A study of gene expression changes at the Bp-2 locus associated with bitter pit symptom expression in apples (Malus pumila)

Bitter pit is a physiological disorder of apples that develops in the latter stages of fruit development and during storage. It is characterized by localized necrotic cells that collapse and form pits in the epidermis and outer cortex of fruit. The disorder has been associated with low calcium concentrations, and poor calcium distribution within fruit. The mechanism that leads to individual cell necrosis, while surrounding cells remain healthy, is not fully understood. In order to ascertain the underlying process of bitter pit incidence in apple fruit, a mapping population of ‘Braeburn’ (susceptible to bitter pit) × ‘Cameo’ (resistant to bitter pit) was used to map the trait over two growing seasons. A subset of 96 genotypes from the mapping population representing the full range of phenotypes in the same ratio as the full population were selected for genotyping and functional characterization. RNA-Seq analysis on fruits samples of three resistant and three susceptible lines at seven developmental stages (21, 42, 63, 84, 105, 126 and 147 days post fertilization) identified a number of candidate genes displaying differential gene expression. A subset of candidate genes selected based on their position within the identified QTL interval on chromosome 16 validated by RT-qPCR, and two candidate genes displaying differential gene expression were highlighted as strong candidates for the control of bitter pit symptom expression at the Bp-2 locus

Identification and validation of a QTL influencing bitter pit symptoms in apple (Malus x domestica)

Bitter pit is one of the most economically important physiological disorders affecting apple fruit production, causing soft discrete pitting of the cortical flesh of the apple fruits which renders them unmarketable. The disorder is heritable; however, the environment and cultural practices play a major role in expression of symptoms. Bitter pit has been shown to be controllable to a certain extent using calcium sprays and dips; however, their use does not entirely prevent the incidence of the disorder. Previously, bitter pit has been shown to be controlled by two dominant genes, and markers on linkage group 16 of the apple genome were identified that were significantly associated with the expression of bitter pit symptoms in a genome-wide association study. In this investigation, we identified a major QTL for bitter pit defined by two microsatellite (SSR) markers. The association of the SSRs with the bitter pit locus, and their ability to predict severe symptom expression, was confirmed through screening of individuals with stable phenotypic expression from an additional mapping progeny. The data generated in this current study suggest a two gene model could account for the control of bitter pit symptom expression; however, only one of the loci was detectable, most likely due to dominance of alleles carried by both parents of the mapping progeny used. The SSR markers identified are cost-effective, robust and multi-allelic and thus should prove useful for the identification of seedlings with resistance to bitter pit using marker-assisted selection in apple breeding programs

Woody lianas increase in dominance and maintain compositional integrity across an Amazonian dam-induced fragmented landscape

Tropical forest fragmentation creates insular biological communities that undergo species loss and changes in community composition over time, due to area- and edge-effects. Woody lianas thrive in degraded and secondary forests, due to their competitive advantage over trees in these habitats. Lianas compete both directly and indirectly with trees, increasing tree mortality and turnover. Despite our growing understanding of liana-tree dynamics, we lack detailed knowledge of the assemblage-level responses of lianas themselves to fragmentation, particularly in evergreen tropical forests. We examine the responses of both sapling and mature liana communities to landscape-scale forest insularization induced by a mega hydroelectric dam in the Brazilian Amazon. Detailed field inventories were conducted on islands created during reservoir filling, and in nearby mainland continuous forest. We assess the relative importance of variables associated with habitat fragmentation such as area, isolation, surrounding forest cover, fire and wind disturbance, on liana community attributes including abundance, basal area, diversity, and composition. We also explore patterns of liana dominance relative to tree saplings and adults ≥10 cm diameter at breast height. We find that 1) liana community composition remains remarkably similar across mainland continuous forest and islands, regardless of extreme area- and edge- effects and the loss of vertebrate dispersers in the latter; and 2) lianas are increasing in dominance relative to trees in the sapling layer in the most degraded islands, with both the amount of forest cover surrounding islands and fire disturbance history predicting liana dominance. Our data suggest that liana communities persist intact in isolated forests, regardless of extreme area- and edge-effects; while in contrast, tree communities simultaneously show evidence of increased turnover and supressed recruitment. These processes may lead to lianas becoming a dominant component of this dam-induced fragmented landscape in the future, due to their competitive advantage over trees in degraded forest habitats. Additional loss of tree biomass and diversity brought about through competition with lianas, and the concurrent loss of carbon storage, should be accounted for in impact assessments of future dam development

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject