Population-level Correlations Research Articles

CONGRuENTS (COsmic-ray, Neutrino, Gamma-ray and Radio Non-Thermal Spectra) – II. Population-level correlations between galactic infrared, radio, and γ-ray emission

ABSTRACT Galaxies obey a number of empirical correlations between their radio, γ-ray, and infrared emission, but the physical origins of these correlations remain uncertain. Here, we use the CONGRuENTS model for broad-band non-thermal emission from star-forming galaxies, which self-consistently calculates energy-dependent transport and non-thermal emission from cosmic ray hadrons and leptons, to predict radio and γ-ray emission for a synthetic galaxy population with properties drawn from a large deep-field survey. We show that our synthetic galaxies reproduce observed relations such as the far infrared (FIR)–radio correlation, the FIR–γ correlation, and the distribution of radio spectral indices, and we use the model to explain the physical origins of these relations. Our results show that the FIR–radio correlation arises because the amount of cosmic ray electron power ultimately radiated as synchrotron emission varies only weakly with galaxy star formation rate as a result of the constraints imposed on gas properties by hydrostatic balance and turbulent dynamo action; the same physics dictates the extent of proton calorimetry in different galaxies, and thus sets the FIR–γ–ray correlation. We further show that galactic radio spectral indices result primarily from competition between thermal free–free emission and energy-dependent loss of cosmic ray electrons to bremsstrahlung and escape into galactic haloes, with shaping of the spectrum by inverse Compton, synchrotron, and ionization processes typically playing a subdominant role. In addition to explaining existing observations, we use our analysis to predict a heretofore unseen correlation between the curvature of galaxies’ radio spectra and their pion-driven γ-ray emission, a prediction that will be testable with upcoming facilities.

A Multi-Center Cross-Sectional Study on Visual Impairment and Depression Among Students - Jiangsu Province, China, 2017-2022.

China exhibits a significantly high prevalence of myopia compared to other countries globally. Children with vision impairment have been found to engage less in physical activities, achieve lower academic performance, and have increased vulnerability to depression. During a six-year observational study, a population-level correlation was identified between varying degrees of visual impairment and the presence of depressive symptoms among students. Specifically, individuals with a visual acuity below 4.0 had a significantly higher odds ratio of 1.90 (95% confidence interval: 1.53-2.37) compared to individuals with normal vision (visual acuity ≥5.0). This study highlights the importance of holistic health interventions that address both visual and psychological aspects. Understanding common mechanisms and influential factors can guide the development of more impactful public health strategies.

Population-Level Correlation Between Incidence of Curable Sexually Transmitted Infections and Human Immunodeficiency Virus (HIV)-1 Among African Women Participating in HIV-1 Pre-Exposure Prophylaxis Trials.

Highly efficacious oral pre-exposure prophylaxis (PrEP) is the global standard for human immunodeficiency virus (HIV)-1 prevention, including in clinical trials of novel PrEP agents using active-comparator designs. The analysis assessed whether incident sexually transmitted infections (STIs) can serve as a surrogate indicator of HIV-1 incidence that might occur in the absence of PrEP. We analyzed data from 3256 women randomized to placebo groups of oral and vaginal PrEP trials (MTN-003/VOICE and MTN-020/ASPIRE). Regression modeling assessed the correlation between incident individual STIs (Neisseria gonorrhoeae, Chlamydia trachomatis, and Trichomonas vaginalis, each considered separately) and incident HIV-1. Across 18 sites in 4 countries (Malawi, South Africa, Uganda, Zimbabwe), STI and HIV-1 incidences were high: HIV-1 4.9, N gonorrhoeae 5.3, C trachomatis 14.5, and T vaginalis 7.1 per 100 person-years. There was limited correlation between HIV-1 incidence and incidence of individual STIs: N gonorrhoeae (r = 0.02, P = .871), C trachomatis (r = 0.49, P = <.001), and T vaginalis (r = 0.10, P = .481). The modest association with C trachomatis was driven by country-level differences in both C trachomatis and HIV-1, with no statistically significant association within countries. Sexually transmitted infection incidence did not reliably predict HIV-1 incidence at the population level among at-risk African women participating in 2 large PrEP trials.

