RESUMEN
Responsive thermochromic fiber materials capable of miniaturization and integrating comfortably and compliantly onto the soft and dynamically deforming human body are promising materials for visualized personal health monitoring. However, their development is hindered by monotonous colors, low-contrast color changes, and poor reversibility. Herein, full-color "off-on" thermochromic fluorescent fibers are prepared based on self-crystallinity phase change and Förster resonance energy transfer for long-term and passive body-temperature monitoring, especially for various personalized customization purposes. The off-on switching luminescence characteristic is derived from the reversible conversion of the dispersion state and fluorescent emission by fluorophores and quencher molecules, which are embedded in the matrix of a phase-change material, during the crystallizing/melting processes. The achievement of full-color fluorescence is attributed to the large modulation range of fluorescence colors according to primary color additive theory. These thermochromic fluorescent fibers exhibit good mechanical properties, fluorescent emission contrast, and reversibility, showing their great potential in flexible smart display devices. Moreover, the response temperature of the thermochromic fibers is controllable by adjusting the phase-change material, enabling body-temperature-triggered luminescence; this property highlights their potential for human body-temperature monitoring and personalized customization. This work presents a new strategy for designing and exploring flexible sensors with higher comprehensive performances.
RESUMEN
Environmental factors can influence diversity and population structure in marine species and accurate understanding of this influence can both improve fisheries management and help predict responses to environmental change. We used 7163 SNPs derived from restriction site-associated DNA sequencing genotyped in 245 individuals of the economically important sea scallop, Placopecten magellanicus, to evaluate the correlations between oceanographic variation and a previously identified latitudinal genomic cline. Sea scallops span a broad latitudinal area (>10 degrees), and we hypothesized that climatic variation significantly drives clinal trends in allele frequency. Using a large environmental dataset, including temperature, salinity, chlorophyll a, and nutrient concentrations, we identified a suite of SNPs (285-621, depending on analysis and environmental dataset) potentially under selection through correlations with environmental variation. Principal components analysis of different outlier SNPs and environmental datasets revealed similar northern and southern clusters, with significant associations between the first axes of each (R2adj = .66-.79). Multivariate redundancy analysis of outlier SNPs and the environmental principal components indicated that environmental factors explained more than 32% of the variance. Similarly, multiple linear regressions and random-forest analysis identified winter average and minimum ocean temperatures as significant parameters in the link between genetic and environmental variation. This work indicates that oceanographic variation is associated with the observed genomic cline in this species and that seasonal periods of extreme cold may restrict gene flow along a latitudinal gradient in this marine benthic bivalve. Incorporating this finding into management may improve accuracy of management strategies and future predictions.
RESUMEN
megasat is software that enables genotyping of microsatellite loci using next-generation sequencing data. Microsatellites are amplified in large multiplexes, and then sequenced in pooled amplicons. megasat reads sequence files and automatically scores microsatellite genotypes. It uses fuzzy matches to allow for sequencing errors and applies decision rules to account for amplification artefacts, including nontarget amplification products, replication slippage during PCR (amplification stutter) and differential amplification of alleles. An important feature of megasat is the generation of histograms of the length-frequency distributions of amplification products for each locus and each individual. These histograms, analogous to electropherograms traditionally used to score microsatellite genotypes, enable rapid evaluation and editing of automatically scored genotypes. megasat is written in Perl, runs on Windows, Mac OS X and Linux systems, and includes a simple graphical user interface. We demonstrate megasat using data from guppy, Poecilia reticulata. We genotype 1024 guppies at 43 microsatellites per run on an Illumina MiSeq sequencer. We evaluated the accuracy of automatically called genotypes using two methods, based on pedigree and repeat genotyping data, and obtained estimates of mean genotyping error rates of 0.021 and 0.012. In both estimates, three loci accounted for a disproportionate fraction of genotyping errors; conversely, 26 loci were scored with 0-1 detected error (error rate ≤0.007). Our results show that with appropriate selection of loci, automated genotyping of microsatellite loci can be achieved with very high throughput, low genotyping error and very low genotyping costs.