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Mixed model approach for IBD-based QTL mapping in a complex oil palm pedigree

Overview of attention for article published in BMC Genomics, October 2015
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Title
Mixed model approach for IBD-based QTL mapping in a complex oil palm pedigree
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-1985-3
Pubmed ID
Authors

Sébastien Tisné, Marie Denis, David Cros, Virginie Pomiès, Virginie Riou, Indra Syahputra, Alphonse Omoré, Tristan Durand-Gasselin, Jean-Marc Bouvet, Benoît Cochard

Abstract

Elaeis guineensis is the world's leading source of vegetable oil, and the demand is still increasing. Oil palm breeding would benefit from marker-assisted selection but genetic studies are scarce and inconclusive. This study aims to identify genetic bases of oil palm production using a pedigree-based approach that is innovative in plant genetics. A quantitative trait locus (QTL) mapping approach involving two-step variance component analysis was employed using phenotypic data on 30852 palms from crosses between more than 300 genotyped parents of two heterotic groups. Genome scans were performed at parental level by modeling QTL effects as random terms in linear mixed models with identity-by-descent (IBD) kinship matrices. Eighteen QTL regions controlling production traits were identified among a large genetically diversified sample from breeding program. QTL patterns depended on the genetic origin, with only one region shared between heterotic groups. Contrasting effects of QTLs on bunch number and weights reflected the close negative correlation between the two traits. The pedigree-based approach using data from ongoing breeding programs is a powerful, relevant and economic approach to map QTLs. Genetic determinisms contributing to heterotic effects have been identified and provide valuable information for orienting oil palm breeding strategies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 2%
United Kingdom 1 2%
France 1 2%
Unknown 58 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 36%
Student > Ph. D. Student 10 16%
Student > Master 6 10%
Student > Doctoral Student 5 8%
Other 4 7%
Other 7 11%
Unknown 7 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 69%
Biochemistry, Genetics and Molecular Biology 5 8%
Medicine and Dentistry 3 5%
Psychology 2 3%
Mathematics 1 2%
Other 2 3%
Unknown 6 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 October 2015.
All research outputs
#17,775,656
of 22,830,751 outputs
Outputs from BMC Genomics
#7,569
of 10,655 outputs
Outputs of similar age
#188,047
of 279,238 outputs
Outputs of similar age from BMC Genomics
#297
of 373 outputs
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