Genetic structure and differentiation in cultivated fig (Ficus carica L.)

One hundred ninety-four germplasm accessions of fig representing the four fig types, Common, Smyrna, San Pedro, and Caprifig were analyzed for genetic diversity, structure, and differentiation using genetic polymorphism at 15 microsatellite loci. The collection showed considerable polymorphism with observed number of alleles per locus ranging from four for five different loci, MFC4, LMFC14, LMFC22, LMFC31 and LMFC35 to nine for LMFC30 with an average of 4.9 alleles per locus. Seven of the 15 loci included in the genetic structure analyses exhibited significant deviation from panmixia, of which two showed excess and five showed deficiency of heterozygote. The cluster analysis (CA) revealed ten groups with 32 instances of synonymy among cultivars and groups differed significantly for frequency and composition of alleles for different loci. The principal components analysis (PCA) confirmed the results of CA with some groups more differentiated than the others. Further, the model based Bayesian approach clustering suggested a subtle population structure with mixed ancestry for most figs. The gene diversity analysis indicated that much of the total variation is found within groups (HG/HT = 0.853; 85.3%) and the among groups within total component (GGT = 0.147) accounted for the remaining 14.7%, of which ~64% accounted for among groups within clusters (GGC = 0.094) and ~36% among clusters (GCT = 0.053). The analysis of molecular variance (AMOVA) showed approximately similar results with nearly 87% of variation within groups and ~10% among groups within clusters, and ~3% among clusters. Overall, the gene pool of cultivated fig analyzed possesses substantial genetic polymorphism but exhibits narrow differentiation. It is evident that fig accessions from Turkmenistan are somewhat genetically different from the rest of the Mediterranean and the Caucasus figs. The long history of domestication and cultivation with widespread dispersal of cultivars with many synonyms has resulted in a great deal of confusion in the identification and classification of cultivars in fig

iWorksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings

The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resulting psychological and economic sequela. As countries start to ease lock-down measures and reopen industries, ensuring a healthy workplace for employees has become imperative. Thus, this paper presents a mobile app-based intelligent portable healthcare (pHealth) tool, called i WorkSafe, to assist industries in detecting possible suspects for COVID-19 infection among their employees who may need primary care. Developed mainly for low-end Android devices, the i WorkSafe app hosts a fuzzy neural network model that integrates data of employees’ health status from the industry’s database, proximity and contact tracing data from the mobile devices, and user-reported COVID-19 self-test data. Using the built-in Bluetooth low energy sensing technology and K Nearest Neighbor and K-means techniques, the app is capable of tracking users’ proximity and trace contact with other employees. Additionally, it uses a logistic regression model to calculate the COVID-19 self-test score and a Bayesian Decision Tree model for checking real-time health condition from an intelligent e-health platform for further clinical attention of the employees. Rolled out in an apparel factory on 12 employees as a test case, the pHealth tool generates an alert to maintain social distancing among employees inside the industry. In addition, the app helps employees to estimate risk with possible COVID-19 infection based on the collected data and found that the score is effective in estimating personal health condition of the app user

Structural versus Electrical Functionalization of Oligo(phenyleneethynylene) Diamine Molecular Junctions

We explore both experimentally and theoretically the conductance and packing of molecular junctions based on oligo(phenyleneethynylene) (OPE) diamine wires, when a series of functional groups are incorporated into the wires. Using the scanning tunnelling microscopy break-junction (STM BJ) technique, we study these compounds in two environments (air and 1,2,4-trichlorobenzene) and explore different starting molecular concentrations. We show that the electrical conductance of the molecular junctions exhibits variations among different compounds, which are significant at standard concentrations but become unimportant when working at a low enough concentration. This shows that the main effect of the functional groups is to affect the packing of the molecular wires, rather than to modify their electrical properties. Our theoretical calculations consistently predict no significant changes in the conductance of the wires due to the electronic structure of the functional groups, although their ability to hinder ring rotations within the OPE backbone can lead to higher conductances at higher packing densities

Metallic, magnetic and molecular nanocontacts

Scanning tunnelling microscopy and break-junction experiments realize metallic and molecular nanocontacts that act as ideal one-dimensional channels between macroscopic electrodes. Emergent nanoscale phenomena typical of these systems encompass structural, mechanical, electronic, transport, and magnetic properties. This Review focuses on the theoretical explanation of some of these properties obtained with the help of first-principles methods. By tracing parallel theoretical and experimental developments from the discovery of nanowire formation and conductance quantization in gold nanowires to recent observations of emergent magnetism and Kondo correlations, we exemplify the main concepts and ingredients needed to bring together ab initio calculations and physical observations. It can be anticipated that diode, sensor, spin-valve and spin-filter functionalities relevant for spintronics and molecular electronics applications will benefit from the physical understanding thus obtained

Genetic diversity, linkage disequilibrium and power of a large grapevine (Vitis vinifera L) diversity panel newly designed for association studies

UMR-AGAP Equipe DAVV (Diversité, adaptation et amélioration de la vigne) ; équipe ID (Intégration de Données)International audienceAbstractBackgroundAs for many crops, new high-quality grapevine varieties requiring less pesticide and adapted to climate change are needed. In perennial species, breeding is a long process which can be speeded up by gaining knowledge about quantitative trait loci linked to agronomic traits variation. However, due to the long juvenile period of these species, establishing numerous highly recombinant populations for high resolution mapping is both costly and time-consuming. Genome wide association studies in germplasm panels is an alternative method of choice, since it allows identifying the main quantitative trait loci with high resolution by exploiting past recombination events between cultivars. Such studies require adequate panel design to represent most of the available genetic and phenotypic diversity. Assessing linkage disequilibrium extent and panel power is also needed to determine the marker density required for association studies.ResultsStarting from the largest grapevine collection worldwide maintained in Vassal (France), we designed a diversity panel of 279 cultivars with limited relatedness, reflecting the low structuration in three genetic pools resulting from different uses (table vs wine) and geographical origin (East vs West), and including the major founders of modern cultivars. With 20 simple sequence repeat markers and five quantitative traits, we showed that our panel adequately captured most of the genetic and phenotypic diversity existing within the entire Vassal collection. To assess linkage disequilibrium extent and panel power, we genotyped single nucleotide polymorphisms: 372 over four genomic regions and 129 distributed over the whole genome. Linkage disequilibrium, measured by correlation corrected for kinship, reached 0.2 for a physical distance between 9 and 458 Kb depending on genetic pool and genomic region, with varying size of linkage disequilibrium blocks. This panel achieved reasonable power to detect associations between traits with high broad-sense heritability (> 0.7) and causal loci with intermediate allelic frequency and strong effect (explaining > 10 % of total variance).ConclusionsOur association panel constitutes a new, highly valuable resource for genetic association studies in grapevine, and deserves dissemination to diverse field and greenhouse trials to gain more insight into the genetic control of many agronomic traits and their interaction with the environment