An update on passive transport in and out of plant cells.

Transport across membranes is critical for plant survival. Membranes are the interfaces at which plants interact with their environment. The transmission of energy and molecules into cells provides plants with the source material and power to grow, develop, defend, and move. An appreciation of the physical forces that drive transport processes is thus important for understanding the plant growth and development. We focus on the passive transport of molecules, describing the fundamental concepts and demonstrating how different levels of abstraction can lead to different interpretations of the driving forces. We summarize recent developments on quantitative frameworks for describing diffusive and bulk flow transport processes in and out of cells, with a more detailed focus on plasmodesmata, and outline open questions and challenges.

µCT trait analysis reveals morphometric differences between domesticated temperate small grain cereals and their wild relatives.

Wheat and barley are two of the founder crops domesticated in the Fertile Crescent, and currently represent crops of major economic importance in temperate regions. Due to impacts on yield, quality and end-use, grain morphometric traits remain an important goal for modern breeding programmes and are believed to have been selected for by human populations. To directly and accurately assess the three-dimensional (3D) characteristics of grains, we combine X-ray microcomputed tomography (µCT) imaging techniques with bespoke image analysis tools and mathematical modelling to investigate how grain size and shape vary across wild and domesticated wheat and barley. We find that grain depth and, to a lesser extent, width are major drivers of shape change and that these traits are still relatively plastic in modern bread wheat varieties. Significant changes in grain depth are also observed to be associated with differences in ploidy. Finally, we present a model that can accurately predict the wild or domesticated status of a grain from a given taxa based on the relationship between three morphometric parameters (length, width and depth) and suggest its general applicability to both archaeological identification studies and breeding programmes.

Barley lys3 mutants are unique amongst shrunken-endosperm mutants in having abnormally large embryos.

Many shrunken endosperm mutants of barley (Hordeum vulgare L.) have been described and several of these are known to have lesions in starch biosynthesis genes. Here we confirm that one type of shrunken endosperm mutant, lys3 (so called because it was first identified as a high-lysine mutant) has an additional phenotype: as well as shrunken endosperm it also has enlarged embryos. The lys3 embryos have a dry weight that is 50-150% larger than normal. Observations of developing lys3 embryos suggest that they undergo a form of premature germination and the mature lys3 grains show reduced dormancy. In many respects, the phenotype of barley lys3 is similar to that of rice GIANT EMBRYO mutants (affected in the OsGE gene). However, the barley orthologue of OsGE is located on a different chromosome from Lys3. Together these results suggest that the gene underlying Lys3 is unlikely to encode a starch biosynthesis protein but rather a protein influencing grain development.

Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography.

Background: Wheat is one of the most widely grown crop in temperate climates for food and animal feed. In order to meet the demands of the predicted population increase in an ever-changing climate, wheat production needs to dramatically increase. Spike and grain traits are critical determinants of final yield and grain uniformity a commercially desired trait, but their analysis is laborious and often requires destructive harvest. One of the current challenges is to develop an accurate, non-destructive method for spike and grain trait analysis capable of handling large populations. Results: In this study we describe the development of a robust method for the accurate extraction and measurement of spike and grain morphometric parameters from images acquired by X-ray micro-computed tomography (µCT). The image analysis pipeline developed automatically identifies plant material of interest in µCT images, performs image analysis, and extracts morphometric data. As a proof of principle, this integrated methodology was used to analyse the spikes from a population of wheat plants subjected to high temperatures under two different water regimes. Temperature has a negative effect on spike height and grain number with the middle of the spike being the most affected region. The data also confirmed that increased grain volume was correlated with the decrease in grain number under mild stress. Conclusions: Being able to quickly measure plant phenotypes in a non-destructive manner is crucial to advance our understanding of gene function and the effects of the environment. We report on the development of an image analysis pipeline capable of accurately and reliably extracting spike and grain traits from crops without the loss of positional information. This methodology was applied to the analysis of wheat spikes can be readily applied to other economically important crop species.

A Cluster Analysis of Reported Sleeping Patterns of 9-Month Old Infants and the Association with Maternal Health: Results from a Population Based Cohort Study.

The aim of this study was to identify, using cluster analysis, novel sleep phenotypes in a population based cohort of infants, and to explore the associations between infant sleep profiles and their mothers' health and well-being. 11,134 mothers of 9-month old infants were interviewed as part of the Growing Up in Ireland National Longitudinal study and reported on their health and infant's sleep patterns. 16 infant sleep variables were recorded together with measures of parental stress, depression, health and well-being. Multiple iterations of a two-step hierarchical cluster analysis were carried out to identify the optimum number of clusters and the subset of parental-reported sleep variables required to identify distinct sleep profiles. Four distinct sleep profiles were identified based on the following variables; (1) infant sleep duration at night, (2) parental sleep duration, (3) does baby wake during night (yes, no)? (4) Usual sleep location for most of the night and, (5) parental reporting of problem infant sleep patterns. This identified two less favorable profiles with both infants and mothers sleeping less and where mothers are more likely to report their infants' sleep patterns as problematic. Mothers of infants belonging to these sleep profiles were more likely to have higher levels of stress, depressive symptoms, and poorer self-reported health than other sleep profiles. Breastfeeding was associated with both groups and rates were highest in a group of infants that were more likely to co-sleep with their parents and have diverse ethnic backgrounds. This study demonstrates, for the first time, two infant sleep profiles with distinct phenotypical frameworks that are significantly associated with maternal stress, depression, and poorer self-report of health.