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

Influence of hunting strategy on foraging efficiency in Galapagos sea lions

The endangered Galapagos sea lion (GSL, Zalophus wollebaeki) exhibits a range of foraging strategies utilising various dive types including benthic, epipelagic and mesopelagic dives. In the present study, potential prey captures (PPC), prey energy consumption and energy expenditure in lactating adult female GSLs (n = 9) were examined to determine their foraging efficiency relative to the foraging strategy used. Individuals displayed four dive types: (a) epipelagic (<100 m; EP); or (b) mesopelagic (>100 m; MP) with a characteristic V-shape or U-shape diving profile; and (c) shallow benthic (<100 m; SB) or (d) deep benthic (>100 m; DB) with square or flat-bottom dive profiles. These dive types varied in the number of PPC, assumed prey types, and the energy expended. Prey items and their energetic value were assumed from previous GSL diet studies in combination with common habitat and depth ranges of the prey. In comparison to pelagic dives occurring at similar depths, when diving benthically, GSLs had both higher prey energy consumption and foraging energy expenditure whereas PPC rate was lower. Foraging efficiency varied across dive types, with benthic dives being more profitable than pelagic dives. Three foraging trip strategies were identified and varied relative to prey energy consumed, energy expended, and dive behaviour. Foraging efficiency did not significantly vary among the foraging trip strategies suggesting that, while individuals may diverge into different foraging habitats, they are optimal within them. These findings indicate that these three strategies will have different sensitivities to habitat-specific fluctuations due to environmental change

Gene expression changes in phosphorus deficient potato (Solanum tuberosum L.) leaves and the potential for diagnostic gene expression markers

Background: There are compelling economic and environmental reasons to reduce our reliance on inorganic phosphate (Pi) fertilisers. Better management of Pi fertiliser applications is one option to improve the efficiency of Pi fertiliser use, whilst maintaining crop yields. Application rates of Pi fertilisers are traditionally determined from analyses of soil or plant tissues. Alternatively, diagnostic genes with altered expression under Pi limiting conditions that suggest a physiological requirement for Pi fertilisation, could be used to manage Pifertiliser applications, and might be more precise than indirect measurements of soil or tissue samples. Results: We grew potato (Solanum tuberosum L.) plants hydroponically, under glasshouse conditions, to control their nutrient status accurately. Samples of total leaf RNA taken periodically after Pi was removed from the nutrient solution were labelled and hybridised to potato oligonucleotide arrays. A total of 1,659 genes were significantly differentially expressed following Pi withdrawal. These included genes that encode proteins involved in lipid, protein, and carbohydrate metabolism, characteristic of Pi deficient leaves and included potential novel roles for genes encoding patatin like proteins in potatoes. The array data were analysed using a support vector machine algorithm to identify groups of genes that could predict the Pi status of the crop. These groups of diagnostic genes were tested using field grown potatoes that had either been fertilised or unfertilised. A group of 200 genes could correctly predict the Pi status of field grown potatoes. Conclusions: This paper provides a proof-of-concept demonstration for using microarrays and class prediction tools to predict the Pi status of a field grown potato crop. There is potential to develop this technology for other biotic and abiotic stresses in field grown crops. Ultimately, a better understanding of crop stresses may improve our management of the crop, improving the sustainability of agriculture