Detection of favorable alleles for plant height and crown rust tolerance in three connected populations of perennial ryegrass (Lolium perenne L.)

Abstract

Plant height, which is an estimator of vegetative yield, and crown rust tolerance are major criteria for perennial ryegrass breeding. Genetic improvement has been achieved through phenotypic selection but it should be speeded up using marker-assisted selection, especially in this heterozygous species suffering from inbreeding depression. Using connected multiparental populations should increase the diversity studied and could substantially increase the power of quantitative trait loci (QTL) detection. The objective of this study was to detect the best alleles for plant height and rust tolerance among three connected populations derived from elite material by comparing an analysis per parent and a multipopulation connected analysis. For the studied traits, 17 QTL were detected with the analysis per parent while the additive and dominance models of the multipopulation connected analysis made it possible to detect 33 and 21 QTL, respectively. Favorable alleles have been detected in all parents. Only a few dominance effects were detected and they generally had lower values than the additive effects. The additive model of the multipopulation connected analysis was the most powerful as it made it possible to detect most of the QTL identified in the other analyses and 11 additional QTL. Using this model, plant growth QTL and rust tolerance QTL explained up to 19 and 38.6% of phenotypic variance, respectively. This example involving three connected populations is promising for an application on polycross progenies, traditionally used in breeding programs. Indeed, polycross progenies actually are a set of several connected populations.

Quantitative Trait Loci (QTL) Identification in the Progeny of a Polycross

“…As expected in perennial ryegrass, we were able to build a genetic map with seven linkage groups, but the map was shorter than expected with only 491 cM, instead of between 700 and 800 cM [19,[22][23][24][25]. The belonging of markers to LG was in agreement with previous studies [22,[26][27][28].…”

“…These regions have already been identified as QTL involved in traits related to leaf growth, such as leaf length, leaf elongation rate, and plant height [22,24,[31][32][33][34][35]. In particular, the QTL on LG4 nearby LpSSR011 and G05_014 is located on the map of [22] nearby a QTL for leaf elongation rate, lamina length, and plant height.…”

“…Moreover, the LD in the progeny allows the genome to be covered with a moderate number of markers. Connected populations have been used successfully for the detection of QTL in inbreeding [24,37] and outbreeding species [38], but it is the first time the progeny of a polycross has been used. …”

“…Six measurements of PH in April were used to estimate PGR ( Figure 2). After the defoliation of all plants on 24 March, PH increased linearly up to a maximum reached after three to six weeks, depending on the plant. This means that at this date (24 March) all plants had re-started their growth after winter.…”

Comparison of three QTL detection models on biochemical, sensory, and yield characters in Coffea canephora

“…The alleles of different parents can be compared within a single model using MCQTL software (Jourjon et al 2005). Studies on maize (Blanc et al 2006;Blanc et al 2007) and on ryegrass (Pauly et al 2012) reported a higher number of QTLs detected with this connected model than in single-population analyses. The multi-parent approach also made QTL positioning more precise for flowering time QTLs in three connected populations of Medicago truncatula (Pierre et al 2008).…”