Glycoprotein composition along the pistil of Malus x domestica and the modulation of pollen tube growth

Abstract

BackgroundThe characteristics of pollen tube growth are not constant, but display distinct patterns of growth within the different tissues of the pistil. In the stigma, the growth rate is slow and autotrophic, whereas in the style, it is rapid and heterotrophic. Very little is known about the interactions between these distinct maternal tissues and the traversing pollen tube and the role of this interaction on the observed metabolism. In this work we characterise pollen tube growth in the apple flower and look for differences in glycoprotein epitope localization between two different maternal tissues, the stigma and the style.ResultsWhile immunocytochemically-detected arabinogalactan proteins were present at high levels in the stigma, they were not detected in the transmitting tissue of the style, where extensins were abundant. Whereas extensins remained at high levels in unpollinated pistils, they were no longer present in the style following pollen tube passage. Similarily, while abundant in unpollinated styles, insoluble polysaccharides such as β-glucans, were depleted in pollinated pistils.ConclusionsThe switch from autotropic to heterotrophic pollen tube growth correlates spatially with a change of glycoprotein epitopes between the stigma and the style. The depletion of extensins and polysaccharides following pollen tube passage in the style suggest a possible contribution to the acceleration of heterotrophic pollen tube growth, which would imply an active contribution of female tissues on prezygotic male–female crosstalk.

Mosaics, mixtures, rotations or pyramiding: What is the optimal strategy to deploy major gene resistance?

“…Nevertheless, in the context of plant disease, different results may be expected owing to the spatial structuration of plant epidemics. In the plant pathology literature, some studies compared two categories of resistance deployment strategies (Djidjou‐Demasse, Moury, & Fabre, 2017; Kiyosawa, 1972; Koller et al., 2018; Sapoukhina, Durel, & Le Cam, 2009; Skelsey, Rossing, Kessel, & van der Werf, 2010), and very few have compared three categories of strategies (Djian‐Caporalino et al., 2014; Lof, de Vallavieille‐Pope, & van der Werf, 2017). Moreover, the durability of resistance and the epidemiological control it provides have rarely been considered jointly, although these are not necessarily correlated (van den Bosch & Gilligan, 2003; Burdon et al., 2014; Fabre, Rousseau, Mailleret, & Moury, 2015; Papaïx et al., 2018).…”

“…Our results are consistent with previous empirical and modelling studies suggesting that, in absence of preadapted pathogens, pyramids of resistance genes (or, similarly, combination of molecules in the context of pesticide applications) outcompete other deployment strategies with regard to durability (Djian‐Caporalino et al., 2014; REX Consortium 2013). In real‐world pathosystems, pyramids of resistance genes are expected to show good durability because of the low probability that the pathogen will simultaneously acquire all of the mutations required to overcome multiple major genes and the potential accumulation of fitness costs associated with these mutations (Leach et al., 2001).…”

“…It is interesting that these factors (pathogen mutation probability and fitness cost of adaptation) may be influenced by the choice of the resistance source, as suggested by empirical evidence that major resistance genes acting with distinct mechanisms are associated with different rates of pathogen adaptation (Djian‐Caporalino et al., 2014; Mundt, 2018). Based on our results, and not surprisingly, resistance genes associated with small rates of pathogen adaptation (requiring several and costly genetic mutations to be overcome) must be favoured for deployment in the field.…”

“…We are aware of only one empirical study designed to compare some of the main categories of deployment (Djian‐Caporalino et al., 2014). This study evaluated the ability of mixtures, rotations and pyramiding of two different resistance sources to control root‐knot nematode of pepper, in both controlled and field conditions.…”

Genetic control of juvenile growth and botanical architecture in an ornamental woody plant, Prunus mumeSieb. et Zucc. as revealed by a high-density linkage map

“…Since a more sophisticated model for linkage mapping has been developed [11-13,18], any type of markers segregating in a full-sib family can be analyzed by simultaneously estimating the linkage and linkage phases. This method was successfully used in poplar tree [14], sugarcane [19,20], a yellow passion fruit population [21], rubber tree [22] and peach [23]. …”