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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Evaluation of algorithms used to order markers on genetic maps

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Author(s):
Mollinari, M. [1] ; Margarido, G. R. A. [1] ; Vencovsky, R. [1] ; Garcia, A. A. F. [1]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, Dept Genet, Escola Super Agr Luiz Queiroz, BR-13400970 Sao Paulo - Brazil
Total Affiliations: 1
Document type: Journal article
Source: HEREDITY; v. 103, n. 6, p. 494-502, DEC 2009.
Web of Science Citations: 21
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 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. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009 (AU)

FAPESP's process: 08/54402-4 - Development of a model to build genetic maps in autopolyploides, with applications in sugarcane
Grantee:Marcelo Mollinari
Support Opportunities: Scholarships in Brazil - Doctorate