Evaluation of algorithms used to order markers on genetic maps

Abstract

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F 2 populations were randomly simulated with 100 and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results.

High-Resolution Genetic Map and QTL Analysis of Growth-Related Traits of Hevea brasiliensis Cultivated Under Suboptimal Temperature and Humidity Conditions

“…The best position for each marker was identified using the TRY and RIPPLE algorithms. All of the analyses were performed using OneMap software v2.1.1 (Margarido et al, 2007; Mollinari et al, 2009). The Kosambi mapping function was used (Kosambi, 1943) to estimate map distances.…”

Characterizing Uncertainty in High-Density Maps from Multiparental Populations

“…This has not been explored even in biparental populations, as previous attempts to characterize this relationship have been based on simulation studies Mollinari et al 2009) rather than on an analytical approach. We focus on multiparental populations as they offer great promise for high-density mapping and as such uncertainty measures are crucial.…”

“…While many algorithms determine marker order, minimizing SARF has been shown to perform well as a heuristic (Olson and Boehnke 1990;Wu et al 2003;Mollinari et al 2009). Since many methods have similar performance, we do not expect the probability derived for SARF to vary greatly if an alternative is used for map construction.…”

Construction of Genetic Linkage Maps of Larch (Larix Kaempferi×Larix Gmelini) by Rapd Markers and Mapping of QTLS for Larch

“…We distinguished the RAPD markers that were in 1:1 segregation ratio to be used for mapping according to χ 2 test [χ 2 0.05 (1) =3.84]. We used JoinMap 3.0 (29), which is widely used for map construction (25), mapping function (23) for constructing genetic linkage maps, and Mapchart 2.2 (31) for drawing the linkage maps. the actual length of the genetic map was the length of the frame diagram, which was the length of linkage group (more than 3 markers); the total length of the linkage group was sum of linkage group, triplets, and linkage pairs.…”