Basic Scale on Insomnia complaints and Quality of Sleep (BaSIQS): Reliability,initial validity and normative scores in higher education students

Based on successive samples totaling more than 5000 higher education students, we scrutinized the reliability, structure, initial validity and normative scores of a brief self-report seven-item scale to screen for the continuum of nighttime insomnia complaints/perceived sleep quality, used by our team for more than a decade, henceforth labeled the Basic Scale on Insomnia complaints and Quality of Sleep (BaSIQS). In study/sample 1 (n?=?1654), the items were developed based on part of a larger survey on higher education sleep–wake patterns. The test–retest study was conducted in an independent small group (n?=?33) with a 2–8 week gap. In study/sample 2 (n?=?360), focused mainly on validity, the BaSIQS was completed together with the Pittsburgh Sleep Quality Index (PSQI). In study 3, a large recent sample of students from universities all over the country (n?=?2995) answered the BaSIQS items, based on which normative scores were determined, and an additional question on perceived sleep problems in order to further analyze the scale’s validity. Regarding reliability, Cronbach alpha coefficients were systematically higher than 0.7, and the test–retest correlation coefficient was greater than 0.8. Structure analyses revealed consistently satisfactory two-factor and single-factor solutions. Concerning validity analyses, BaSIQS scores were significantly correlated with PSQI component scores and overall score (r?=?0.652 corresponding to a large association); mean scores were significantly higher in those students classifying themselves as having sleep problems (p?<?0.0001, d?=?0.99 corresponding to a large effect size). In conclusion, the BaSIQS is very easy to administer, and appears to be a reliable and valid scale in higher education students. It might be a convenient short tool in research and applied settings to rapidly assess sleep quality or screen for insomnia complaints, and it may be easily used in other populations with minor adaptations.     

Current methods for molecular typing of Campylobacter species

Campylobacter remains one of the most common bacterial causes of gastroenteritis worldwide. Tracking sources of this organism is challenging due to the large numbers of human cases, and the prevalence of this organism throughout the environment due to growth in a wide range of animal species. Many molecular subtyping methods have been developed to characterize Campylobacter species, but only a few are commonly used in molecular epidemiology studies. This review examines the applicability of these methods, as well as the role that emerging whole genome sequencing technologies will play in tracking sources of Campylobacter spp. infection.     

DNase I and Proteinase K eliminate DNA from injured or dead bacteria but not from living bacteria in microbial reference systems and natural drinking water biofilms for subsequent molecular biology analyses

Molecular techniques, such as polymerase chain reaction (PCR) and quantitative PCR (qPCR), are very sensitive, but may detect total DNA present in a sample, including extracellular DNA (eDNA) and DNA coming from live and dead cells. DNase I is an endonuclease that non-specifically cleaves single- and double-stranded DNA. This enzyme was tested in this study to analyze its capacity of digesting DNA coming from dead cells with damaged cell membranes, leaving DNA from living cells with intact cell membranes available for DNA-based methods. For this purpose, an optimized DNase I/Proteinase K (DNase/PK) protocol was developed. Intact Staphylococcus aureus cells, heat-killed Pseudomonas aeruginosa cells, free genomic DNA of Salmonella enterica, and a mixture of these targets were treated according to the developed DNase/PK protocol. In parallel, these samples were treated with propidium monoazide (PMA) as an already described assay for live-dead discrimination. Quantitative PCR and PCR-DGGE of the eubacterial 16S rDNA fragment were used to test the ability of the DNase/PK and PMA treatments to distinguish DNA coming from cells with intact cell membranes in the presence of DNA from dead cells and free genomic DNA. The methods were applied to three months old autochthonous drinking water biofilms from a pilot facility built at a German waterworks. Shifts in the DNA patterns observed after DGGE analysis demonstrated the applicability of DNase/PK as well as of the PMA treatment for natural biofilm investigation. However, the DNase/PK treatment demonstrated some practical advantages in comparison with the PMA treatment for live/dead discrimination of bacterial targets in drinking water systems.     

DISENTANGLING EVOLUTIONARY CAUSE‐EFFECT RELATIONSHIPS WITH PHYLOGENETIC CONFIRMATORY PATH ANALYSIS

Confirmatory path analysis is a statistical technique to build models of causal hypotheses among variables and test if the data conform with the causal model. However, classical path analysis techniques ignore the nonindependence of observations due to phylogenetic relatedness among species, possibly leading to spurious results. Here, we present a simple method to perform phylogenetic confirmatory path analysis (PPA). We analyzed simulated datasets with varying amounts of phylogenetic signal in the data and a known underlying causal structure linking the traits to estimate Type I error and power. Results show that Type I error for PPA appeared to be slightly anticonservative (range: 0.047–0.072) but path analysis models ignoring phylogenetic signal resulted in much higher Type I error rates, which were positively related to the amount of phylogenetic signal (range: 0.051 for λ= 0 to 0.916 for λ= 1). Further, the power of the test was not compromised when accounting for phylogeny. As an example of the application of PPA, we revisit a study on the correlates of aggressive broodmate competition across seven avian families. The use of PPA allowed us to gain greater insight into the plausible causal paths linking species traits to aggressive broodmate competition.     

