-dominant markers. Since combining RK15-1 (female)-and AKM (male)-derived markers into one map resulted in distorted marker order, such as large gaps and incorrect assignment of markers, possibly due to limitations of the mapping algorithm (Jansen 2009, Knapp et al 1995, Tan and Fu 2007, Tan et al 2017, the segregation data of RK15-1-and AKM-derived markers were separately combined with that of co-dominant markers. After the reduction of the numbers of the dominant markers that were mapped at the same position, the resulting RK15-1-and AKM-derived maps spanned 988.6 and 1127.5 cM, with average marker densities of 1.40 and 1.53 cM, respectively (Table 1, Supplemental Fig.…”

“…Thus, use of dominant markers to map construction is important for GRAS-Di technology. However, it is reported that estimating recombination frequencies between dominant markers is least efficient in F 2 progeny, particularly in repulsion dominant markers (Jansen 2009, Knapp et al 1995, Tan and Fu 2007, Tan et al 2017. To overcome this challenge, Miki et al (2020) and Fekih et al (2023) mapped the GRAS-Di amplicon sequences to the reference genome sequence to revise irregular marker orders, and thereafter, the recombination frequencies of the dominant markers were estimated by R/qtl software.…”