Chasing genetic correlation breakers to stimulate population resilience to climate change

Global climate change introduces new combinations of environmental conditions, which is expected to increase stress on plants. This could affect many traits in multiple ways that are as yet unknown but will likely require the modification of existing genetic relationships among functional traits potentially involved in local adaptation. Theoretical evolutionary studies have determined that it is an advantage to have an excess of recombination events under heterogeneous environmental conditions. Our study, conducted on a population of radiata pine (Pinus radiata D. Don), was able to identify individuals that show high genetic recombination at genomic regions, which potentially include pleiotropic or collocating QTLs responsible for the studied traits, reaching a prediction accuracy of 0.80 in random cross-validation and 0.72 when whole family was removed from the training population and predicted. To identify these highly recombined individuals, a training population was constructed from correlation breakers, created through tandem selection of parents in the previous generation and their consequent mating. Although the correlation breakers showed lower observed heterogeneity possibly due to direct selection in both studied traits, the genomic regions with statistically significant differences in the linkage disequilibrium pattern showed higher level of heretozygosity, which has the effect of decomposing unfavourable genetic correlation. We propose undertaking selection of correlation breakers under current environmental conditions and using genomic predictions to increase the frequency of these ’recombined’ individuals in future plantations, ensuring the resilience of planted forests to changing climates. The increased frequency of such individuals will decrease the strength of the population-level genetic correlations among traits, increasing the opportunity for new trait combinations to be developed in the future.

Exposure to Family Member Incarceration and Adult Well-being in the United States

More than half of the adult population in the United States has ever had a family member incarcerated, an experience more common among Black individuals. The impacts of family incarceration on well-being are not fully understood. To assess the associations of incarceration of a family member with perceived well-being and differences in projected life expectancy. This nationally representative cross-sectional study used data from the 2018 Family History of Incarceration Survey to examine how experiences of family member incarceration were associated with a holistic measure of well-being, including physical, mental, social, financial, and spiritual domains. Well-being was used to estimate change in life expectancy and was compared across varying levels of exposure to immediate and extended family member incarceration using logistic regression models to adjust for individual and household characteristics. Data were analyzed from October 2019 to April 2020. Respondents' history of family member incarceration, including immediate and extended family members. The main outcome was self-reported life-evaluation, a measure of overall well-being from the 100 Million Healthier Lives Adult Well-being Assessment. Respondents were considered thriving with a current life satisfaction score of 7 or greater and a future life optimism score of 8 or greater, each on a scale of 0 to 10. Other outcomes included physical health, mental health, social support, financial well-being, and spiritual well-being, each measured with separate scales. Additionally, life expectancy projections were estimated using population-level correlations with the Life Evaluation Index. All percentages were weighted to more closely represent the US population. Of 2815 individuals included in analysis, 1472 (51.7%) were women, 1765 (62.8%) were non-Hispanic White, and 868 (31.5%) were aged 35 to 54 years. A total of 1806 respondents (45.0%) reported having an immediate family member who was incarcerated. Compared with respondents with no family incarceration, any family member incarceration was associated with lower well-being overall (thriving: 69.5% [95% CI, 65.0%-75.0%] vs 56.9% [95% CI, 53.9%-59.9%]) and in every individual domain (eg, physical thriving: 51.1% [95% CI, 46.2-56.0] vs 35.5% [95% CI, 32.6%-38.3%]) and with a mean (SE) estimated 2.6 (0.03) years shorter life expectancy. Among those with any family incarceration, Black respondents had a mean (SE) estimated 0.46 (0.04) fewer years of life expectancy compared with White respondents. These findings suggest that family member health and well-being may be an important avenue through which incarceration is associated with racial disparities in health and mortality. Decarceration efforts may improve population-level well-being and life expectancy by minimizing detrimental outcomes associated with incarceration among nonincarcerated family members.

Malleability of gamma rhythms enhances population-level correlations.

