Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models

Measuring attentional selection of object categories using hierarchical frequency tagging

In the present study, we used Hierarchical Frequency Tagging (Gordon et al., 2017) to investigate in electroencephalography how different levels of the neural processing hierarchy interact with category-selective attention during visual object recognition. We constructed stimulus sequences of cyclic wavelet scrambled face and house stimuli at two different frequencies (f1 = 0.8 Hz and f2 = 1 Hz). For each trial, two stimulus sequences of different frequencies were superimposed and additionally augmented by a sinusoidal contrast modulation with f3 = 12.5 Hz. This allowed us to simultaneously assess higher level processing using semantic wavelet-induced frequency-tagging (SWIFT) and processing in earlier visual levels using steady-state visually evoked potentials (SSVEPs), along with their intermodulation (IM) components. To investigate the category specificity of the SWIFT signal, we manipulated the category congruence between target and distractor by superimposing two sequences containing stimuli from the same or different object categories. Participants attended to one stimulus (target) and ignored the other (distractor). Our results showed successful tagging of different levels of the cortical hierarchy. Using linear mixed-effects modeling, we detected different attentional modulation effects on lower versus higher processing levels. SWIFT and IM components were substantially increased for target versus distractor stimuli, reflecting attentional selection of the target stimuli. In addition, distractor stimuli from the same category as targets elicited stronger SWIFT signals than distractor stimuli from a different category indicating category-selective attention. In contrast, for IM components, this category-selective attention effect was largely absent, indicating that IM components probably reflect more stimulus-specific processing.

Local climate and vernalization sensitivity predict the latitudinal patterns of flowering onset in the crop wild relative Linum bienne Mill

BACKGROUND AND AIMS

The timing of flowering onset is often correlated with latitude, indicative of climatic gradients. Flowering onset in temperate species commonly requires exposure to cold temperatures, known as vernalization. Hence, population differentiation of flowering onset with latitude might reflect adaptation to the local climatic conditions experienced by populations.

METHODS

Within its western range, seeds from Linum bienne populations (the wild relative of cultivated Linum usitatissimum) were used to describe the latitudinal differentiation of flowering onset to determine its association with the local climate of the population. A vernalization experiment including different crop cultivars was used to determine how vernalization accelerates flowering onset, in addition to the vernalization sensitivity response among populations and cultivars. Additionally, genetic differentiation of L. bienne populations along the latitudinal range was scrutinized using microsatellite markers.

KEY RESULTS

Flowering onset varied with latitude of origin, with southern populations flowering earlier than their northern counterparts. Vernalization reduced the number of days to flowering onset, but vernalization sensitivity was greater in northern populations compared with southern ones. Conversely, vernalization delayed flowering onset in the crop, exhibiting less variation in sensitivity. In L. bienne, both flowering onset and vernalization sensitivity were better predicted by the local climate of the population than by latitude itself. Microsatellite data unveiled genetic differentiation of populations, forming two groups geographically partitioned along latitude.

CONCLUSIONS

The consistent finding of latitudinal variation across experiments suggests that both flowering onset and vernalization sensitivity in L. bienne populations are under genetic regulation and might depend on climatic cues at the place of origin. The association with climatic gradients along latitude suggests that the climate experienced locally drives population differentiation of the flowering onset and vernalization sensitivity patterns. The genetic population structure suggests that past population history could have influenced the flowering initiation patterns detected, which deserves further work.

Genetic underpinnings of arthropod community distributions in Populus trichocarpa

Community genetics seeks to understand the mechanisms by which natural genetic variation in heritable host phenotypes can encompass assemblages of organisms such as bacteria, fungi, and many animals including arthropods. Prior studies that focused on plant genotypes have been unable to identify genes controlling community composition, a necessary step to predict ecosystem structure and function as underlying genes shift within plant populations. We surveyed arthropods within an association population of Populus trichocarpa in three common gardens to discover plant genes that contributed to arthropod community composition. We analyzed our surveys with traditional single-trait genome-wide association analysis (GWAS), multitrait GWAS, and functional networks built from a diverse set of plant phenotypes. Plant genotype was influential in structuring arthropod community composition among several garden sites. Candidate genes important for higher level organization of arthropod communities had broadly applicable functions, such as terpenoid biosynthesis and production of dsRNA binding proteins and protein kinases, which may be capable of targeting multiple arthropod species. We have demonstrated the ability to detect, in an uncontrolled environment, individual genes that are associated with the community assemblage of arthropods on a host plant, further enhancing our understanding of genetic mechanisms that impact ecosystem structure.

Night-to-night variability of objective sleep outcomes in youth Middle Eastern football players

OBJECTIVE

To describe components of night-to-night variation in objective measures of sleep.

METHODS

We conducted a secondary data analysis of consecutive and chronologically ordered actigraphy-based measurements for time in bed (min), time asleep (min), and wake-after-sleep onset (min). This investigation examined 575 individual night-based measures available for a sub-sample of fifty-two, male youth Middle Eastern football players tracked over a 14-day surveillance period (chronological age range: 12.1 to 16 years). Distinct multivariable-adjusted generalized additive models included each objective sleep outcome measure as dependent variable and disaggregated components of variation for night measurement-by-sleep period interaction, week part (weekday or weekend), and study participant random effects from within-subject night-to-night sleep variation.

RESULTS

The within-subject standard deviation (SD) of ±98 min (95% confidence interval [CI], 92 to 104 min) for time in bed, ±87 min (95%CI, 82 to 93 min) for time asleep, and ±23 min (95%CI, 22 to 25 min) for wake-after-sleep-onset overwhelmed other sources of variability and accounted for ∼44% to 53% of the overall night-to-night variation. The night measurement-by-fragmented sleep period interaction SD was ±83 min (95%CI, 44 to 156 min) for time in bed, ±67 min (95%CI, 34 to 131 min) for time asleep, and ±15 min (95%CI, 7 to 32 min) for wake-after-sleep-onset that accounted for ∼22% to 32% of each sleep outcome measure overall variability.

CONCLUSIONS

Substantial random night-to-night within-subject variability poses additional challenges for strategies aiming to mitigate problems of insufficient and inconsistent sleep that are detrimental to school learning and youth athlete development processes.

An inquiline mosquito modulates microbial diversity and function in an aquatic microecosystem

Understanding microbial roles in ecosystem function requires integrating microscopic processes into food webs. The carnivorous pitcher plant, Sarracenia purpurea, offers a tractable study system where diverse food webs of macroinvertebrates and microbes facilitate digestion of captured insect prey, releasing nutrients supporting the food web and host plant. However, how interactions between these macroinvertebrate and microbial communities contribute to ecosystem functions remains unclear. We examined the role of the pitcher plant mosquito, Wyeomyia smithii, in top-down control of the composition and function of pitcher plant microbial communities. Mosquito larval abundance was enriched or depleted across a natural population of S. purpurea pitchers over a 74-day field experiment. Bacterial community composition and microbial community function were characterized by 16S rRNA amplicon sequencing and profiling of carbon substrate use, bulk metabolic rate, hydrolytic enzyme activity, and macronutrient pools. Bacterial communities changed from pitcher opening to maturation, but larvae exerted minor effects on high-level taxonomic composition. Higher larval abundance was associated with lower diversity communities with distinct functions and elevated nitrogen availability. Treatment-independent clustering also supported roles for larvae in curating pitcher microbial communities through shifts in community diversity and function. These results demonstrate top-down control of microbial functions in an aquatic microecosystem.

