@article{
 title = {A model for quantitative trait loci mapping, linkage phase, and segregation pattern estimation for a full-sib progeny},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {Composite interval mapping,Full-sib progeny,Genetic architecture,Mixture models,Outbred species},
 pages = {791-801},
 volume = {10},
 id = {5ceef82b-f33c-3e78-adeb-46aec883410a},
 created = {2015-11-22T13:21:23.000Z},
 file_attached = {false},
 profile_id = {e36cbae0-8a6b-3799-b43a-920a55c297dc},
 last_modified = {2015-11-22T13:21:23.000Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 abstract = {Quantitative trait loci (QTL) mapping is an important approach for the study of the genetic architecture of quantitative traits. For perennial species, inbred lines cannot be obtained due to inbreed depression and a long juvenile period. Instead, linkage mapping can be performed by using a full-sib progeny. This creates a complex scenario because both markers and QTL alleles can have different segregation patterns as well as different linkage phases between them. We present a two-step method for QTL mapping using full-sib progeny based on composite interval mapping (i.e., interval mapping with cofactors), considering an integrated genetic map with markers with different segregation patterns and conditional probabilities obtained by a multipoint approach. The model is based on three orthogonal contrasts to estimate the additive effect (one in each parent) and dominance effect. These estimatives are obtained using the EM algorithm. In the first step, the genome is scanned to detect QTL. After, segregation pattern and linkage phases between QTL and markers are estimated. A simulated example is presented to validate the methodology. In general, the new model is more effective than existing approaches, because it can reveal QTL present in a full-sib progeny that segregates in any pattern present and can also identify dominance effects. Also, the inclusion of cofactors provided more statistical power for QTL mapping. © 2014 The Author(s).},
 bibtype = {article},
 author = {Gazaffi, R. and Margarido, G.R.A. and Pastina, M.M. and Mollinari, M. and Garcia, A.A.F.},
 journal = {Tree Genetics and Genomes},
 number = {4}
}

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A simulated example is presented to validate the methodology. In general, the new model is more effective than existing approaches, because it can reveal QTL present in a full-sib progeny that segregates in any pattern present and can also identify dominance effects. 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