An important problem in systems neuroscience is to understand how information is communicated among brain regions, and it has been proposed that communication is mediated by neuronal oscillations, such as rhythms in the gamma band. We sought to investigate this idea by using a network model with two components, a source (sending) and a target (receiving) component, both built to resemble local populations in the cerebral cortex. To measure the effectiveness of communication, we used population-level correlations in spike times between the source and target. We found that after correcting for a response time that is independent of initial conditions, spike-time correlations between the source and target are significant, due in large measure to the alignment of firing events in their gamma rhythms. But, we also found that regular oscillations cannot produce the results observed in our model simulations of cortical neurons. Surprisingly, it is the irregularity of gamma rhythms, the absence of internal clocks, together with the malleability of these rhythms and their tendency to align with external pulses - features that are known to be present in gamma rhythms in the real cortex - that produced the results observed. These findings and the mechanistic explanations we offered are our primary results. Our secondary result is a mathematical relationship between correlations and the sizes of the samples used for their calculation. As improving technology enables recording simultaneously from increasing numbers of neurons, this relationship could be useful for interpreting results from experimental recordings.

Assessing the Population-Level Correlation of Medication Regimen Complexity and Adherence Indices Using Electronic Health Records and Insurance Claims.

Nonadherence to medication regimens can lead to adverse health care outcomes and increasing costs. To (a) assess the level of medication complexity at an outpatient setting using population-level electronic health record (EHR) data and (b) evaluate its association with medication adherence measures derived from medication-dispensing claims. We linked EHR data with insurance claims of 70,054 patients who had an encounter with a U.S. midwestern health system between 2012 and 2013. We constructed 3 medication-derived indices: medication regimen complexity index (MRCI) using EHR data; medication possession ratio (MPR) using insurance pharmacy claims; and prescription fill rates (PFR; 7 and 30 days) using both data sources. We estimated the partial correlation between indices using Spearman's coefficient (SC) after adjusting for age and sex. The mean age (SD) of 70,054 patients was 37.9 (18.0) years, with an average Charlson Comorbidity Index of 0.308 (0.778). The 2012 data showed mean (SD) MRCI, MPR, and 30-day PFR of 14.6 (17.8), 0.624 (0.310), and 81.0 (27.0), respectively. Patients with previous inpatient stays were likely to have high MRCI scores (36.3 [37.9], P < 0.001) and were less adherent to outpatient prescriptions (MPR = 50.3 [27.6%], P < 0.001; 30-day PFR = 75.7 [23.6%], P < 0.001). However, MRCI did not show a negative correlation with MPR (SC = -0.31, P < 0.001) or with 30-day PFR (SC = -0.17, P < 0.001) at significant levels. Medication complexity and adherence indices can be calculated on a population level using linked EHR and claims data. Regimen complexity affects patient adherence to outpatient medication, and strength of correlations vary modestly across populations. Future studies should assess the added values of MRCI, MPR, and PFR to population health management efforts. No outside funding supported this study. The authors have nothing to disclose. The abstract of this work was presented at INFORMS Healthcare Conference, held on July 27-29, 2019, in Cambridge, MA.

Population modeling of tumor growth curves and the reduced Gompertz model improve prediction of the age of experimental tumors.

Tumor growth curves are classically modeled by means of ordinary differential equations. In analyzing the Gompertz model several studies have reported a striking correlation between the two parameters of the model, which could be used to reduce the dimensionality and improve predictive power. We analyzed tumor growth kinetics within the statistical framework of nonlinear mixed-effects (population approach). This allowed the simultaneous modeling of tumor dynamics and inter-animal variability. Experimental data comprised three animal models of breast and lung cancers, with 833 measurements in 94 animals. Candidate models of tumor growth included the exponential, logistic and Gompertz models. The exponential and-more notably-logistic models failed to describe the experimental data whereas the Gompertz model generated very good fits. The previously reported population-level correlation between the Gompertz parameters was further confirmed in our analysis (R2 > 0.92 in all groups). Combining this structural correlation with rigorous population parameter estimation, we propose a reduced Gompertz function consisting of a single individual parameter (and one population parameter). Leveraging the population approach using Bayesian inference, we estimated times of tumor initiation using three late measurement timepoints. The reduced Gompertz model was found to exhibit the best results, with drastic improvements when using Bayesian inference as compared to likelihood maximization alone, for both accuracy and precision. Specifically, mean accuracy (prediction error) was 12.2% versus 78% and mean precision (width of the 95% prediction interval) was 15.6 days versus 210 days, for the breast cancer cell line. These results demonstrate the superior predictive power of the reduced Gompertz model, especially when combined with Bayesian estimation. They offer possible clinical perspectives for personalized prediction of the age of a tumor from limited data at diagnosis. The code and data used in our analysis are publicly available at https://github.com/cristinavaghi/plumky.