Recolonization of secondary forests by a locally extinct Caribbean anole through the lens of range expansion theory

Disturbance and recovery dynamics are characteristic features of many ecosystems. Disturbance dynamics are widely studied in ecology and conservation biology. Still, we know less about the ecological processes that drive ecosystem recovery. The ecological processes that mediate ecosystem recovery stand at the intersection of many theoretical frameworks. Range expansion theory is one of these complementary frameworks that can provide unique insights into the population-level processes that mediate ecosystem recovery, particularly fauna recolonization. Although the biodiversity patterns that follow the fauna recolonization of recovering forests have been well described in the literature, the ecological processes at the population level that drive these patterns remain conspicuously unknown. In this study, we tested three fundamental predictions of range expansion theory during the recolonization of recovering forests in Puerto Rico by a shade specialist anole, Anolis gundlachi. Range expansion theory predicts that individuals at the early stages of recolonization (i.e., younger forests) would have a high prevalence of dispersive traits, experience less density dependence, and suffer less parasitism. To test these predictions, we conducted a chronosequence study applying space-for-time substitution where we compared phenotypic traits (i.e., body size, body condition, and relative limb size), population density, population growth rates, and Plasmodium parasitism rates among lizard populations living in young (<30 years), mid (~40-70 years), and old-growth forests (>75 years). Lizard populations in younger forests had lower densities, higher population growth rates, and lower rates of Plasmodium parasitism compared with old-growth forests. Still, while we found that individuals had larger body sizes, and longer forelimbs in young forests in one site, this result was not consistent among sites. This suggests a potential trade-off between the traits that provide a dispersal advantage during the initial stages of recolonization and those that are advantageous to establish in novel environmental conditions. Overall, our study emphasizes the suitability of range expansion theory to describe fauna recolonization but also highlights that the ecological processes that drive recolonization are time-dependent, complex, and nuanced.

Higher body condition with infection by Haemoproteus parasites in Bananaquits (Coereba flaveola)

Parasite transmission is a heterogenous process in host-parasite interactions. This heterogeneity is particularly apparent in vector-borne parasite transmission where the vector adds an additional level of complexity. Haemosporidian parasites, a widespread protist, cause a malaria-like disease in birds globally, but we still have much to learn about the consequences of infection to hosts' health. In the Caribbean, where malarial parasites are endemic, studying host-parasites interactions may give us important insights about energetic trade-offs involved in malarial parasites infections in birds. In this study, we tested the consequences of Haemoproteus infection on the Bananaquit, a resident species of Puerto Rico. We also tested for potential sources of individual heterogeneity in the consequences of infection such as host age and sex. To quantify the consequences of infection to hosts' health we compared three complementary body condition indices between infected and uninfected individuals. Our results showed that Bananaquits infected by Haemoproteus had higher body condition than uninfected individuals. This result was consistent among the three body condition indices. Still, we found no clear evidence that this effect was mediated by host age or sex. We discuss a set of non-mutually exclusive hypotheses that may explain this pattern including metabolic syndrome, immunological responses leading to host tolerance or resistance to infection, and potential changes in consumption rates. Overall, our results suggest that other mechanisms, may drive the consequences of avian malarial infection.

Using drone-retrieved multispectral data for phenomic selection in potato breeding

Predictive breeding approaches, like phenomic or genomic selection, have the potential to increase the selection gain for potato breeding programs which are characterized by very large numbers of entries in early stages and the availability of very few tubers per entry in these stages. The objectives of this study were to (i) explore the capabilities of phenomic prediction based on drone-derived multispectral reflectance data in potato breeding by testing different prediction scenarios on a diverse panel of tetraploid potato material from all market segments and considering a broad range of traits, (ii) compare the performance of phenomic and genomic predictions, and (iii) assess the predictive power of mixed relationship matrices utilizing weighted SNP array and multispectral reflectance data. Predictive abilities of phenomic prediction scenarios varied greatly within a range of - 0.15 and 0.88 and were strongly dependent on the environment, predicted trait, and considered prediction scenario. We observed high predictive abilities with phenomic prediction for yield (0.45), maturity (0.88), foliage development (0.73), and emergence (0.73), while all other traits achieved higher predictive ability with genomic compared to phenomic prediction. When a mixed relationship matrix was used for prediction, higher predictive abilities were observed for 20 out of 22 traits, showcasing that phenomic and genomic data contained complementary information. We see the main application of phenomic selection in potato breeding programs to allow for the use of the principle of predictive breeding in the pot seedling or single hill stage where genotyping is not recommended due to high costs.

A wheat chromosome segment substitution line series supports characterization and use of progenitor genetic variation

Genome-wide introgression and substitution lines have been developed in many plant species, enhancing mapping precision, gene discovery, and the identification and exploitation of variation from wild relatives. Created over multiple generations of crossing and/or backcrossing accompanied by marker-assisted selection, the resulting introgression lines are a fixed genetic resource. In this study we report the development of spring wheat (Triticum aestivum L.) chromosome segment substitution lines (CSSLs) generated to systematically capture genetic variation from tetraploid (T. turgidum ssp. dicoccoides) and diploid (Aegilops tauschii) progenitor species. Generated in a common genetic background over four generations of backcrossing, this is a base resource for the mapping and characterization of wheat progenitor variation. To facilitate further exploitation the final population was genetically characterized using a high-density genotyping array and a range of agronomic and grain traits assessed to demonstrate the potential use of the populations for trait localization in wheat.

Permutation Tests for Assessing Potential Non-Linear Associations between Treatment Use and Multivariate Clinical Outcomes

In many psychometric applications, the relationship between the mean of an outcome and a quantitative covariate is too complex to be described by simple parametric functions; instead, flexible nonlinear relationships can be incorporated using penalized splines. Penalized splines can be conveniently represented as a linear mixed effects model (LMM), where the coefficients of the spline basis functions are random effects. The LMM representation of penalized splines makes the extension to multivariate outcomes relatively straightforward. In the LMM, no effect of the quantitative covariate on the outcome corresponds to the null hypothesis that a fixed effect and a variance component are both zero. Under the null, the usual asymptotic chi-square distribution of the likelihood ratio test for the variance component does not hold. Therefore, we propose three permutation tests for the likelihood ratio test statistic: one based on permuting the quantitative covariate, the other two based on permuting residuals. We compare via simulation the Type I error rate and power of the three permutation tests obtained from joint models for multiple outcomes, as well as a commonly used parametric test. The tests are illustrated using data from a stimulant use disorder psychosocial clinical trial.