THE GENOMIC TRAJECTORY OF HYBRID SWARMS: OUTCOMES OF REPEATED CROSSES BETWEEN POPULATIONS OF TIGRIOPUS CALIFORNICUS

Introgressive hybridization between genetically divergent populations is an important evolutionary process. The degree to which repeated hybridization events between the same parental taxa lead to similar genomic outcomes is unknown. This study addressed this question by following genomic trajectories of replicate hybrid swarms of the copepod Tigriopus californicus over many generations of free mating. Swarm composition was determined both by differential reproductive success of founder individuals and subsequent selection on hybrid genotypes. For one cross, between two populations showing differential fitness in the laboratory and no hybrid breakdown, the genetic trajectory was highly repeatable: replicates rapidly became dominated by alleles from the fitter parent. In a second cross, between two populations showing similar fitness and significant F2 hybrid breakdown, alleles from alternative populations dominated different replicates. Swarms exhibited a general temporal trend of decreasing cytonuclear mismatch. Some patterns of differential introgression across the genome were strikingly congruent amongst swarm replicates, both within and between cross types, and reflected patterns of segregation distortion previously observed within controlled crosses between the same parental populations. Differences in heterozygosity between the sexes, and evidence for a previously suspected sex‐distortion locus, suggest that complex interactions between sex and genotype influence hybrid swarm outcome.     

On the origins,rapid expansion and genetic diversity of native Americans from hunting‐gatherers to agriculturalists

Given the importance of Y‐chromosome haplogroup Q to better understand the source populations of contemporary Native Americans, we studied 8 biallelic and 17 microsatellite polymorphisms on the background of 128 Q Y‐chromosomes from geographically targeted populations. The populations examined in this study include three from the Tuva Republic in Central Asia (Bai‐Tai, Kungurtug, and Toora‐Hem, n = 146), two from the northeastern tip of Siberia (New Chaplino and Chukchi, n = 32), and two from Mesoamerica (Mayans from Yucatan, Mexico n = 72, and Mayans from the Guatemalan Highlands, n = 43). We also see evidence of a dramatic Mesoamerican post‐migration population growth in the ubiquitous and diverse Y‐STR profiles of the Mayan and other Mesoamerican populations. In the case of the Mayans, this demographic growth was most likely fueled by the agricultural‐ and trade‐based subsistence adopted during the Pre‐Classic, Classic and Post‐Classic periods of their empire. The limited diversity levels observed in the Altaian and Tuvinian regions of Central Asia, the lowest of all populations examined, may be the consequence of bottleneck events fostered by the spatial isolation and low effective population size characteristic of a nomadic lifestyle. Furthermore, our data illustrate how a sociocultural characteristic such as mode of subsistence may be of impact on the genetic structure of populations. We analyzed our genetic data using Multidimensional Scaling Analysis of populations, Principal Component Analysis of individuals, Median‐joining networks of M242, M346, L54, and M3 individuals, age estimations based on microsatellite variation utilizing genealogical and evolutionary mutation rates/generation times and estimation of Y‐ STR average gene diversity indices. Am J Phys Anthropol, 2013. © 2013 Wiley Periodicals, Inc.     

Genetic Mapping and Genomic Selection Using Recombination Breakpoint Data

The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers are located in a few chromosomes of the genome leads to linkage disequilibrium among markers. This suggests that dimension reduction can also be achieved through data manipulation. High-density markers are used to infer recombination breakpoints, which then facilitate construction of bins. The bins are treated as new synthetic markers. The number of bins is always a manageable number, on the order of a few thousand. Using the bin data of a recombinant inbred line population of rice, we demonstrated genetic mapping, using all bins in a simultaneous manner. To facilitate genomic selection, we developed a method to create user-defined (artificial) bins, in which breakpoints are allowed within bins. Using eight traits of rice, we showed that artificial bin data analysis often improves the predictability compared with natural bin data analysis. Of the eight traits, three showed high predictability, two had intermediate predictability, and two had low predictability. A binary trait with a known gene had predictability near perfect. Genetic mapping using bin data points to a new direction of genomic data analysis.     

Analysis of Allele-Specific Expression in Mouse Liver by RNA-Seq: A Comparison With Cis-eQTL Identified Using Genetic Linkage

We report an analysis of allele-specific expression (ASE) and parent-of-origin expression in adult mouse liver using next generation sequencing (RNA-Seq) of reciprocal crosses of heterozygous F₁ mice from the parental strains C57BL/6J and DBA/2J. We found a 60% overlap between genes exhibiting ASE and putative cis-acting expression quantitative trait loci (cis-eQTL) identified in an intercross between the same strains. We discuss the various biological and technical factors that contribute to the differences. We also identify genes exhibiting parental imprinting and complex expression patterns. Our study demonstrates the importance of biological replicates to limit the number of false positives with RNA-Seq data.