Population-level macrolide consumption is associated with clarithromycin resistance in Helicobacter pylori: An ecological analysis

Bystander selection has been shown to result in strong population-level correlations between the level of antimicrobial consumption in the general population and resistance to that antimicrobial or similar antimicrobials in a range of bacteria. The prevalence of clarithromycin resistance in Helicobacter pylori has been increasing rapidly resulting in increased difficulty to eradicate this infection. Using country- and WHO-world-region-level macrolide resistance data from a systematic review and macrolide consumption data from the MIDAS Quantum data base, we tested the hypothesis that the prevalence of clarithromycin resistance was correlated with macrolide consumption. At a country level, we found these variables to be positively correlated (Spearman’s rho=0.49; P=0.007). Whilst positive, the correlation between macrolide consumption and primary resistance was not statistically significant at world region level (Spearman’s rho=0.95; P=0.05).

Medical Marijuana Users are More Likely to Use Prescription Drugs Medically and Nonmedically.

Previous studies have found a negative population-level correlation between medical marijuana availability in US states, and trends in medical and nonmedical prescription drug use. These studies have been interpreted as evidence that use of medical marijuana reduces medical and nonmedical prescription drug use. This study evaluates whether medical marijuana use is a risk or protective factor for medical and nonmedical prescription drug use. Simulations based upon logistic regression analyses of data from the 2015 National Survey on Drug Use and Health were used to compute associations between medical marijuana use, and medical and nonmedical prescription drug use. Adjusted risk ratios (RRs) were computed with controls added for age, sex, race, health status, family income, and living in a state with legalized medical marijuana. Medical marijuana users were significantly more likely (RR 1.62, 95% confidence interval [CI] 1.50-1.74) to report medical use of prescription drugs in the past 12 months. Individuals who used medical marijuana were also significantly more likely to report nonmedical use in the past 12 months of any prescription drug (RR 2.12, 95% CI 1.67-2.62), with elevated risks for pain relievers (RR 1.95, 95% CI 1.41-2.62), stimulants (RR 1.86, 95% CI 1.09-3.02), and tranquilizers (RR 2.18, 95% CI 1.45-3.16). Our findings disconfirm the hypothesis that a population-level negative correlation between medical marijuana use and prescription drug harms occurs because medical marijuana users are less likely to use prescription drugs, either medically or nonmedically. Medical marijuana users should be a target population in efforts to combat nonmedical prescription drug use.

Have Standard Formulas Correcting Correlations for Range Restriction Been Adequately Tested?: Minor Sampling Distribution Quirks Distort Them.

Most study samples show less variability in key variables than do their source populations due most often to indirect selection into study participation associated with a wide range of personal and circumstantial characteristics. Formulas exist to correct the distortions of population-level correlations created. Formula accuracy has been tested using simulated normally distributed data, but empirical data are rarely available for testing. We did so in a rare data set in which it was possible: the 6-Day Sample, a representative subsample of 1,208 from the Scottish Mental Survey 1947 of cognitive ability in 1936-born Scottish schoolchildren (70,805). 6-Day Sample participants completed a follow-up assessment in childhood and were re-recruited for study at age 77 years. We compared full 6-Day Sample correlations of early-life variables with those of the range-restricted correlations in the later-participating subsample, before and after adjustment for direct and indirect range restriction. Results differed, especially for two highly correlated cognitive tests; neither reproduced full-sample correlations well due to small deviations from normal distribution in skew and kurtosis. Maximum likelihood estimates did little better. To assess these results' typicality, we simulated sample selection and made similar comparisons using the 42 cognitive ability tests administered to the Minnesota Study of Twins Reared Apart, with very similar results. We discuss problems in developing further adjustments to offset range-restriction distortions and possible approaches to solutions.

The trans-generational impact of population density signals on host-parasite interactions.