Long-term patterns of grassland vegetation and species richness in a full-factorial NPK fertilization experiment

Species-rich grasslands contribute significantly to conserving environmental quality in Europe but have suffered for decades due to area reduction and degradation from nutrient addition of agricultural or pollution origins. Studying the effects of grassland fertilization can supply useful information on their degradation patterns and restoration possibilities. On a valley meadow in the Italian Alps fertilized with farmyard manure until 1976, a fertilization trial with 4 replicates and 27 treatments from the factorial combination of three levels of nitrogen (N), phosphorus (P) and potassium (K) was established in 1977 and surveyed until 2003 for botanical composition on 18 m2 plots. The change of species composition and species richness (SR) occurring over the surveying period was analyzed. Six types of vegetation successions were identified, mostly with homogeneous nutrient combinations and only marginal influence by the amount of nutrients added. In all successions, the vegetation change was significant compared to the pre-experiment situation and more rapid but less persistent for abundance than for presence-absence. From about 33.6 species per plot surveyed in 1976, SR had the highest increase in the succession with no-fertilization or only-P or only-K addition (40.2 species in the period 1991-2003). The N + P + K (27.2 species) and N + P (26.3 species) successions had the strongest negative impact on SR. In the other successions (N + K, P + K and only N) SR increased or decreased little. No soil acidification and no negative effect on SR from the acidifying N-fertilizer ammonium nitrate was observed thanks to the buffering power of the Ca‑carbonate soil content. In the two successions with the highest SR variation the SR changed rapidly in the first period but fluctuated later around a constant value. In the succession with significant but little SR variation, this trend was not obvious due to the considerable interannual SR fluctuation. In all successions, the SR change was the result of a balance between logarithmic trends of species loss and gain. Species loss was probably caused by stochastic extinction of low-abundance species, but in NP, it was also due to the establishment of the aggressive-growth-habit Festuca rubra. For species gain, the suitability of incoming species to new fertility conditions was an important factor. Trial results showed that in calcareous, permeable soils, the species richness of central European grassland is especially endangered by the combined addition of N and P (with or without K), more than the only-N addition. However, they also showed that the restoration of grassland that had been degraded due to high NPK inputs from agriculture and NP enrichment from water and atmosphere pollution is possible with the cessation of fertilization and without seed addition if the surrounding landscape is species-rich and plants with aggressive growth habits are not established. Management for grassland biodiversity conservation should avoid the utilization of soil-acidifying fertilizers, reducing the P input beside the N input and limiting the introduction and spreading of aggressive grass species, such as Festuca rubra.

Global effects of identity and aging on the human sperm methylome

BACKGROUND

As the average age of fatherhood increases worldwide, so too does the need for understanding effects of aging in male germline cells. Molecular change, including epigenomic alterations, may impact offspring. Age-associated change to DNA cytosine methylation in the cytosine-guanine (CpG) context is a hallmark of aging tissues, including sperm. Prior studies have led to accurate models that predict a man's age based on specific methylation features in the DNA of sperm, but the relationship between aging and global DNA methylation in sperm remains opaque. Further clarification requires a more complete survey of the methylome with assessment of variability within and between individuals.

RESULTS

We collected sperm methylome data in a longitudinal study of ten healthy fertile men. We used whole-genome bisulfite sequencing of samples collected 10 to 18 years apart from each donor. We found that, overall, variability between donors far exceeds age-associated variation. After controlling for donor identity, we see significant age-dependent genome-wide change to the methylome. Notably, trends of change with age depend on genomic location or annotation, with contrasting signatures that correlate with gene density and proximity to centromeres and promoter regions.

CONCLUSIONS

We uncovered epigenetic signatures that reflect a stable process which begins in early adulthood, progressing steadily through most of the male lifespan, and warrants consideration in any future study of the aging sperm epigenome.

Age-related differences in resting-state functional connectivity from childhood to adolescence

The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development.

Need for approval from others and face concerns as predictors of interpersonal conflict outcome in 29 cultural groups

The extent to which culture moderates the effects of need for approval from others on a person's handling of interpersonal conflict was investigated. Students from 24 nations rated how they handled a recent interpersonal conflict, using measures derived from face-negotiation theory. Samples varied in the extent to which they were perceived as characterised by the cultural logics of dignity, honour, or face. It was hypothesised that the emphasis on harmony within face cultures would reduce the relevance of need for approval from others to face-negotiation concerns. Respondents rated their need for approval from others and how much they sought to preserve their own face and the face of the other party during the conflict. Need for approval was associated with concerns for both self-face and other-face. However, as predicted, the association between need for approval from others and concern for self-face was weaker where face logic was prevalent. Favourable conflict outcome was positively related to other-face and negatively related to self-face and to need for approval from others, but there were no significant interactions related to prevailing cultural logics. The results illustrate how particular face-threatening factors can moderate the distinctive face-concerns earlier found to characterise individualistic and collectivistic cultural groups.

Determinants of departure to natal dispersal across an elevational gradient in a long-lived raptor species

Attributes of natal habitat often affect early stages of natal dispersal. Thus, environmental gradients at mountain slopes are expected to result in gradients of dispersal behavior and to drive elevational differences in dispersal distances and settlement behavior. However, covariation of environmental factors across elevational gradients complicates the identification of mechanisms underlying the elevational patterns in dispersal behavior. Assuming a decreasing food availability with elevation, we conducted a food supplementation experiment of red kite (Milvus milvus) broods across an elevational gradient toward the upper range margin and we GPS-tagged nestlings to assess their start of dispersal. While considering timing of breeding and breeding density across elevation, this allowed disentangling effects of elevational food gradients from co-varying environmental gradients on the age at departure from the natal home range. We found an effect of food supplementation on age at departure, but no elevational gradient in the effect of food supplementation. Similarly, we found an effect of breeding density on departure age without an underlying elevational gradient. Supplementary-fed juveniles and females in high breeding densities departed at younger age than control juveniles and males in low breeding densities. We only found an elevational gradient in the timing of breeding. Late hatched juveniles, and thus individuals at high elevation, departed at earlier age compared to early hatched juveniles. We conclude that favorable natal food conditions, allow for a young departure age of juvenile red kites. We show that the elevational delay in breeding is compensated by premature departure resulting in an elevational gradient in departure age. Thus, elevational differences in dispersal behaviour likely arise due to climatic factors affecting timing of breeding. However, the results also suggest that spatial differences in food availability and breeding density affect dispersal behavior and that their large-scale gradients within the distributional range might result in differential natal dispersal patterns.

Does image editing improve the quality of latent prints? An analysis of image-editing techniques in one crime laboratory

Field research within latent print comparison has remained sparse in the context of an otherwise growing body of literature examining the discipline. Studies examining how ACE-V procedures are implemented within active crime laboratories are especially lacking in light of research suggesting significant variability in examiner practices despite standardized ACE-V procedures. To date, no studies have examined a potentially important aspect of the Analysis phase: digital image editing. We provide information on the prevalence and types of latent print image editing within one laboratory (i.e., Houston Forensic Science Center), examine the potential effect of image editing on objective print quality and clarity (i.e., LQMetrics scores), and explore potential examiner differences in editing effectiveness. Results indicate that most latent prints are edited in some manner, and that image editing improves the quality and clarity of print images as defined by an objective quality metric, although examiners varied in their ability to improve the clarity of print images. Findings suggest that formal guidance or documentation of standard editing procedures would likely improve the reliability of examiner conclusions early in the latent print comparison process.

