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Garin, V.

Publications and source records attributed to Garin, V..

2 recordsLinked to original sources

The influence of QTL allelic diversity on QTL detection in multi-parent populations: a simulation study in sugar beet

Multi-parent populations (MPPs) are important resources for studying plant genetic architecture and detecting quantitative trait loci (QTLs). In MPPs, the QTL effects can show various levels of allelic diversity, which is an important factor influencing the detection of QTLs. In MPPs, the allelic effects can be more or less specific. They can depend on an ancestor, a parent or the combination of parents in a cross. In this paper, we evaluated the effect of QTL allelic diversity on the QTL detection power in MPPs. We simulated: a) cross-specific QTLs; b) parental and ancestral QTLs; and c) bi-allelic QTLs. Inspired by a real application, we tested different MPP designs (diallel, chessboard, factorial, and NAM) derived from five or nine parents to explore the ability to sample genetic diversity and detect QTLs. Using a fixed total population size, the QTL detection power was larger in MPPs with fewer but larger crosses derived from a reduced number of parents. The use of a larger set of parents was useful to detect rare alleles with a large phenotypic effect. The benefit of using a larger set of parents was however conditioned on an increase of the total population size. We also determined empirical confidence intervals for QTL location to compare the resolution of different designs. For QTLs representing 6% of the phenotypic variation, using 1600 offspring individuals, we found 95% empirical confidence intervals of 50 and 26 cM for cross-specific and bi-allelic QTLs, respectively. MPPs derived from less parents with few but large crosses generally increased the QTL detection power. Using a larger set of parents to cover a wider genetic diversity can be useful to detect QTLs with a reduced minor allele frequency when the QTL effect is large and when the total population size is increased.

genetics

The usefulness of multi-parent multi-environment QTL analysis: an illustration in different NAM populations

Commonly QTL detection in multi-parent population (MPPs) data measured in multiple environments (ME) is done by a single environment analysis on phenotypic values averaged across environments. This method can be useful to detect QTLs with a consistent effect across environments but it does not allow to estimate environment-specific QTL (QTLxE) effects. Running separate single environment analyses is a possibility to measure QTLxE effects but those analyses do not model the genetic covariance due to the use of the same genotype in different environments. In this paper, we propose methods to analyze MPP-ME QTL experiments using simultaneously the data from several environments and modelling the genotypic covariances. Using data from the EU-NAM and the US-NAM populations, we show that these methods allow to estimate the QTLxE effects and that they give a more precise description of the trait genetic architecture than separate within environment analyses. The MPP-ME models we propose can also be extended to integrate environmental indices (e.g. temperature, precipitation, etc.) to understand better the mechanisms behind the QTLxE effects. Therefore, our methodology allows to exploit the full potential of MPP-ME data: to estimate QTL effect variations a) within the MPP between sub-populations due to different genetic backgrounds; and b) between environments.

genetics