BackgroundThe density of a host population is a key parameter underlying disease transmission, but it also has implications for the expression of disease through its effect on host physiology. In response to higher densities, individuals are predicted to either increase their immune investment in response to the elevated risk of parasitism, or conversely to decrease their immune capacity as a consequence of the stress of a crowded environment. However, an individual’s health is shaped by many different factors, including their genetic background, current environmental conditions, and maternal effects. Indeed, population density is often sensed through the presence of info-chemicals in the environment, which may influence a host’s interaction with parasites, and also those of its offspring. All of which may alter the expression of disease, and potentially uncouple the presumed link between changes in host density and disease outcomes.ResultsIn this study, we used the water flea Daphnia magna and its obligate bacterial parasite Pasteuria ramosa, to investigate how signals of high host density impact on host-parasite interactions over two consecutive generations. We found that the chemical signals from crowded treatments induced phenotypic changes in both the parental and offspring generations. In the absence of a pathogen, life-history changes were genotype-specific, but consistent across generations, even when the signal of density was removed. In contrast, the influence of density on infected animals depended on the trait and generation of exposure. When directly exposed to signals of high-density, host genotypes responded differently in how they minimised the severity of disease. Yet, in the subsequent generation, the influence of density was rarely genotype-specific and instead related to ability of the host to minimise the onset of infection.ConclusionOur findings reveal that population level correlations between host density and infection capture only part of the complex relationship between crowding and the severity of disease. We suggest that besides its role in horizontal transmission, signals of density can influence parasite epidemiology by modifying mechanisms of resistance across multiple generations, and elevating variability via genotype-by-environment interactions. Our results help resolve why some studies are able to find a positive correlation between high density and resistance, while others uncover a negative correlation, or even no direct relationship at all.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-016-0828-4) contains supplementary material, which is available to authorized users.

Plasma markers of oxidative stress are uncorrelated in a wild mammal.

Oxidative stress, which results from an imbalance between the production of potentially damaging reactive oxygen species versus antioxidant defenses and repair mechanisms, has been proposed as an important mediator of life-history trade-offs. A plethora of biomarkers associated with oxidative stress exist, but few ecological studies have examined the relationships among different markers in organisms experiencing natural conditions or tested whether those relationships are stable across different environments and demographic groups. It is therefore not clear to what extent studies of different markers can be compared, or whether studies that focus on a single marker can draw general conclusions regarding oxidative stress. We measured widely used markers of oxidative damage (protein carbonyls and malondialdehyde) and antioxidant defense (superoxide dismutase and total antioxidant capacity) from 706 plasma samples collected over a 4-year period in a wild population of Soay sheep on St Kilda. We quantified the correlation structure among these four markers across the entire sample set and also within separate years, age groups (lambs and adults), and sexes. We found some moderately strong correlations between some pairs of markers when data from all 4years were pooled. However, these correlations were caused by considerable among-year variation in mean marker values; correlation coefficients were small and not significantly different from zero after accounting for among-year variation. Furthermore, within each year, age, and sex subgroup, the pairwise correlation coefficients among the four markers were weak, nonsignificant, and distributed around zero. In addition, principal component analysis confirmed that the four markers represented four independent axes of variation. Our results suggest that plasma markers of oxidative stress may vary dramatically among years, presumably due to environmental conditions, and that this variation can induce population-level correlations among markers even in the absence of any correlations within contemporaneous subgroups. The absence of any consistent correlations within years or demographic subgroups implies that care must be taken when generalizing from observed relationships with oxidative stress markers, as each marker may reflect different and potentially uncoupled biochemical processes.

DAMASCENE and Meta-Ecological Research: A Bridge Too Far.

Population level studies commonly induce the ecological fallacy, i.e., the belief that a relationship identified at the population level implies a cause and effect relationship at the level of the individual. A recent research report (DAMASCENE) that related clinical trial effect sizes in cardiovascular cell therapy trials to reporting discrepancies in the trials themselves has compounded meta-analysis difficulties with ecological fallacy issues. This dangerous combination has produced misleading conclusions and speculation that the research community should set aside.

The relationship between DNA methylation, genetic and expression inter-individual variation in untransformed human fibroblasts.