Genetic architecture of multiple mutualisms and mating system in Turnera ulmifolia

Plants often associate with multiple arthropod mutualists. These partners provide important services to their hosts, but multiple interactions can constrain a plant's ability to respond to complex, multivariate selection. Here, we quantified patterns of genetic variance and covariance among rewards for pollination, biotic defence and seed dispersal mutualisms in multiple populations of Turnera ulmifolia to better understand how the genetic architecture of multiple mutualisms might influence their evolution. We phenotyped plants cultivated from 17 Jamaican populations for several mutualism and mating system-related traits. We then fit genetic variance-covariance (G) matrices for the island metapopulation and the five largest individual populations. At the metapopulation level, we observed significant positive genetic correlations among stigma-anther separation, floral nectar production and extrafloral nectar production. These correlations have the potential to significantly constrain or facilitate the evolution of multiple mutualisms in T. ulmifolia and suggest that pollination, seed dispersal and defence mutualisms do not evolve independently. In particular, we found that positive genetic correlations between floral and extrafloral nectar production may help explain their stable coexistence in the face of physiological trade-offs and negative interactions between pollinators and ant bodyguards. Locally, we found only small differences in G among our T. ulmifolia populations, suggesting that geographic variation in G may not shape the evolution of multiple mutualisms.

Characterizing phenotypic diversity in marine populations of the threespine stickleback

The threespine stickleback (Gasterosteus aculeatus) is an important model for studying the evolution of vertebrate morphology. Sticklebacks inhabit freshwater, brackish, and marine northern hemisphere waters. Anadromous and marine populations (hereafter marine) are assumed to have remained unchanged morphologically from ancestral marine sticklebacks, despite marine environments varying on regional and local scales. Recent studies suggest that genetic and phenotypic structure exists in marine populations, yet the scale of this variation, and its ecological causes remain unclear. Our goal was to assess morphological trait variation in marine stickleback populations around Southern British Columbia (BC) and determine if oceanographic and habitat characteristics were associated with this variation. Between May-July 2019, we sampled 534 sticklebacks from 15 sites around Vancouver Island, a region characterized by a large diversity of oceanographic and habitat features. We characterized trait variation using two-dimensional (2D) geometric morphometric analysis, comparing individuals between oceanographic regions and habitats. We focused on head and body shape. We found that marine sticklebacks varied morphologically among and between regions and habitats, but the variation did not appear to be related to environmental variation. Sexual dimorphism was the largest source of variation, but oceanographic and habitat variables influenced differences between sexes. We concluded that marine sticklebacks offer abundant opportunities for expanding our knowledge of drivers of morphology.

Developmental trajectories of cortical thickness by functional brain network: The roles of pubertal timing and socioeconomic status

The human cerebral cortex undergoes considerable changes during development, with cortical maturation patterns reflecting regional heterogeneity that generally progresses in a posterior-to-anterior fashion. However, the organizing principles that govern cortical development remain unclear. In the current study, we characterized age-related differences in cortical thickness (CT) as a function of sex, pubertal timing, and two dissociable indices of socioeconomic status (i.e., income-to-needs and maternal education) in the context of functional brain network organization, using a cross-sectional sample (n = 789) diverse in race, ethnicity, and socioeconomic status from the Lifespan Human Connectome Project in Development (HCP-D). We found that CT generally followed a linear decline from 5 to 21 years of age, except for three functional networks that displayed nonlinear trajectories. We found no main effect of sex or age by sex interaction for any network. Earlier pubertal timing was associated with reduced mean CT and CT in seven networks. We also found a significant age by maternal education interaction for mean CT across cortex and CT in the dorsal attention network, where higher levels of maternal education were associated with steeper age-related decreases in CT. Taken together, our results suggest that these biological and environmental variations may impact the emerging functional connectome.

Robust Permutation Tests for Penalized Splines

Penalized splines are frequently used in applied research for understanding functional relationships between variables. In most applications, statistical inference for penalized splines is conducted using the random effects or Bayesian interpretation of a smoothing spline. These interpretations can be used to assess the uncertainty of the fitted values and the estimated component functions. However, statistical tests about the nature of the function are more difficult, because such tests often involve testing a null hypothesis that a variance component is equal to zero. Furthermore, valid statistical inference using the random effects or Bayesian interpretation depends on the validity of the utilized parametric assumptions. To overcome these limitations, I propose a flexible and robust permutation testing framework for inference with penalized splines. The proposed approach can be used to test omnibus hypotheses about functional relationships, as well as more flexible hypotheses about conditional relationships. I establish the conditions under which the methods will produce exact results, as well as the asymptotic behavior of the various permutation tests. Additionally, I present extensive simulation results to demonstrate the robustness and superiority of the proposed approach compared to commonly used methods.

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene-based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for missense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood-ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability.

Correct specification of design matrices in linear mixed effects models: tests with graphical representation

Linear mixed effects models (LMMs) are a popular and powerful tool for analysing grouped or repeated observations for numeric outcomes. LMMs consist of a fixed and a random component, which are specified in the model through their respective design matrices. Verifying the correct specification of the two design matrices is important since mis-specifying them can affect the validity and efficiency of the analysis. We show how to use empirical stochastic processes constructed from appropriately ordered and standardized residuals from the model to test whether the design matrices of the fitted LMM are correctly specified. We define two different processes: one can be used to test whether both design matrices are correctly specified, and the other can be used only to test whether the fixed effects design matrix is correctly specified. The proposed empirical stochastic processes are smoothed versions of cumulative sum processes, which have a nice graphical representation in which model mis-specification can easily be observed. The amount of smoothing can be adjusted, which facilitates visual inspection and can potentially increase the power of the tests. We propose a computationally efficient procedure for estimating p-values in which refitting of the LMM is not necessary. Its validity is shown by using theoretical results and a large Monte Carlo simulation study. The proposed methodology could be used with LMMs with multilevel or crossed random effects.

Key features of the genetic architecture and evolution of host-microbe interactions revealed by high-resolution genetic mapping of the mucosa-associated gut microbiome in hybrid mice

Determining the forces that shape diversity in host-associated bacterial communities is critical to understanding the evolution and maintenance of metaorganisms. To gain deeper understanding of the role of host genetics in shaping gut microbial traits, we employed a powerful genetic mapping approach using inbred lines derived from the hybrid zone of two incipient house mouse species. Furthermore, we uniquely performed our analysis on microbial traits measured at the gut mucosal interface, which is in more direct contact with host cells and the immune system. Several mucosa-associated bacterial taxa have high heritability estimates, and interestingly, 16S rRNA transcript-based heritability estimates are positively correlated with cospeciation rate estimates. Genome-wide association mapping identifies 428 loci influencing 120 taxa, with narrow genomic intervals pinpointing promising candidate genes and pathways. Importantly, we identified an enrichment of candidate genes associated with several human diseases, including inflammatory bowel disease, and functional categories including innate immunity and G-protein-coupled receptors. These results highlight key features of the genetic architecture of mammalian host-microbe interactions and how they diverge as new species form.

The digestive system, particularly the large intestine, hosts many types of bacteria which together form the gut microbiome. The exact makeup of different bacterial species is specific to an individual, but microbiomes are often more similar between related individuals, and more generally, across related species. Whether this is because individuals share similar environments or similar genetic backgrounds remains unclear. These two factors can be disentangled by breeding different animal lineages – which have different genetic backgrounds while belonging to the same species – and then raising the progeny in the same environment.

To investigate this question, Doms et al. studied the genes and microbiomes of mice resulting from breeding strains from multiple locations in a natural hybrid zone between different subspecies. The experiments showed that 428 genetic regions affected the makeup of the microbiome, many of which were known to be associated with human diseases. Further analysis revealed 79 genes that were particularly interesting, as they were involved in recognition and communication with bacteria. These results show how the influence of the host genome on microbiome composition becomes more specialized as animals evolve.

