Alain Charcosset

Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize

Quantitative trait loci (QTL) detection experiments have often been restricted to large biallelic populations. Use of connected multiparental crosses has been proposed to increase the genetic variability addressed and to test for epistatic interactions between QTL and the genetic background. We present here the results of a QTL detection performed on six connected F2 populations of 150 F2:3 families each, derived from four maize inbreds and evaluated for three traits of agronomic interest. The QTL detection was carried out by composite interval mapping on each population separately, then on the global design either by taking into account the connections between populations or not. Epistatic interactions between loci and with the genetic background were tested. Taking into account the connections between populations increased the number of QTL detected and the accuracy of QTL position estimates. We detected many epistatic interactions, particularly for grain yield QTL (R2 increase of 9.6%). Use of connections for the QTL detection also allowed a global ranking of alleles at each QTL. Allelic relationships and epistasis both contribute to the lack of consistency for QTL positions observed among populations, in addition to the limited power of the tests. The potential benefit of assembling favorable alleles by marker-assisted selection are discussed.

MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments

BackgroundIntegration of multiple results from Quantitative Trait Loci (QTL) studies is a key point to understand the genetic determinism of complex traits. Up to now many efforts have been made by public database developers to facilitate the storage, compilation and visualization of multiple QTL mapping experiment results. However, studying the congruency between these results still remains a complex task. Presently, the few computational and statistical frameworks to do so are mainly based on empirical methods (e.g. consensus genetic maps are generally built by iterative projection).ResultsIn this article, we present a new computational and statistical package, called MetaQTL, for carrying out whole-genome meta-analysis of QTL mapping experiments. Contrary to existing methods, MetaQTL offers a complete statistical process to establish a consensus model for both the marker and the QTL positions on the whole genome. First, MetaQTL implements a new statistical approach to merge multiple distinct genetic maps into a single consensus map which is optimal in terms of weighted least squares and can be used to investigate recombination rate heterogeneity between studies. Secondly, assuming that QTL can be projected on the consensus map, MetaQTL offers a new clustering approach based on a Gaussian mixture model to decide how many QTL underly the distribution of the observed QTL.ConclusionWe demonstrate using simulations that the usual model choice criteria from mixture model literature perform relatively well in this context. As expected, simulations also show that this new clustering algorithm leads to a reduction in the length of the confidence interval of QTL location provided that across studies there are enough observed QTL for each underlying true QTL location. The usefulness of our approach is illustrated on published QTL detection results of flowering time in maize. Finally, MetaQTL is freely available at http://bioinformatics.org/mqtl.

Experimental evaluation of several cycles of marker-assisted selection in maize

A program was initiated in 1994 to compare the efficiency of marker-assisted selection (MAS) and conventional phenotypic selection. A population of 300 F3:4 families was generated from the cross between two maize inbred lines F2 and F252 and selected on an index combining grain yield and grain moisture at harvest. This population was characterised for 93 RFLP markers and evaluated as testcrosses in a large range of environments. Three methods of selection were applied (i) two cycles of conventional phenotypic selection; (ii) two cycles of MAS based on an index combining phenotypic values and QTL genetic values and (iii) one cycle of combined MAS followed by two cycles of selection based only on the QTL effects estimated in the first generation. The different populations were characterised for RFLP markers. The evolution of allele frequencies showed that selection on only-markers was very efficient for fixing QTL alleles found favourable in the initial population. This evolution was quite different from that observed for phenotypic selection or combined MAS. Genetic gain was evaluated and found significant for each method of selection. Nevertheless, the difference between phenotypic selection and combined MAS was not significant. The two additional cycles of MAS on only-markers did not improve significantly the genetic value of the population. Moreover, the genetic variance of this population remained high, despite most of the QTL initially detected were almost fixed. The results suggest that the QTL effects estimated in the initial population were not stable due to epistasis and/or QTL by environment interactions.

Use of molecular markers for the development of new cultivars and the evaluation of genetic diversity

Molecular markers bring new information on the determinism of trait variation and the organisation of genetic diversity within plant species of agricultural interest. We review here how this information can be used to increase the efficiency of plant breeding programs, considering both theoretical analyses and recent experimental data. Use of mapping information to assemble alleles of interest is discussed first, considering an increasing complexity in trait determinism and its consequences on the breeding schemes. Experimental data now confirm the efficiency of these approaches. They call however, for (i) a better modelling of phenotype determinism, to better anticipate the final effect of marker assisted selection and (ii) studies that would address trait variation determinism within a broad diversity, to increase the probability to identify alleles of key interest and identify stable marker-trait associations. Recent promising developments in genetic diversity analysis are discussed with respect to these last objectives.

Meta-analysis of QTL involved in silage quality of maize and comparison with the position of candidate genes.

A meta-analysis of quantitative trait loci (QTL) associated with plant digestibility and cell wall composition in maize was carried out using results from 11 different mapping experiments. Statistical methods implemented in “MetaQTL” software were used to build a consensus map, project QTL positions and perform meta-analysis. Fifty-nine QTL for traits associated with digestibility and 150 QTL for traits associated with cell wall composition were included in the analysis. We identified 26 and 42 metaQTL for digestibility and cell wall composition traits, respectively. Fifteen metaQTL with confidence interval (CI) smaller than 10xa0cM were identified. As expected from trait correlations, 42% of metaQTL for digestibility displayed overlapping CIs with metaQTL for cell wall composition traits. Coincidences were particularly strong on chromosomes 1 and 3. In a second step, 356 genes selected from the MAIZEWALL database as candidates for the cell wall biosynthesis pathway were positioned on our consensus map. Colocalizations between candidate genes and metaQTL positions appeared globally significant based on χ2 tests. This study contributed in identifying key chromosomal regions involved in silage quality and potentially associated genes for most of these regions. These genes deserve further investigation, in particular through association mapping.

Detection of marker-QTL associations by studying change in marker frequencies with selection

The value of selective genotyping for the detection of QTL has already been studied from a theoretical point of view but with the assumption of a negligible contribution

Out of America: tracing the genetic footprints of the global diffusion of maize

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Overview of QTL detection in plants and tests for synergistic epistatic interactions

of the QTL to the phenotypic variance. For predicting change in gene frequency, we show that this assumption is only valid for