BackgroundDNA methylation plays an essential role in the regulation of gene expression. While its presence near the transcription start site of a gene has been associated with reduced expression, the variation in methylation levels across individuals, its environmental or genetic causes, and its association with gene expression remain poorly understood.ResultsWe report the joint analysis of sequence variants, gene expression and DNA methylation in primary fibroblast samples derived from a set of 62 unrelated individuals. Approximately 2% of the most variable CpG sites are mappable in cis to sequence variation, usually within 5 kb. Via eQTL analysis with microarray data combined with mapping of allelic expression regions, we obtained a set of 2,770 regions mappable in cis to sequence variation. In 9.5% of these expressed regions, an associated SNP was also a methylation QTL. Methylation and gene expression are often correlated without direct discernible involvement of sequence variation, but not always in the expected direction of negative for promoter CpGs and positive for gene-body CpGs. Population-level correlation between methylation and expression is strongest in a subset of developmentally significant genes, including all four HOX clusters. The presence and sign of this correlation are best predicted using specific chromatin marks rather than position of the CpG site with respect to the gene.ConclusionsOur results indicate a wide variety of relationships between gene expression, DNA methylation and sequence variation in untransformed adult human fibroblasts, with considerable involvement of chromatin features and some discernible involvement of sequence variation.

Component processes in reading: shared and unique variance in serial and isolated naming speed

Reading ability is comprised of several component processes. In particular, the connection between the visual and verbal systems has been demonstrated to play an important role in the reading process. The present study provides a review of the existing literature on the visual verbal connection as measured by two tasks, rapid serial naming and isolated (or discrete-trial) naming speed, as they relate to reading ability. For each identified study, a secondary data analysis was conducted using the provided correlations between serial naming, isolated naming, and reading. The same analysis was repeated for average population-level correlations among these constructs using meta-analytic weighting techniques. Results suggested that isolated naming acts as a suppressor variable in the relation of serial naming with reading, indicating that there exists at least one cognitive component of the serial naming task that is predictive of reading but is not shared with isolated naming speed. The effect has several implications for understanding the underlying cognitive components reading ability, which are discussed.

Quantitative High-Throughput Screening for Chemical Toxicity in a Population-Based In Vitro Model

A shift in toxicity testing from in vivo to in vitro may efficiently prioritize compounds, reveal new mechanisms, and enable predictive modeling. Quantitative high-throughput screening (qHTS) is a major source of data for computational toxicology, and our goal in this study was to aid in the development of predictive in vitro models of chemical-induced toxicity, anchored on interindividual genetic variability. Eighty-one human lymphoblast cell lines from 27 Centre d'Etude du Polymorphisme Humain trios were exposed to 240 chemical substances (12 concentrations, 0.26nM-46.0μM) and evaluated for cytotoxicity and apoptosis. qHTS screening in the genetically defined population produced robust and reproducible results, which allowed for cross-compound, cross-assay, and cross-individual comparisons. Some compounds were cytotoxic to all cell types at similar concentrations, whereas others exhibited interindividual differences in cytotoxicity. Specifically, the qHTS in a population-based human in vitro model system has several unique aspects that are of utility for toxicity testing, chemical prioritization, and high-throughput risk assessment. First, standardized and high-quality concentration-response profiling, with reproducibility confirmed by comparison with previous experiments, enables prioritization of chemicals for variability in interindividual range in cytotoxicity. Second, genome-wide association analysis of cytotoxicity phenotypes allows exploration of the potential genetic determinants of interindividual variability in toxicity. Furthermore, highly significant associations identified through the analysis of population-level correlations between basal gene expression variability and chemical-induced toxicity suggest plausible mode of action hypotheses for follow-up analyses. We conclude that as the improved resolution of genetic profiling can now be matched with high-quality in vitro screening data, the evaluation of the toxicity pathways and the effects of genetic diversity are now feasible through the use of human lymphoblast cell lines.

Confirmation and fine-mapping of a major QTL for resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar): population-level associations between markers and trait.