Overall, the work by Doms et al. helps to pinpoint the genes that impact the microbiome; this knowledge could be helpful to examine how these interactions contribute to the emergence of conditions such as diabetes or inflammatory bowel disease, which are linked to perturbations in gut bacteria.

Associations between physical exercise patterns and pain symptoms in individuals with endometriosis: a cross-sectional mHealth-based investigation

OBJECTIVES

This study investigates the association of daily physical exercise with pain symptoms in endometriosis. We also examined whether an individual's typical weekly (ie, habitual) exercise frequency influences (ie, moderates) the relationship between their pain symptoms on a given day (day t) and previous-day (day t-1) exercise.

PARTICIPANTS

The sample included 90 382 days of data from 1009 participants (~85% non-Hispanic white) living with endometriosis across 38 countries.

STUDY DESIGN

This was an observational, retrospective study conducted using data from a research mobile app (Phendo) designed for collecting self-reported data on symptoms and self-management of endometriosis.

PRIMARY OUTCOME MEASURES

The two primary outcomes were the composite day-level pain score that includes pain intensity and location, and the change in this score from previous day (Δ-score). We applied generalised linear mixed-level models to examine the effect of previous-day exercise and habitual exercise frequency on these outcomes. We included an interaction term between the two predictors to assess the moderation effect, and adjusted for previous-day pain, menstrual status, education level and body mass index.

RESULTS

The association of previous-day (day t-1) exercise with pain symptoms on day t was moderated by habitual exercise frequency, independent of covariates (rate ratio=0.96, 95% CI=0.95 to 0.98, p=0.0007 for day-level pain score, B=-0.14, 95% CI=-0.26 to -0.016, p=0.026 for Δ-score). Those who regularly engaged in exercise at least three times per week were more likely to experience favourable pain outcomes after having a bout of exercise on the previous day.

CONCLUSIONS

Regular exercise might influence the day-level (ie, short-term) association of pain symptoms with exercise. These findings can inform exercise recommendations for endometriosis pain management, especially for those who are at greater risk of lack of regular exercise due to acute exacerbation in their pain after exercise.

How Much Training Do We Need? Assessing the Validity and Interrater Reliability of the PDM-2's Psychodiagnostic Chart among Less Experienced Clinicians

The Psychodynamic Diagnostic Manual - Second Edition (PDM-2) has emerging evidence supporting its clinical utility, yet one of the main limitations remains the conjecture that considerable training and experience is required. It also remains unclear how the PDM-2 framework compares with current DSM measures of personality pathology such as the Level of Personality Functioning Scale (LPFS). The aim of the present study is to examine these issues by testing whether less clinically experienced second year doctoral psychology students are able to reliably assess patients' level of personality pathology using the PDM-2's Psychodiagnostic Chart (PDC-2), and to investigate the convergence between the PDC-2 and the LPFS. Results showed adequate inter-rater reliability for both of the main PDC-2 axes, with 52% of the variance for the overall personality organization (P-Axis) rating, and 29% of the overall M-Axis score being due to rater consensus. Reliability of individual ratings ranged from fair to excellent for the overall scores on both axes (ICC = 0.59 to .90). Results also showed that student evaluations were valid, with the latter's assessment of the patients' level of personality organization converging both with the experts' rating of the PDC-2 as well as the LPFS. Implications for clinical training are discussed.

Wood Nutrient-Water-Density Linkages Are Influenced by Both Species and Environment

Tropical trees store a large amount of nutrients in their woody tissues, thus triggering the question of what the functional association of these elements with other wood traits is. Given the osmotic activity of mineral elements such as potassium, sodium, and calcium, these elements should be strong candidates in mediating the water storing capacity in tropical trees. We investigated the role of wood nutrients in facilitating wood water storage in trees by using branch samples from 48 tropical tree species in South America and examined their associations with wood density (ρ). Wood density varied from 316 kg/m3 in Peru plots, where the soil nutrient status is relatively higher, to 908 kg/m3 in Brazil plots, where the nutrient availability is lower. Phosphorus content in wood varied significantly between plots with lowest values found in French Guiana (1.2 mol/m3) and plots with highest values found in Peru (43.6 mol/m3). Conversely, potassium in woody tissues showed a significant cross-species variation with Minquartia guianensis in Brazil showing the lowest values (8.8 mol/m3) and with Neea divaricata in Peru having the highest values (114 mol/m3). We found that lower wood density trees store more water in their woody tissues with cations, especially potassium, having a positive association with water storage. Specific relationships between wood cation concentrations and stem water storage potential nevertheless depend on both species' identity and growing location. Tropical trees with increased water storage capacity show lower wood density and have an increased reliance on cations to regulate this reservoir. Our study highlights that cations play a more important role in tropical tree water relations than has previously been thought, with potassium being particularly important.

Statistical inference for ordinal predictors in generalized additive models with application to Bronchopulmonary Dysplasia

Objective

Discrete but ordered covariates are quite common in applied statistics, and some regularized fitting procedures have been proposed for proper handling of ordinal predictors in statistical models. Motivated by a study from neonatal medicine on Bronchopulmonary Dysplasia (BPD), we show how quadratic penalties on adjacent dummy coefficients of ordinal factors proposed in the literature can be incorporated in the framework of generalized additive models, making tools for statistical inference developed there available for ordinal predictors as well.

Results

The approach presented allows to exploit the scale level of ordinally scaled factors in a sound statistical framework. Furthermore, several ordinal factors can be considered jointly without the need to collapse levels even if the number of observations per level is small. By doing so, results obtained earlier on the BPD data analyzed could be confirmed.

Local Insect Availability Partly Explains Geographical Differences in Floral Visitor Assemblages of Arum maculatum L. (Araceae)

Geographical variation in abundance and composition of pollinator assemblages may result in variable selection pressures among plant populations and drive plant diversification. However, there is limited knowledge on whether differences in local visitor and pollinator assemblages are the result of site-specific strategies of plants to interact with their pollinators and/or merely reflect the pollinator availability at a given locality. To address this question, we compared locally available insect communities obtained by light-trapping with assemblages of floral visitors in populations of Arum maculatum (Araceae) from north vs. south of the Alps. We further investigated whether and how the abundance of different visitors affects plants' female reproductive success and examined the pollen loads of abundant visitors. Local insect availability explained inter-regional differences in total visitor abundance, but only partly the composition of visitor assemblages. Northern populations predominantly attracted females of Psychoda phalaenoides (Psychodidae, Diptera), reflecting the high availability of this moth fly in this region. More generalized visitor assemblages, including other psychodid and non-psychodid groups, were observed in the south, where the availability of P. phalaenoides/Psychodidae was limited. Fruit set was higher in the north than in the south but correlated positively in both regions with the abundance of total visitors and psychodids; in the north, however, this relationship disappeared when visitor abundances were too high. High pollen loads were recorded on both psychodids and other Diptera. We demonstrate for the first time that the quantitative assessment of floral visitor assemblages in relation to locally available insect communities is helpful to understand patterns of geographical variation in plant-pollinator interactions. This combined approach revealed that geographical differences in floral visitors of A. maculatum are only partly shaped by the local insect availability. Potential other factors that may contribute to the geographical pattern of visitor assemblages include the region-specific attractiveness of this plant species to flower visitors and the population-specific behavior of pollinators.

