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Multipoint-likelihood maximization mapping on 4 segregating populations to achieve an integrated framework map for QTL analysis in pot azalea (Rhododendron simsii hybrids).

De Keyser E, Shu QY, Van Bockstaele E, De Riek J - BMC Mol. Biol. (2010)

Bottom Line: As a result, plants with attractive flowering are kept too long in the breeding cycle.This is the first map of azalea up to our knowledge.AFLP and SSR markers are used as a reference backbone and functional markers (EST and MYB) were added as candidate genes for QTL analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Agricultural and Fisheries Research (ILVO), Plant Sciences Unit, Caritasstraat 21, 9090 Melle, Belgium. ellen.dekeyser@ilvo.vlaanderen.be

ABSTRACT

Background: Azalea (Rhododendron simsii hybrids) is the most important flowering pot plant produced in Belgium, being exported world-wide. In the breeding program, flower color is the main feature for selection, only in later stages cultivation related plant quality traits are evaluated. As a result, plants with attractive flowering are kept too long in the breeding cycle. The inheritance of flower color has been well studied; information on the heritability of cultivation related quality traits is lacking. For this purpose, QTL mapping in diverse genetic backgrounds appeared to be a must and therefore 4 mapping populations were made and analyzed.

Results: An integrated framework map on four individual linkage maps in Rhododendron simsii hybrids was constructed. For genotyping, mainly dominant scored AFLP (on average 364 per population) and MYB-based markers (15) were combined with co-dominant SSR (23) and EST markers (12). Linkage groups were estimated in JoinMap. A consensus grouping for the 4 mapping populations was made and applied in each individual mapping population. Finally, 16 stable linkage groups were set for the 4 populations; the azalea chromosome number being 13. A combination of regression mapping (JoinMap) and multipoint-likelihood maximization (Carthagène) enabled the construction of 4 maps and their alignment. A large portion of loci (43%) was common to at least two populations and could therefore serve as bridging markers. The different steps taken for map optimization and integration into a reference framework map for QTL mapping are discussed.

Conclusions: This is the first map of azalea up to our knowledge. AFLP and SSR markers are used as a reference backbone and functional markers (EST and MYB) were added as candidate genes for QTL analysis. The alignment of the 4 maps on the basis of framework markers will facilitate in turn the alignment of QTL regions detected in each of the populations. The approach we took is thoroughly different than the recently published integrated maps and well-suited for mapping in a non-model crop.

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Mapping strategy. Example of the different maps that were constructed starting from 4 individual populations (illustrated with LG5 from population AxB). Per population, the most optimal map (Optimized map AxB LG5) and a framework map (Framework map AxB LG5) was constructed using Multipoint ML mapping (Carthagène). An integrated framework map, with a combination of all markers appearing in at least two populations and all markers that were part of the individual framework maps, was then optimized (Optimized integrated map LG5). A final map for each population was constructed with the integrated framework map as a grid (Final map AxB LG5). Carthagène [28] commands (preceded by a feather) are printed in between the maps Framework/bridging markers and their origin are marked in red.
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Figure 1: Mapping strategy. Example of the different maps that were constructed starting from 4 individual populations (illustrated with LG5 from population AxB). Per population, the most optimal map (Optimized map AxB LG5) and a framework map (Framework map AxB LG5) was constructed using Multipoint ML mapping (Carthagène). An integrated framework map, with a combination of all markers appearing in at least two populations and all markers that were part of the individual framework maps, was then optimized (Optimized integrated map LG5). A final map for each population was constructed with the integrated framework map as a grid (Final map AxB LG5). Carthagène [28] commands (preceded by a feather) are printed in between the maps Framework/bridging markers and their origin are marked in red.

Mentions: Carthagène [28] can handle outbred data as far as phases are fixed (either known or fixed to the most probable phases). Following the recommendations by the authors in the manual, we did not take the "two way pseudo-test cross" mapping approach [29] but applied the more complex hexadecimal encoding based on the Mapmaker syntax. Mapping in Carthagène for the individual mapping populations started for each linkage group from an initial map produced from the (random) marker order in the initial data set by the "sem" command. Map improving combined the commands "greedy" using a taboo search technique (greedy 1 0 1 15 0), and "flips" applying all possible permutations in a sliding window on the current best map (flips 5 5.0 1). The "polish" command, displacing each individual marker in all possible intervals, was finally used to check if the most optimized map had been reached. Framework mapping i.e. a map including only a restricted number of markers such that all alternative map orders have a log-likelihood not within a given threshold of the framework map, was made by "buildfw" (buildfw 2 2 {} 0); non-framework markers were then incorporated in the framework map (buildfw 0 0 {"specific framework map marker order"} 0). We refer to the Carthagène manual for extensive information on the parameters used [28]. A schematic representation of the mapping strategy that was followed is given in Figure 1.


