Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 407982
Title A comparison of population types used for QTL mapping in Arabidopsis thaliana
Author(s) Keurentjes, J.J.B.; Willems, W.; Eeuwijk, F.A. van; Nordborg, M.; Koornneef, M.
Source Plant genetic resources: characterization and utilization 9 (2011)2. - ISSN 1479-2621 - p. 185 - 188.
Department(s) Laboratory of Genetics
Biometris (WU MAT)
Publication type Refereed Article in a scientific journal
Publication year 2011
Keyword(s) quantitative trait loci - flowering-time - natural variation - line populations - inbred lines - resource - genetics - plants
Abstract In Arabidopsis, a variety of mapping populations have been used for the detection of quantitative trait loci (QTLs) responsible for natural variation. In this study, we presentan overview of the advantages and disadvantages of the different types of populations used. To do this, we compare the results of both experimental and natural populations for the commonly analysed trait flowering time. It is expected that genome wide association (GWA) mapping will be an increasingly important tool for QTL mapping because of the high allelic richness and mapping resolution in natural populations. In Arabidopsis, GWA mapping becomes ever more facilitated by the increasing availability of re-sequenced genomes of many accessions. However, specifically designed mapping populations such as recombinant inbred lines and near isogenic lines will remain important. The high QTL detection power of such experimental populations can identify spurious GWA associations, and their unique genomic structure is superior for investigating the role of low-frequency alleles. Future QTL studies will therefore benefit from a combined approach of GWA and classical linkage analysis.
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