Simultaneous test and estimation of total genetic effect in eQTL integrative analysis through mixed models

Integration of expression quantitative trait loci (eQTL) into genome-wide association studies (GWASs) is a promising manner to reveal functional roles of associated single-nucleotide polymorphisms (SNPs) in complex phenotypes and has become an active research field in post-GWAS era. However, how to efficiently incorporate eQTL mapping study into GWAS for prioritization of causal genes remains elusive. We herein proposed a novel method termed as Mixed transcriptome-wide association studies (TWAS) and mediated Variance estimation (MTV) by modeling the effects of cis-SNPs of a gene as a function of eQTL. MTV formulates the integrative method and TWAS within a unified framework via mixed models and therefore includes many prior methods/tests as special cases. We further justified MTV from another two statistical perspectives of mediation analysis and two-stage Mendelian randomization. Relative to existing methods, MTV is superior for pronounced features including the processing of direct effects of cis-SNPs on phenotypes, the powerful likelihood ratio test for assessment of joint effects of cis-SNPs and genetically regulated gene expression (GReX), two useful quantities to measure relative genetic contributions of GReX and cis-SNPs to phenotypic variance, and the computationally efferent parameter expansion expectation maximum algorithm. With extensive simulations, we identified that MTV correctly controlled the type I error in joint evaluation of the total genetic effect and proved more powerful to discover true association signals across various scenarios compared to existing methods. We finally applied MTV to 41 complex traits/diseases available from three GWASs and discovered many new associated genes that had otherwise been missed by existing methods. We also revealed that a small but substantial fraction of phenotypic variation was mediated by GReX. Overall, MTV constructs a robust and realistic modeling foundation for integrative omics analysis and has the advantage of offering more attractive biological interpretations of GWAS results.

Sex-specific variation in the genome-wide recombination rate

In most species that reproduce sexually, successful gametogenesis requires recombination during meiosis. The number and placement of crossovers (COs) vary among individuals, with females and males often presenting the most striking contrasts. Despite the recognition that the sexes recombine at different rates (heterochiasmy), existing data fail to answer the question of whether patterns of genetic variation in recombination rate are similar in the two sexes. To fill this gap, we measured the genome-wide recombination rate in both sexes from a panel of wild-derived inbred strains from multiple subspecies of house mice (Mus musculus) and from a few additional species of Mus. To directly compare recombination rates in females and males from the same genetic backgrounds, we applied established methods based on immunolocalization of recombination proteins to inbred strains. Our results reveal discordant patterns of genetic variation in the two sexes. Whereas male genome-wide recombination rates vary substantially among strains, female recombination rates measured in the same strains are more static. The direction of heterochiasmy varies within two subspecies, Mus musculus molossinus and Mus musculus musculus. The direction of sex differences in the length of the synaptonemal complex and CO positions is consistent across strains and does not track sex differences in genome-wide recombination rate. In males, contrasts between strains with high recombination rate and strains with low recombination rate suggest more recombination is associated with stronger CO interference and more double-strand breaks. The sex-specific patterns of genetic variation we report underscore the importance of incorporating sex differences into recombination research.

Fisher Scoring for crossed factor linear mixed models

The analysis of longitudinal, heterogeneous or unbalanced clustered data is of primary importance to a wide range of applications. The linear mixed model (LMM) is a popular and flexible extension of the linear model specifically designed for such purposes. Historically, a large proportion of material published on the LMM concerns the application of popular numerical optimization algorithms, such as Newton-Raphson, Fisher Scoring and expectation maximization to single-factor LMMs (i.e. LMMs that only contain one "factor" by which observations are grouped). However, in recent years, the focus of the LMM literature has moved towards the development of estimation and inference methods for more complex, multi-factored designs. In this paper, we present and derive new expressions for the extension of an algorithm classically used for single-factor LMM parameter estimation, Fisher Scoring, to multiple, crossed-factor designs. Through simulation and real data examples, we compare five variants of the Fisher Scoring algorithm with one another, as well as against a baseline established by the R package lme4, and find evidence of correctness and strong computational efficiency for four of the five proposed approaches. Additionally, we provide a new method for LMM Satterthwaite degrees of freedom estimation based on analytical results, which does not require iterative gradient estimation. Via simulation, we find that this approach produces estimates with both lower bias and lower variance than the existing methods.

SUPPLEMENTARY INFORMATION

The online version supplementary material available at 10.1007/s11222-021-10026-6.

A functional mixed model for scalar on function regression with application to a functional MRI study

Motivated by a functional magnetic resonance imaging (fMRI) study, we propose a new functional mixed model for scalar on function regression. The model extends the standard scalar on function regression for repeated outcomes by incorporating subject-specific random functional effects. Using functional principal component analysis, the new model can be reformulated as a mixed effects model and thus easily fit. A test is also proposed to assess the existence of the subject-specific random functional effects. We evaluate the performance of the model and test via a simulation study, as well as on data from the motivating fMRI study of thermal pain. The data application indicates significant subject-specific effects of the human brain hemodynamics related to pain and provides insights on how the effects might differ across subjects.

A genomics resource for genetics, physiology, and breeding of West African sorghum

Local landrace and breeding germplasm is a useful source of genetic diversity for regional and global crop improvement initiatives. Sorghum (Sorghum bicolor L. Moench) in western Africa (WA) has diversified across a mosaic of cultures and end uses and along steep precipitation and photoperiod gradients. To facilitate germplasm utilization, a West African sorghum association panel (WASAP) of 756 accessions from national breeding programs of Niger, Mali, Senegal, and Togo was assembled and characterized. Genotyping-by-sequencing (GBS) was used to generate 159,101 high-quality biallelic single nucleotide polymorphisms (SNPs), with 43% in intergenic regions and 13% in genic regions. High genetic diversity was observed within the WASAP (π = .00045), only slightly less than in a global diversity panel (GDP) (π = .00055). Linkage disequilibrium (LD) decayed to background level (r² < .1) by ∼50 kb in the WASAP. Genome-wide diversity was structured both by botanical type and by populations within botanical type with eight ancestral populations identified. Most populations were distributed across multiple countries, suggesting several potential common gene pools across the national programs. Genome-wide association studies (GWAS) of days to flowering (DFLo) and plant height (PH) revealed eight and three significant quantitative trait loci (QTL), respectively, with major height QTL at canonical height loci Dw3 and SbHT7.1. Colocalization of two of eight major flowering time QTL with flowering genes previously described in U.S. germplasm (Ma6 and SbCN8) suggests that photoperiodic flowering in West African sorghum is conditioned by both known and novel genes. This genomic resource provides a foundation for genomics-enabled breeding of climate-resilient varieties in WA.

Determinants of healthcare worker turnover in intensive care units: A micro-macro multilevel analysis

BACKGROUND

High turnover among healthcare workers is an increasingly common phenomenon in hospitals worldwide, especially in intensive care units (ICUs). In addition to the serious financial consequences, this is a major concern for patient care (disrupted continuity of care, decreased quality and safety of care, increased rates of medication errors, …).

OBJECTIVE

The goal of this article was to understand how the ICU-level nurse turnover rate may be explained from multiple covariates at individual and ICU-level, using data from 526 French registered and auxiliary nurses (RANs).