BackgroundInfectious pancreatic necrosis (IPN) is one of the most prevalent and economically devastating diseases in Atlantic salmon (Salmo salar) farming worldwide. The disease causes large mortalities at both the fry- and post-smolt stages. Family selection for increased IPN resistance is performed through the use of controlled challenge tests, where survival rates of sib-groups are recorded. However, since challenge-tested animals cannot be used as breeding candidates, within-family selection is not performed and only half of the genetic variation for IPN resistance is being exploited. DNA markers linked to quantitative trait loci (QTL) affecting IPN resistance would therefore be a powerful selection tool. The aim of this study was to identify and fine-map QTL for IPN-resistance in Atlantic salmon, for use in marker-assisted selection to increase the rate of genetic improvement for this trait.ResultsA genome scan was carried out using 10 large full-sib families of challenge-tested Atlantic salmon post-smolts and microsatellite markers distributed across the genome. One major QTL for IPN-resistance was detected, explaining 29% and 83% of the phenotypic and genetic variances, respectively. This QTL mapped to the same location as a QTL recently detected in a Scottish Atlantic salmon population. The QTL was found to be segregating in 10 out of 20 mapping parents, and subsequent fine-mapping with additional markers narrowed the QTL peak to a 4 cM region on linkage group 21. Challenge-tested fry were used to show that the QTL had the same effect on fry as on post-smolt, with the confidence interval for QTL position in fry overlapping the confidence interval found in post-smolts. A total of 178 parents were tested for segregation of the QTL, identifying 72 QTL-heterozygous parents. Genotypes at QTL-heterozygous parents were used to determine linkage phases between alleles at the underlying DNA polymorphism and alleles at single markers or multi-marker haplotypes. One four-marker haplotype was found to be the best predictor of QTL alleles, and was successfully used to deduce genotypes of the underlying polymorphism in 72% of the parents of the next generation within a breeding nucleus. A highly significant population-level correlation was found between deduced alleles at the underlying polymorphism and survival of offspring groups in the fry challenge test, parents with the three deduced genotypes (QQ, Qq, qq) having mean offspring mortality rates of 0.13, 0.32, and 0.49, respectively. The frequency of the high-resistance allele (Q) in the population was estimated to be 0.30. Apart from this major QTL, one other experiment-wise significant QTL for IPN-resistance was detected, located on linkage group 4.ConclusionThe QTL confirmed in this study represents a case of a major gene explaining the bulk of genetic variation for a presumed complex trait. QTL genotypes were deduced within most parents of the 2005 generation of a major breeding company, providing a solid framework for linkage-based MAS within the whole population in subsequent generations. Since haplotype-trait associations valid at the population level were found, there is also a potential for MAS based on linkage disequilibrium (LD). However, in order to use MAS across many generations without reassessment of linkage phases between markers and the underlying polymorphism, the QTL needs to be positioned with even greater accuracy. This will require higher marker densities than are currently available.

If you feel bad, it's unfair: A quantitative synthesis of affect and organizational justice perceptions.

Whereas research interest in both individual affect/temperament and organizational justice has grown substantially in recent years, affect's role in the perception of organizational justice has received scant attention. Here, the authors integrate these literatures and test bivariate relationships between state affect (e.g., moods), trait affect (e.g., affectivity), and organizational justice variables using meta-analytically aggregated effect sizes. Results indicated that state and trait positive and negative affect exhibit statistically significant relationships with perceptions of distributive, procedural, and interactional justice in the predicted directions, with mean population-level correlations ranging in absolute magnitude from M(rho) = .09 to M(rho) = .43. Correlations involving state affect generally were larger but not significantly different from those involving trait affect. Finally, the authors propose ideas for investigations at the primary-study level.

Population level correlation between pre‐alighting and post‐alighting host plant preference in the Glanville fritillary butterfly

Summary1. In many populations of the Glanville fritillary butterflyMelitaea cinxia, ovipositing females exhibit a post‐alighting preference for one of the potential host plant species available. The work reported here aimed to establish whether females with different post‐alighting preferences can discriminate between their host plant species prior to alighting, and whether pre‐alighting and post‐alighting preferences are correlated at the population level.2. Alighting and oviposition events were recorded for groups of females from six populations in greenhouse and field experiments.3. Landing frequencies did not change with experience, indicating thatM. cinxiafemales did not learn from previous encounters with host plants.4. Females from populations exhibiting post‐alighting preference searched efficiently for their host plants in the sense that they landed mainly on the species on which they oviposited predominantly. Pre‐alighting and post‐alighting preferences were correlated at the population level.5. The correlation between pre‐alighting and post‐alighting preferences helps to explain why in nature, where the host plants often occur in distinct patches, females are more likely to colonise habitat patches in which their preferred host plant is abundant.