Multipoint-likelihood maximization mapping on 4 segregating populations to achieve an integrated framework map for QTL analysis in pot azalea (Rhododendron simsii hybrids).

De Keyser E, Shu QY, Van Bockstaele E, De Riek J - BMC Mol. Biol. (2010)

Mapping strategy. Example of the different maps that were constructed starting from 4 individual populations (illustrated with LG5 from population AxB). Per population, the most optimal map (Optimized map AxB LG5) and a framework map (Framework map AxB LG5) was constructed using Multipoint ML mapping (Carthagène). An integrated framework map, with a combination of all markers appearing in at least two populations and all markers that were part of the individual framework maps, was then optimized (Optimized integrated map LG5). A final map for each population was constructed with the integrated framework map as a grid (Final map AxB LG5). Carthagène [28] commands (preceded by a feather) are printed in between the maps Framework/bridging markers and their origin are marked in red.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2837023&req=5

Figure 1: Mapping strategy. Example of the different maps that were constructed starting from 4 individual populations (illustrated with LG5 from population AxB). Per population, the most optimal map (Optimized map AxB LG5) and a framework map (Framework map AxB LG5) was constructed using Multipoint ML mapping (Carthagène). An integrated framework map, with a combination of all markers appearing in at least two populations and all markers that were part of the individual framework maps, was then optimized (Optimized integrated map LG5). A final map for each population was constructed with the integrated framework map as a grid (Final map AxB LG5). Carthagène [28] commands (preceded by a feather) are printed in between the maps Framework/bridging markers and their origin are marked in red.
Mentions: Carthagène [28] can handle outbred data as far as phases are fixed (either known or fixed to the most probable phases). Following the recommendations by the authors in the manual, we did not take the "two way pseudo-test cross" mapping approach [29] but applied the more complex hexadecimal encoding based on the Mapmaker syntax. Mapping in Carthagène for the individual mapping populations started for each linkage group from an initial map produced from the (random) marker order in the initial data set by the "sem" command. Map improving combined the commands "greedy" using a taboo search technique (greedy 1 0 1 15 0), and "flips" applying all possible permutations in a sliding window on the current best map (flips 5 5.0 1). The "polish" command, displacing each individual marker in all possible intervals, was finally used to check if the most optimized map had been reached. Framework mapping i.e. a map including only a restricted number of markers such that all alternative map orders have a log-likelihood not within a given threshold of the framework map, was made by "buildfw" (buildfw 2 2 {} 0); non-framework markers were then incorporated in the framework map (buildfw 0 0 {"specific framework map marker order"} 0). We refer to the Carthagène manual for extensive information on the parameters used [28]. A schematic representation of the mapping strategy that was followed is given in Figure 1.

Bottom Line: As a result, plants with attractive flowering are kept too long in the breeding cycle.This is the first map of azalea up to our knowledge.AFLP and SSR markers are used as a reference backbone and functional markers (EST and MYB) were added as candidate genes for QTL analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Agricultural and Fisheries Research (ILVO), Plant Sciences Unit, Caritasstraat 21, 9090 Melle, Belgium. ellen.dekeyser@ilvo.vlaanderen.be

ABSTRACT

Background: Azalea (Rhododendron simsii hybrids) is the most important flowering pot plant produced in Belgium, being exported world-wide. In the breeding program, flower color is the main feature for selection, only in later stages cultivation related plant quality traits are evaluated. As a result, plants with attractive flowering are kept too long in the breeding cycle. The inheritance of flower color has been well studied; information on the heritability of cultivation related quality traits is lacking. For this purpose, QTL mapping in diverse genetic backgrounds appeared to be a must and therefore 4 mapping populations were made and analyzed.

Results: An integrated framework map on four individual linkage maps in Rhododendron simsii hybrids was constructed. For genotyping, mainly dominant scored AFLP (on average 364 per population) and MYB-based markers (15) were combined with co-dominant SSR (23) and EST markers (12). Linkage groups were estimated in JoinMap. A consensus grouping for the 4 mapping populations was made and applied in each individual mapping population. Finally, 16 stable linkage groups were set for the 4 populations; the azalea chromosome number being 13. A combination of regression mapping (JoinMap) and multipoint-likelihood maximization (Carthagène) enabled the construction of 4 maps and their alignment. A large portion of loci (43%) was common to at least two populations and could therefore serve as bridging markers. The different steps taken for map optimization and integration into a reference framework map for QTL mapping are discussed.

Conclusions: This is the first map of azalea up to our knowledge. AFLP and SSR markers are used as a reference backbone and functional markers (EST and MYB) were added as candidate genes for QTL analysis. The alignment of the 4 maps on the basis of framework markers will facilitate in turn the alignment of QTL regions detected in each of the populations. The approach we took is thoroughly different than the recently published integrated maps and well-suited for mapping in a non-model crop.

Show MeSH
Related in: MedlinePlus