METHODS

A cross-sectional study was conducted in ICUs of Paris-area hospitals in 2013. First, we developed a small extension of a multi-level modeling method proposed in 2007 by Croon and van Veldhoven and validated its properties using a comprehensive simulation study. Second, we applied this approach to explain RAN turnover in French ICUs.

RESULTS

Based on the simulation study, the approach we proposed allows to estimate the regression coefficients with a relative bias below 7% for group-level factors and below 12% for individual-level factors. In our data, the mean observed RAN turnover rate was 0.19 per year (SD = 0.09). Based on our results, social support from colleagues and supervisors as well as long durations of experience in the profession were negatively associated with turnover. Conversely, number of children and impossibility to skip a break due to workload were significantly associated with higher rates of turnover. At ICU-level, number of beds, presence of intermediate care beds (continuous care unit) in the ICU and staff-to-patient ratio emerged as significant predictors.

CONCLUSIONS

The findings of this research may help decision makers within hospitals by highlighting major determinants of turnover among RANs. In addition, the new approach proposed here could prove useful to researchers faced with similar micro-macro data.

Associations between Neighborhood SES and Functional Brain Network Development

Higher socioeconomic status (SES) in childhood is associated with stronger cognitive abilities, higher academic achievement, and lower incidence of mental illness later in development. While prior work has mapped the associations between neighborhood SES and brain structure, little is known about the relationship between SES and intrinsic neural dynamics. Here, we capitalize upon a large cross-sectional community-based sample (Philadelphia Neurodevelopmental Cohort, ages 8-22 years, n = 1012) to examine associations between age, SES, and functional brain network topology. We characterize this topology using a local measure of network segregation known as the clustering coefficient and find that it accounts for a greater degree of SES-associated variance than mesoscale segregation captured by modularity. High-SES youth displayed stronger positive associations between age and clustering than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. The moderating effect of SES on positive associations between age and clustering was strongest for connections of intermediate length and was consistent with a stronger negative relationship between age and local connectivity in these regions in low-SES youth. Our findings suggest that, in late childhood and adolescence, neighborhood SES is associated with variation in the development of functional network structure in the human brain.

Sex-specific spatial variation in fitness in the highly dimorphic Leucadendron rubrum

Sexual dimorphism in plants may emerge as a result of sex-specific selection on traits enhancing access to nutritive resources and/or to sexual partners. Here we investigated sex-specific differences in selection of sexually dimorphic traits and in the spatial distribution of effective fecundity (our fitness proxy) in a highly dimorphic dioecious wind-pollinated shrub, Leucadendron rubrum. In particular, we tested for the effect of density on male and female effective fecundity. We used spatial and genotypic data of parent and offspring cohorts to jointly estimate individual male and female effective fecundity on the one hand and pollen and seed dispersal kernels on the other hand. This methodology was adapted to the case of dioecious species. Explicitly modelling dispersal avoids the confounding effects of heterogeneous spatial distribution of mates and sampled seedlings on the estimation of effective fecundity. We also estimated selection gradients on plant traits while modelling sex-specific spatial autocorrelation in fecundity. Males exhibited spatial autocorrelation in effective fecundity at a smaller scale than females. A higher local density of plants was associated with lower effective fecundity in males but was not related to female effective fecundity. These results suggest sex-specific sensitivities to environmental heterogeneity in L. rubrum. Despite these sexual differences, we found directional selection for wider canopies and smaller leaves in both sexes, and no sexually antagonistic selection on strongly dimorphic traits in L. rubrum. Many empirical studies in animals similarly failed to detect sexually antagonistic selection in species expressing strong sexual dimorphism, and we discuss reasons explaining this common pattern.

Honeybee colonies compensate for pesticide-induced effects on royal jelly composition and brood survival with increased brood production

Sublethal doses of pesticides affect individual honeybees, but colony-level effects are less well understood and it is unclear how the two levels integrate. We studied the effect of the neonicotinoid pesticide clothianidin at field realistic concentrations on small colonies. We found that exposure to clothianidin affected worker jelly production of individual workers and created a strong dose-dependent increase in mortality of individual larvae, but strikingly the population size of capped brood remained stable. Thus, hives exhibited short-term resilience. Using a demographic matrix model, we found that the basis of resilience in dosed colonies was a substantive increase in brood initiation rate to compensate for increased brood mortality. However, computer simulation of full size colonies revealed that the increase in brood initiation led to severe reductions in colony reproduction (swarming) and long-term survival. This experiment reveals social regulatory mechanisms on colony-level that enable honeybees to partly compensate for effects on individual level.

Hormone-mediated dispersal and sexual maturation in males of the social paper wasp Polistes lanio

Sex-biased dispersal is common in social species, but the dispersing sex may delay emigration if associated benefits are not immediately attainable. In the social Hymenoptera (ants, some bees and wasps), newly emerged males typically disperse from the natal nest whilst most females remain as philopatric helpers. However, little information exists on the mechanisms regulating male dispersal. Furthermore, the conservation of such mechanisms across the Hymenoptera and any role of sexual maturation are also relatively unknown. Through field observations and mark-recapture, we observed that males of the social paper wasp Polistes lanio emerge from pupation sexually immature, and delay dispersal from their natal nest for up to 7 days whilst undergoing sexual maturation. Delayed dispersal may benefit males by allowing them to mature in the safety of the nest and thus be more competitive in mating. We also demonstrate that both male dispersal and maturation are associated with juvenile hormone (JH), a key regulator of insect reproductive physiology and behaviour, which also has derived functions regulating social organisation in female Hymenoptera. Males treated with methoprene (a JH analogue) dispersed earlier and possessed significantly larger accessory glands than their age-matched controls. These results highlight the wide role of JH in social hymenopteran behaviour, with parallel ancestral functions in males and females, and raise new questions on the nature of selection for sex-biased dispersal.

The maize shoot ionome: Its interaction partners, predictive power, and genetic determinants

An improved understanding of how to manipulate the accumulation and enrichment of mineral elements in aboveground plant tissues holds promise for future resource efficient and sustainable crop production. The objectives of this study were to (a) evaluate the influence of Fe regimes on mineral element concentrations and contents in the maize shoot as well as their correlations, (b) examine the predictive ability of physiological and morphological traits of individual genotypes of the IBM population from the concentration of mineral elements, and (c) identify genetic factors influencing the mineral element composition within and across Fe regimes. We evaluated the concentration and content of 12 mineral elements in shoots of the IBM population grown in sufficient and deficient Fe regimes and found for almost all mineral elements a significant (α = 0.05) genotypic variance. Across all mineral elements, the variance of genotype*Fe regime interactions was on average even more pronounced. High prediction abilities indicated that mineral elements are powerful predictors of morphological and physiological traits. Furthermore, our results suggest that ZmHMA2/3 and ZmMOT1 are major players in the natural genetic variation of Cd and Mo concentrations and contents of maize shoots, respectively.

Gestational Age is Dimensionally Associated with Structural Brain Network Abnormalities Across Development

Prematurity is associated with diverse developmental abnormalities, yet few studies relate cognitive and neurostructural deficits to a dimensional measure of prematurity. Leveraging a large sample of children, adolescents, and young adults (age 8-22 years) studied as part of the Philadelphia Neurodevelopmental Cohort, we examined how variation in gestational age impacted cognition and brain structure later in development. Participants included 72 preterm youth born before 37 weeks' gestation and 206 youth who were born at term (37 weeks or later). Using a previously-validated factor analysis, cognitive performance was assessed in three domains: (1) executive function and complex reasoning, (2) social cognition, and (3) episodic memory. All participants completed T1-weighted neuroimaging at 3 T to measure brain volume. Structural covariance networks were delineated using non-negative matrix factorization, an advanced multivariate analysis technique. Lower gestational age was associated with both deficits in executive function and reduced volume within 11 of 26 structural covariance networks, which included orbitofrontal, temporal, and parietal cortices as well as subcortical regions including the hippocampus. Notably, the relationship between lower gestational age and executive dysfunction was accounted for in part by structural network deficits. Together, these findings emphasize the durable impact of prematurity on cognition and brain structure, which persists across development.

A More Efficient Causal Mediator Model Without the No-Unmeasured-Confounder Assumption

Mediator models have been developed primarily under the assumption of no-unmeasured-confounding. In many situations, this assumption is violated and may lead to the identification of mediator variables that actually are statistical artifacts. The rank preserving model (RPM) is an alternative approach to estimate controlled direct and mediator effects. It is based on the structural mean models framework and a no-effect-modifier assumption. The RPM assumes that unobserved confounders do not interact with treatment or mediators. This assumption is often more plausible to hold than the no-unmeasured-confounder assumption. So far, models using the no-effect-modifier assumption have been rarely used, which might be due to its low power and inefficiency in many scenarios. Here, a semi-parametric nonlinear extension, the nRPM, is proposed that overcomes this inefficiency using thin plate regression splines that both increase the predictive power of the model and decrease the misspecification present in many situations. In a simulation study, it is shown that the nRPM provides estimates that are robust against the violation of the no-effect-modifier assumption and that are substantively more efficient than those of the RPM. The model is illustrated using a data set on CD4 cell counts in a context of the human immunodeficiency virus (HIV).

Characterization of the transcriptional divergence between the subspecies of cultivated rice (Oryza sativa)

Background

Cultivated rice consists of two subspecies, Indica and Japonica, that exhibit well-characterized differences at the morphological and genetic levels. However, the differences between these subspecies at the transcriptome level remains largely unexamined. Here, we provide a comprehensive characterization of transcriptome divergence and cis-regulatory variation within rice using transcriptome data from 91 accessions from a rice diversity panel (RDP1).

Results

The transcriptomes of the two subspecies of rice are highly divergent. Japonica have significantly lower expression and genetic diversity relative to Indica, which is likely a consequence of a population bottleneck during Japonica domestication. We leveraged high-density genotypic data and transcript levels to identify cis-regulatory variants that may explain the genetic divergence between the subspecies. We identified significantly more eQTL that were specific to the Indica subspecies compared to Japonica, suggesting that the observed differences in expression and genetic variability also extends to cis-regulatory variation.

Conclusions

Using RNA sequencing data for 91diverse rice accessions and high-density genotypic data, we show that the two species are highly divergent with respect to gene expression levels, as well as the genetic regulation of expression. The data generated by this study provide, to date, the largest collection of genome-wide transcriptional levels for rice, and provides a community resource to accelerate functional genomic studies in rice.

Anonymous fecal sampling and NIRS studies of diet quality: Problem or opportunity?

Investigating the drivers of diet quality is a key issue in wildlife ecology and conservation. Fecal near infrared reflectance spectroscopy (f-NIRS) is widely used to assess dietary quality since it allows for noninvasive, rapid, and low-cost analysis of nutrients. Samples for f-NIRS can be collected and analyzed with or without knowledge of animal identities. While anonymous sampling allows to reduce the costs of individual identification, as it neither requires physical captures nor DNA genotyping, it neglects the potential effects of individual variation. As a consequence, regression models fitted to investigate the drivers of dietary quality may suffer severe issues of pseudoreplication. I investigated the relationship between crude protein and ecological predictors at different time periods to assess the level of individual heterogeneity in diet quality of 22 marked chamois Rupicapra rupicapra monitored over 2 years. Models with and without individual grouping effect were fitted to simulate identifiable and anonymous fecal sampling, and model estimates were compared to evaluate the consequences of anonymizing data collection and analysis. The variance explained by the individual random effect and the value of diet repeatability varied with seasons and peaked in winter. Despite the occurrence of individual variation in dietary quality, ecological parameter estimates under identifiable or anonymous sampling were consistently similar. This study suggests that anonymous fecal sampling may provide robust estimates of the relationship between dietary quality and ecological correlates. However, since the level of individual heterogeneity in dietary quality may vary with species- or study-specific features, inconsequential pseudoreplication should not be assumed in other taxa. When individual differences are known to be inconsequential, anonymous sampling allows to optimize the trade-off between sampling intensity and representativeness. When pseudoreplication is consequential, however, no conclusive remedy exists to effectively resolve nonindependence.

Combining Experimental Evolution and Genomics to Understand How Seed Beetles Adapt to a Marginal Host Plant

Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve-and-resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic datasets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus.

Is 'heavy' up or down? Testing the vertical spatial representation of weight

Smaller numbers are typically responded to faster with a bottom than a top key, whereas the opposite occurs for larger numbers (a vertical spatial-numerical association of response codes: i.e. the vertical SNARC effect). Here, in four experiments, we explored whether a vertical spatial-magnitude association can emerge for lighter vs. heavier items. Participants were presented with a central target stimulus that could be a word describing a material (e.g. 'paper', 'iron': Experiment 1), a numerical quantity of weight (e.g. '1 g', '1 kg': Experiment 2) or a picture associated with a real object that participants weighed before the experiment (Experiments 3a/3b). Participants were asked to respond either to the weight (Experiments 1-3a) or to the size (i.e. weight was task-irrelevant; Experiment 3b) of the stimuli by pressing vertically placed keys. In Experiments 1 and 2, faster responses emerged for the lighter-bottom/heavier-top mapping-in line with a standard SNARC-like effect-whereas in Experiment 3a the opposite mapping emerged (lighter-top/heavier-bottom). No evidence of an implicit weight-space association emerged in Experiment 3b. Overall, these results provide evidence indicating a possible context-dependent vertical spatial representation of weight.

Defining the Role of the MADS-Box Gene, Zea Agamous-like1, a Target of Selection During Maize Domestication

Genomic scans for genes that show the signature of past selection have been widely applied to a number of species and have identified a large number of selection candidate genes. In cultivated maize (Zea mays ssp. mays) selection scans have identified several hundred candidate domestication genes by comparing nucleotide diversity and differentiation between maize and its progenitor, teosinte (Z. mays ssp. parviglumis). One of these is a gene called zea agamous-like1 (zagl1), a MADS-box transcription factor, that is known for its function in the control of flowering time. To determine the trait(s) controlled by zagl1 that was (were) the target(s) of selection during maize domestication, we created a set of recombinant chromosome isogenic lines that differ for the maize versus teosinte alleles of zagl1 and which carry cross-overs between zagl1 and its neighbor genes. These lines were grown in a randomized trial and scored for flowering time and domestication related traits. The results indicated that the maize versus teosinte alleles of zagl1 affect flowering time as expected, as well as multiple traits related to ear size with the maize allele conferring larger ears with more kernels. Our results suggest that zagl1 may have been under selection during domestication to increase the size of the maize ear.